A network of 14 meteorological stations was installed across the Annapurna range before
the 1999 monsoon season, and expanded to 19 stations encompassing 28 rain gauges in
2000. Rainfall is totalled every 30min. ‘Look-down’ distance rangers and g-ray loggers
measure snow depth and total water content, respectively, once a day at high elevations
(.2,500m inthe Greater Himalaya).Only liquid precipitation is measuredin the Tibetan
zone, such that the annual (but not the monsoon) total is underestimated here. The data
presentedhere(Fig. 2b)represent monsoon averagesbased onthe longest recordavailable
from each station.
Apatite fission-track dating
Followingmineral separation, apatiteswerepolished, etchedandirradiated.Standardand
induced track densities were determined on Brazil ruby muscovite external detectors
(geometry factor 0.5), and fossil track densities were determined on internal mineral
surfaces. Ages were calculated using z ¼ 359 ^ 20 for dosimeter glass CN-5. All ages are
central ages and are reported with 1j errors. Long-term erosion rates are conservatively
estimated on the basis of the fission-track age, and assuming a geothermal gradient of
1008Ckm21and an annealing temperature of 1408C.
A 3-arcsec(,90m)digital elevation model (DEM) isthebasis ofalltopographicanalyses.
Hillslope angles are calculated at every pixel in the DEM based on a 3 £ 3 pixel
(,180 £ 180m) grid. Mean hillslope angles were extracted from a moving, 5-km-radius
window centred on the Marsyandi River. Maximum, minimum and mean elevation (Fig.
2) were calculated along a 50-km-wide swath oriented perpendicular to the strike of the
photographs, and transferred first to 1:50,000 scale topographic maps and then to the
digital topography. Based on glacial hypsometry, equilibrium-line altitudes were
estimated with an assumed accumulation-area ratio of 0.65. To avoid uncertainty
introduced by avalanches on to glaciers from adjacent high peaks, 29 small glaciers (95%
are ,2.5km2), lacking high headwalls, were analysed. The regional equilibrium-line
altitude gradient shows little sensitivity to accumulation-area ratios ranging from 0.4 to
Specific stream power
(,4,200m elevation) of the study area. These basins drain approximately half of the
landscape and are sufficiently large to be fluvial, as opposed to colluvial/debris flow,
channels. Monsoon rainfall was smoothed across the meteorological network to define an
average precipitationgradientperpendicular tothestrikeofthetopography. Thisgradient
was then extrapolated parallel to strike across the study area. For each river segment
$500m long, channel gradients (S) wereextracted from the DEM, and discharge (Q) was
all rainfall is assumed to enter channels. Channel width (W) is calculated as 1022Q0.4.
water and g is gravitational acceleration. Channel gradients and specific stream power are
binned every 5km.
Received 20 June; accepted 4 November 2003; doi:10.1038/nature02187.
1. Koons, P. O. The topographic evolution of collisional mountain belts: A numerical look at the
Southern Alps, New Zealand. Am. J. Sci. 289, 1041–1069 (1989).
2. Beaumont, C., Jamieson, R. A., Nguyen, M. H. & Lee, B. Himalayan tectonics explained by extrusion
3. Willett, S. D. Orogeny and orography: The effects of erosion on the structure of mountain belts.
J. Geophys. Res. 104, 28957–28982 (1999).
4. Hodges, K. V. Tectonics of the Himalaya and southern Tibet from two perspectives. Geol. Soc. Am.
Bull. 112, 324–350 (2000).
5. Tapponnier, P. et al. Oblique stepwise rise and growth of the Tibetan Plateau. Science 394, 1671–1677
6. Burchfiel, B. D. et al. The South Tibetan detachment system, Himalayan orogen: Extension
contemporaneous with and parallel to shortening in a collisional mountain belt. Geol. Soc. Am. Spec.
Pap. 269, 1–41 (1992).
7. Harrison, T. M. et al. A late Miocene-Pliocene origin for the central Himalayan inverted
metamorphism. Earth Planet. Sci. Lett. 146, E1–E7 (1997).
8. Catlos, E. J. et al. Geochronologic and thermobarometric constraints on the evolution of the Main
Central Thrust, central Nepal Himalaya. J. Geophys. Res. 106, 16177–16204 (2001).
9. Robinson, D. M. et al. Kinematic model for the Main Central thrust in Nepal. Geology 31, 359–362
10. Hurtado, J. M. Jr, Hodges, K. V. & Whipple, K. Neotectonics of the Thakkhola Graben and
Soc. Am. Bull. 113, 222–240 (2001).
12. Stu ¨we, K., White, L. & Brown, R. The influence of eroding topography on steady-state isotherms.
Application to fission track analysis. Earth Planet. Sci. Lett. 124, 63–74 (1994).
13. Willett, S. D. & Brandon, M. T. On steady states in mountain belts. Geology 30, 175–178 (2002).
14. Zeitler, P. K. Cooling history of the NW Himalaya, Pakistan. Tectonics 4, 127–151 (1985).
15. Tippett, J. M. & Kamp, P. J. J. Fission track analysis of the Late Cenozoic vertical kinematics of
continental Pacific crust, South Island, New Zealand. J. Geophys. Res. 98, 16119–16148 (1993).
16. Porter, S. C. Some geological implication of average Quaternary glacial conditions. Quat. Res. 32,
17. Ehlers,T.A., Armstrong, P.A.&Chapman,D.S. Normalfaultthermalregimesandthe interpretation
of low-temperature thermochronometers. Phys. Earth Planet. Inter. 126, 179–194 (2001).
Go ¨ttinger Geogr. Abh. 81, 105–121 (1986).
19. Duncan, C. C., Klein, A. J., Masek, J. G. & Isacks, B. L. Comparison of Late Pleistocene and modern
glacier extents in central Nepal based on digital elevation data and satellite imagery. Quat. Res. 49,
20. Hallet, B., Hunter, L. & Bogen, J. Rates of erosion and sediment evacuation by glaciers: A review of
field data and their implications. Glob. Planet. Change 12, 213–235 (1996).
21. Hodges, K. V., Parrish, R. R. & Searle, M. P. Tectonic evolution of the central Annapurna Range,
Nepalese Himalayas. Tectonics 15, 1264–1291 (1996).
22. Burbank, D. W. et al. Bedrock incision, rock uplift, and threshold hillslopes in the northwestern
Himalaya. Nature 379, 505–510 (1996).
23. Whipple, K. E., Kirby, E. & Brocklehurst, S. H. Geomorphic limits to climate-induced increases in
topographic relief. Nature 401, 39–43 (1999).
24. Sklar, L. & Dietrich, W. E. Sediment supply, grain size and rock strength controls on rates of river
incision into bedrock. Geology 29, 1087–1090 (2001).
25. Wang, Q. et al. Present-day crustal deformation in China constrained by Global Positioning System
measurements. Science 294, 574–577 (2001).
26. Willett, S. D., Slingerland, R. & Hovius, N. Uplift, shortening, and steady state topography in active
mountain belts. Am. J. Sci. 301, 455–485 (2001).
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Acknowledgements This work benefited from discussions with K. Hodges, J. Lave ´, A. Heimsath,
K. Whipple, P. Koons, M. Brandon and T. Ehlers. We thank P. Molnar and C. Beaumont for
comments and suggestions. Logistical support from Himalayan Experience and the Nepalese
Department ofHydrology andMeteorology is gratefullyacknowledged.This workwasfunded by
the NSF Continental Dynamics program and by NASA.
Competing interests statement The authors declare that they have no competing financial
Correspondence and requests for materials should be addressed to D.W.B.
consequences of trophy hunting
Curtis Strobeck4& Marco Festa-Bianchet5
1Department of Animal and Plant Sciences, University of Sheffield,
Sheffield S10 2TN, UK
2Alberta Department of Sustainable Development, Fish and Wildlife Division,
Box 1059, Canmore, Alberta T0L 0M0, Canada
3Montana Conservation Science Institute, Missoula, Montana 59803, USA
4Department of Biological Sciences, University of Alberta, Edmonton,
Alberta T6G 2E9, Canada
5De ´partementdebiologie, Universite ´deSherbrooke,Sherbrooke,Que ´becJ1K2R1,
Phenotype-based selective harvests, including trophy hunting,
ment if they target heritable traits1–3. Here we show that in an
evolutionary response to sport hunting of bighorn trophy rams
(Ovis canadensis) body weight and horn size have declined
significantly over time. We used quantitative genetic analyses,
based on a partly genetically reconstructed pedigree from a
30-year study of a wild population in which trophy hunting
targeted rams with rapidly growing horns4, to explore the
evolutionary response to hunter selection on ram weight and
rams were of significantly higher genetic ‘breeding value’ for
weight and horn size than rams that were not harvested. Rams of
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NATURE|VOL 426|11 DECEMBER 2003|www.nature.com/nature
high breeding value were also shot at an early age, and thus did
not achieve high reproductive success5. Declines in mean breed-
ing values for weight and horn size therefore occurred in
response to unrestricted trophy hunting, resulting in the pro-
duction of smaller-horned, lighter rams, and fewer trophies.
Sport harvesting is one of the most pervasive and potentially
intrusive human activities that affect game mammal populations
globally6. Hunters are willing to pay large sums to hunt trophy
mountain ungulates in various parts of the world, and many
mountain sheep (Ovis canadensis and O. dalli) populations in
North America are managed primarily to produce large-horned
trophy rams for sport hunters. A world-class trophy ram is an
extremely valuable commodity, and hunting permits have been
auctioned for hundreds of thousands of dollars7. One sport hunter
paid over Can$1 million in 1998 and 1999 for special permits to
hunt trophy rams in Alberta, Canada7. In many parts of North
America, sport harvest of mountain sheep is often restricted only
by the availability of rams whose horns reach a minimum size
prescribed by regulations. Although the use of income generated
from sport hunting towards enhancing and conserving mountain
has been paid to the potential evolutionary consequences, and
hence the sustainability, of harvest regimes2,3.
Wildlife management has traditionally focused on demographic
and ecological factors that affect numbers and growth rates in
harvested populations8–11. However, the life-historychanges experi-
enced by species subject to commercial fisheries strongly suggest
that intensive harvesting practices can elicit an evolutionary
response in wild stocks12–15. Experimental size-selective harvesting
treatments on an exploited fish demonstrated evolutionary effects
on somatic growth and population productivity in the opposite
direction of the size bias of the harvest13. Recent reviews have called
attention to the potential selective effects of sport hunting on wild
ungulates, in which large-horned or large-antlered males are selec-
tively targeted2,3. The increased frequency of tuskless elephants in
many African populations has also been suggested to have occurred
in response to selective ivory poaching16. Here we use data from the
long-term study of a harvested bighorn sheep population at Ram
Mountain, Alberta, Canada, to investigate the evolutionary con-
Fifty-seven rams have been shot at Ram Mountain since 1975, or
about 40% of the rams legally available for harvest in each year (see
Methods), for a yearly harvest of between zero and six rams17. Most
trophy-harvested rams were shot before reaching 8 years of age (45
of 57 rams), and nine were shot as early as the age of 4 years. In
bighorn sheep, much of the total horn length is added from the ages
of 2 to 4 years, and at Ram Mountain the probability of a ram being
horn growth over this interval4. ‘Animal model’18quantitative
genetic analysis of 395 horn-length and 447 weight measurements
taken from 192 rams at ages 2, 3 and 4 years from 1971 to 2002
revealed narrow-sense heritabilities of 0.69 ^ 0.10 and 0.41 ^ 0.11
Figure 1 Selection against high-breeding-value rams imposed by trophy hunting.
a, Breeding values (means ^ s.e.m.) for horn length and weight of trophy-harvested
rams (filled bars) and non-trophy-harvested rams (open bars). b, Relationship between
the age at harvest for trophy-harvested rams and their breeding value. c, Relationship
their breeding value.
Figure 2 Observed changes in mean weight and horn length and in the population size
from 1972to 2002.a, Relationship between weight(mean ^ s.e.m.) of 4-year-oldrams
and year (N ¼ 133 rams). b, Relationship between horn length (mean ^ s.e.m.) of
4-year-old rams and year (N ¼ 119 rams). c, Changes in population size (taken as the
number of ewes aged at least 2 years plus yearlings17) over time.
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NATURE|VOL 426|11 DECEMBER 2003|www.nature.com/nature
(means ^ s.e.m.), respectively (see Methods), and a strong positive
additive geneticcorrelation between the two(þ0.84 ^ 0.10). Com-
parison of expected genetic ‘breeding values’ (twice the expected
deviation of an individual’s offspring phenotype from the popu-
lation mean owing to the additive effect of the offspring’s inherited
genes18) extracted from this model (Fig. 1a) indicates that hunters
selectively harvest rams with high breeding values for horn length
(trophy-harvested mean, þ 0.61 ^ 0.28; non-harvested mean,
21.24 ^ 0.48; t-test: t148¼ 24.16, P , 0.001) and weight (tro-
phy-harvested mean, þ0.70 ^ 0.28; non-harvested mean,
20.89 ^ 0.48; t-test: t148¼ 23.26, P ¼ 0.0014).
Within seasons, mating success in bighorn sheep increases with
dominance rank19, age and horn length5. The positive effect of large
horns on mating success increases from about 6 years of age5, when
rams arecapable of defending oestrous ewes during the rut. The age
have an important impact on the number of offspring he can sire.
harvested ram was shot and his breeding value for horn length
(generalized linear model (GLM) with Poisson errors: x2
P ¼ 0.031;Fig.1b)butnotfor weight(GLM:x2
data not shown). Trophy-harvested rams with high breeding values
for body and horn size were therefore less likely to reach the ages at
which they achieve high rates of paternity in this population5. As a
consequence, there was a negative relationship between breeding
value for horn length and lifetime mating success, measured as the
number of paternities assigned over their lifetime, among trophy-
harvested rams (GLM with negative binomial error: x2
P ¼ 0.0034; Fig. 1c). The mean sire breeding value of individuals
fathered by trophy-harvested rams was therefore significantly less
than zero for both weight (one-sample t-test: mean ¼ 22.41,
s.e.m. ¼ 0.37, t59¼ 26.50, P , 0.001) and
(mean ¼ 21.84, s.e.m. ¼ 0.19, t59¼ 29.68, P , 0.001). The
mean sire breeding value of individuals fathered by rams that
died a natural death was also significantly less than zero for both
weight (one-samplet-test:mean ¼ 21.24,
t182¼ 27.14, P , 0.001) and horn length (mean ¼ 22.10,
s.e.m. ¼ 0.16, t182¼ 220.43, P , 0.001). The low breeding values
of rams not harvested (Fig. 1a) and the reduced longevity and
potential reproductive output of the higher-quality trophy-har-
vested rams (Fig. 1b, c) combine to suggest that the selection
imposed by trophy hunting had a negative impact on the evol-
utionary trajectory of horn length and body weight in this popu-
lation during our study.
Is there evidence of a response to selective harvesting at the
population level? Significant declines in both ram weight (linear
mixed-effect model including year of birth and individual as a
(1)¼ 1.80,P ¼ 0.18;
s.e.m. ¼ 0.17,
random effects, and age, time and resource index as fixed effects:
btime¼ 20.30, s.e.m. ¼ 0.09, t25¼ 23.42, P ¼ 0.0021) and horn
length (linear mixed-effect model including year of birth and
individual as a random effects, and age, time and resource index
as fixed effects: btime¼ 20.35, s.e.m. ¼ 0.12, t23¼ 22.97,
P ¼ 0.0068) were observed over the course of the study (Fig. 2a,
b) after controlling for environmental effects such as population
density (Fig. 2c) using an index of resource availability (see
Methods; weight: bresources¼ 0.81, s.e.m. ¼ 0.17, t25¼ 4.72,
P , 0.001; horn length:
t23¼ 3.32, P ¼ 0.0030). These are very rapid rates of phenotypic
change20, corresponding to 20.30/12.9 ¼ 20.023 and 20.35/
13.6 ¼ 20.026 standard deviations per year, or 20.14 and 20.15
haldanes(ref.20)assuming ageneration timeof6years.Analysesof
breeding valuesare consistent with genetically basedresponses (Fig.
ram weight (linear mixed-effect model including year of birth as a
random effect, and time and resource index as fixed effects:
btime¼ 20.071, s.e.m. ¼ 0.012, t33¼ 26.02, P , 0.001) and
horn length (linear mixed-effect model including year of birth as
a random effect, and time and resource index as fixed effects:
btime¼ 20.075, s.e.m. ¼ 0.011, t33¼2 6.76, P , 0.001). Such
declines in breeding value over time are indicative of a microevolu-
tionary response to selection21in the Ram Mountain population.
Unrestricted harvesting of trophy rams has thus contributed to a
decline in the very traits that determine trophy quality. Hunters
have selectively targeted rams of high genetic quality before their
reproductive peak, depleting the genes that confer rapid early body
and horn growth. Wildlife harvesting that is selective and suffi-
ciently severe might elicit an undesired evolutionary response when
the target trait is heritable. There might also be unexpected effects
on genetically correlated traits, such as female body weight or
of harvested populations as anthropogenic selection pushes traits
away from their naturally selected optima. Because such changes
will be extremely difficult to reverse, wildlife managers must
consider the genetic effects and the evolutionary implications of
alternative harvest strategies2,3. The move to adopt a ‘full curl’
restriction in parts of Alberta in 1996, which limits harvest to
strategy to minimize further deterioration of the genetic quality of
s.e.m. ¼ 0.22,
s.e.m. ¼ 0.025,t33¼ 1.49,P ¼ 0.15;
s.e.m. ¼ 0.024,t33¼ 2.08,P ¼ 0.045;
Population and study site
The bighorn sheep population on Ram Mountain, Alberta, Canada (528N, 1158W,
to Ram Mountain fromthe main species range has not been documented, and is probably
rare because of isolation of the population by about 30km of coniferous forest. Eachyear,
sheep were captured in a corral trap baited with salt from late May to early October, and
marked with colouredplastic ear tags orcanvas collars for individual identification. Adult
rams were captured once or twice in most summers from early June to mid-July. At each
capture, sheep were weighed to the nearest 250g with a Detecto spring scale. Horn length
along the outside curvature was measured with tape. The longer of the left and right horn
measurements was used, because rams can have a varying amount of horn removed by
wear. For further details on field methods see refs 17, 23 and 24.
Bighorn males on Ram Mountain can be legally harvested by Alberta resident hunters
from late August to the end of October. Until 1996, rams with horns describing at least
four-fifths of a curl (‘trophy’ rams) could be harvested by any hunter holding a trophy
sheep licence17. As any resident could purchase a licence, the harvest was limited only by
rams. Consequently, only three rams have been shot since 1996. Individual weight and
horn length measurements from rams captured between 1971 and 2002 were adjusted to
5 June (ref. 24). Because the youngest age at which rams were shot by hunters was 4 years,
weusedweightandhornlength data fromages2, 3and4yearsto avoidbias dueto hunter
Maternity was known from field observations for 709 of the 894 (79.3%) marked sheep
Figure 3 Changes in the mean breeding value of cohorts born between 1967 and 2002.
a, Relationship between breeding value (mean ^ s.e.m.) for weight and year of birth
(N ¼ 783 individuals). b, Relationship between breeding value(mean ^ s.e.m.) for horn
length and year of birth (N ¼ 783 individuals).
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NATURE|VOL 426|11 DECEMBER 2003|www.nature.com/nature
whose fates have been followed since 1971. Tissue sampling for DNA analyses started in
1988. Blood samples were taken from all captured sheep until 1993 and stored in
preservative at 2208C. Sampling resumed in 1997, when hair samples weretaken fromall
captured sheep by plucking 50–100 hairs including roots from the back or flank. Hairs
were kept either in paper envelopes or plastic bags containing about 5g of silica at room
the ear with an 8-mm punch. Ear tissue was kept at 2208C in a solution of 20%
dimethylsulphoxide saturated with NaCl. We sampled 433 marked individuals over the
course of the study.
DNAwas extracted fromblood witha standardphenol–chloroform method, and from
either 20–30 hairs including follicles or about 5mg of ear tissue, using the QIAamp tissue
extraction kit (Qiagen Inc., Mississauga, Ontario). Polymerase chain reaction
amplification at 20 ungulate-derived microsatellite loci, 15 as described previously5plus
MCM527, BM4025, MAF64, OarFCB193 and MAF92 (refs 25, 26), and fragment analysis
were performed as described elsewhere5. After correction for multiple comparisons, we
found no evidence for allelic or genotypic disequilibria at or among these 20 loci.
Paternity of 241 individuals was assigned by using the likelihood-based approach
described in CERVUS27at a confidence level of more than 95% with input parameters
given in ref. 5. After paternity analysis, we used KINSHIP28to identify 31 clusters of 104
paternal half-sibs among the unassigned offspring. A paternal half-sibship consisted of all
having a likelihood ratio of the probability of a paternal half-sib relationship versus
unrelated with an associated P , 0.05 (ref. 28). Members of reconstructed paternal half-
sibships were assigned a common unknown paternal identity for the animal model
analyses. Paternal identity links in the pedigree werethereforedefined for 345 individuals.
Animal model analyses
Breeding values, genetic variance components and heritabilities were estimated by using a
multiple trait restricted-estimate maximum-likelihood (REML) model implemented by
the programs PEST29and VCE30. An animal model was fitted in which the phenotype of
each animal was broken down into components of additive genetic value and other
random and fixed effects: y ¼ Xb þ Za þ Pc þ e, where y was a vector of phenotypic
values, b was a vector of fixed effects, a and c were vectors of additive genetic and
permanent environmental, e was a vector of residual values, and X, Z and P were the
corresponding design matrices relating records to the appropriate fixed or random
effects18. Fixed effects included age (factor) and the average weight of yearling ewes in the
year of measurement (covariate), which is a better index of resource availability than
population size because it accounts for time-lagged effects4. The permanent
environmental effect grouped repeated observations on the same individual to quantify
any remaining between-individual variance over and above that due to additive genetic
effects, which would be due to maternal or other long-term environmental and non-
additive genetic effects.
The total phenotypic variance (Vp) was therefore partitioned into three components:
the additive genetic variance (Va), the permanent environmental variance (Ve) and the
residual variance (Vr), thus: Vp¼ Vaþ Veþ Vr. Heritability was calculated as h2¼ Va/
Vp. The VCE30program returns standard errors on all variance components and ratios.
Best linear unbiased predictors of individual breeding values were quantified by using
REML estimates of the variance components obtained with PEST29. All statistical tests
were conducted in SPLUS 6.1.
Received 11 August; accepted 17 October 2003; doi:10.1038/nature02177.
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Acknowledgements We thank the many students, colleagues, volunteers and assistants that
Our research was funded by the Alberta Conservation Association, Alberta Fish and Wildlife
Division, Alberta Recreation, Sports, Parks and Wildlife Foundation, Eppley Foundation for
Research, Foundation for North American Wild Sheep, National Geographic Society, Natural
Environment Research Council (UK), Natural Sciences and Engineering Research Council of
Canada, Rocky Mountain Elk Foundation (Canada), and the Universite ´ de Sherbrooke. We are
grateful for the logistical support of the Alberta Forest Service.
Competing interests statement The authors declare that they have no competing financial
Correspondence and requests for materials should be addressed to D.W.C.
The role of evolution in the
emergence of infectious diseases
Rustom Antia1,Roland R.Regoes1,JacobC.Koella2& CarlT.Bergstrom3
1Department of Biology, Emory University, Atlanta, Georgia 30322, USA
2Laboratoire de Parasitologie Evolutive, Universite ´ Pierre et Marie Curie,
75252 Paris, France
3Department of Biology, University of Washington, Seattle, Washington 98195,
It is unclear when, where and how novel pathogens such as
human immunodeficiency virus (HIV), monkeypox and severe
acute respiratory syndrome (SARS) will cross the barriers that
separate their natural reservoirs from human populations and
ignite the epidemic spread of novel infectious diseases. New
pathogens are believed to emerge from animal reservoirs when
ecological changes increase the pathogen’s opportunities to enter
the human population1and to generate subsequent human-to-
human transmission2. Effective human-to-human transmission
requires that the pathogen’s basic reproductive number, R0,
should exceed one, where R0is the average number of secondary
infections arising from one infected individual in a completely
susceptible population3. However, an increase in R0, even when
insufficient to generate an epidemic, nonetheless increases the
number ofsubsequently infected individuals. Hereweshow that,
letters to nature
NATURE|VOL 426|11 DECEMBER 2003|www.nature.com/nature