Content uploaded by Jocelyn Poissant
Author content
All content in this area was uploaded by Jocelyn Poissant
Content may be subject to copyright.
Quantitative genetics and sex-specific selection
on sexually dimorphic traits in bighorn sheep
Jocelyn Poissant
1
, Alastair J. Wilson
2
, Marco Festa-Bianchet
3
,
John T. Hogg
4
and David W. Coltman
1,
*
1
Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada T6G 2E9
2
Institute of Evolutionary Biology, University of Edinburgh, West Mains Road, Edinburgh EH9 3JT, UK
3
De
´
partment de biologie, Universite
´
de Sherbrooke, Que
´
bec, Canada J1K 2R1
4
Montana Conservation Science Institute, 5200 Upper Miller Creek Road, Missoula, MT 59803, USA
Sexual conflict at loci influencing traits shared between the sexes occurs when sex-specific selection
pressures are antagonistic relative to the genetic correlation between the sexes. To assess whether there is
sexual conflict over shared traits, we estimated heritability and intersexual genetic correlations for highly
sexually dimorphic traits (horn volume and body mass) in a wild population of bighorn sheep (Ovis canadensis)
and quantified sex-specific selection using estimates of longevity and lifetime reproductive success. Body mass
and horn volume showed significant additive genetic variance in both sexes, and intersexual genetic
correlations were 0.24G0.28 for horn volume and 0.63G0.30 for body mass. For horn volume, selection
coefficients did not significantly differ from zero in either sex. For body weight, selection coefficients were
positive in females but did not differ from zero in males. The absence of detectable sexually antagonistic
selection suggests that currently there are no sexual conflicts at loci influencing horn volume and body mass.
Keywords: animal model; genetic correlation; heritability; lifetime reproductive success; selection;
sexual conflict
1. INTRODUCTION
The widespread occurrence of sexual dimorphism
suggests that optimal trait values often differ between the
sexes ( Fairbairn 2007). Because traits shared by the sexes
are typically influenced by the same genes (Roff 1997),
sexual conflicts at loci influencing shared traits (intralocus
sexual conflicts; Arnqvist & Rowe 2005) may be common.
While negative cross-sex genetic correlations for fitness in
many laboratory and wild populations (Chippindale et al.
2001; Brommer et al. 2007; Foerster et al. 2007) suggest
that such sexual conflicts may be common (Arnqvist &
Rowe 2005), they have very rarely been studied in nature
(Arnqvist & Rowe 2005; Rowe & Day 2006).
Since Darwin’s (1871) suggestion that certain con-
spicuous male traits may have evolved through male–male
combat, the massive sexually selected horns of male
bighorn sheep (Ovis canadensis; figure 1) have attracted
much attention from evolutionary biologists (Geist 1966;
Fitzsimmons et al. 1995; Coltman et al. 2002, 2003, 2005;
Festa-Bianchet et al. 2004). On the other hand, the smaller
horns of females have almost never been studied and have
no clearly known fitness benefit. The presence of horns in
females could result from a genetic correlation with male
horns. Alternatively, horns may be useful to both sexes but
differ in size if they have different functions. For example,
female horns may play an important role in defence
against predators and intraspecific competition (Packer
1983; Roberts 1996).
The aim of this study was to test for the presence of
sexual conflict at loci influencing horn size and body
weight in a pedigreed population of wild bighorn sheep
studied extensively for over 35 years (Coltman et al. 2005).
Because a sexual conflict at the genetic level requires
heritable traits, we first quantified additive genetic
variance in both sexes. We then assessed the importance
of genetic constraints on the evolution of sexual dimorph-
ism by estimating intersexual genetic correlations (r
g
).
Finally, we quantified sex-specific selection using field
estimates of longevity and reproductive success. Signi-
ficant heritability in both sexes for a shared trait could lead
to sexual conflict at the genetic level if it was combined
with sexually antagonistic selection and an intersexual
r
g
O0. Conflict would also be present when selection is in
the same direction in both sexes but where r
g
!0. We
included body mass in our analyses not only to control for
the influence of body size on horn size, but also to contrast
quantitative genetic parameters and selection at traits
varying in their degree of sexual dimorphism (horn size
being much more dimorphic than body mass). This study
represents a rare test of sexual conflict at loci influencing
shared traits (Arnqvist & Rowe 2005; Rowe & Day 2006)
and provides much needed information on the importance
of genetic constraints on the evolution of sexual dimorph-
ism in nature (Rice & Chippindale 2001; Fairbairn 2007).
2. MATERIAL AND METHODS
(a) Study site and data collection
The study population inhabits Ram Mountain, Alberta,
Canada (528 N, 1158 W, elevation 1080–2170 m). Techniques
used to capture, mark, measure and monitor individuals are
Proc. R. Soc. B (2008) 275, 623–628
doi:10.1098/rspb.2007.1361
Published online 23 January 2008
One contribution of 18 to a Special Issue ‘Evolutionary dynamics of
wild populations’.
* Author for correspondence (dcoltman@ualberta.ca).
Received 7 November 2007
Accepted 28 November 2007
623 This journal is q 2008 The Royal Society
described in detail elsewhere (Jorgenson et al. 1993). The data
presented here were collected from 1970 to 2006. Briefly,
animals were captured in a corral trap baited with salt from late
May to September or early October each year. Almost all
animals were marked as lambs or yearlings, so that their exact
age was known. Individuals first captured as adults were aged
by counting horn growth rings. Marked sheep were monitored
throughout their lifetime.
Ewes and young rams are usually captured multiple times
each year, while rams 3 years and older are typically caught
only one to three times per season, usually in June or July. At
each capture, sheep are weighed to the nearest 250 g with a
Detecto spring scale. The horn length along the outside
curvature and the horn base circumference are measured to the
nearest millimetre for both horns using tape. Horn volume
(cm
3
) was calculated assuming a conical shape using the
average horn base circumference of both horns and the length
of the longest horn to reduce the influence of horn breakage.
(b) Pedigree information
The pedigree used in this study includes 764 maternal and
435 paternal links. It differs from the one in Coltman et al.
(2005) by the addition of individuals born between 2003 and
2006. Maternity was accurately determined from field
observations of suckling behaviour. Paternity was determined
using paternity test and half-sib reconstruction based on
genotypes at approximately 30 microsatellite loci for samples
collected from 1988 to 2006. The laboratory and statistical
methods are detailed in Coltman et al. (2005).
(c) Quantitative genetic analysis
Phenotypic variance in horn volume and body mass was
partitioned into additive genetic and other components using
an animal model and restricted maximum likelihood with the
program ASR
EML v. 2.0 (Gilmour et al.2006). The animal
model is a form of mixed model incorporating pedigree
information where the phenotype of each individual is
modelled as the sum of its additive genetic value and other
random and fixed effects. This method is particularly useful for
the study of natural populations because it optimizes the use of
information from complex and incomplete pedigrees when
estimating quantitative genetic parameters (Kruuk 2004).
Prior to analysis each trait for each age/sex class was
standardized to a standard deviation of unity. We then
partitioned the phenotypic variance left after taking into
account fixed effects into five components: additive genetic
(V
a
), permanent environmental (V
pe
), year (V
y
), year of birth
(V
yob
) and residual (V
r
). We also attempted to include a
maternal effect component but this often caused convergence
problems for bivariate models. Since the influence of maternal
effects for body size is known to be negligible by age 2 in the
study population (Wilson et al.2005), we decided not to
include maternal effects and to restrict our analysis to adult
sheep (2 years old and older). We also excluded animals older
than 5 years because the distribution of phenotypes in older
males is biased by trophy hunting (Coltman et al.2003;
Festa-Bianchet et al.2004) and most rams become vulnerable
to hunting at 5–7 years of age depending on their rate of horn
growth. Year and year of birth were fitted to account for the
influence of environmental variation (Postma 2006; Kruuk &
Hadfield 2007). Since different individuals were sampled at
different points within sampling seasons, we included day of
capture (continuous, second-order polynomial, with 24 May
as day 0) as a fixed effect. Since growth patterns differ between
age classes, we also fitted age (factor) and the age!date
interaction. We used bivariate models to estimate covariances
and correlations within and between the sexes. The signi-
ficance of (co)variance components was assessed using
likelihood ratio tests. Narrow sense heritability (h
2
) and other
ratios were calculated by dividing the appropriate variance
component by V
p
(e.g. V
a
/V
p
for h
2
), where V
p
ZV
a
CV
pe
C
V
y
CV
yob
CV
r
. The significance of ratios and correlations was
not explicitly tested but was instead inferred from the
significance of their associated (co)variance components.
Since a main objective of this study was to assess the
importance of genetic constraints, we also verified whether
genetic correlations were smaller than unity using likelihood
ratio tests. The number of individuals and measurements
included in the animal models are presented in table 1.
(d) Selection analysis
Our selection analyses were based on estimates of lifetime
reproductive success (LRS, number of lambs produced that
survived to weaning), longevity (in years) and mean
reproductive success (MRSZLRS!longevity
K1
). Separate
analyses were performed for males and females. We only
included animals that were born before 1996 so that every
individual had the opportunity to reach 10 years of age. For
LRS and MRS, we only included genotyped males that have
been DNA sampled and therefore included in paternity
analyses. Females that had received contraceptive implants
and individuals removed for translocations or research
purposes were excluded from the analysis. To account for
changes in density and environmental conditions, we fitted
year of birth as a factor in all models. Cohorts comprising a
single informative individual were therefore omitted (1968
and 1994 for male longevity, 1980 and 1994 for male
reproductive success and 1974 for female longevity and
reproductive success).
(a)
(b)
Figure 1. (a) Adult male and (b) female bighorn sheep from Ram Mountain, Alberta, Canada. Photos by Julien Martin.
624 J. Poissant et al. Sexual conflict in bighorn sheep
Proc. R. Soc. B (2008)
We estimated sex-specific standardized linear and quad-
ratic selection differentials and gradients using linear
regression (Lande & Arnold 1983). For phenotypic values,
we used body mass and horn volume at age 4 corrected to 5
June. These corrected values were obtained using individual
linear regressions for individuals sampled multiple times and
using mean population growth rate for individuals sampled
only once. The significance of coefficients was tested using
generalized linear models with negative binomial error for
LRS and Poisson error for longevity. For MRS, we used a
linear model with a square root transformation. Neither
quadratic nor interaction terms were statistically significant
and are therefore not shown. These analyses were performed
using S-P
LUS v. 7.0 ( Insightful).
3. RESULTS
(a) Quantitative genetic parameters
Body mass and horn volume showed significant additive
genetic variance in both sexes (table 2). The proportion of
phenotypic variance explained by additive genetic effects
after accounting for fixed effects ranged from 0.11G0.05
for female body mass (FBM) to 0.32G0.12 for male body
mass (MBM) and male horn volume (MHV; table 3). Year
and year of birth were also significant for all traits and
combined they explained 33–58% of the variation (tables
2 and 3). Finally, permanent environmental effects which
include non-additive genetic variance were also significant
for all traits and accounted for 14–27% of the variation
(tables 2 and 3).
Table 2. Additive genetic, year, year of birth and permanent environmental (co)variance components and correlations within
and between the sexes for body mass and horn volume in adult bighorn sheep. (Variance components are on the diagonal while
covariance components are below the diagonal and correlations are above the diagonal. Variance components were obtained
with sex-specific univariate animal models whereas covariances where obtained from bivariate models. Significance of
(co)variance components was tested with likelihood ratio tests.
p!0.05,
p!0.01 and
p!0.001. The significance of
genetic correlations (in italics when different from zero) was inferred from the significance of associated covariance components.
†
Identifies genetic correlations significantly smaller than unity (
†
p!0.05 and
††
p!0.01). Standard errors generated by ASREML
are also presented. MBM, male body mass; MHV, male horn volume; FBM, female body mass and FHV, female horn volume.)
MBM MHV FBM FHV
additive genetic
MBM 0.19 (0.07)
0.74 (0.15) 0.63 (0.30) 0.27 (0.30)
†
MHV 0.15 (0.07)
0.22 (0.09)
0.02 (0.29)
††
0.24 (0.28)
†
FBM 0.08 (0.04)
0.00 (0.05) 0.10 (0.04)
0.63 (0.20)
†
FHV 0.06 (0.06) 0.06 (0.07) 0.10 (0.05)
0.25 (0.10)
year
MBM 0.08 (0.02)
0.70 (0.11) 0.51 (0.16) 0.53 (0.15)
MHV 0.06 (0.02)
0.10 (0.03)
K0.56 (0.14) K0.23 (0.20)
FBM 0.07 (0.03)
K0.11 (0.04)
0.28 (0.08)
0.90 (0.04)
FHV 0.05 (0.02)
K0.02 (0.02) 0.19 (0.06)
0.11 (0.03)
year of birth
MBM 0.12 (0.05)
0.96 (0.04) 0.10 (0.26) 0.30 (0.25)
MHV 0.15 (0.06)
0.18 (0.06)
K0.10 (0.23) 0.37 (0.22)
FBM 0.02 (0.04) K0.03 (0.06) 0.26 (0.08)
0.93 (0.04)
FHV 0.05 (0.04) 0.08 (0.06) 0.29 (0.09)
0.26 (0.09)
permanent environment
MBM 0.12 (0.06)
0.75 (0.20) ——
MHV 0.10 (0.06)
0.14 (0.08)
——
FBM — — 0.13 (0.04)
0.32 (0.17)
FHV — — 0.06 (0.04) 0.28 (0.08)
Table 1. Phenotypic data for body mass (kg) and horn volume (cm
3
) in bighorn sheep. (Number of individuals and observations
included in the animal models are indicated as well as age-specific trait means and variation (s.d.). Each sex/age class was
standardized (s.d. of unity) prior to analysis.)
trait/age
males females
23452345
body mass
individuals 203 169 142 119 235 222 199 177
observations 502 340 237 184 703 695 609 544
mean 56.6 69.1 77.3 83.5 48.6 56.3 60.0 62.5
s.d. 10.5 10.1 10.4 10.6 7.9 7.4 7.1 7.2
horn volume
individuals 201 169 145 121 225 210 189 164
observations 498 339 240 186 620 596 526 457
mean 486.8 1133.7 1877.8 2412.6 70.6 103.2 120.0 124.9
s.d. 237.4 431.1 597.6 592.2 24.2 25.7 27.2 25.6
Sexual conflict in bighorn sheep J. Poissant et al. 625
Proc. R. Soc. B (2008)
The r
g
estimates were relatively large and significantly
positive for three pairs of traits (table 2). These included r
g
for pairs of traits within each sex (body mass versus horn
volume) and between male and FBM. On the other hand,
intersexual r
g
involving horn volume was all relatively
small and significantly smaller than unity (table 2).
With the exception of covariance between MHV and
female traits, year and year of birth appeared to affect pairs
of traits similarly (table 2). In particular, year and year of
birth correlations were close to unity for pairs of traits
within each sex. The within-sex correlation for permanent
environmental effects was close to unity in males (0.75G
0.20) and negligible in females (0.06G0.04; table 2).
(b) Selection analysis
Selection coefficients were relatively small in both sexes
(table 4). In males, none of the selection coefficients for
body mass and horn volume were significant. However,
MHV showed a non-significant trend for a negative
association with longevity after accounting for selection
on body mass (K0.11G0.06, pZ0.13; table 4). In females,
selection differentials and gradients for body mass were all
positive and significant. There was no evidence for
directional selection on female horn volume (FHV).
4. DISCUSSION
(a) Quantitative genetic parameters
Body mass and horn volume showed significant additive
genetic variance in both sexes. Quantitative genetic
parameters had previously been estimated for FBM and
male traits (Re
´
ale et al. 1999; Coltman et al. 2003, 2005;
Pelletier et al.2007) but not for female horn size.
Heritability of horn volume in females was comparable
with the male estimate (h
2
Z0.24G0.09 versus 0.32G
0.12, respectively).
Our estimates of the genetic correlation between horn
size and body mass in females were significantly smaller
than unity. This is important because it suggests that horn
volume can evolve relative to body size in that sex. In
contrast, the same genetic correlation was not significantly
smaller than unity in males (0.74G0.15, pZ0.11). This is
consistent with the results of Coltman et al.(2003, 2005)
and suggests that the evolution of horn size relative to
body mass may be more constrained in males.
One of our main goals was to evaluate the importance
of genetic constraints on the evolution of sexual dimorph-
ism in bighorn sheep. As previously shown (Coltman et al.
2003, 2005), we found that the evolution of body size
sexualdimorphismmaybeconstrainedbyalarge
intersexual r
g
(0.63G0.30). On the other hand, r
g
was
smaller than unity for many other pairs of traits, which
suggests that horn volume should be able to evolve partly
independently in each sex and that sex-specific optima
could be reached more readily (Lande 1980). In
particular, the intersexual r
g
for horn volume was quite
small (0.24G0.28) and similar to estimates reported for
other highly sexually dimorphic traits in other species (e.g.
fat deposition in humans, Comuzzie et al. 1993; antenna
length in the fly Prochyliza xanthostoma, Bonduriansky &
Rowe 2005). This is consistent with the prediction that
sexual dimorphism and intersexual r
g
should be negatively
correlated in response to sexually divergent selection
(Bonduriansky & Rowe 2005; Fairbairn & Roff 2006).
(b) Selection analysis
None of the selection coefficients differed significantly
from zero in males. However, rams with fast-growing
Table 4. Sex-specific standardized directional selection differentials (S
0
i
) and gradients (b
0
i
) for body mass and horn volume in
bighorn sheep. (Male and female data were analysed separately. Analyses were based on phenotypic values on 5 June at 4 years
old. Fitness was defined as LRS (number of lambs produced that survived to weaning over an individual’s lifetime), longevity (in
years) and mean reproductive success (MRS, LRS!longevity
K1
).) Significant coefficients ( p!0.05) are italicized.
trait fitness metric n S
0
i
p b
0
i
p
male body mass LRS 72 K0.09 (0.25) 0.68 K0.12 (0.36) 0.87
longevity 129 K0.02 (0.04) 0.72 0.04 (0.05) 0.49
MRS 72 0.03 (0.21) 0.99 K0.02 (0.29) 0.91
male horn volume LRS 72 K0.05 (0.26) 0.50 0.03 (0.38) 0.58
longevity 128 K0.08 (0.05) 0.15 K0.11 (0.06) 0.13
MRS 72 0.06 (0.21) 0.89 0.07 (0.31) 0.86
female body mass LRS 137 0.13 (0.06) !0.05 0.16 (0.07) !0.01
longevity 137 0.09 (0.04) !0.05 0.11 (0.04) !0.05
MRS 137 0.08 (0.04) !0.05 0.10 (0.05) !0.05
female horn volume LRS 133 0.06 (0.05) 0.29 0.01 (0.06) 0.97
longevity 133 0.03 (0.03) 0.39 K0.01 (0.04) 0.87
MRS 133 0.01 (0.04) 0.73 K0.02 (0.04) 0.22
Table 3. Sex-specific proportions of phenotypic variance explained by additive genetic (h
2
), year, year of birth and permanent
environmental effects. (Standard errors generated by ASR
EML are also presented. MBM, male body mass; MHV, male horn
volume; FBM, female body mass and FHV, female horn volume.)
trait h
2
year year of birth perm. env.
MBM 0.32 (0.12) 0.13 (0.04) 0.20 (0.07) 0.21 (0.11)
MHV 0.32 (0.12) 0.14 (0.04) 0.25 (0.07) 0.20 (0.11)
FBM 0.11 (0.05) 0.30 (0.06) 0.28 (0.07) 0.14 (0.04)
FHV 0.24 (0.09) 0.11 (0.03) 0.25 (0.07) 0.27 (0.08)
626 J. Poissant et al. Sexual conflict in bighorn sheep
Proc. R. Soc. B (2008)
horns are artificially selected against by trophy hunters
in the study population (Coltman et al. 2003; Festa-
Bianchet et al.2004). Each year approximately 40% of
rams with horns that satisfy the legal definition of a
harvestable ram are shot. The trend towards a negative
association between horn volume and longevity after
controlling for selection on body mass (K0.11G0.06,
pZ 0.13) probably results from hunting pressure. A
similar negative relationship between horn volume and
longevity was documented in Soay sheep where it
probably results from the cost of growing and carrying
large horns (Robinson et al.2006). In our study
population, any natural selection against large horns is
unlikely to be expressed because of trophy hunting
(Coltman et al.2003; Festa-Bianchet et al.2004). It may
also be that artificial selection more effectively targets total
horn length or morphology rather than horn volume in
bighorn sheep. For example, harvest restrictions are based
on horn length and shape, not on horn volume. Similarly,
horn length is a good correlate of mating success in rams
after accounting for age (Coltman et al. 2002). Horn
volume may reflect the metabolic costs of growing and
carrying horns, however, total horn length may be more
relevant in terms of artificial and sexual selection.
Selection differentials and gradients for body mass
were all significantly positive in females. Coltman et al.
(2005) and Pelletier et al.(2007)also observed positive
relationships between body mass in June and female
fitness. On the other hand, horn volume does not appear
to be under directional selection in females. This
contrasts with the negative association observed between
horn size and LRS in female Soay sheep (Robinson et al.
2006). It may be that female horns in bighorn sheep are
so small relative to body size that they do not incur an
easily detectable fitness cost.
In summary, we tested for intralocus sexual conflict in a
wild population of bighorn sheep by estimated quan-
titative genetic parameters and selection coefficients for
two sexually dimorphic traits. Because all traits showed
significant additive genetic variance and all genetic
correlations were positive, sexual conflicts at the genetic
level are possible in the presence of sexually antagonistic
selection. However, the absence of detectable sexually
antagonistic selection suggests that there are currently no
such conflicts.
This research was funded by the Alberta Conservation
Association, the Yukon Department of Environment, the
Natural Environment Research Council (UK), the Natural
Sciences and Engineering Research Council (NSERC,
Canada), Sustainable Resource Development (Alberta),
Alberta Ingenuity, the Charles Engelhard Foundation,
Eppley Foundation for Research, Juniper Hill, Inc., National
Geographic Society and the Tim and Karen Hixon Foun-
dation. We are grateful for the logistic support of the Alberta
Forest Services. J.P. was supported by graduate scholarships
from the University of Alberta, Alberta Ingenuity and
NSERC. A.J.W. was supported by the Natural Environment
Research Council (UK). D.W.C. is an Alberta Ingenuity
Scholar. We would like to thank Loeske Kruuk, Bill Hill,
Fanie Pelletier and anonymous referees for their comments
on previous versions of this manuscript. We also thank the
many students, colleagues, volunteers and assistants who
contributed to this research. In particular, Jon Jorgenson
provided invaluable help and expertise for over 30 years.
REFERENCES
Arnqvist, G. & Rowe, L. 2005 Sexual conflict. Princeton, NJ:
Princeton University Press.
Bonduriansky, R. & Rowe, L. 2005 Intralocus sexual conflict
and the genetic architecture of sexually dimorphic traits in
Prochyliza xanthostoma (Diptera: Piophilidae). Evolution
59, 1965–1975.
Brommer, J. E., Kirkpatrick,M., Qvarnstro¨m, A. & Gustafsson,
L. 2007 The intersexual genetic correlation for lifetime
fitness in the wild and its implications for sexual selection.
PLoS ONE 2, e744. (doi:10.1371/journal.pone.0000744)
Chippindale, A. K., Gibson, J. R. & Rice, W. R. 2001
Negative genetic correlation for adult fitness between
sexes reveals ontogenetic conflict in Drosophila. Proc. Natl
Acad. Sci. USA 98, 1671–1675. (doi:10.1073/pnas.
041378098)
Coltman, D. W., Festa-Bianchet, M., Jorgenson, J. T. &
Strobeck, C. 2002 Age-dependent sexual selection in
bighorn rams. Proc. R. Soc. B 269, 165–172. (doi:10.1098/
rspb.2001.1851)
Coltman, D. W., O’Donoghue, P., Jorgenson, J. T., Hogg,
J. T., Strobeck, C. & Festa-Bianchet, M. 2003 Undesir-
able consequences of trophy hunting. Nature 426,
655–658. (doi:10.1038/nature02177)
Coltman, D. W., O’Donoghue, P., Hogg, J. T. & Festa-
Bianchet, M. 2005 Selection and genetic (co)variance in
bighorn sheep. Evolution 59, 1372–1382.
Comuzzie, A. G., Blangero, J., Mahaney, M. C., Mitchell,
B. D., Stern, M. P. & Maccluer, J. W. 1993 Quantitative
genetics of sexual dimorphism in body fat measurements.
Am. J. Hum. Biol. 5, 725–734. (doi:10.1002/ajhb.131
0050616)
Darwin, C. 1871 The descent of man and selection in relation to
sex. London, UK: J. Murray.
Fairbairn, D. J. 2007 Introduction: the enigma of sexual size
dimorphism. In Sex, size and gender roles. Evolutionary
studies of sexual dimorphism (eds D. J. Fairbairn, W. U.
Blanckenhorn & T. Sze
´
kely), pp. 1–15. Oxford, UK:
Oxford University Press.
Fairbairn, D. J. & Roff, D. A. 2006 The quantitative genetics of
sexual dimorphism: assessing the importance of sex-linkage.
Heredity 97,319–328.(doi:10.1038/sj.hdy.6800895)
Festa-Bianchet, M., Coltman, D. W., Turelli, L. & Jorgenson,
J. T. 2004 Relative allocation to horn and body growth in
bighorn rams varies with resource availability. Behav. Ecol.
15, 305–312. (doi:10.1093/beheco/arh014)
Fitzsimmons, N. N., Buskirk, S. W. & Smith, M. H. 1995
Population history, genetic variability, and horn growth in
bighorn sheep. Conserv. Biol. 9, 314–323. (doi:10.1046/
j.1523-1739.1995.9020314.x)
Foerster, K., Coulson, T., Sheldon, B. C., Pemberton, J. M.,
Clutton-Brock, T. H. & Kruuk, L. E. B. 2007 Sexually
antagonistic genetic variation for fitness in red deer. Nature
447, 1107–1110. (doi:10.1038/nature05912)
Geist, V. 1966 The evolutionary significance of mountain sheep
horns. Evolution 20,558–566.(doi:10.2307/2406590)
Gilmour, A. R., Gogel, B. J., Cullis, B. R. & Thompson, R.
2006 ASR
EML user guide. Release 2.0. Hemel Hempstead,
UK: VSN International.
Jorgenson, J. T., Festa-Bianchet, M. & Wishart, W. D. 1993
Harvesting bighorn ewes: consequences for population
size and trophy ram production. J. Wildl. Manage. 57,
429–435. (doi:10.2307/3809267)
Kruuk, L. E. B. 2004 Estimating genetic parameters in
natural populations using the ‘animal model’. Phil. Trans.
R. Soc. B 359, 873–890. (doi:10.1098/rstb.2003.1437)
Kruuk, L. E. B. & Hadfield, J. D. 2007 How to separate
genetic and environmental causes of similarity between
relatives. J. Evol. Biol. 20, 1890–1903. (doi:10.1111/
j.1420-9101.2007.01377.x)
Sexual conflict in bighorn sheep J. Poissant et al. 627
Proc. R. Soc. B (2008)
Lande, R. 1980 Sexual dimorphism, sexual selection, and
adaptation in polygenic characters. Evolution 34, 292–305.
(doi:10.2307/2407393)
Lande, R. & Arnold, S. J. 1983 The measurement of selection
on correlated characters. Evolution 37 , 1210–1226.
(doi:10.2307/2408842)
Packer, C. 1983 Sexual dimorphism: the horns of African
antelopes. Science 221, 1191–1193. (doi:10.1126/science.
221.4616.1191)
Pelletier, F., Reale, D., Garant, D., Coltman, D. W. & Festa-
Bianchet, M. 2007 Selection on heritable seasonal
phenotypic plasticity of body mass. Evolution 61,
1969–1979. (doi:10.1111/j.1558-5646.2007.00160.x)
Postma, E. 2006 Implications of the difference between true
and predicted breeding values for the study of natural
selection and micro-evolution. J. Evol. Biol. 19, 309–320.
(doi:10.1111/j.1420-9101.2005.01007.x)
Re
´
ale, D., Festa-Bianchet, M. & Jorgenson, J. T. 1999
Heritability of body mass varies with age and season in
wild bighorn sheep. Heredity 83, 526–532. (doi:10.1038/sj.
hdy.6885430)
Rice, W. R. & Chippindale, A. K. 2001 Intersexual ontogenetic
conflict. J. Evol. Biol. 14,685–693.(doi:10.1046/j.1420-
9101.2001.00319.x)
Roberts, S. C. 1996 The evolution of hornedness in female
ruminants. Behaviour 133 , 399–442.
Robinson, M. R., Pilkington, J. G., Clutton-Brock, T. H.,
Pemberton, J. M. & Kruuk, L. E. B. 2006 Live fast, die
young: trade-offs between fitness components and sexually
antagonistic selection on weaponry in soay sheep.
Evolution 60, 2168–2181.
Roff, D. A. 1997 Evolutionary quantitative genetics. New York,
NY: Chapman & Hall.
Rowe, L. & Day, T. 2006 Detecting sexual conflict and
sexually antagonistic coevolution. Phil. Trans. R. Soc. B
361, 277–285. (doi:10.1098/rstb.2005.1788)
Wilson, A. J., Kruuk, L. E. B. & Coltman, D. W. 2005
Ontogenetic patterns in heritable variation for body size:
using random regression models in a wild ungulate
population. Am. Nat. 166, E177–E192. (doi:10.1086/
497441)
628 J. Poissant et al. Sexual conflict in bighorn sheep
Proc. R. Soc. B (2008)
A preview of this full-text is provided by The Royal Society.
Content available from Proceedings of the Royal Society B
This content is subject to copyright.
