Faculty of Science

DISENTANGLING THE MECHANISMS OF PLUMAGE COLOUR EVOLUTION IN
TYRANNID FLYCATCHERS
2022 | SYDNEY MORGAN MILLER

B.Sc. HONOURS THESIS - BIOLOGY

DISENTANGLING THE MECHANISMS OF PLUMAGE COLOUR EVOLUTION IN
TYRANNID FLYCATCHERS

by

SYDNEY MORGAN MILLER

A THESIS SUBMITTED IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF

BACHELOR OF SCIENCE (HONS.)
in the
DEPARTMENT OF BIOLOGICAL SCIENCES
(Animal Biology)

This thesis has been accepted as conforming to the required standards by:
Matthew Reudink (Ph.D.), Thesis Supervisor, Dept. Biological Sciences
Nancy Flood (Ph.D.), Co-supervisor, Dept. Biological Sciences
Natasha Ramroop Singh (Ph.D.), External examiner, Dept. Biological Sciences

Dated this 22nd day of April, 2022, in Kamloops, British Columbia, Canada
© Sydney Morgan Miller, 2022

ABSTRACT
In birds, plumage coloration is an important visual signal involved in communication and
survival that varies greatly across species. Plumage colour evolution is influenced by a variety of
factors including phylogeny, predation pressure, sexual selection, light and resource availability,
and ecological context. Tyrant flycatchers are an interesting group because although there are many
monomorphic species with drab plumage, some species are quite colourful. Given the complexity
of factors involved, the mechanisms influencing plumage colour evolution in Tyrant flycatchers
are likely complex, involving multiple drivers. To account for the fact that differences in the
availability of resources and light will result in differences in the acquisition and transmission of
plumage signals, we calculated red and blue chromaticity values from red, blue, green scores
originally extracted from digitally scanned images from the Birds of the World. Next, we used
phylogenetically controlled analyses to assess the influence of a variety of ecological factors on
plumage colouration, and dichromatism. Finally, we examined the extent of range overlap among
species to test if plumage varies to a greater extent in overlapping species due to reinforcement of
pre-mating isolating mechanisms (i.e., for species recognition). We found that diet, precipitation,
and temperature all influence colour expression, that precipitation and latitude influence the extent
of dichromatism, and finally that the extent of range overlap affects plumage divergence between
species. Taken together, our results highlight the complexity of plumage evolution in Tyrant
flycatchers and demonstrate that the evolution of plumage colouration is driven by a combination
of ecological, geographic, and biological factors.

Thesis Supervisor: Professor Matthew Reudink

ii

ACKNOWLEDGMENTS
This research was completed on the traditional lands of the Tk'emlúps te Secwépemc within
Secwépemc'ulucw, the traditional and unceded territory of the Secwépemc Peoples.

Thank you to J. Dale for sharing the RGB colour scores (Dale et al. 2015), and Dr. Sean Mahoney
as well as the entire BEAC lab for support throughout the completion of this project.

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TABLE OF CONTENTS

ABSTRACT .................................................................................................................................. ii
ACKNOWLEDGEMENT ........................................................................................................... iii
LIST OF FIGURES ...................................................................................................................... v
LIST OF TABLES ....................................................................................................................... iv
INTRODUCTION ......................................................................................................................... 1
MATERIALS AND METHODS ................................................................................................. 5
DATA COLLECTION ........................................................................................................ 5
PHYLOGENETIC METHODS .......................................................................................... 6
STATISTICAL ANALYSIS ............................................................................................... 6
RANGE OVERLAP ............................................................................................................ 7
RESULTS ...................................................................................................................................... 7
EFFECTS OF ECOLOGICAL FACTORS ON CHROMATICITY SCORES .................. 7
EFFECTS OF ECOLOGICAL FACTORS ON DICHROMATISM ................................. 14
EFFECTS OF RANGE OVERLAP ON TYRANNIDAE COLOUR EVOLUTION ....... 17
DISCUSSION .............................................................................................................................. 16
LITURATURE CITED ............................................................................................................... 21
APPENDIX .................................................................................................................................. 25

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LIST OF FIGURES

Figure 1. Effects of dietary guild on the red and blue chromaticity scores for male and female
Tyrant flycatchers .......................................................................................................................... 10
Figure 2. Effects of precipitation on the red and blue chromaticity scores for male and female
Tyrant flycatchers .......................................................................................................................... 11
Figure 3. Effects of the maximum temperature of the warmest month on the red chromaticity scores
for male and female Tyrant flycatchers .......................................................................................... 12
Figure 4. Effect of precipitation on the level of dichromatism via red chromaticity in Tyrant
flycatchers ..................................................................................................................................... 14
Figure 5. Effects of latitude on the level of red and blue dichromatism in Tyrant flycatchers
....................................................................................................................................................... 15

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LIST OF TABLES

Table 1. Full and top model results evaluating the relationship between ecological and
geographical variables on red and blue chromaticity in male and female Tyrant flycatchers
......................................................................................................................................................... 8
Table 2. Effect tests of best fit models explaining chromaticity values of Tyrant flycatchers after a
stepwise AIC reduction procedure. Significant terms are bolded ................................................... 9
Table 3. Full and top model selection results to evaluate the relationship between ecological and
geographical variables on dichromatism in Tyrant flycatchers ...................................................... 13
Table 4. Results of best fit models explaining chromaticity values of Tyrant flycatchers after a
stepwise AIC reduction procedure. Significant terms are bolded .................................................. 14

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INTRODUCTION
In birds, feather colours and patterns are important visual signals that vary among and
within species (Andersson 1994). Across species, the factors influencing plumage evolution are
many and varied and can be driven by both adaptive (natural and sexual selection) and neutral
processes. For example, plumage characteristics of birds may be under selection to match specific
environments to increase camouflage (Wolf 2015). In addition to crypsis, differences in plumage
colouration may influence thermoregulation. Gloger’s rule (1833), which has received ample
empirical support (Delhey 2019, reviewed by Zink and Remsen 1986), predicts that more heavily
pigmented animals should be found closer to the equator, where it is more humid and less
pigmented animals should be found at higher latitudes, where it is more arid. Humid areas are
hypothesized to have higher bacteria loads and the heavily pigmented feathers found in these areas
may be less susceptible to bacterial degradation (Burtt and Ichida 2004). Lighter colored feathers
may also aid in crypsis in arid environments; however, a study testing Gloger’s rule with species
exhibiting carotenoid-based pigments found the opposite pattern (Chui and Doucet 2009). Still,
support for Gloger’s rule is widespread among those studying birds (Review by Zink and Remsen
1986).
Ornamental colours can evolve through sexual selection when individuals prefer specific,
and/or bright colours, leading to an elaboration of those traits (Hill 2015). In birds, females are
typically the choosy sex and numerous experimental and observational studies have demonstrated
that females prefer males with more elaborate plumage (Hill and McGraw 2006). Plumage can act
as a direct indicator of male condition or quality, but elaborate plumage can also evolve simply
through female preference for specific signals (e.g., though sensory bias, Hill 2015). Males with
elaborate colours may be perceived as higher quality because the acquisition of pigments (e.g.,

1

carotenoids) can be costly, meaning only individuals in good physiological condition during moult
can produce the most colourful displays (Hill 2015, Hill and McGraw 2006). Regardless of the
mechanism, if colourful males are more successful at obtaining mates and females prefer more
colourful males, more elaborate plumage can quickly evolve (Hill 2015).
Additionally, sexual selection can lead to plumage divergence within species, resulting in
sexual dichromatism (Badyaev and Hill 2003). Dichromatism arises when there is stronger mate
choice pressure on one sex within the species that results in more elaborate ornamentation in that
sex (Bailey 1978, Simpson et al. 2015). Alternatively, dichromatism can arise through the loss of
elaborate ornaments in one sex due to relaxation of sexual selection and/or increased selection for
crypsis (Simpson et al. 2015). This change in sexual dichromatism is seen in New World woodwarblers (Parulidae). A study looking into the mechanism driving the variation in female
ornamentation found that more colourful female plumage is lost when there is reduced social
selection pressure on females and an increase in predation risk with migration. The results of this
study show that social and natural selection are driving the alternative plumage in female woodwarblers, as opposed to sexual selection (Simpson et al. 2015).
At a broader scale, sexual selection can drive species radiations by driving the
diversification of phenotypic traits associated with mate choice (Cooney et al. 2017). In the
presence of strong intra-sex competition, and a change in inter-sex mate preference, the plumage
signals that increase matting success can diverge, leading to reproductive isolation (Lande 1981).
When many species are living in sympatry and competition is high, plumage signal divergence is
magnified and can result in radiation events; when the signals diverge. Reproductive isolation
separates species based on mate choice (Seddon et al. 2013).
Birds that are closely related often have similar plumage colour and patterns due to shared
ancestry; however, when these closely related species have overlapping ranges, their signals are
2

more likely to diverge (Sætre et al. 1997, Seddon 2005). This phenomenon could be explained by
the species recognition hypothesis, which states that species living in sympatry are more likely to
have signals that diverge, allowing individuals of the same species to recognize one another and
avoid hybridization with other species (Simpson et al. 2021). In their study of wood warblers,
Simpson et al. found that warblers with overlapping ranges exhibited more plumage divergence.
However, they also found that an increased number of species in one area will limit the signal
divergence since there is only a certain number of signals that wood-warblers can display and
recognize. Thus, when there are too many species living in the same area, limitations on the number
of signals that can be displayed and recognized, thus create more overlap of signals (Simpson et
al. 2021).
Finally, other ecological aspects of a species’ environment may influence colour evolution.
The sensory drive hypothesis states that systems of communication will change based on
environmental factors (Boughman 2002). In the case of plumage colouration these environmental
factors can include resource availability, which may restrict the nutrients needed for colour
expression (Hill and McGraw 2006) and light availability, which may affect signal transmission of
(Endler 1993). For example, birds that display carotenoid-based colours are unable to synthesize
these pigments and must obtain them from the diet, metabolically convert the compounds, and
ultimately deposit them in feathers. Carotenoid compounds will absorb and then emit certain
wavelengths of light, resulting in red, orange, and yellow plumage colouration (Badyaev and Hill
2003, Hill and McGraw 2006). Another way that plumage colour can be produced is through the
interaction of light and nanostructures in the feathers. Composed of a combination of melanin,
keratin, collagen, and other biomolecules, these nanostructures interact with light and transmit blue,
green, and iridescent colours (Hill and McGraw 2006). For both carotenoid- and structural-based
plumage, the environment in which those traits are displayed (e.g., open grassland vs. forest
3

understory) can influence signal transmission through differences in both resource availability and
the available wavelengths of light, thus influencing signal efficacy.
Tyrant flycatchers are an interesting group with which to study the evolution of visual
signals because although there are many monomorphic species with drab plumage, some species
are quite colourful. The mix of conserved, drab plumage traits among many species, combined
with high elaboration in other, raises fundamental questions about the factors driving plumage
evolution in Tyrannidae. These flycatchers breed throughout North, South, and Central America,
across broad climatic and ecological gradients. Because they occur across different ecological
contexts, the factors that contribute to their plumage evolution are likely complex and difficult to
disentangle. In this study, we will use chromaticity values to quantify carotenoid-based and
structural-based colouration separately, to investigate how ecological variables affect the signal
divergence in flycatchers, and gain insight on how these differences arise and are maintained. Using
a phylogenetically controlled analysis, we will test whether both carotenoid-based and structuralbased colouration have been shaped by ecological and geographical factors. Additionally, we will
use range extents to test the species recognition hypothesis. We predict that overall, plumage will
vary among species (Mahoney et al. 2020) and that we will find more variability in plumage
colouration with varying habitats, breeding ranges, climatic conditions, and location of breeding
grounds. We expect to find support for the sensory drive hypothesis and in cases where there is
range overlap, we expect to find support for the species recognition hypothesis (Simpson et al.
2021).

4

METHODS
Data Collection
Tyrannidae plumage colour data was obtained for 399 species from Dale et al. (2015). Dale
et al. used digitally scanned images from the Handbook of the Birds of the World to score plumage
colour on males and females of each species from six patches (crown, forehead, nape, throat, upper
breast, and lower breast). The patches used were found to be consistently included in the
illustrations and important for communication. Colour patch values were measured by Dale et al.
from 400 randomly selected pixels to obtain Red-green-blue (RGB) values. These values were then
corrected using species with similar colouration and averaged to provide a single plumage colour
score for males and females of each Tyrannidae species. These scores were used to provide a
measurement for the general degree of colour elaboration in each species and sex and are ideally
suited to large-scale comparative studies (Dale et al. 2015).
To account for the fact that carotenoid-based colouration and structural-based colouration
leads to elaborate plumage ornamentation through different physiological mechanisms, we
calculated chromaticity values using the red and blue colour scores extracted from the RGB values
provided by Dale et al. (2015). Chromaticity values provide an estimate of the relative contribution
of short and long wavelengths to the expressed colour and can act as a reliable metric for measuring
variation in carotenoid and structural plumage coloration separately (Dey et al. 2015). To calculate
red chromaticity we used the equation: R/(R+G+B), and to calculate blue chromaticity we used the
equation: B/(R+G+B), where R is the red value, G is the green value, and B is the blue value (Dey
et al. 2015).
We calculated red and blue dichromatism values to represent the level of dichromatism in
each Tyrannidae species. Red dichromatism was calculated by subtracting the female red

5

chromaticity score from the male chromaticity score, and blue dichromatism was calculated by
subtracting the female blue chromaticity score from the male blue chromaticity score.
To examine the factors influencing plumage colouration, we collected data on diet, habitat
type, and geographic region (data from Pageau et al. (2020), based on Wilman et al. (2014),
Barçante et al. (2017), and [“BirdLife Data Zone” n.d.]).

Phylogenetic Methods
To control for non-independence of related species, we downloaded 1000 potential
phylogenies from birdtree.org (Jetz et al. 2012; 2014) for all Tyrannidae species. We then used
TreeAnnotator in BEAST v1.10.1 (Suchard et al. 2018) to construct a maximum clade credibility
tree using 1% burn in and mean node heights.

Statistical Analysis
All analyses were performed in R 3.5.3 (R Core Team 2017) using phylogenetic generalized
least squares (PGLS) analyses in the nlme package (Pinheiro et al. 2018). We used a series of PGLS
models to ask how plumage colouration (red and blue chromaticity) and dichromatism (red and
blue) are affected by diet, habitat, latitude, range overlap, and geographic region. To determine
which variables, or combination of variables, best explained variation in colouration, we used
stepwise model reduction based on Akaike Information Criterion (AIC). First, we constructed a
full model which included either red or blue chromaticity or dichromatism as the response variable,
and the latitude of the centroid range, feeding guild, habitat type, annual precipitation, and the max
temperature of the warmest month as the main effects. Separate models were constructed for each
sex. Next, we carried out model reduction for all possible models using the StepAIC function in
the MASS package and compared candidate models based on AIC (Burnham, and Anderson 2003).
6

Changes in AIC values within 4 are considered to be competitive and the final model was
chosen based on the lowest AIC (Burnham and Anderson 2003).

Range overlap
Range extents (centroid latitudes, and longitudes) of each species were taken from the
International Union for Conservation of Nature species lists (iucn.org). To assess the relationship
between plumage distance and geographic distance, we constructed pairwise distance matrices
between all comparisons of species’ range centroids and their chromaticity variables (red and blue
chromaticity). To calculate plumage distances, we used the vegdist function in the Vegan package
for R, which calculates Euclidean distances (Oksanen et al. 2008). Geographic distances were
calculated using linear distance (km) between all comparisons of range centroids. We then
conducted a Mantel test in R, under the hypothesis that chromaticity distances would be larger if
species’ ranges overlapped more (i.e., trait distance is negatively related to geographic distance).

RESULTS
Effects of ecological factors on chromaticity scores
The top performing model for male red chromaticity (Table 1) included dietary guild
(F=6.57, P=0.002), habitat (F=6.57, p=0.004), and the maximum temperature of the warmest
month (F=7.17, p=0.0078, Table 2). Likewise, the top model for female red chromaticity included
dietary guild (F=7.26, p=0.0008), habitat (F=13.57, p=0.0003, Table 2), and the maximum
temperature of the warmest month (F=6.23, p=0.013). Next, we found that the top model (Table 1)
for male blue chromaticity included dietary guild (F=6.03, p=0.003) and annual precipitation
(F=8.42, p=0.004, Table 2). The top model for female blue chromaticity included dietary guild
(F=5.92, p=0.0029), and annual precipitation (F=11.31, p=0.0008, Tables 1, 2).
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Table 1. Full and top model results to evaluate the relationship between ecological and geographical variables on red and blue
chromaticity in male and female Tyrant flycatchers.
Variable

Sex

Model
Top

Model terms
Dietary Guild + Annual Precipitation + Maximum
temperature of the warmest month

K
6

AICc
-1206.51

△AICc
0

AICcWt
0.96

Cum.Wt
0.96

LL
609.37

Full

Latitude + Dietary guild + Habitat + Annual
precipitation + Maximum temperature of the
warmest month
Dietary Guild + Annual Precipitation + Maximum
temperature of the warmest month

10

-1200.12

6.38

0.04

1

610.36

6

-1256.09

0

0.96

0.96

634.16

Latitude + Dietary guild + Habitat + Annual
precipitation + Maximum temperature of the
warmest month
Dietary guild + Annual precipitation

10

-1249.96

6.13

0.04

1

635.28

5

-995.07

0

0.87

0.87

502.61

Latitude + Dietary guild + Habitat + Annual
precipitation + Maximum temperature of the
warmest month
Dietary guild + Annual precipitation

10

-991.25

3.81

0.13

1

505.92

5

-1020.93

0

0.94

0.94

515.55

Latitude + Dietary guild + Habitat + Annual
precipitation + Maximum temperature of the
warmest month

10

-1015.28

5.65

0.06

1

517.94

Male

Red
Chromaticity

Top
Female
Full
Top
Male

Blue
Chromaticity

Full
Top

Female

Full

K=number of parameters, Likelihood=model likelihood, LL=log likelihood, Cum.Wt=cumulative model weight

8

Table 2. Effect tests of best fit models explaining chromaticity values of Tyrant flycatchers after a
stepwise AIC reduction procedure. Significant terms are bolded.
Variable

Sex
Male

Red
Chromaticity
Female

Blue
Chromaticity

Male
Female

Fixed effects
Dietary guild
Annual precipitation
Maximum temperature of
the warmest month
Dietary guild
Annual precipitation
Maximum temperature of
the warmest month
Dietary guild
Annual precipitation
Dietary guild
Annual precipitation

Model df
2
1

Residual df
374
374

F
6.57
8.35

p
0.0016
0.0041

1
2
1

374
375
375

7.17
7.26
13.57

0.0078
0.0008
0.0003

1
2
1
2
1

374
374
374
375
375

6.23
6.03
8.42
5.92
11.31

0.0130
0.0026
0.0039
0.0029
0.0008

We found that herbivores had the highest red chromaticity scores, while invertivores and
omnivores had the highest blue chromaticity scores (Figure 1). Both males and females showed a
positive relationship between annual precipitation and red chromaticity, and a negative relationship
between annual precipitation and blue chromaticity (Figure 2). We found a positive relationship
between maximum temperature of the warmest month and red chromaticity, but the relationship
between maximum temperature of the warmest month and blue chromaticity was not significant
(Figure 3).

9

Figure 1. Effects of dietary guild on the red and blue chromaticity scores for male and
female Tyrant flycatchers.

10

Figure 2. Effects of precipitation on the red and blue chromaticity scores for male and
female Tyrant flycatchers.

11

Figure 3. Effects of the maximum temperature of the warmest month on the red
chromaticity scores for male and female Tyrant flycatchers.

Effects of ecological factors on dichromatism
When looking at sexual dichromatism in red chromaticity, the top model included habitat
(F=2.46, p=0.062), annual precipitation (F=9.25, p=0.003), and the latitude of the centroid of the
breeding range (F=5.85, p=0.016; Table 3). For dichromatism in blue chromaticity, the top model
included the maximum temperature of the warmest month (F=2.67, p=0.1030), habitat (F=2.11,
p=0.099), and the latitude of the centroid of the breeding range (F=8.56, p=0.004, Tables 3, 4).

12

Table 3. Full and top model selection results to evaluate the relationship between ecological and geographical variables on dichromatism
in Tyrant flycatchers.
Variable
Red
dichromatism

Model
Top

Model terms
Habitat + Annual precipitation + Latitude

K
7

AICc
3380.64

△AICc
0

AICcWt
0.95

Cum.Wt
0.95

LL
-1683.17

Full

Latitude + Dietary guild + Habitat +
Annual precipitation + Maximum
temperature of the warmest month
Maximum temperature of the warmest
month + Habitat + Latitude

10

3386.50

5.86

0.05

1.00

-1682.95

7

3203.55

0.00

0.9

0.9

-1594.63

Latitude + Dietary guild + Habitat +
Annual precipitation + Maximum
temperature of the warmest month

10

3207.90

4.34

0.1

1.0

-1593.65

Top
Blue
dichromatism

Full

K=number of parameters, Likelihood=model likelihood, LL=log likelihood, Cum.Wt=cumulative model weight

13

Table 4. Results of best fit models explaining chromaticity values of Tyrant flycatchers after a
stepwise AIC reduction procedure. Significant terms are bolded.
Variable
Red
dichromatism

Blue
dichromatism

Fixed effects

Model df

Residual df

F

p

Habitat
Annual
precipitation
Latitude
Maximum
temperature of the
warmest month
Habitat
Latitude

3

373

2.46

0.0624

1
1

373
373

9.25
5.85

0.0025
0.0160

1
3
1

373
373
373

2.67
2.11
8.56

0.1030
0.0985
0.0036

We found a positive relationship between annual precipitation and red dichromatism
(Figure 4) and that there was not a significant relationship between annual precipitation and blue
dichromatism. There is a positive relationship between latitude and both red and blue dichromatism
(Figure 5).

Figure 4. Effect of precipitation on the level of dichromatism via red chromaticity in Tyrant
flycatchers.

14

Figure 5. Effects of latitude on the level of red and blue dichromatism in Tyrant flycatchers.

Effects of range overlap on Tyrannidae colour evolution
When looking at the effect of range overlap on plumage divergence we found a negative
relationship between chromaticity distance and geographical distance (r=-0.039 (95% CI: -0.046,
-0.031), p=0.009).

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DISCUSSION
Plumage colouration is an important visual signal that aids in communication, mate choice,
predator avoidance and species recognition. With plumage colouration playing such an important
role in many facets of a bird’s reproduction and survival, the mechanisms driving plumage colour
evolution within the large Family Tyrannidae are complex. Our phylogenetic comparative analysis
indicates that variation in plumage colouration among flycatchers is associated with diet and
climate, both of which may influence resource availability for growing ornamental feathers.
Overall, herbivores have the highest red chromaticity values (likely due to high expression of
carotenoid-based plumage), while invertivores and omnivores have the highest blue chromaticity
values (associated with structural plumage) (Figure 1). Higher levels of precipitation were
positively associated with red chromaticity and negatively associated with blue chromaticity
(Figure 2). Additionally, we found that there was a negative relationship between climates with
warmer temperatures and red chromaticity (Figure 3), and that there was no significant relationship
between temperature and blue chromaticity. These patterns appear to be consistent across both
males and females. In addition, higher levels of precipitation were associated with a greater amount
of red dichromatism (Figure 4), and at higher latitudes there was greater blue and red dichromatism
(Figure 5). Lastly, we found that species with greater range overlap have a greater chromaticity
distance, meaning that species living closer to each other are more likely to look different. Overall,
our results are consistent with the sensory drive hypothesis, Gloger’s rule and the species
recognition hypothesis.
The sensory drive hypothesis proposed by Endler (1992) suggests that environmental
conditions alter the expression of signals to better match their environment. Based on this, we
predicted that we would find divergence in plumage colouration with changes in environmental
factors (diet, precipitation, temperature). Support for this hypothesis was found by Marchetti
16

(1993) who observed that Phylloscopus warblers were brighter when living in darker habitats and
duller when living in habitats with more light (Gomez and Théry 2004). Our findings that plumage
colouration was influenced by diet, precipitation, and temperature are consistent with the sensory
drive hypothesis and suggest that in Tyrant flycatchers, plumage signals are influenced by
environmental factors. However, it can be challenging to disentangle the mechanisms by which
these environmental factors influence plumage expression or efficacy. In both females and males,
we found that herbivores had the highest red chromaticity values (Figure 1), which could be
attributed to resource availability. Carotenoid-based pigments cannot be synthesized by birds and
thus need to be obtained through the diet. Herbivorous species that are gaining carotenoid pigments
directly from the plants they eat may be better able to acquire sufficient dietary pigments to be able
to modify and synthesize sufficient carotenoids into growing feathers to create more elaborate
ornaments (Peneaux et al. 2021).
Overall, we suggest that our metric representing carotenoid-based colouration—red
chromaticity—is likely directly influenced by resource availability though diet. Similarly, blue
chromaticity may be directly influenced by diet, because although birds can synthesis melanin
themselves, the precursors (phenylalanine and cysteine) come from their diet (Galván and Solano
2016). Again, this demonstrates how resource availability (specifically, food availability) can
influence the plumage colours of birds. For example, in Anna’s hummingbirds (Calypte anna),
where it was found that varying protein levels in the diet influenced iridescent colour expression,
with protein richer diets resulting in birds with more colourful feathers than those characteristics
of the birds subjected to a diet lower in protein (Meadows et al. 2012). With protein being a source
of the precursors to melanin, we can assume that the protein content in the diet of tyrant flycatchers
is influencing their plumage colouration.

17

Similarly, we predict that precipitation has an influence on colour though resource
availability, where habitats with more rainfall will have the ability to produce more of the resources
needed to support bright plumage (Ward et al. 2021). A study done by Reudink et al. (2015) found
that more rainfall was associated with the production of more highly saturated colours in American
redstarts (Setophaga ruticilla), which the authors suggested was driven by an increase in available
insect biomass during moult. In our study we found a similar pattern, with more rainfall being
associated with higher red chromaticity scores (Figure 2). When looking at blue chromaticity and
rainfall we found that areas with lower levels of precipitation were associated with higher blue
chromaticity scores (Figure 2). A possible explanation for this is that flycatchers living in drier
habitats use structural colours as a more efficacious signal (Medina I et al. 2017). A study done on
mountain bluebirds (Sialia currucoides) found that along with precipitation, temperature also
increased the production of bright, structurally coloured feathers (Ward et al. 2021). From this we
can assume that temperature could also be indirectly affecting the relationship we have found
between diet and chromaticity (Ward et al. 2021). Our results show that there is a negative
relationship between red chromaticity and temperature (Figure 3), and that temperature did not
have a significant effect on blue chromaticity. One possibility is that the negative relationship found
between red chromaticity and temperature could be due to the stress that is added when
temperatures become too hot, causing a decrease in foraging activity (Edwards et al. 2015).
Gloger’s rule predicts that brighter coloured individuals will be found at lower latitudes,
where there is more precipitation and warmer temperatures. We did not find a significant
relationship between red and blue chromaticity and latitude; however, we did find a positive
relationship between latitude and both red and blue dichromatism (Figure 5). Based on previous
studies that found increased dichromatism at higher latitudes (Friedman et al. 2009, Simpson et al.
2015), we predicted that latitude would be positively associated with both red and blue
18

dichromatism in Tyrannidae. Our results confirm that an increase in latitude was associated with
an increase in sexually dimorphic species, for both red and blue chromaticity. This increase in
dichromatism with latitude could be caused by an increase in intrasexual competition, or an
increase in predation risk with migration (Badyaev and Hill 2003). Friedman et al. 2009 examined
the effects of migration on sexual dichromatism in New world orioles (genus Icterus), independent
of sexual selection, and found that sexual dichromatism is 23 times more likely to evolve in
migratory species, caused by a reduction in female elaboration. To better understand the evolution
of dichromatism in Tyrannidae, future studies should use ancestral state reconstructions to
determine whether dichromatism results from a loss or gain of elaboration and whether this pattern
is associated with gains of migratory behaviour.
The species recognition hypothesis states that differences among species in plumage
elaboration have evolved to reduce hybridization, by allowing birds to recognize individuals that
are not of the same species (Sætre et al. 1997, Seddon 2005). As such, we predicted that species
living in closer proximity would display more divergence in their plumage elaboration. Consistent
with our hypothesis, we found a negative relationship between red and blue chromaticity distance
and geographic distance; however, the relationship was relatively weak. This weak relationship
suggests that there is likely another aspect of flycatcher appearance or behaviour that has a stronger
influence on species recognition. A study focusing on chestnut-bellied flycatchers (Monarcha
castaneiventris) found that both plumage and song are used in species recognition, implying that
we would likely also find multiple factors influencing species recognition if we examined this at
the family level (Uy et al. 2009). A study done on another group of flycatchers (Empidonax traillii)
by Mahoney et al. 2020 found that when looking at the subspecies level, song, not plumage, is
strongly associated with species recognition. Thus, song may in fact, be a better delineator of
species’ boundaries in at least some members of this family.
19

Overall, this large-scale phylogenetic analysis examines the factors influencing the
evolution of Tyrant flycatcher plumage colouration, focusing on the underlying processes that have
allowed the plumage to evolve and diverge. Our study showed that plumage colouration was
influenced by a complex combination of ecological, biological, and geographical factors. Plumage
colouration appear to be strongly influenced by diet and weather, though the extent of
dichromatism was most strongly influenced by latitude. To better understand the mechanisms
driving dichromatism in Tyrannidae, future studies could investigate whether dichromatism results
from a loss or gain of plumage elaboration due to migratory behaviour—a pattern observed in
orioles and warblers (Friedman et al. 2009, Simpson et al. 2015). Although we did find that species
living closer together are more likely to have dissimilar plumage, the relationship was weak and
we predict that song, instead of plumage, may be more important for maintaining species
boundaries.

20

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APPENDIX
Table 5. Post hoc test results examining the effects of dietary guild on red and blue chromaticity.
Bolded terms are significant.
Variable

Sex
Male

Red chromaticity
Female

Male
Blue
chromaticity
Female

Guild

emmean

SE

df

t.ratio

p-value

Herbivore

0.447

0.0482

374

9.280

<.0001

Invertivore

0.381

0.0452

374

8.446

<.0001

Omnivore

0.394

0.0456

374

8.647

<.0001

Herbivore

0.444

0.0451

374

9.829

<.0001

Invertivore

0.382

0.0423

374

9.023

<.0001

Omnivore

0.397

0.0427

374

9.283

<.0001

Herbivore

0.185

0.0638

375

2.907

0.0039

Invertivore

0.266

0.0597

375

4.450

<.0001

Omnivore

0.254

0.0604

375

4.207

<.0001

Herbivore

0.191

0.0617

375

3.097

0.0021

Invertivore

0.265

0.0577

375

4.594

<.0001

Omnivore

0.25

0.0583

375

4.293

<.0001

emmean = estimated marginal means, SE = standard error, df = degrees of freedom, t.ratio = test
statistic

25