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Sustainable trophy hunting
of African lions
Q1
Karyl Whitman, Anthony M. Starfield, Henley S. Quadling & Craig Packer
Department of Ecology, Evolution and Behavior, University of Minnesota,
1987 Upper Buford Circle, Saint Paul, Minnesota 55108, USA
.............................................................................................................................................................................
In most species, sport hunting of male trophy animals can only
reduce overall population size when the rate of removal of males
is so high that females can no longer be impregnated
1
. However,
where males provide extensive paternal care, the removal of even
a few individuals could harm the population as a whole
2,3
.In
species such as lions, excessive trophy hunting could theoretically
cause male replacements (and associated infanticide
4,5
)to
become sufficiently common to prevent cubs reaching adulthood.
Here we simulate the population consequences of lion trophy
hunting using a spatially explicit, individual-based, stochastic
model parameterized with 40 years of demographic data from
northern Tanzania. Although our simulations confirm that
infanticide increases the risk of population extinction, trophy
hunting could be sustained simply by hunting males above a
minimum age threshold, and this strategy maximizes both the
quantity and the quality of the long-term kill. We present a
simple non-invasive technique for estimating lion age in popu-
lations lacking long-term records, and suggest that quotas would
be unnecessary in any male-only trophy species where age
determination could be reliably implemented.
Male lions reach sexual maturity at about 2.5 yr of age and live to
a maximum of about 15 yr in nature
6
. The lion’s mane reaches full
size at about 4 yr (ref. 7), and peak reproductive success is attained
by about 8 yr (ref. 8). African lions live in stable social groups
(‘prides’) containing an average of six breeding females and a
coalition of 2–3 adult males. The resident coalition sires all cubs
born during their tenure
9
, but most coalitions only remain resident
for about 2 yr on average
—
long enough to rear a single cohort of
young to independence
10
. Rather than wait for mothers with
dependent offspring to rear their current brood, incoming males
typically kill all cubs #9 months of age and evict older subadults
when they first take over a pride
4,5
. Trophy hunting is expected to
increase the rate of male takeovers, as larger coalitions dominate
smaller ones
11
and the loss of even one male from a resident
coalition renders it more vulnerable to being ousted
12
.
We developed a comprehensive simulation model that tracks the
fate of each individual in a population
13
(see Methods), and we
present results based on ‘populations’ comprising a maximum of
ten prides of #9 females per pride. Outcomes of hunting should be
most sensitive to factors that limit population size: the maximum
number of prides in the population, maximum pride size, and the
incidence of infanticide. We therefore ran simulations of popu-
lations containing a maximum of five prides with #10 females and
ten prides with #7 females, and our conclusions were unchanged.
The impact of infanticide is emphasized below (see Fig. 1). At each
six-month time step, animals survive and breed according to
probabilities observed in the long-term lion studies in the Serengeti
National Park and in Ngorongoro Crater
14,15
. Demographic param-
eters depend on the age, sex and social status of individual lions.
Probability of female recruitment depends on the number of adult
females in the pride, whereas probability of male takeovers depends
onthesizeandageofresidentcoalitionsversuschallenging
nomadic coalitions. An emerging property of these interactions is
a density-dependence that leads to a quasi-equilibrium where the
total population size fluctuates slightly (with demographic stochas-
ticity) around a well-defined average. Preliminary trials started the
populations with an arbitrary set of individuals and an arbitrary age
distribution, and proceeded (without trophy hunting) until the
population reached a stable size and age-structure that served as the
standardized starting point for all simulations.
Trophy-hunting strategies were varied in two ways. First, the
minimum age of eligible males ranged from $3yrto$6 yr. Second,
quotas could range from 0 to 20 males per year. Individual males
were removed according to the age minimum, but at random with
respect to pride or nomadic status. Figure 1 illustrates the effects
of these strategies after 30 yr (as start-up populations required
20–25 yr to equilibrate). Figure 1a and b shows that if offtake
included males as young as three years of age, the female population
would invariably collapse if quotas were too high. But as the
minimum age of trophy males was raised, the chances of population
persistence increased markedly
—
to the point where removing males
$6 yr in age had no substantial effect regardless of quota size. Note
Figure 1 Effects of trophy hunting as a function of quota size and male age. Average
outcome after 100 runs is shown from shooting males of the following ages: $3 yr old
(red), $4 yr (orange), $5 yr (blue), $6 yr (green). a, Number of adult females after 30 yr
in hypothetical populations where males are non-infanticidal. b, Number of females in
infanticidal populations; note that infanticidal populations are smaller and more vulnerable
to trophy hunting. c, Total number of males harvested over 30 yr in infanticidal
populations. d, Total number of 5–6-yr-old ‘trophies’ harvested in infanticidal
populations.
Figure 2 Female population size through time as a function of quota size and male age in
infanticidal populations. Red indicates average outcome over 100 runs from annual
quota of 10 males, orange from quota of 6 males, blue from quota of 4, and green from
quota of 2. a–d, Female population size when hunters shoot males that are $3 yr old (a),
$4yr (b), $5yr(c) and $6yr(d).
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that the sensitivity to over-hunting is exacerbated by infanticide: if
we eliminate infanticide from the model, the resultant populations
are always larger regardless of hunting strategy (Fig. 1a)
—
but
removing too many young males will still drive the population to
extinction because females are eventually unable to mate. Figure 2
shows the average size of the female population through time as a
function of male age and quota size. Shooting too many young
males leads to an inevitable decline in population size, whereas
quota size is irrelevant when hunting is restricted to older males.
Running the simulations for 50 yr in infanticidal populations,
quotas of more than two $3- or $4-yr-old males per year produced
at least one case of extinction per 100 runs, whereas there were no
extinctions when hunting was restricted to $5- or $6-yr-olds.
By only removing $5- or $6-yr-old males, younger males have
the opportunity to remain resident long enough to rear a cohort of
young. By removing males in a manner that sustains population
growth, the population can yield more males in the long run. Figure
1c and d shows that the cumulative number of males harvested over
30yrisalsosensitivetomaleageandquota,but,again,the
detrimental impact of trophy hunting is largely avoided by main-
taining a minimum age of 5–6 yr, and the total number of high-
quality ‘trophies’ (large-maned males of 5–6 yr) taken at random
from these populations is also highest. Hunting fees are highest in
reserves with greater opportunities to shoot trophy animals, so it is
noteworthy that the most impressive males are so ‘expendable’ to
the population. Figure 3 shows the expected annual harvest of
‘trophy males’ through time. By restricting offtake to $5- or $6-yr-
old males, hunters harvest a greater cumulative number of trophy
males and are likely to gain a steadier offtake each year.
Hunters often estimate male age on the basis of mane size or
colouration, but these phenotypes are only loosely correlated with
age and vary greatly across the geographic range of the lion
7
. The
most reliable index in the Serengeti/Ngorongoro lions is the extent
of dark pigmentation in the tip of the nose, which becomes
increasingly freckled with age (Fig. 4). Individual variation in
nose colouration is sufficiently low that age can be estimated up
to 8–9 yr (Table 1). The noses of 5-yr-old males are 50% black, so a
simple rule of thumb would be to restrict all trophy hunting to
males with noses that are more than half black. However, the noses
of Ngorongoro males darkened more slowly than Ngorongoro
females and Serengeti males/females (Fig. 4), thus site-specific
data may be necessary to provide accurate age estimates. However,
in areas with slower rates of nose darkening, the 50% rule would
safely restrict hunting to $8-yr-old males.
Detailed predictions of these simulations should be interpreted
with caution, because they rely on demographic patterns in two
adjacent populations in northern Tanzania and may not apply to
every situation. Nevertheless, our results do point to possible
conflicts between conservation and consumption. Figures 1b and
2 suggest that lion populations will be larger if trophy hunting is
restricted to males $6 yr, but this strategy entails an opportunity
cost: long-term harvests are highest from hunting males with ages
$5 yr (Fig. 1c and d, Fig. 3). Our analysis also treats the lion
population as a ‘closed system’, sustained solely by birth rates of the
resident females, which exemplifies populations most at risk from
overexploitation. ‘Open’ systems involve game reserves immediately
adjacent to national parks where excess males and females can freely
disperse from protected areas into low density hunting areas. Our
analysis also assumes that trophies are removed at random accord-
ing to residence status. If hunters followed a more sophisticated
approach by selectively targeting nomadic males or resident males
whose cubs have recently reached independence, trophy hunting
Figure 3 Annual offtake of 5–6-yr-old ‘trophy’ males as a function of quota size and male
age in infanticidal populations. Red indicates average outcome of 100 runs from
annual quota of 10 males, orange from quota of 6 males, blue from quota of 4, and green
from quota of 2. Annual offtake of trophies when hunters shoot males that are $3 yr old
(a), $4yr(b), $5yr (c) and $6yr (d).
Figure 4 Age estimation for adult lions using nose colouration. a, Identification
photograph of a 3-yr-old Serengeti male. b, Excised photo of nose tip. c, GIS rendering of
nose colouration. d, Age-change of nose colouration for males and females in two
separate populations. After controlling for age, there was no effect of sex on nose colour in
the Serengeti, but Ngorongoro males had lighter noses than Ngorongoro females
(P ¼ 0.0485) and Serengeti males (P ¼ 0.0281).
letters to nature
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could greatly reduce the incidence of infanticide, and population
sizes would approach the levels predicted by Fig. 1a.
Assuming an average pride range of 100 km
2
, our simulated
population of 10 prides would yield fewer than 3 males per
1,000 km
2
per year (Fig. 1c). Hunting quotas in 34 reserves in
Tanzania in 1995 were set at an average of 3.8 males per 1,000 km
2
(median, 2.8; range, 0.5–13.4). Although the expectations from
these concessions were generally set at an appropriate order of
magnitude, quotas have increased in many Tanzanian reserves over
the past five years, and quotas are even higher in parts of Africa
where lion population densities are considerably lower. Therefore,
realistic lion harvests for most areas may not generate sufficient
revenue to be economically viable in the long term unless conces-
sions establish an auction system
16
or sell hunting ‘opportunities’
(which may or may not succeed in killing a lion) rather than attempt
to base their income exclusively on successful hunts.
Our model shows clearly that age is a critical variable enabling the
persistence of trophy species with extensive paternal care. As long as
hunting is restricted to a safe minimum age (and the rule is honestly
enforced
17
), there is no risk of setting excessive quotas even in areas
where it is impossible to estimate the overall population size
18
.
Lions’ noses continue to darken until they are at least 9 yr old, so
rough estimates of male age can easily be made (Table 1). Thus
despite the complexity of lion social structure and the complex
consequences of male removal, populations can be sustained by
following a simple harvest rule, combined with a simple technique
for age-assessment.
Although our model was designed to examine the impact of
trophy hunting in only one species, our findings have broad
significance. First, highly valued ‘trophy’ animals are individuals
with unusually well-developed secondary sexual characteristics,
such as large antlers, horns, tusks or mane. Although these traits
generally grow with age, high-quality individuals may show preco-
cious physical development and thus be shot before they are able to
breed
—
with negative evolutionary effects on the population as a
whole
19
. Thus it is particularly important to assess age indepen-
dently from the ‘trophy’ phenotype, and to set age thresholds high
enough to ensure successful breeding by the best males. Second, the
hunting industry has always been based on some sort of quota
system, even though quotas are generally viewed as arbitrary and
difficult to enforce
16,20,21
. Our analysis suggests that quotas could
eventually become irrelevant to the conservation of lions and any
other trophy species (whether infanticidal or not) where hunting is
restricted to males. With basic information on breeding biology and
social behaviour (such as infanticide and other quirks of male
behaviour
22
), an age-threshold criterion could be calculated that
would minimize the adverse effects from killing all of the eligible
males each year. By excluding the younger adult males from the
annual kill, females would always be impregnated and vulnerable
offspring would generally be protected by their fathers. A
Methods
Simulation model
In the Windows-driven Cþþ model
12
, female lions and their dependent offspring are
organized into ‘prides’ that defend spatially arranged and interconnected territories. The
model ignores environmental stochasticity, so the maximum number of territories and
maximum pride size is held constant for a given set of simulations. The model
distinguishes between sex and age class (cubs ,6 months, cubs 6–12 months, cubs 12–24
months, subadult males and females, adult males and females) and tracks individuals by
social and reproductive status. Only 3–13-yr-old females produce cubs; females are not
able to breed again until they lose their entire litter or their surviving offspring reach 2 yr of
age. Males are classified as either subadult, nomadic or resident; lone males may join up
with other lone males or groups of two. Nomadic and subadult males move freely between
and within pride territories a specified number of times per time step, but do not breed
with females. Residents may be affiliated with up to 3 prides at once. Competition for pride
residence is determined by using a competition matrix
23
that weights overall competitive
strength according to male age and coalition size. Cubs are killed with an age-specific
probability when new males first enter a pride.
At each time step, the model simulates cub production using a random number for
each eligible female that draws her litter size from a distribution, determines individual
survival (assigned by random number according to the observed survival rate for animals
of that age, sex and social status
—
see Supplementary Information), updates ages for
survivors, organizes 2-yr-old males in each pride into subadult male groups, promotes
3-yr-old males into nomadic groups, and determines the fate of subadult females.
Recruitment of females into their natal pride depends on the number of adult females
already in the pride and the specified upper limit for that pride (which can be temporarily
exceeded by no more than two females). If the subadult females cannot be accommodated
in their natal pride, they are allowed to search for empty territories, but they die if they
cannot find any vacancies. At ‘equilibrium’, the simulated populations closely matched real
populations in terms of the male:female:cub ratio, the average age of resident males, and
the size range of subadult cohorts. To test the effects of trophy hunting, each simulation
ran for 30 or 50 yr with 100 replicates. The initial age structure, reproductive history, pride
affiliation, and distribution were identical for each replicate. Harvesting occurred at
random (within the rules) every 6 months, although it was not always possible to meet the
quota.
Nose assessments
Close-up colour photographs (n ¼ 189) were taken of 105 known-aged lions, including 73
females and 32 males from the Serengeti National Park and Ngorongoro Crater, Tanzania,
between 1999 and 2002. Each photograph was first digitized at high resolution into a.tif
file, and the fleshy part of the nose (‘nose tip’) from each image was excised using Adobe
Photoshop 4.01 LE. We then used the Spatial Analyst extension of ESRI Arcview 3.2 to
rasterize each cut-out nose tip and assign each newly created ‘grid’ a range of colour values.
By limiting the colour values to either ‘black’ or ‘not black’, the nasal pigmentation pattern
was ‘mapped’ and quantified for the percentage of readable pixels that contained ‘black’.
We used linear multiple regression to assess the effect of age, sex, habitat and population
on pigmentation. In cases where multiple photographs were available for the same
individual, the mean pigmentation score was regressed against mean age.
Received 25 November 2003; accepted 4 February 2004; doi:10.1038/nature02395.
Published online 22 February 2004.
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Table 1 Statistical relationship between nose blackness and age
Proportion
black
Estimated age
in years (s.e.)
95% p.i 75% p.i 50% p.i
.............................................................................................................................................................................
0.10 2.66 (1.24) 0.17–5.15 1.21–4.10 1.81–3.50
0.20 3.25 (1.24) 0.77–5.72 1.81–4.69 2.41–4.09
0.30 3.84 (1.23) 1.37–6.30 2.40–5.27 3.00–4.68
0.40 4.42 (1.23) 1.97–6.89 3.00–5.86 3.59–5.26
0.50 5.02 (1.23) 2.56–7.48 3.59–6.45 4.18–5.85
0.60 5.61 (1.23) 3.14–8.07 4.18–7.04 4.77–6.44
0.70 6.20 (1.23) 3.73–8.66 4.77–7.63 5.36–7.04
0.80 6.79 (1.24) 4.32–9.26 5.35–8.23 5.95–7.63
0.90 7.38 (1.24) 4.90–9.87 5.94–8.82 6.54–8.22
1.00 7.97 (1.25) 5.58–10.47 6.52–9.42 7.12–8.82
.............................................................................................................................................................................
s.e., standard error; p.i., predicted interval. Predicted values are based upon the least-squares
regression of a truncated data set for 63 known-aged females in the Serengeti and Ngorongoro
aged #10 yr (y ¼ 2.0667 þ 5.9037arcsin(x); r
2
¼ 0.75, P , 0.0001). Predicted intervals at 95%,
75% and 50% are included for upper and lower bounds.
letters to nature
NATURE | doi:10.1038/nature02395 | www.nature.com/nature 3
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Supplementary Information accompanies the paper on www.nature.com/nature.
Acknowledgements We thank the government of Tanzania for permission; K.W. was supported
by the Wildlife Conservation Society, Big Game Special Projects Foundation, John D. & Catherine
T. MacArthur Foundation, Graduate School of the University of Minnesota, Dayton-Wilkie
Foundation, and Global Wildlife Trust; C.P. was supported by the McKnight Foundation and NSF
LTREB and Animal Behavior programmes. We thank T. Gelatt, P. West, G. Hopcraft, M. Craft,
B. Kissui, L. Frank, S. Mduma, T. Ramme, W. Testa, T. Coulson and N. Leader-Williams for
advice, assistance and discussion.
Competing interests statement The authors declare that they have no competing financial
interests.
Correspondence and requests for materials should be addressed to C.P. (packer@cbs.umn.edu).
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Author Queries
JOB NUMBER: 2395
JOURNAL: Nature
Table count =1 Figure count =4
Q1 In Acknowledgements, please clarify ‘permission’; per-
mission for what? Please note that we have left ‘kill’ rather
than ‘harvest’ in the first paragraph, as this will help the
general reader. Please check that the display items are as
follows (doi:10.1038/nature02395): Figures 1–4 (all col-
our); Tables 1; Boxes none. Please check all figures (and
tables if any) very carefully as they have been re-labelled,
re-sized and adjusted to Nature’s style.Article classifi-
cation: broad area …1, 9, 12; subclassification
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Author’s corrections – Page 1
Author’s corrections – Page 3
Author’s corrections – Page 2
Author’s corrections – Page 4
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