B I O L O G I C A L C O N S E RVAT I O N
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available at www.sciencedirect.com
journal homepage: www.elsevier.com/locate/biocon
Animal breeding systems and big game hunting: Models
and application 5
T.M. Caroa,*, C.R. Youngb,c,1, A.E. Cauldwelld, D.D.E. Browne
a
Department of Wildlife, Fish and Conservation Biology and Center for Population Biology, University of California, Davis, CA 95616, USA
Department of Ecology and Evolutionary Biology, University of California, 1156 High Street, Santa Cruz, CA 95064, USA
c
Monterey Bay Aquarium Research Institute, 7700 Sandholdt Road, Moss Landing, CA 95039, USA
d
Kagera Kigoma Game Reserves Rehabilitation Project (EDF), P.O. Box 77, Kibondo, Tanzania
e
Animal Behavior Graduate Group, University of California, Davis, CA 95616, USA
b
A R T I C L E I N F O
A B S T R A C T
Article history:
We apply an age- and stage-structured model incorporating varying harem sizes, paternal
Received 31 March 2008
care and infanticide to examine the effect of hunting on sustainability of populations.
Received in revised form
Compared to standard carnivore and herbivore models, these models produce different
11 December 2008
outcomes for sustainable offtake when either adults, or adult males are harvested. Larger
Accepted 14 December 2008
harem size increases sustainable offtake whereas paternal care and infanticide lowers it.
Where males are monogamous, populations are vulnerable to male offtake, regardless of
Keywords:
paternal care. Surprisingly, an incidental take of 10% of other age–sex-classes has very little
Harem size
effect on these findings. Indiscriminate (subsistence) hunting of all age–sex classes has a
Harvest models
dramatic effect on certain populations. Applying these behavior–sensitive models to tourist
Infanticide
hunting in the Selous Game Reserve, Tanzania, we find that across the Reserve hunting
Exploitation
quotas were generally set at sustainable rates except for leopard (Panthera pardus). In certain
Large mammals
hunting blocks within the Reserve, however, quotas for eland (Taurotragus oryx), hartebeest
Paternal care
(Alcelaphus buselaphus), lion (Panthera leo), reedbuck (Redunca arundinum), sable antelope
(Hippotragus niger), warthog (Phacochoerus aethiopicus) and waterbuck (Kobus ellipsiprymnus)
are set at unsustainably high rates. Moreover, particular blocks are consistently awarded
high quotas. Behaviorally sensitive models refine predictions for population viability, specify data required to make predictions robust, and demonstrate the necessity of incorporating behavioral ecological knowledge in conservation and management.
Ó 2008 Elsevier Ltd. All rights reserved.
1.
Introduction
Organized hunting of wild animals for sport can have considerable conservation benefits (Taylor and Dunstone, 1996;
Lewis and Alpert, 1997; Hurt and Ravn, 2000; Reynolds et al.,
2001; Lewis and Jackson, 2005; Lindsey et al., 2007). For example, in Eastern and Southern Africa it is widely recognized
that areas set aside for hunting big game animals protect
5
Responsibilities: TMC devised and coordinated the project, helped collate life history parameters, breeding system data and densities,
and wrote and revised the bulk of manuscript; CRY analyzed the models and wrote parts of methods and results pertaining to the
models; AEC collected the Selous hunting data; DDEB collated life history parameters and densities.
* Corresponding author: Tel.: +1 530 752 0596; fax: +1 530 752 4154.
E-mail addresses: [email protected] (T.M. Caro), [email protected] (C.R. Young), [email protected] (A.E. Cauldwell),
[email protected] (D.D.E. Brown).
1
Present address: Department of Organismic and Evolutionary Biology, Harvard University, 16 Divinity Avenue, Cambridge, MA 02138,
USA.
0006-3207/$ - see front matter Ó 2008 Elsevier Ltd. All rights reserved.
doi:10.1016/j.biocon.2008.12.018
910
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habitats that might otherwise be turned over to agriculture
(Pelkey et al., 2000), protect populations of large mammals
(Caro et al., 1998a) and can benefit local people (Eltringham,
1984; Bond, 2001; Borgerhoff Mulder and Coppolilllo, 2005).
Nonetheless, exploitation of the populations of particular
species always has the potential to reduce population sizes
to levels at which hunting is no longer economically profitable or even to cause population extinction in extreme cases
(Adams, 2004). Unfortunately, it is difficult to estimate animal
population sizes and to monitor them over time, and in most
parts of the world hunting quotas are set through informed
guesswork (Baldus and Cauldwell, 2004). Therefore it would
be helpful from both an ecological and economic point of
view to set hunting industries on a firmer scientific footing.
This is particularly true in Africa where it is difficult to provide the scientific input needed for good management.
The impact of hunting on animal populations depends on
several factors that include age of individuals removed, sex
and reproductive condition, and, of course, the number of
individuals taken (Festa-Bianchet, 2003). In an effort to regulate hunting, most countries have laws that pertain to these
variables that include restricting offtake to adults or to adult
males, to certain times of the year, and setting strict limits
on the number of animals that hunters may shoot. In some
countries, hunting seasons are tailored to each species, as
in the USA, whereas in others, one hunting season pertains
to all species and must necessarily be a compromise in protecting the reproductive interests of different species. Recently, it has been recognized that the breeding system of
the population being exploited can also affect the ability of
the population to respond to hunting pressure (Milner et al.,
2007; Price and Gittleman, 2007). For example, modeling
shows that populations of monogamous species and species
in which males commit infanticide are particularly susceptible to removal of males (Greene et al., 1998; Whitman et al.,
2004).
In practice, however, the rules surrounding hunting are
difficult to enforce (Lindsey et al., 2007). While it is relatively
easy to limit legal hunting to particular seasons, it is more difficult to ensure that hunting quotas are adhered to and that
only certain age–sex classes are taken. This is particularly evident when sexes are difficult to distinguish, or more unfortunately, when hunters are unscrupulous and take more than
their allocation (Caro and Baldus, 2006).
The purpose of this paper is to explore the way in which
hunting practice has the potential to affect animal populations in East Africa when their breeding systems are taken
into account. In order to highlight the effects of hunting policy on animal populations, we focus on tourist hunting practices in the largest game reserve in the world, the Selous
Game Reserve in Tanzania, where hunting is an important
economic activity (Baldus and Cauldwell, 2004; Cauldwell,
2004; Leader-Williams et al., 1996). Building on a previous
modeling exercise (Young and Towbin, submitted for publication), we address how different degrees of hunting offtake affect the intrinsic rate of population increase in species where
males help in rearing offspring, in species where males commit infanticide and in species where harem size varies. We
have chosen these three criteria for the following reasons.
(1) When game policy was being developed in Tanzania in
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the 1970s, scientists and laypeople believed that females were
solely responsible for raising offspring; behavioral ecologists
now know that male care is important in many species (Clutton-Brock, 1991). (2) At that time, infanticide by extra-group
males was unknown. The first documentation of it was by
Bertram (1975) for lions but it is now suspected for several
other species (Breden and Hausfater, 1990). (3) If species exhibit paternal care, population growth rates are reduced, and
this effect interacts with hunting policy (Young and Towbin,
submitted for publication). (4) Harem size is known to affect
sustainable harvest (Greene et al., 1998).
1.1.
Background to tourist hunting in Tanzania
Tanzania has set aside 180,000 km2 for tourist hunting and offers a large number of species for sport hunting, principally
mammals, but also upland birds (Tanzania Wildlife Conservation Act, 2002); it is the most popular big game hunting country in Africa (Lindsey et al., 2006, 2007). In practice, a hunting
company takes out a lease on one or several hunting blocks
which are segments of a Game Reserve, Game Controlled
Area or Open Area, and the company is allocated a speciesspecific hunting quota for the season. A portion of this quota
is then offered to clients who come to stay at hunting camps
for 1, 2 or 3 week long periods. Clients sometimes fly between
different hunting blocks leased by the same company in order
to shoot species found only in certain parts of the country but
quotas pertain to a hunting block. Hunting season commences on July 1st each year and ends on December 31st. In
most parts of southern Tanzania where many of the hunting
blocks are found, the effective hunting season finishes in
November when the rains begin and roads become impassable (Baldus and Cauldwell, 2004).
Tourist hunters are allowed to shoot a large number of
game species (Table 1). In 15 species with marked sexual
dimorphism, only males can be taken, but in most other species both sexes can be shot providing females are not believed
to be pregnant, nursing or accompanied by dependent young
(Tanzania Wildlife Conservation Act, 1974). Tanzanian residents are allowed to shoot a total of 22 species for meat. In
six of these species, only males are legally hunted but for
the other 16 species animals of any age–sex class can be shot
(Table 1).
The paper is organized as follows. Having documented
those species that are hunted in Tanzania, and in particular
in Selous, we next describe the breeding systems of the 24
most commonly sought after species in Selous and, for the
sake of generality, collapse them into two different carnivore
breeding system types and eight herbivore types. We then
examine sustainable offtake predicted by the 10 model formulations specifically tailored to these breeding systems.
For each of these scenarios, we determine the effect of incidental hunting on sustainable offtake. At the end of the paper, we compare the output of these models to hunting
quotas and actual hunting offtake of the 24 species in the Selous in order to determine whether current hunting practices
are more or less sustainable than the predictions that arise
from the models. This exercise also highlights which hunting
blocks are being awarded overly generous hunting quotas. Finally, we suggest which species may require new hunting
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Table 1 – Game species of mammals listed in the fourth schedule of the Tanzania Wildlife Conservation Act, 1974 together
with listed scientific names and hunting policy. Species hunted in Selous are shown in italics.
Common name
Scientific name
Legally hunted by
A
Tourists
Baboon – olive
Baboon – yellow
Buffalo
Bushbuck
Bushpig
Caracal
Cat – civet
Cat – genet
Cat – serval
Cat – wild
Dikdik
Duiker – Abbots
Duiker – blue
Duiker – common
Duiker – red
Eland
Elephant
Galago
Fox – bat-eared
Gazelle – Grant’s
Gazelle – Thomson’s
Gerenuk
GiraffeC
Hare – African
Hare – jumping
Hartebeest – Coke’sa
Hartebeest – Lichenstein’sa
Hippopotamus
Hedgehog
Hog – giant forest
Hyena – spotted
Hyrax – rock
Hyrax – tree
Impala
Jackal – golden
Jackal – striped
Jackal – silver-backed
Klipspringer
Kudu – greater
Kudu – lesser
Leopard
Lion
Mongoose
Monkey – colobus (b and w)C
Monkey – blue
Monkey – SykesC
Monkey – vervet
Oribi
Oryx
Otter
Pigmy antelope (suni)
Porcupine
Puku
Ratel
Reedbuck – bohorb
Reedbuck – mountain
Reedbuck – southernb
RhinocerosC
Roan antelope
Sable antelope
Sharpe’s grysbok
Papio anubis
Papio cynocephalus
Syncerus caffer
Tragelaphus scriptus
Potamochoerus porcus
Felis caracal
Civetiictis civetta
Genetta genetta
Felis serval
Felis lybica
Rynchotragus kirkii
Cephalophus spadix
Cephalophus monticola
Sylvicapra grimmia
Cephalophus natalensis
Taurotragus oryx
Loxodonta africana
Galago senegalensis
Otocyon megalotis
Gazella grantii
Gazella thomsonii
Litocraneous walleri
Giraffa camelopardalis
Lepus capensis
Pedetes surdaster
Alcelaphus buselaphus cokei
Alcelaphus buselaphus lichensteinii
Hippopotamus amphibius
Erinaceus preuneri
Hylochoerus meinertzhageni
Crocuta crocuta
Heterohyrx procavia
Dendrohyrax aboreous
Aepyceros melampus
Canis aureus
Canis adustus
Canis mesomelas
Oreotragus oreotragus
Strepsiceros strepsiceros
Strepsiceros imberbis
Panthera pardus
Panthera leo
Viverridae
Colobus spp.
Cercopithecus spp
Cercopithecus spp.
Cercopithecus aethiops
Ourebia ourebi
Oryx gazella
Aonyx lutra
Nesotragus moschatus
Hystrix galeata
Adenota vardoni
Mellivora capensis
Redunca redunca
Redunca fulvorufula
Redunca arundinum
Diceros bicornis
Hippotragus equinnus
Hippotragus niger
Nototragus sharpei
MF
MF
M
M
MF
MF
MF
MF
MF
MF
MF
MF
MF
MF
MF
M
MFB
MF
MF
M
M
M
MF
MF
MF
MF
MF
MF
MF
MF
MF
MF
M
MF
MF
MF
MF
M
M
M
M
MF
MF
MF
MF
MF
MF
MF
MF
MF
MF
M
MF
M
M
M
ResidentsA
All
All
All
All
All
All
M
M
M
All
All
All
All
M
All
All
M
M
M
M
MF
(continued on next page)
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Table 1 – Continued
Common name
Scientific name
Legally hunted by
TouristsA
Sitatunga
Steinbuck
Topi
Warthog
Waterbuck –
Waterbuck –
Wild dog#
Wildebeest –
Wildebeest –
Zebra
Zorilla
commonc
defessac
Nyasad
white-beardedd
Tragelaphus spekei
Raphiceros campestris
Damaliscus korrigum jimela
Phacochoerus aethiopicus
Kobus ellipsiprymus
Kobus defessa
Lycaon pictus
Connochaetes taurinus taurinus
Connochaetes taurinus albojubatus
Equus burchelli
Inctonyx striatus
M
M
MF
MF
M
M
MF
MF
MF
MF
ResidentsA
All
All
All
All
All
A M: adult males, F: adult females and All: all age–sex classes.
B Only elephants with tusks each over 20 kgs.
C These species can no longer be legally hunted.
a–d Treated as the same species in analyses.
restrictions as a result of incorporating behavioral ecological
knowledge about their specific breeding system.
2.
Methods
2.1.
Study area
The Selous Game Reserve is a World Heritage Site situated in
southeastern Tanzania (Fig. 1), and covers approximately
45,000 km2, about the size of Ireland. Much of it is drained
by the Rufiji River formed after the Luwegu and Kilombero
Rivers join; it also has three major tributaries, the Luhombero,
Njenje and Mbarang’andu, that join it within the Reserve. The
southeast is drained by the Matandu River. The east receives
approximately 750 mm or rain per year, the west 1300 mm.
The northern sixth of the Reserve is open wooded grassland
dominated by Terminalia spinosa and Hyphaene thebaica, and
by Borassus aethiopium along the rivers. The southern 5/6th
of the Reserve is deciduous miombo woodland with Brachystegia spiciformis, B. boehmii dominating, as well as Julbernardia
globiflora, Pterocarpus angolensis, Dalbergia melanoxylon, Isoberlinia spp., Diplorhyncus condylocarpus and Combretum spp. This
occurs as closed woodland and dense thickets in the centre
and south, as open woodland in the west, and as scattered
Fig. 1 – Location of the Selous Game Reserve in Tanzania.
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Fig. 2 – Detail of Selous Game Reserve hunting blocks.
National Parks (Mikumi and Udzungwa) are shown in light
grey; Kilombero Game Controlled Area, and Kilwa and
Liwale Open Areas in medium grey.
tree grassland in the east (see Creel and Creel (2002) and Stephenson (1990) for details).
For tourist hunting purposes, the Game Reserve is divided
into 47 hunting blocks and there are adjacent Game Controlled Areas and Open Areas where hunting is allowed
(Fig. 2). The Selous alone generates 35% of the tourist hunting
income for the Government of Tanzania (Baldus and Cauldwell, 2004; Kibonde, 2006).
2.2.
Species classifications
We used the Tanzania Wildlife Act of 1974 and AEC’s data on
Selous quotas and offtake 1988–1997 to determine the species
hunted in Selous and the hunting policies for both tourist and
resident hunters (Table 1). Then, using authoritative guides
for African mammals, Estes (1991), Kingdon (1997), Nowak
(1999) and Stuart and Stuart (2001), legally hunted species
were first classified according to whether adult males provide
parental care either through regular offspring defense or
through food provisioning. Next, species were classified as
to whether males are known to commit infanticide, a behavior that may occur when new males usurp harem holders or
when males encounter a harem where there are no biological
fathers to defend the group; male territorial defense of cubs
therefore came under this heading. Finally, species were classified according to harem size (Table 2). Harem sizes determine whether reproduction is male or female-limited, and
can substantially alter predictions of population responses
to hunting pressures (Greene et al., 1998; Young and Towbin,
submitted for publication).
2.3.
Standard and tailored models
We applied an age–sex structured density independent model
to determine maximum sustainable harvest for a variety of
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913
parameterizations and hunting policies (details in Young
and Towbin, submitted for publication). We chose to use a
density independent model because we assumed that, in contrast to populations in national parks, hunted populations are
not likely to be at carrying capacity or limited by resources
due to sustained hunting pressure from both legal tourist
hunting and illegal hunting (Holmern et al., 2007). The model
allows a variable number of stage- and sex-specific age classes (jm: number of juvenile male cohorts, jf: juvenile female
cohorts, am: adult male cohorts, af: adult female cohorts) as
well as stage- and sex-specific survival rates for male and female birth-class individuals (sM and sF, respectively), male and
female juveniles (rM and rF), and male and female adults (qM
and qF) (see Fig. 3). Inaccuracies in longevity estimates have
little effect on reproductive output because of low survival
probabilities in old animals. Various aspects of species’ breeding systems are also included in subsequent iterations of the
model, including fecundity (m), harem size (h), both paternal
(pM) and maternal (pF) care, and infanticide (p) with time steps
measured in inter-birth intervals with survivorship parameters corresponding to the species’ particular inter-birth interval (Young and Towbin, submitted for publication).
Hunting policies defined by legally hunted stage–sex classes include: adult males, or both male and female adults.
Indiscriminate and illegal ‘‘subsistence’’ hunting of all age–
sex classes also occurs. A particular hunting policy also includes an offtake level, defined as the proportion of the total
population that is harvested, ph. In our model analyses, we
use the conventional but arbitrary maximum sustainable
yield for a species as the largest offtake level for which population growth rates remain positive, k > 1. In addition to the
legally hunted classes, we allow a proportion of encounters,
pI, to result in deaths of individuals mistakenly identified as
legal. We assume that these additional kills are incidental
take and do not count towards the legal offtake level. When
included in the model, we assumed that pI = 0.10. We chose
this figure as a rough balance between hunters taking more
than 10% of females or juveniles and not declaring them on
the one hand, and hunters reporting some of this incidental
take as legal offtake, on the other, bearing in mind that data
on illegal hunting bags are unavailable at present. For leopards (Panthera pardus), we assume an incidental take of
pI = 0.30 because genetic studies have determined that about
30% of the leopards killed in Tanzania are female (Spong
et al., 2000).
We consider archetypal large carnivores and large herbivores defined by what is necessarily an amalgamation of different survival rates and fecundities of various species. We
first consider a standard model for each of these archetypes
in which species are monogamous, provide no paternal care,
and do not commit infanticide. We do this for illustrative purposes, namely to demonstrate the shortcomings of using population models that do not incorporate information on
animal breeding systems. We then tailor these two standard
or generic models to correspond to common breeding systems found among hunted species in the Selous (Table 3). Survivorship, numbers of stage–age classes, and fecundities are
the same for the standard and tailored models.
The carnivore survival rates are defined as: sM = 0.7,
sF = 0.7, rM = 0.8, rF = 0.8, rM = 0.8, and rF = 0.9. The number
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Table 2 – Aspects of breeding systems of game species (mammals) hunted by tourists in Tanzania.
Baboona
Buffalo
Bushbuck
Bushpig
Caracal
Catb
Dikdik
Duikerc
Elandd
Elephant
Galago
Fox – bat-eared
Gazelle – Grant’sd
Gazelle – Thomson’sd
Gerenukd
Hare – African
Hare – jumping
Hartebeest
Hippopotamus
Hedgehog
Hog – giant forest
Hyena – spotted
Hyrax – rock
Hyrax – tree
Impalad
Jackale
Klipspringer
Kudu – greaterd
Kudu – lesserd
Leopardd
Liond
Mongoose
Monkey – blue
Monkey – vervet
Oribi
Oryx
Otter
Pigmy antelope
Porcupine
Pukud
Ratel
Reedbuckh
Roand
Sabled
Sharpe’s grysbok
Sitatunga
Steinbuck
Topi
Warthog
Waterbuckd
Wildebeest
Zebra
Zorilla
a
b
c
d
e
f
g
h
Offspring accompany
parent during hunting season?
Male of care offspring?
Yes
Yes
Yes
Yes
Yes/No
Yes/No
Yes
Yes
Yes
Yes
Yes
Yes/No
Yes
Yes
Yes
No
No
Yes
Yes/No
No
Yes
Yes/No
Yes/No
No
Yes
Yes/No
Yes/No
Yes
Yes
Yes/No
Yes/No
Yes/No
Yes
Yes
Yes
Yes
Yes/No
Yes
Yes
Yes
Yes/No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes/No
No
No
No
No
No
No
Yes
Yes?
No
No
No?
Yes
No
No
No
No
No
No
No
No
No
No
No
No
No
Yes
Yes
No
No
No
No
Yesf/Nog
No
No
Yes
No
Yes?
Yes
No?
No
No?
No
No
No
Yes?
No
Yes
No
No
No
No
No
No?
Olive and yellow baboon combined.
Civet, genet, serval and wildcat combined.
Abbots, blue, common and red combined.
Species in which only adult males can be legally shot.
Golden, black-backed and side-striped combined.
Dwarf and banded mongoose;.
Slender, grey, white-tailed and marsh mongoose species.
Bohor, mountain and southern combined.
Infanticide by males?
Yes
No
No
No
Yes?
No?
No
No
No
No
No
No
No
No
No
No
No
No
Yes
No
No
No
No
No
No
No
No
No
No
Yes?
Yes
No
Yes?
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
Yes
No
Group size
>5
>5
2–5
2–5
1
1
2–5
2–5
>5
>5
1
2–5
>5
>5
2–5
1
1
>5
>5
1
1
>5
>5
1
>5
2–5
2–5
2–5
2–5
1
>5
1g/>5f
>5
>5
2–5
>5
1?
2–5
2–5
>5
2–5
2–5
>5
>5
2–5?
2–5?
2–5
>5
>5
>5
>5
>5
2–5?
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Fig. 3 – (A) The stage–age structured model of Young and Towbin (submitted for publication). The model tracks the
demography of the sexes separately. Age classes (boxes corresponding to reproductive cohorts) are classified by the birth,
juvenile and adult stages. The model tracks the numbers of individuals belonging to each age class. The stages have stagespecific survival rates (s, r, and q) that determine the fraction of individuals that move to the adjacent age class in the next
generation in the absence of hunting. Hunting policy defines which stage–sex classes are legal to hunt (i.e., adult males,
adults of both sexes, or subsistence hunting that allows juveniles and adults of both sexes to be hunted) and the hunting
pressure applied to the population (i.e., quota). (B) The temporal order of calculations is for a single generation of the model.
Mortality is first calculated based on the natural survival rates (s, r, and q), hunting mortality, and mortality of individuals in
the birth class due to infanticide or parental care. After mortality, the remaining adults are collected into breeding groups
(e.g., harems or monogamous pairs), and are allowed to reproduce (i.e., add individuals to the next time step’s birth class).
Finally individuals are shifted one age class to the right, and the population census is taken.
Table 3 – Selous species categorizations for tailored models; species known or suspected of being infanticidal are in italics.
Paternal Care
Yes
No
Approximate harem size
1
Klipspringer
Warthog
2
5
1
5
10
Suni
Oribi
Duiker
Zebra
Bushpig
Leopard
Ratel
Porcupine
Steinbuck
Lion
Waterbuck
Bushbuck
Greater Kudu
Reedbuck
Roan
Hippopotamus
Hartebeest
Wildebeest
Sable
Impala
Eland
Buffalo
Puku
Elephant
Jackal
Parental care refers to males maintaining a territory around females, maintaining vigilance for mates and their offspring, or being involved in
antipredator defense of their offspring.
of cohorts in each carnivore stage–sex class are: jm = 3, jf = 2,
am = 8, af = 13; juvenile males take longer to reach sexual
maturity than females so we ascribed them an additional
juvenile cohort. We assumed an average fecundity of 2.5 offspring per reproductive female per inter-birth interval. We always assumed that carnivores are monogamous (i.e., harem
size, h = 1). The herbivore survival rates are defined as:
sM = 0.8, sF = 0.8, rM = 0.85, rF = 0.85, qM = 0.875, and
qF = 0.925. The number of cohorts in each herbivore stage–
sex class are: jm = 2, jf = 2, am = 10, af = 12. We assumed an
average fecundity of one offspring per reproductive female
per inter-birth interval. Harem size was variable under the
herbivore scenario (i.e., h = 1, 2, 5, or 10). Note, life history
variables for the carnivore and herbivore were a conglomeration of parameters of many species ranging, for instance,
from leopard (Panthera pardus) to zorilla (Inctonyx striatus),
and eland (Taurotragus oryx) to oribi (Ourebia ourebi) and are
therefore modal values of well-worked species, poorly known
species and best guesses. In short, we made a conscious decision to sacrifice accuracy in life tables of a handful of wellworked species for general conclusions about most of the
important larger mammals hunted in Tanzania.
Infanticide, maternal care, and paternal care, when included, were parameterized as: p = 1.0 (i.e., the extreme case
916
B I O L O G I C A L C O N S E RVAT I O N
where death of a reproductive male always leads to the death
of that male’s offspring due to infanticide), pM = 1.0 (i.e., the
severe case where male mortality always leads to the death
of a male’s offspring due to lack of paternal care) and
pF = 1.0 (i.e., female mortality always leads to the death of a
female’s offspring due to lack of maternal care). All of the tailored models include maternal care because this is ubiquitous
in mammals. Therefore, the realized birth-class survival (i.e.,
accounting for infant mortality due to natural maternal mortality), calculated using Eqs. (44)–(49) in Young and Towbin
(submitted for publication), is 0.63 for carnivores and 0.74
for herbivores. If paternal care is included in the model, natural adult mortality produces a realized birth-class survival of
0.50 for carnivores and 0.65 for herbivores. The realized birthclass survivorship under maternal care (sF = 0.63) as well as
juvenile (qF = 0.85) and adult survival rates (qF = 0.925) are
similar to observed rates for buffalo (Synerus caffer) (sF = 0.67,
rF = 0.86, qF = 0.93) and wildebeest (Connochaetes taurinus)
(sF = 0.75, rF = 0.89, qF = 0.79) in the Serengeti (Grange et al.,
2004). The reduction in realized birth-class survival for species exhibiting paternal care is similarly observed in zebra
(Equus burchelli) on the Serengeti, although in our parameterization, realized birth-class survival is higher than estimates
for Serengeti zebra (95% confidence interval of s = 0.30–0.48;
Grange et al., 2004). For African mammals, there are actually
rather few commonly hunted species for which other life history variables are known to which we can verify our model
parameter values.
2.4.
Population estimation and actual hunting intensities
In order to compare model results to actual hunting offtake
occurring in Selous, for some species we collated density estimates from aerial census data that have been carried out by
Tanzania Wildlife monitoring teams over the Selous; these
counts are not age or sex-specific. These estimates were the
averages of the October 1986, September 1989, June 1991, September 1994, October 1998 and October 2002 censuses (Caro,
2005; Stoner et al., 2007) resulting in one population estimate
for each species in the Selous. We used these estimates for
eland, greater kudu Tragelaphus strepsiceros, hartebeest (Alcelaphus buselaphus), hippopotamus (Hippopotamus amphibius),
puku (Kobus vardonii), sable antelope (Hippotragus niger), waterbuck (Kobus ellipsiprymnus), wildebeest and zebra. These are
the best available population data that we have for these species at present because permission is not granted to conduct
ground surveys in the hunted part of the Selous Game Reserve. For other species that are difficult to count from the
air (Caro et al., 2000), we used density estimates from a foot
survey conducted in three hunting blocks in a miombo habitat similar to the Selous, in the Rukwa Game Reserve of western Tanzania (Waltert et al., 2008). These species were
bushbuck (Tragelaphus scriptus), bushpig (Potamochoerus porcus), common duiker (Sylivcapra grimmia), impala (Aepyceros
melampus), reedbuck (Redunca arundinum), and warthog (Phacochoerus aethiopicus). For elephant (Loxodonta africana), we
used the up-to-date figure from Baldus (2006). For klipspringer
(Oreotragus oreotragus), oribi, steenbok (Raphicerus campestris)
and suni (pigmy antelope) (Neotragus batesi), we arbitrarily divided the Rukwa ‘‘small antelope’’ density by four. In addition,
1 4 2 ( 2 0 0 9 ) 9 0 9 –9 2 9
for buffalo, we used the Rukwa density of 1.6/km2 rather than
the average aerial census density of 2.0/km2 because, one
author, AEC, who has extensive field experience of buffalo
in Selous, felt the latter figure was too high. For lions (Panthera
leo), we used data from in depth studies in Selous (Creel and
Creel, 1996); for leopards, we used Estes (1991). We then generated a total estimated population size for each block by
multiplying density by block area taken from Cauldwell
(2004). All these estimates are necessarily crude but they are
the best available at present.
Next, we compared sustainable offtake that we operationally defined as the percentage of the population, for which
k > 1, as predicted by the tailored models with (a) the percentage of the block population allocated for hunting and (b) the
percent of the block population that was actually taken by
hunters as based on Tanzania Wildlife Division inventory records averaged across years 1988–1997. This enabled us to
determine whether permissible offtake and actual offtake exceeded or fell below calculated sustainable offtake. The model
did not include interactions between population size and
hunting success because we assumed hunters would continue
to fill their quota based on their prior agreement with the hunting company rather than according to population abundance.
3.
Results
Of the 53 mammal game species or species constellations (e.g.,
mongooses) hunted by tourists in Tanzania, 35 give birth to
offspring that accompany them during hunting season, four
produce offspring that are not with them, leaving 14 species
where information is equivocal as to whether offspring
accompany their parents during this period (Table 2). Therefore there is a potential for hunters to shoot females with
dependent young in a minimum of 66% of the species that
they are allowed to shoot if they do not check whether females
are lactating or have young close by. Males help care for offspring in 11 out of the 53 species, and it is notable that males
may be legally shot in all of these 11 species! Infanticide by
males is relatively uncommon. Infanticide occurs or is
thought to occur in 7 out of 53 species. Males are exclusively
targeted in only two of these species, lion and leopard.
Of the 53 game species, 32 are solitary or live in large
groups where removal of a single individual is unlikely to
influence subsequent survival or reproduction of conspecifics,
whereas perhaps 19 species live in small permanent groups of
less than five animals where Allee effects (Allee, 1931) might
become important as a result of the removal of an individual.
Our model does not include Allee effects, and the results of
our model should be interpreted with caution for species or
populations in which Allee effects might be important.
Focusing on species hunted in Selous, and separating species by whether males care for offspring, commit infanticide,
or the species lives in small groups, the following pattern
emerged (Table 3). Most Selous game species show no paternal care; the majority of species live in harems of 5–10 individuals, and few show infanticide. We now discuss the
response to hunting of 24 of these species, omitting jackal
species, ratel (Mellivora capensis) and porcupine (Hystrix galeata) which feature little in hunters’ bags.
B I O L O G I C A L C O N S E RVAT I O N
917
1 4 2 ( 2 0 0 9 ) 9 0 9 –9 2 9
Fig. 4 – Standard carnivore and herbivore models. (A) Standard carnivore model: Effect of hunting quota (ph) on population
growth rates (k) under the three hunting policies (marked). (B) Standard herbivore model: Effect of hunting quota on
population growth rates under the three hunting policies. (C) and (D) Standard carnivore and herbivore models respectively:
Both panels show, for three different hunting policies (marked), the effect of increasing the hunting quota (ph) on the
proportion of the subpopulation that will be removed.
Table 4 – Model predictions of stable stage–sex structure and female to male ratio under the carnivore and herbivore guild
models (harem size = 1, no parental care, no infanticide, no incidental take).
Guild
Carnivored
Herbivoree
a
b
c
d
e
Hunting policy MSY a Subpop. HIb Relative frequencies of stage–sex classesc Female to male ratio % females
in harems
A
J
J
Adult
Juv.
A
No hunting
Male
Adult
Subsistence
0.018
0.063
0.062
No hunting
Male
Adult
Subsistence
0.023
0.062
0.063
m
f
0.121
0.121
0.062
0.15
0.12
0.15
0.14
0.36
0.44
0.30
0.34
0.28
0.25
0.32
0.29
m
0.21
0.19
0.23
0.22
f
2.4
3.8
2.0
2.4
0.8
0.7
0.7
0.8
42
27
49
42
0.094
0.094
0.063
0.27
0.22
0.26
0.26
0.37
0.47
0.35
0.36
0.18
0.16
0.20
0.19
0.18
0.16
0.20
0.19
1.4
2.2
1.3
1.4
1.0
1.0
1.0
1.0
73
46
76
74
Maximum sustainable yield, as a proportion of the total population, under the specified hunting policy.
Subpopulation hunting intensity: proportion of the subpopulation harvested.
Am = adult male class, Af = adult female class, Jm = juvenile male class, and Jf = juvenile female class.
Juvenile female cohorts = 2, juvenile male cohorts = 3, adult female cohorts = 13, adult male cohorts = 8, and fecundity = 2.5.
Juvenile female cohorts = 2, juvenile male cohorts = 2, adult female cohorts = 12, adult male cohorts = 10, and fecundity = 1.0.
918
3.1.
B I O L O G I C A L C O N S E RVAT I O N
The standard models
1 4 2 ( 2 0 0 9 ) 9 0 9 –9 2 9
that, even under no hunting, the population stage–sex structure is skewed towards females (when male survival is lower
than that of females and quite a large proportion of females
are non-reproductive, see percent of females in harems column). In other words, the population is always reproductively
male-limited when males have lower survival and the species
is monogamous.
With knowledge of the stationary age–sex classes in the
population for these hunting intensities, these maximum
sustainable quotas correspond to 12.0% of the carnivore male
subpopulation, 12.0% of the carnivore adult subpopulation, or
6.2% of the whole carnivore population as before (Fig. 4C). For
herbivores, the above levels of offtake constitute 9.4% of the
male subpopulation, 9.4% of the adult subpopulation, or
6.3% of the whole population (Fig. 4D).
Young and Towbin (submitted for publication) develop a basic
model that explores the response of population growth rates
to hunting under three different hunting policies (Fig. 3). Here,
we reexamine this basic model by parameterizing an archetypal large carnivore and large herbivore to address variation
in life history parameters between these mammalian guilds.
In the standard models, we assume no parental care, no
infanticide and a harem size of one. In our model analyses,
for simplicity we define the maximum sustainable yield as
the largest quota for which population growth rates remain
positive, k > 1. In practice, of course, it would be unwise to
set quotas at or even close to this level. However, this boundary is a useful tool to compare the sustainability of hunting
policies under different models.
Our two standard models showed that hunters could remove 1.8% of the carnivore population if they shot only
males, 6.3% if they shot both adult males and females, and
6.2% if they shot any age–sex class before the population
started to decline (Fig. 4A). For herbivores, they could remove
2.3% of the population if they killed only males, 6.2% if they
shot both adult males and females, and 6.3% if they shot
any age–sex class (Fig. 4B). Adult and subsistence hunting policies under both the carnivore and herbivore models allow
larger sustainable quotas than male hunting policies because
male hunting alone shifts the age–sex structure of the population. This is shown clearly in Table 4 where it can be seen
3.2.
The tailored models
For our tailored models, we again divided our scenarios into
two major categories, carnivores and herbivores. Next, we divided carnivores into two scenarios, ‘‘lion’’ and ‘‘leopard’’,
and, in the interests of conciseness, collapsed the 22 herbivore species into eight scenarios, ‘‘Impala’’, ‘‘Kudu’’, ‘‘Steinbok’’, ‘‘Hippo’’, ‘‘Hartebeest’’, ‘‘Zebra’’, ‘‘Oribi’’ and ‘‘Warthog’’
to incorporate differences in breeding system parameters
(Table 5) clearly recognizing that this categorization ignores
details of species-specific differences. The first five scenarios
correspond to species in which only adult males are hunted,
Table 5 – Model predictions of stable stage–sex structure and female to male ratio under the ten carnivore and herbivore
models.
Model
Lion
ha
5
Pat. careb
N
Inf.c
Y
Leopard
2.5
N
Y
Impala
10
N
N
Kudu
5
N
N
Steinbok
1
N
N
Hippo
10
N
Y
Hartebeest
10
N
N
Zebra
5
Y
Y
Oribi
2
Y
N
Warthog
1
Y
N
a
b
c
d
e
Hunting
policy
No hunting
Males
No hunting
Males
No hunting
males
No hunting
Males
No hunting
Males
No hunting
Adults
No hunting
Adults
No hunting
Adults
No hunting
Adults
No hunting
Adults
MSYd
ITe
(%)
0.051
9.9
0.038
6.8
0.068
5.9
0.060
6.3
0.010
8.0
0.051
5.9
0.071
5.9
0.051
5.9
0.051
5.9
0.021
6.7
Relative frequencies of stage–sex classesf
Am
Af
Jm
Jf
0.13
0.03
0.13
0.06
0.26
0.04
0.26
0.06
0.28
0.26
0.27
0.27
0.26
0.26
0.27
0.27
0.27
0.27
0.28
0.28
0.30
0.54
0.30
0.48
0.35
0.49
0.35
0.52
0.40
0.44
0.36
0.36
0.35
0.34
0.36
0.36
0.36
0.36
0.40
0.40
0.32
0.25
0.32
0.27
0.19
0.24
0.19
0.21
0.16
0.15
0.18
0.19
0.19
0.20
0.18
0.19
0.18
0.19
0.16
0.16
0.25
0.18
0.25
0.20
0.19
0.24
0.19
0.21
0.16
0.15
0.18
0.19
0.19
0.20
0.18
0.19
0.18
0.19
0.16
0.16
Female to male ratio
Adults
2.3
17.0
2.3
7.9
1.3
12.6
1.3
8.2
1.4
1.7
1.4
1.3
1.3
1.3
1.4
1.3
1.4
1.3
1.4
1.4
Juv.
0.8
0.7
0.8
0.7
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
Harem size.
Paternal care: Y = included in the model, N = not included. Note: all models include maternal care.
Infanticide: Y = included in the model and N = not included.
Maximum sustainable yield, as a proportion of the total population, under the specified hunting policy.
Percent reduction in maximum sustainable yield assuming 10% of kills are incidental take (except for leopard, where 30% of kills are
incidental). Incidental classes for each species are described in the text.
f Am = adult male class, Af = adult female class, Jm = juvenile male class, and Jf = juvenile female class.
B I O L O G I C A L C O N S E RVAT I O N
1 4 2 ( 2 0 0 9 ) 9 0 9 –9 2 9
919
Fig. 5 – Tailored models. Solid lines assume that incidental take, pI= 0. Dashed lines assume that incidental take, pI = 0.1; for
leopards, pI = 0.3. Subsistences 1 and 2 are offtake of juveniles and adults of both sexes of warthog and buffalo, respectively.
whereas the last five scenarios correspond to species in which
adult males and females are hunted.
3.3.
Carnivores
Hunters are only allowed to shoot male lions. Coalitions of
usually 2–3 male lions hold a pride of 5–10 females but show
no paternal care as defined by regular care of offspring. When
a coalition of males replaces another, the incoming coalition
kills offspring fathered by the previous coalition. Since smaller coalitions are more likely to lose fights to larger coalitions,
removal of a territorial male increases the probability of
infanticide (Packer et al., 1988). We set harem size as five in
the ‘‘lion scenario’’. Hunting offtake can reach 5.1% of the
population before the population growth rate declines to
k < 1 (Fig. 5A). Therefore, the maximum sustainable quota under this scenario is 5.1%. If we add an incidental take of juvenile males because they are difficult to distinguish from adult
males in the field, sustainable offtake is reduced to 4.6% (a
9.9% reduction). We do not consider an incidental take of females because the sexes are dimorphic and easily distinguishable, nor do we consider adult males <5–6 years old
taking as incidental because males of this age are still allowed
to be shot legally in Tanzania (Whitman et al., 2007).
Tourist hunters are only legally allowed to shoot male
leopards. Male leopards defend territories that overlap those
of two to three female territories but they show no paternal
care. Incoming males commit infanticide if they take over
the territory of the current male. We set harem size as 2.5
in our leopard scenario. The maximum sustainable quota under this scenario is only 3.8% of the population (Fig. 5B). However, approximately 30% of the leopards killed in Tanzania are
female (Spong et al., 2000). If we add a 30% incidental take of
adult females, sustainable offtake is reduced to 3.6%.
3.4.
Herbivores where adult males are shot
Turning now to herbivores, tourist hunters are allowed to
shoot males in strongly sexually dimorphic species, but
adults of both sexes in many other species. The majority of
herbivore species show no paternal care and no infanticide.
We therefore separated herbivores into eight groups.
Among buffalo, eland, impala, puku, and sable antelope,
only males may be hunted. In these species, termed here
the ‘‘impala scenario’’, there is no paternal care, no infanticide, and these species are highly polygynous. We set harem
size at 10 recognizing that this is an underestimate in some
populations. Offtake here should not exceed 6.8% of the population if population is to remain viable (Fig. 5C). Adding an
incidental take of 10% of juvenile males lowers the sustainable offtake to 6.4%.
Among greater kudu, waterbuck, bushbuck, roan antelope
Hippotragus equinus and reedbuck (‘‘kudu scenario’’), where
hunters are similarly allowed to hunt only males, harem size
is smaller, so we assumed a harem size of five. Again, there is
no paternal care or infanticide. The maximum sustainable
920
B I O L O G I C A L C O N S E RVAT I O N
quota for the ‘‘kudu scenario’’ is 6.0% (Fig. 5D). Allowing incidental take of juvenile males results in a sustainable hunting
offtake of 5.6%.
Adult males are legally hunted in steinbok. Steinbok are
monogamous, so we assumed a harem size of one. There is
no paternal care or infanticide. The maximum sustainable
quota for this species is only 1.0% (Fig. 5E); incidental take
of juvenile males results in a 0.9% sustainable offtake. This
differs from the standard model because of maternal care.
In all cases except steinbok, a male hunting policy alters
the stationary age/sex structure of the population (Table 5).
The steinbok stationary age/sex structure does not change
much, because the species is monogamous and cannot tolerate high male hunting pressures. The rest of the herbivore
models (below) assume adult hunting of both sexes which alters the stationary age/sex structure very little.
1 4 2 ( 2 0 0 9 ) 9 0 9 –9 2 9
em size = 1) because several studies have indicated that they
are a favored food in the diet of poachers and that they are
under threat across Tanzania (Stoner et al., 2007; Caro,
2008). Legal hunting offtake aside, warthog populations could
withstand an offtake of only 2.3% if all age–sex classes were
taken (Fig. 5K). Similarly, poachers frequently target buffalo
(no paternal care, no infanticide, harem size = 10). Independent of legal hunting, this species can sustain subsistence
hunting offtake of up to 8.2% (Fig. 5L).
3.7.
Tourist hunting quotas and offtake in Selous
It is extremely difficult to tell male and female hippopotami
apart because their testes are internal and they spend much
time in water. In the ‘‘hippopotamus scenario’’ there is no
paternal care but there is infanticide. Harem size is large,
h = 10 (or more). The maximum sustainable quota for this
species is 5.1% (Fig. 5F), which is reduced to 4.8% if incidental
take of juvenile males and females is included.
In hartebeest, wildebeest and elephant (‘‘hartebeest scenario’’), there is no paternal care, no infanticide, and harem size
is large; we set it at 10. In this ‘‘hartebeest scenario’’, k < 1 when
offtake reaches 5.0% (Fig. 5G) and stays at 5.0% when incidental
take is set at 10% juvenile males and females.
In both zebra and bushpig (‘‘zebra scenario’’), infanticide
has been reported anecdotally. In these species there is paternal care in the form of offspring defense, and harems are of
medium size. We categorized these as five. In this ‘‘zebra scenario’’, k > 1 when offtake reaches 5.0% (Fig. 5H) and stays at
5.0% when incidental take is set at 10% juvenile males and
females.
In the many duiker species, males show paternal care
through antipredator vigilance, but there is no infanticide
and these species are monogamous or bigamous. Thus for
this ‘‘oribi scenario’’, which includes species such as oribi,
common duiker and suni, harem size is two. The proportion
of the population that can be removed before the population
declines is 5.1% (Fig. 5I), which is reduced to 4.8% when
including incidental take of juvenile males and females.
Warthog and klipspringer show paternal care, principally
through antipredator defense, but there is no infanticide
and harem size is one. The maximum sustainable quota for
the ‘‘warthog scenario’’ is 2.1% (Fig. 5J). Adding a 10% offtake
of juvenile males and females reduces the maximum sustainable quota to 2.0%. Model predictions for these 10 scenarios
are summarized in Table 5. Note that while the exact date
that a female with attendant offspring is shot will affect offspring survival probability, we did not attempt to model this.
We now compare the predictions of these specific tailored
models to hunting quotas and actual tourist hunting offtake
across the whole Selous Game Reserve and then across
individual hunting blocks for each of 22 species separately
(roan antelope do not occur in Selous, and puku only occur
in a very small area along Kilombero River to the extreme
west and are not a significant game species in Selous). Perhaps optimistically we assumed that hunting is done professionally and therefore disregarded incidental take.
Appendix A shows that across the whole Selous 20 species
were allocated quotas less than calculated sustainable offtake and only one exceeded it. This was leopard. When
the 43 hunting blocks were examined separately, however,
it was apparent that certain species were allocated quotas
that consistently surpassed calculated sustainable offtake
based on tailored models and estimated population sizes
in blocks. These were eland, hartebeest, leopard, lion, reedbuck, sable antelope, warthog, waterbuck and possibly
steinbok. Some of these quotas were far larger than calculated sustainable offtake, notably leopard and lion, two of
the species for which the greatest number of hunting
blocks exceed calculated sustainable offtake. Despite these
generous quotas, there were very few instances indeed
where actual offtake was higher than calculated sustainable
offtake and seven out of eight of these were in one hunting
block, KY1/Gonabis. Indeed, for a number of species such as
oribi, steinbok and suni (pigmy antelope), no kills were
reported.
Turning to the hunting blocks in Appendix A, there was
great variability in the number of species for which quotas
went above calculated sustainable offtake. In 22 out of 43
blocks, quotas of only one or none of the 21 species exceeded
calculated sustainable offtake, whereas in two out of 43
blocks, 50% or more of species’ hunting quotas were over calculated sustainable offtake (elephant are not included on
quotas as offtake is controlled by setting minimum trophy
sizes). These blocks were M1 and U1, and quotas for the
remaining 19 blocks were often consistently high across species. For instance, approximately one third of species’ quotas
appeared high in blocks K3, K4, KY1/Gonabis, L1, LU5, M2, R3,
and U2. These data on hunting blocks are more robust than
data broken down by species because they rely less heavily
on accurate densities for a given species.
3.6.
4.
3.5.
Herbivores where adult males and females are shot
Subsistence hunting
We were also interested in modeling offtake based on subsistence hunting of warthog (paternal care, no infanticide, har-
Discussion
Our goal in this paper was to parameterize the exploitation
models of Young and Towbin (submitted for publication) to
B I O L O G I C A L C O N S E RVAT I O N
make them applicable to large mammals hunted in the
important game reserve of East Africa, the Selous. Since
we are now assessing contemporary hunting practice that
may be of interest to managers, and the Wildlife Division
of Tanzania in particular, it is important to outline the
shortcomings of these analyses at the outset. These analyses are timely given the attempts to certify the tourist
hunting industry in Tanzania (Nshala, 1999).
First, there are a number of difficulties with the parameterizations of the models. Notably, we approximated parameters for group sizes, fecundity, and sex ratio based on
values taken from the literature that came from studies in
many parts of Africa, frequently national parks or protected
areas. Harem sizes and sex ratios may not always represent
those in hunted areas in general or in the Selous specifically;
moreover there is likely to be intrapopulation variation within the Selous itself. Furthermore, we had to estimate survival rates for both sexes, and this was very difficult as so
few studies have examined survivorship in the wild. Our
estimates are principally based on a handful of prominent
studies from one or two species that we hope approximate
other similar-sized species in the herbivore or carnivore
guild. We did not attempt sensitivity analyses as these are
beyond the scope of this paper, and they would be difficult
to verify because so little is known about inter-population
variability in life history parameters of most exploited species. Nonetheless, our parameters are satisfyingly similar
to single species studies elsewhere with good data (e.g.,
Grange et al., 2004).
We also made a number of assumptions about species
densities. First, densities for large animals were derived
from an average of aerial censuses conducted over a 15year time span. Aerial censuses provide reasonably good
estimates of larger mammals (Caro et al., 2000). For the
smaller or more secretive herbivores, and also buffalo, we
used a foot census from a different miombo area but nevertheless where big game hunting has occurred for many
years, the Rukwa Game Reserve. For lion we used estimates
from the northern Selous but from an unhunted area which
will make predictions about this species rather generous. Finally, we took leopard density from the literature. While
density estimates derive from diverse sources, there is no
a priori evidence to suggest aerial or ground, Selous or
non-Selous sources show systematic bias for those species
involved. In sum, there is no question that some of these
density estimates are necessarily coarse and may even be
optimistically large which would make our estimates of
sustainable offtake generous.
We used these densities to calculate population sizes in
each hunting block, and this introduces further inaccuracies
because blocks vary in types of habitat they support, some
containing more open floodplains, others more rivers and
so on. There are known soil and vegetation differences in
the Selous Game Reserve but their relationship to animal
densities is poorly understood. Applying a uniform density
to each hunting block is therefore very coarse indeed.
Nonetheless, in the absence of systematic surveys in each
block, it is unfortunately the best approximation that we
have. We wanted to focus on blocks because this is the
1 4 2 ( 2 0 0 9 ) 9 0 9 –9 2 9
921
level at which decisions are made by the Wildlife
Division.
Hunting offtake presents an additional problem. While
hunting quotas are correct, offtake may not be entirely accurate due to documented reporting difficulties (Baldus and
Cauldwell, 2004) with the magnitude of bias for different species unknown. Finally, although there is no resident hunting
in Selous, which removes an unknown source of offtake, illegal hunting from nearby villages is common (Gillingham and
Lee, 1999) and this may affect our conclusions. For example, if
market forces change and demand for bush meat increases,
then illegal hunting may reduce population sizes of certain
species and thereby change sustainable tourist hunting
offtake.
Our assumptions are therefore three-tiered. There are
concerns about the assumptions that went into the standard and tailored models, about estimating densities, and
about accuracy of data on hunting practices. All of these
will affect recommendations about hunting policy (Regan
et al., 2005). Our exercise is an initial attempt to assess sustainability of hunting in a very important hunting area in
Africa, an attempt that can and should be followed up if
better data on offtake and population sizes become
available.
4.1.
Standard and tailored models
The point at which a given level of offtake drives populations into decline is sometimes, but not always, strikingly
different between standard and tailored models. The standard model assumes a harem size of 1 (h = 1) but higher
harem sizes generally increase sustainable offtake. The
other breeding details (paternal care and infanticide) reduce
sustainable offtake. If then, a tailored model with say h = 5,
maternal care only, and infanticide is compared with the
standard model, the effects often, but not always, cancel
each other out. The magnitude of these antagonistic effects
will depend on the particular survival rates of the species,
principally the difference in survival rates between males
and females.
In general, both standard and tailored models allowed
for generous offtake levels between 2% and 7%; it is customary to set quotas much more cautiously at 2% of an
estimated population size (Baldus and Cauldwell, 2004).
For species in which only males are harvested, the standard
model that does not take breeding system into account allows for 1.8% and 2.3% of the carnivore or herbivore population respectively to be shot before lambda falls below 1.
The tailored models, however, allowed more animals to be
removed: 5.1% of lions to be shot, 6.8% of ‘‘impala’’, and
6.0% of ‘‘kudu’’, surprisingly high figures. Only for ‘‘steinbok’’ does knowledge of breeding system lower sustainable
harvest with 1.0% being removed before the population
starts to decline. Thus, depending on the species, breeding
system assumptions raise or lower sustainable offtake by
a considerable amount when male offtake is the mode of
removal. The large increase in sustainable offtake is due
to the effect of harem size because large harems (h = 5–10)
allow greater numbers of males to be harvested. The 56%
922
B I O L O G I C A L C O N S E RVAT I O N
reduction in sustainable quota size for the ‘‘steinbok’’ model
compared to the standard herbivore model is due solely to
the inclusion of maternal care in the tailored model.
For species in which both adult males and females can
be removed, the standard model allowed for 6.3% or 6.2%
of the respective carnivore or herbivore population to be
removed sustainably. For some species, the tailored models predicted similar figures (differing only by approximately 20%): 3.8% of ‘‘leopard’’, 5.1% of ‘‘hippo’’,
‘‘hartebeest’’, ‘‘zebra’’ and ‘‘oribi’’. Knowledge of breeding
systems substantially lowered sustainable offtake for
‘‘warthog’’, 2.1%, and leopard, 3.8%. Thus for populations
where male and female offtake is legal, tailored models
may lower offtake predictions by 20–80%, at least in these
large African mammals. It is worth noting that species
subject to male hunting show more of a ‘‘shoulder’’ in
the relationship between population growth rate and hunting pressure whereas a linear relationship exists in species
where both males and females are taken. Therefore populations may be more subject to threshold declines under
male hunting pressure.
For some species, then, differences between the standard
and tailored models forcefully highlight the importance of
understanding animal breeding systems when trying to predict effects of harvesting (Greene et al., 1998; Milner-Gulland,
1994; Rowe and Hutchings, 2003; Whitman et al., 2004, 2007;
Milner et al., 2007). In particular, we found that for those
species where males are monogamous, populations are very
susceptible to male offtake, regardless of whether males
showed paternal care (‘‘steinbok’’ and ‘‘warthog’’ models).
Thus it is clear that species with small harem sizes and
paternal care and where only males are shot are very sensitive to hunting pressure, even as low as 1% of the population. This finding would never have been uncovered using
simplistic exploitation models. For other species, however,
addition of breeding system information affects exploitation
models little.
4.2.
Incidental take
In our analyses we addressed the issue of incidental take,
that is killing age–sex classes that are different from legally
hunted classes. We did this because there are persistent rumours that hunters sometimes act illegally in the field and
we wanted to incorporate this aspect of uncertainty (Deines
et al., 2007). We found remarkably little impact of incidental
take when it was set at 10%. We based the incidental take
on an accepted figure of 10% of wounded individuals being
lost (Baldus and Cauldwell, 2004) and adjusted it to juvenile
males or to juvenile males and females depending on the
ease with which sexes can be distinguished in the field
and on which sexes are on the hunting roster. Thus we believe that this magnitude of take is an appropriate approximation and is neither too optimistic nor too pessimistic a
figure. That said, failure to shoot the correct age–sex class
in 1 out of 10 cases has very little effect on any population
except lions. Thus whatever one’s position on the occurrence or rate of mistakes in the field, it likely has rather little impact on population growth rates.
1 4 2 ( 2 0 0 9 ) 9 0 9 –9 2 9
4.3.
Subsistence hunting
We modeled subsistence hunting of two species, both of
which are believed to be under increasing pressure throughout Tanzania. Warthog are thought to be declining in most
areas of the country (Stoner et al., 2007) and buffalo are a
highly sought after meat species (Arcese et al., 1995). We
found that the warthog breeding system (paternal care, no
infanticide, harem size of one) predisposes it to being sensitive to an illegal offtake, characteristic of poachers, of only
2% before its populations start to decline. Thus it is perhaps
unsurprising that this species is in decline across Tanzania.
For buffalo, with no paternal care, no infanticide, and a large
harem size, the situation is more optimistic: populations do
not start to decline until 8% of individuals (of all age–sex classes) are taken through poaching.
4.4.
Tourist hunting in Selous
Overall, our modeling suggests that mammal populations in
the Selous Game Reserve are relatively unaffected by tourist
hunting practices. The quotas allocated for most species are
low and this is still true even if our population estimates
are as much as double what they should be. Only in the
case of leopard are overall quotas a cause for concern,
and perhaps bushbuck but we are less confident about estimated density for this species. Problems with hunting quotas for lion and leopard have been noted before for the
Selous (Creel and Creel, 1997; Spong et al., 2000) and elsewhere in Tanzania (Caro et al., 1998b). In regards to actual
offtake, there is cause for cautious optimism with numbers
taken rarely exceeding 1.5% of the population, whatever
species is considered. Even in a worse case scenario of population sizes of big game animals in the Selous being overestimated by a factor of two, offtake would never exceed
3%.
Considering individual hunting blocks, some striking
patterns emerge. Appendix A shows that in many blocks
quotas are high for bushbuck, eland, hartebeest, klipspringer, leopard, lion, reedbuck, sable antelope, warthog, waterbuck and perhaps steinbok. While low population density
estimates for certain species might undoubtedly account
for apparently high quotas, this is unlikely to be true for
lion and leopard because densities for those species come
from protected areas and are therefore likely to be higher
than in Selous. In contrast, certain species such as bushpig
and impala are being given low allocations and could sustain greater offtake per year. Buffalo are an anomaly. Our
data do not indicate overly high quotas for this species despite a general perception in Tanzania that they are being
overhunted (Baldus and Cauldwell, 2004) and that they are
the most preferred species of tourist hunters (Lindsey
et al., 2006).
Turning to the hunting blocks, quota allocations for
many blocks are appropriately below calculated sustainable
offtake for most species but certainly five and perhaps as
many as 10 blocks are being offered very generous quotas
indeed. It is interesting to note that Cauldwell (2004) in a
separate analysis concluded that blocks M1 and M2 suffer
B I O L O G I C A L C O N S E RVAT I O N
heavy hunting pressure and our data show generous quotas
in these blocks. Most of the problem blocks are situated in
the northwest and central region of the Selous where game
densities are traditionally higher than in the southern part
of the Game Reserve (UNEP-WCMC Protected Areas Programme – Selous Game Reserve, http://www.unepwcmc.org/sites/wh/selous.html, accessed 12/10/2008) so
they more likely reflect long term generous allocations
rather than low population densities. In contrast to these
quotas, very few blocks seem to be actually overhunted
according to our models despite the rule that hunting companies have to fulfill 40% of their total quota (all species
combined) to avoid being fined by the Wildlife Division (Baldus and Cauldwell, 2004). The exception to this is block
KY1/Gonabis where seven out of the 24 species are apparently overhunted.
4.5.
Conclusions
In summary, we recommend a reduction of hunting quotas
for certain species in the Selous Game Reserve, notably
eland, hartebeest, lion, reedbuck, sable antelope, warthog
and waterbuck but particularly leopard and bushbuck.
Warthog are especially susceptible to offtake because of
their breeding system. These reductions can be achieved
by focusing on quotas for particular blocks (see Appendix
A) rather than across all blocks in Selous. Moreover, many
species’ quotas in certain hunting blocks, namely K3, K4,
LU5, M1, M2, R3, U1, and U2, should be lowered, as their
levels appear unsustainable at present. We recognize that
reallocation of quotas between blocks is difficult given that
blocks are leased to different hunting companies.
Our analyses highlight four important issues. First, many
of the parameters that went into the large number of models
were based on best guess estimates or data borrowed from
studies in other parts of Africa or even taken from similar
species. There is a danger in such extrapolations. Better life
history data on hunted species need to be collected. Ideally,
studies should be conducted in those very areas where hunting quotas are under review. Thus, to achieve hunting policies
that remain within sustainable quotas, hunters or hunting
companies need to invite researchers to collect data on life
history parameters including longevity, sex ratio of both adult
and juvenile classes, age at first breeding, and social system.
For long lived large mammals, this may demand a permanent
research presence in a hunting area and a section of the population that is immune to hunts. Interestingly, this is akin to
the situation in Selous where some northern hunting blocks
have been turned over to photographic tourism and researchers are allowed to work unimpeded.
Second, our application of models to a real site, the Selous, demonstrates the importance of collecting data on
population sizes from hunting blocks. Presently, there are
no ground counts of animal populations in Selous hunting
blocks. Instead, we had to use aerial censuses and ground
estimates from elsewhere, which can differentially bias
density estimates considerably. Regular ground counts carried out in hunting blocks, most efficiently by hunting com-
1 4 2 ( 2 0 0 9 ) 9 0 9 –9 2 9
923
pany employees, could provide important data that could be
used to validate this and future models, particularly if data
on sex ratios were also collected. Such counts are unlikely
to be conducted on a regular basis, however, and estimating
large animal population sizes in hunting blocks remains a
persistent difficulty. Routine documentation of trophy metrics would also be very helpful (Baldus and Cauldwell,
2004) and may be easier to organize than population
censuses.
Third, marrying sophisticated modeling techniques with
information on animal breeding systems gives managers
the opportunity to assess whether their harvesting and conservation practices are appropriate. Most models of exploitation incorporate life history data or approximations
thereof but do not incorporate information about parental
care, group size or infanticide. In some situations these
data radically affect predictions about sustainable offtake,
in other situations they do not. Yet, we could not have predicted that monogamous species were so sensitive to male
offtake without constructing tailored models. We think it is
crucial to present the output of breeding system sensitive
models to improve long-term sustainability of hunting.
Finally, our analyses highlight the effectiveness of
encouraging modelers to work in real life situations. Our
analyses were conducted through an interchange between
the modelers seeking parameters, and the fieldworkers asking for more sensitive configurations of the models. Alone,
neither party could have achieved this level of sensitivity
and generality.
Acknowledgements
We are most grateful to Marc Mangel who organized and coordinated the collaboration. We thank Peter Towbin for discussion, Jen Hunter for help with structuring the Appendix A,
and Rolf Baldus, Marco Festa-Bianchet, Craig Packer and very
helpful anonymous reviewers for comments on the
manuscript.
Appendix A
Species are listed by column and 43 of the 47 Selous hunting blocks leased to hunting safari companies during the
period 1988–1997 are listed down the left hand side (excluding blocks B1, LU1, LU4, and Z1; KY1/Gonabis were combined for purposes of analyses). Areas of blocks (from
Baldus and Cauldwell, 2004), are listed in km2 in the second
column. For each block, the three rows respectively show
the estimated population size, percentage of the block population allowed by the average hunting quota averages between 1988 and 1997, and actual percentage of the
estimated block population killed averaged over those years.
There were no data on elephant quotas; kill data come from
Tanzania Wildlife Authority Budget reports years 1988–1992
(E. Severre, pers comm.). Quotas or kills were divided by
block population and multiplied by 100 to obtain population
percentages. Those that exceed calculated sustainable offtake are shown in bold (see Table A1).
924
B I O L O G I C A L C O N S E RVAT I O N
1 4 2 ( 2 0 0 9 ) 9 0 9 –9 2 9
Table A1 – Predicted maximum sustainable yield, hunting quotas, and actual offtake for hunting blocks in the Selous
Game Reservea.
Area (km2)
Buff.
Bushb.
Bushp.
Duiker
Eland
Eleph.
Harbst.
Hippo
Impala
Klipspr.
G. Kudu
6.8%
1.6
6.0%
0.4
5.0%
0.58
5.0%
1.15
6.8%
0.06
5.0%
1.38
5.0%
0.22
5.1%
0.38
6.8%
0.97
2.1%
0.16
6.0%
0.3
43,486
69,578
0.8
0.3
17,394
0.6
0.1
25,222
0.4
0.1
50,009
0.2
0.0
2609
5.4
1.5
60,011
–
0.0
9567
3.4
1.3
16,525
0.9
0.3
42,181
0.9
0.3
6958
0.6
0.0
13,046
0.9
0.2
423
677
2.2
0.7
1248
0.8
0.1
1202
0.8
0.0
725
0.8
0.1
603
3.0
0.4
1291
1.1
0.2
853
4.7
1.7
739
3.4
0.1
984
2.0
0.4
3456
0.3
0.2
2016
0.5
0.3
2712
0.4
0.2
1755
0.9
0.7
976
0.8
0.2
901
1.1
0.3
1414
0.8
0.5
2330
0.4
0.3
2597
0.3
0.3
842
1.2
169
1.2
0.1
312
1.3
0.0
300
1.3
0.0
181
1.1
0.0
151
2.0
0.1
323
1.2
0.0
213
2.3
0.4
185
1.6
0.0
246
0.8
0.0
864
0.1
0.0
504
0.2
0.0
678
0.4
0.0
439
0.5
0.2
244
0.8
0.1
225
1.8
0.0
354
0.3
0.1
582
0.2
0.1
649
0.2
0.0
210
1.9
245
1.2
0.3
452
0.9
0.0
436
0.5
0.0
263
0.8
0.1
219
0.9
0.0
468
0.9
0.0
309
1.9
0.7
268
1.1
0.0
357
0.0
0.0
1253
0.1
0.1
731
0.3
0.1
983
0.3
0.1
636
0.5
0.1
354
0.6
0.1
327
0.6
0.1
513
0.2
0.0
844
0.1
0.0
941
0.1
0.1
305
1.3
486
0.2
0.1
897
0.6
0.0
864
0.5
0.0
521
1.0
0.0
434
0.5
0.0
928
0.4
0.0
613
0.7
0.0
531
0.6
0.0
707
0.3
0.0
2484
0.0
0.1
1449
0.1
0.1
1949
0.3
0.1
1262
0.2
0.0
702
0.3
0.0
647
0.8
0.0
1017
0.1
0.0
1674
0.1
0.0
1866
0.1
0.0
605
0.8
25
3.9
3.2
47
8.5
0.0
45
4.4
0.7
27
29.4
0.7
23
17.7
0.9
48
6.2
0.4
32
31.3
12.2
28
14.4
0.4
37
10.8
0.8
130
2.3
1.5
76
5.3
3.0
102
3.9
1.8
66
3.0
1.8
37
5.5
0.0
34
11.8
1.8
53
5.7
3.8
87
2.3
1.8
97
2.1
1.3
32
12.7
584
–
0.0
1076
–
0.0
1036
–
0.0
625
–
0.0
520
–
0.0
1114
–
0.0
736
–
0.1
638
–
0.0
849
–
0.0
2981
–
0.1
1739
–
0.2
2339
–
0.0
1514
–
0.0
842
–
0.0
777
–
0.0
1220
–
0.1
2009
–
0.0
2240
–
0.0
726
–
93
6.4
3.5
172
3.5
0.6
165
3.0
0.2
100
4.0
0.2
83
18.1
1.4
178
3.9
1.0
117
14.5
5.0
102
7.9
0.6
135
7.4
2.7
475
1.7
1.2
277
2.9
2.1
373
2.1
0.9
241
2.5
1.3
134
1.5
1.0
124
8.1
1.4
194
3.1
2.0
320
1.6
1.5
357
1.4
1.2
116
5.2
161
0.6
0.4
296
1.7
0.1
285
0.7
0.0
172
2.3
0.1
143
3.5
1.1
307
1.6
0.5
203
2.5
0.0
176
2.3
0.0
234
2.1
0.7
821
0.5
0.3
479
0.8
0.4
644
0.6
0.2
417
1.0
0.3
232
0.9
0.4
214
2.8
0.7
336
0.6
0.6
553
0.4
0.4
617
0.3
0.4
200
2.5
410
0.7
0.3
757
1.3
0.1
728
0.8
0.1
439
2.3
0.1
366
3.3
0.5
783
1.3
0.2
517
5.4
2.2
448
2.7
0.1
597
2.2
0.6
2095
0.4
0.3
1222
0.7
0.5
1644
0.5
0.3
1064
1.0
0.5
592
1.4
0.2
546
1.1
0.4
857
1.0
0.4
1412
0.4
0.3
1574
0.3
0.2
510
2.0
68
0.0
0.0
125
0.0
0.0
120
0.0
0.0
72
5.5
0.0
60
5.0
0.0
129
0.0
0.0
85
0.0
0.0
74
2.7
0.0
98
1.0
0.0
346
0.3
0.0
202
0.5
0.0
271
0.0
0.0
176
1.1
0.0
98
1.0
0.0
90
2.2
0.0
141
0.0
0.0
233
0.0
0.0
260
0.0
0.0
84
3.6
127
0.8
0.7
234
1.7
0.0
225
0.9
0.0
136
2.2
0.0
113
3.5
0.2
242
1.7
0.0
160
2.5
0.5
139
2.9
0.0
185
0.5
0.1
648
0.5
0.3
378
0.8
0.6
509
0.0
0.0
329
0.3
0.2
183
1.1
0.1
169
2.4
0.0
265
1.1
0.6
437
0.2
0.3
487
0.2
0.1
158
2.5
Tailoredmodel
Density/km2
Total
Quota
Offtake
Block name
IH1
Quota
Offtake
K1
Quota
Offtake
K2
Quota
Offtake
K3
Quota
Offtake
K4
Quota
Offtake
K5
Quota
Offtake
KY1/Gonabisi
Quota
Offtake
L1
Quota
Offtake
LA1
Quota
Offtake
LL1
Quota
Offtake
LL2
Quota
Offtake
LL3
Quota
Offtake
LU2
Quota
Offtake
LU3
Quota
Offtake
LU5
Quota
Offtake
LU6
Quota
Offtake
LU7
Quota
Offtake
LU8
Quota
Offtake
M1
Quota
780
751
453
377
807
533
462
615
2160
1260
1695
1097
610
563
884
1456
1623
526
B I O L O G I C A L C O N S E RVAT I O N
925
1 4 2 ( 2 0 0 9 ) 9 0 9 –9 2 9
Table A1 – Continued
Area (km2)
Offtake
M2
Quota
Offtake
MA1
Quota
Offtake
MB1
Quota
Offtake
MB2
Quota
Offtake
MB3
Quota
Offtake
MH1
Quota
Offtake
MJ1
Quota
Offtake
MK1
Quota
Offtake
ML1
Quota
Offtake
MS1
Quota
Offtake
MT1
Quota
Offtake
MT2
Quota
Offtake
N1
Quota
Offtake
N2
Quota
Offtake
R1
Quota
Offtake
R2
Quota
Offtake
R3
Quota
Offtake
R4
Quota
Offtake
RU1
Quota
Offtake
U1
Quota
Offtake
U2
Quota
408
1677
2152
1044
1679
1361
2472
808
788
1336
845
1453
1912
1437
453
879
329
384
1691
368
519
Buff.
Bushb.
Bushp.
Duiker
Eland
Eleph.
Harbst.
Hippo
Impala
0.2
653
2.3
0.1
2683
0.5
0.1
3443
0.3
0.3
1670
0.7
0.5
2686
0.1
0.1
2178
0.2
0.1
3955
0.1
0.1
1293
2.2
0.8
1261
0.3
0.3
2138
0.5
0.2
1352
0.3
0.3
2325
0.4
0.3
3059
0.3
0.2
2299
0.2
0.1
725
2.1
0.1
1406
0.9
0.3
526
4.7
0.6
614
1.6
0.3
2706
0.4
0.1
589
3.1
0.1
830
2.2
0.0
163
2.5
0.0
671
0.6
0.0
861
0.1
0.0
418
0.2
0.0
672
0.1
0.0
544
0.0
0.0
989
0.1
0.1
323
0.9
0.1
315
0.3
0.2
534
0.6
0.1
338
0.3
0.1
581
0.2
0.1
765
0.1
0.0
575
0.2
0.2
181
1.7
0.0
352
0.9
0.1
132
2.3
0.2
154
1.3
0.0
676
0.4
0.1
147
2.7
0.0
208
1.9
0.0
237
1.7
0.0
973
0.4
0.0
1248
0.1
0.0
606
0.2
0.1
974
0.1
0.1
789
0.1
0.0
1434
0.1
0.0
469
0.6
0.1
457
0.2
0.0
775
0.4
0.1
490
0.2
0.1
843
0.1
0.1
1109
0.1
0.0
833
0.1
0.0
263
1.1
0.0
510
0.6
0.0
191
1.6
0.0
223
0.9
0.0
981
0.3
0.1
213
1.9
0.0
301
1.3
0.0
469
1.1
0.0
1929
0.2
0.0
2475
0.0
0.0
1201
0.1
0.0
1931
0.1
0.1
1565
0.0
0.0
2843
0.0
0.0
929
0.0
0.0
906
0.0
0.0
1536
0.4
0.1
972
0.2
0.1
1671
0.1
0.1
2199
0.0
0.0
1653
0.1
0.0
521
0.2
0.0
1011
0.2
0.0
378
0.5
0.0
442
0.2
0.0
1945
0.3
0.1
423
0.9
0.0
597
0.7
0.0
24
16.3
0.8
101
4.0
0.4
129
2.3
0.9
63
4.8
2.1
101
2.0
0.5
82
1.2
1.0
148
1.3
0.8
48
10.3
3.3
47
2.1
2.3
80
5.0
1.2
51
3.9
2.4
87
3.4
2.3
115
1.7
1.0
86
2.3
0.9
27
7.4
0.0
53
3.8
0.8
20
20.3
1.0
23
4.3
0.4
101
3.9
1.5
22
13.6
0.0
31
9.6
0.0
563
–
0.0
2314
–
0.0
2970
–
0.0
1441
–
0.0
2317
–
0.0
1878
–
0.1
3411
–
0.1
1115
–
0.0
1087
–
0.1
1844
–
0.1
1166
–
0.4
2005
–
0.1
2639
–
0.1
1983
–
0.1
625
–
0.0
1213
–
0.0
454
–
0.0
530
–
0.0
2334
–
0.0
508
–
0.0
716
–
0.3
90
11.1
0.7
369
1.6
0.4
473
1.9
1.4
230
3.5
2.4
369
1.1
0.9
299
1.3
1.1
544
0.7
0.8
178
4.5
1.9
173
2.9
2.1
294
2.7
1.0
186
2.2
2.5
320
2.5
2.0
421
1.9
1.1
316
1.3
0.9
100
6.0
0.4
193
3.1
1.2
72
19.3
2.2
84
5.9
1.2
372
2.2
1.0
81
18.5
0.2
114
13.1
0.1
155
3.2
0.1
637
0.8
0.1
818
0.5
0.3
397
1.0
0.5
638
0.3
0.2
517
0.4
0.3
939
0.2
0.1
307
0.0
0.0
299
0.7
0.4
508
0.8
0.2
321
0.6
0.8
552
0.7
0.5
727
0.4
0.3
546
0.4
0.2
172
1.2
0.0
334
0.9
0.1
125
1.6
0.1
146
2.1
0.2
643
0.6
0.1
140
3.6
0.0
197
2.5
0.0
396
2.5
0.2
1627
0.6
0.1
2087
0.4
0.2
1013
0.9
0.5
1629
0.2
0.2
1320
0.3
0.2
2398
0.2
0.1
784
2.3
0.8
764
0.5
0.5
1296
0.6
0.2
820
0.5
0.5
1409
0.6
0.4
1855
0.4
0.2
1394
0.3
0.2
439
1.4
0.0
853
1.2
0.2
319
4.1
0.6
372
3.2
0.4
1640
0.5
0.2
357
3.6
0.0
503
2.6
Klipspr.
G. Kudu
0.0
0.0
65
122
0.0
1.6
0.0
0.0
268
503
1.1
0.6
0.0
0.1
344
646
0.3
0.5
0.0
0.1
167
313
0.6
1.0
0.0
0.4
269
504
0.0
0.4
0.0
0.2
218
408
0.5
0.5
0.0
0.2
396
742
0.0
0.3
0.0
0.2
129
242
0.0
2.1
0.0
0.4
126
236
0.0
0.8
0.0
0.5
214
401
0.0
1.0
0.0
0.3
135
254
0.7
0.8
0.0
0.5
232
436
0.4
0.7
0.0
0.4
306
574
0.0
0.5
0.0
0.2
230
431
0.0
0.5
0.0
0.2
72
136
0.0
0.7
0.0
0.0
141
264
0.7
0.8
0.0
0.0
53
99
0.0
0.0
0.0
0.0
61
115
1.6
2.6
0.0
0.0
271
507
0.0
0.8
0.0
0.2
59
110
5.1
2.7
0.0
0.0
83
156
3.6
1.9
(continued on next page)
926
B I O L O G I C A L C O N S E RVAT I O N
1 4 2 ( 2 0 0 9 ) 9 0 9 –9 2 9
Table A1 – Continued
Area (km2)
Offtake
U3
Quota
Offtake
U4
Quota
Offtake
Y1
Quota
Offtake
Buff.
Bushb.
Bushp.
Duiker
Eland
Eleph.
Harbst.
Hippo
Impala
Klipspr.
G. Kudu
0.1
1237
1.1
0.1
1248
0.8
0.3
1381
1.3
0.4
0.0
309
1.3
0.0
312
1.0
0.1
345
1.7
0.1
0.0
448
0.9
0.1
452
0.7
0.2
501
1.0
0.0
0.0
889
0.4
0.1
897
0.7
0.1
992
0.4
0.0
1.0
46
8.6
0.4
47
8.5
2.1
52
11.6
1.9
0.0
1067
–
0.0
1076
–
0.0
1191
–
0.1
0.5
170
3.5
0.8
172
4.7
1.9
190
5.3
1.1
0.1
294
1.7
0.2
296
1.3
0.5
328
3.0
0.5
0.1
750
1.3
0.1
757
1.1
0.5
837
1.4
0.5
0.0
124
2.4
0.0
125
0.0
0.0
138
0.0
0.0
0.0
232
1.3
0.0
234
1.7
0.1
259
1.5
0.1
Leop.
Lion
Oribi
Reedb.
Sable
Steinb.
Suni
Warth.
Waterb.
Wilbst.
Zebra
3.8
0.08
5.1
0.11
5.1
0.16
6.0
0.11
6.8
0.07
1.0
0.16
5.1
0.16
2.1
0.51
6.0
0.08
5.0
0.76
5.0
0.35
43,486
3479
4.5
1.3
4783
3.4
0.9
6958
0.3
0.0
4783
3.1
0.8
3044
4.1
1.0
6958
0.5
0.0
6958
0.6
0.0
22,178
1.2
0.0
3479
5.4
2.8
33,049
1.1
0.2
15,220
1.8
0.7
423
34
3.0
1.5
62
6.4
0.2
60
6.7
0.0
36
11.0
0.2
30
16.6
0.4
65
9.3
0.9
43
28.1
5.9
37
13.5
0.5
49
6.1
0.8
173
2.3
1.3
101
3.0
1.8
136
2.9
0.9
88
2.3
1.1
49
6.1
1.5
45
8.9
1.8
47
2.1
1.1
86
4.7
0.0
83
4.8
0.0
50
10.0
0.0
41
9.6
1.2
89
6.8
0.9
59
20.5
6.3
51
9.8
0.4
68
5.9
1.0
238
1.7
0.7
139
2.9
1.4
186
2.7
0.8
121
1.7
1.1
67
3.0
0.1
62
6.5
0.5
68
1.5
0.0
125
0.0
0.0
120
0.0
0.0
72
2.8
0.0
60
0.0
0.0
129
0.0
0.0
85
0.0
0.0
74
0.0
0.0
98
0.0
0.0
346
0.3
0.0
202
0.5
0.0
271
1.5
0.0
176
0.0
0.0
98
0.0
0.0
90
0.0
0.0
47
4.3
1.9
86
4.7
0.3
83
6.1
0.0
50
16.1
0.0
41
7.2
1.2
89
3.4
0.0
59
15.4
6.3
51
5.9
0.2
68
4.4
0.4
238
1.3
1.1
139
2.2
1.2
186
2.1
0.5
121
2.5
0.3
67
0.0
0.0
62
6.5
0.2
30
3.4
5.1
55
5.5
0.7
53
7.6
0.2
32
12.6
0.0
26
11.4
0.8
56
5.3
0.7
37
10.7
1.1
32
12.4
0.3
43
2.3
1.2
151
3.3
1.2
88
4.5
2.3
119
3.4
1.0
77
2.6
1.4
43
4.7
0.7
39
10.1
0.3
68
0.0
0.0
125
3.2
0.0
120
0.0
0.0
72
4.1
0.0
60
0.0
0.0
129
3.1
0.0
85
0.0
0.0
74
0.0
0.0
98
0.0
0.0
346
0.0
0.0
202
0.0
0.0
271
0.0
0.0
176
0.0
0.0
98
0.0
0.0
90
0.0
0.0
68
0.0
0.0
125
0.0
0.0
120
0.0
0.0
72
4.1
0.0
60
5.0
0.0
129
3.1
0.0
85
0.0
0.0
74
0.0
0.0
98
0.0
0.0
346
0.0
0.0
202
0.0
0.0
271
0.7
0.0
176
0.0
0.0
98
0.0
0.0
90
0.0
0.0
216
1.9
0.0
398
2.0
0.0
383
1.0
0.0
231
3.5
0.0
192
4.2
0.0
412
1.5
0.0
272
7.4
0.0
236
2.1
0.0
314
3.2
0.0
1102
0.7
0.0
643
1.6
0.0
864
0.9
0.0
559
1.1
0.0
311
1.6
0.0
287
2.8
0.0
34
3.0
5.3
62
11.2
1.1
60
10.0
0.5
36
22.1
0.6
30
13.3
2.7
65
10.8
1.7
43
18.8
29.3
37
13.5
0.8
49
6.1
4.7
173
1.7
3.4
101
3.0
5.9
136
2.9
2.3
88
6.8
4.3
49
8.2
0.2
45
8.9
2.4
321
0.6
0.4
593
1.7
0.1
571
1.2
0.0
344
1.7
0.0
287
5.2
0.3
613
1.6
0.1
405
6.9
1.3
351
2.8
0.0
467
2.6
0.1
1642
0.4
0.2
958
0.7
0.1
1288
0.6
0.2
834
0.8
0.4
464
1.7
0.2
428
2.3
0.3
148
2.0
1.0
273
3.7
0.3
263
2.7
0.2
159
2.5
0.4
132
4.5
0.8
282
2.5
0.6
187
8.6
6.6
162
4.3
0.4
215
4.6
1.8
756
0.7
0.8
441
1.1
1.2
593
1.7
0.7
384
0.8
1.1
214
2.3
0.4
197
5.1
0.8
773
780
863
Area (km2)
Tailored model (%)
Density/km2
Total
Quota
Offtake
Block name
IH1
Quota
Offtake
K1
Quota
Offtake
K2
Quota
Offtake
K3
Quota
Offtake
K4
Quota
Offtake
K5
Quota
Offtake
KY1/Gonabisi
Quota
Offtake
L1
Quota
Offtake
LA1
Quota
Offtake
LL1
Quota
Offtake
LL2
Quota
Offtake
LL3
Quota
Offtake
LU2
Quota
Offtake
LU3
Quota
Offtake
LU5
Quota
Offtake
780
751
453
377
807
533
462
615
2160
1260
1695
1097
610
563
B I O L O G I C A L C O N S E RVAT I O N
927
1 4 2 ( 2 0 0 9 ) 9 0 9 –9 2 9
Table A1 – Continued
LU6
Quota
Offtake
LU7
Quota
Offtake
LU8
Quota
Offtake
M1
Quota
Offtake
M2
Quota
Offtake
MA1
Quota
Offtake
MB1
Quota
Offtake
MB2
Quota
Offtake
MB3
Quota
Offtake
MH1
Quota
Offtake
MJ1
Quota
Offtake
MK1
Quota
Offtake
ML1
Quota
Offtake
MS1
Quota
Offtake
MT1
Quota
Offtake
MT2
Quota
Offtake
N1
Quota
Offtake
N2
Quota
Offtake
R1
Quota
Offtake
R2
Quota
Offtake
R3
Quota
Area (km2)
Leop.
Lion
Oribi
Reedb.
Sable
Steinb.
Suni
Warth.
Waterb.
Wilbst.
884
71
2.8
1.6
116
1.7
1.5
130
1.5
1.2
42
9.5
0.2
33
12.3
0.6
134
3.0
0.7
172
1.7
1.1
84
3.6
3.1
134
1.5
1.0
109
0.9
0.6
198
1.0
1.1
65
9.3
1.7
63
3.2
3.2
107
4.7
1.4
68
3.0
3.1
116
2.6
1.4
153
2.0
1.1
115
1.7
1.4
36
11.0
0.8
70
5.7
1.0
26
11.4
97
3.1
2.6
160
1.2
1.2
179
1.1
0.6
58
6.9
0.3
45
8.9
0.2
184
2.2
0.3
237
1.3
1.0
115
2.6
1.7
185
1.1
0.8
150
1.3
0.7
272
0.7
0.4
89
6.8
1.6
87
2.3
1.2
147
3.4
1.1
93
2.2
1.1
160
2.5
1.3
210
1.4
0.8
158
1.3
0.8
50
8.0
0.8
97
4.1
0.3
36
8.3
141
0.0
0.0
233
0.0
0.0
260
0.0
0.0
84
0.0
0.0
65
0.0
0.0
268
0.0
0.0
344
0.3
0.0
167
0.6
0.0
269
0.0
0.0
218
0.0
0.0
396
0.0
0.0
129
0.0
0.0
126
0.0
0.0
214
1.9
0.0
135
0.0
0.0
232
0.0
0.0
306
0.0
0.0
230
0.0
0.0
72
0.0
0.0
141
0.0
0.0
53
0.0
97
2.1
1.6
160
0.6
0.9
179
0.6
1.0
58
6.9
0.3
45
22.3
0.2
184
2.2
0.4
237
1.3
0.7
115
2.6
1.7
185
0.5
0.3
150
1.3
0.6
272
0.7
0.3
89
4.5
0.6
87
2.3
1.2
147
2.7
0.8
93
1.1
1.7
160
1.9
0.9
210
1.0
0.8
158
0.6
0.9
50
8.0
0.6
97
5.2
0.3
36
11.1
62
1.6
1.9
102
2.0
1.5
114
1.8
1.0
37
10.9
0.3
29
14.0
0.4
117
3.4
0.5
151
2.0
0.6
73
4.1
0.7
118
1.7
0.9
95
2.1
0.9
173
1.2
0.7
57
3.5
0.2
55
3.6
2.7
94
4.3
1.4
59
3.4
2.5
102
3.9
1.9
134
2.2
0.8
101
2.0
1.5
32
6.3
0.0
62
4.9
0.2
23
8.7
141
0.0
0.0
233
0.0
0.0
260
0.0
0.0
84
4.8
0.0
65
6.1
0.0
268
1.5
0.0
344
0.0
0.0
167
0.0
0.0
269
0.0
0.0
218
0.0
0.0
396
0.0
0.0
129
0.0
0.0
126
0.0
0.0
214
0.0
0.0
135
0.0
0.0
232
0.0
0.0
306
0.0
0.0
230
0.0
0.0
72
0.0
0.0
141
0.0
0.0
53
0.0
141
0.0
0.0
233
0.0
0.0
260
0.0
0.0
84
4.8
0.0
65
0.0
0.0
268
1.5
0.0
344
0.0
0.0
167
0.0
0.0
269
0.4
0.0
218
0.5
0.0
396
0.0
0.0
129
0.0
0.0
126
0.8
0.0
214
0.9
0.0
135
0.7
0.0
232
0.0
0.0
306
0.0
0.0
230
0.0
0.0
72
0.0
0.0
141
0.0
0.0
53
1.9
451
1.1
0.0
743
0.4
0.0
828
0.2
0.3
268
3.0
0.0
208
3.8
0.0
855
0.7
0.0
1098
0.4
0.3
532
0.8
0.0
856
0.2
0.0
694
0.4
0.0
1261
0.2
0.0
412
3.2
0.0
402
0.5
0.0
681
1.2
0.0
431
0.5
0.0
741
1.1
0.0
975
0.4
0.0
733
0.3
0.0
231
2.6
0.0
448
1.1
0.0
168
7.7
71
4.2
3.3
116
2.6
2.7
130
1.5
1.6
42
16.6
1.2
33
21.4
0.9
134
6.0
0.9
172
2.9
1.9
84
6.0
2.3
134
1.5
1.6
109
1.8
1.6
198
0.5
1.1
65
6.2
7.4
63
3.2
3.5
107
3.7
2.4
68
3.0
4.7
116
2.6
4.3
153
2.0
1.7
115
1.7
2.4
36
5.5
1.1
70
4.3
2.0
26
15.2
672
1.2
0.4
1107
0.4
0.3
1233
0.3
0.4
400
2.5
0.1
310
2.9
0.0
1275
0.8
0.1
1636
0.4
0.3
793
1.0
0.5
1276
0.2
0.1
1034
0.4
0.1
1879
0.2
0.1
614
2.8
0.1
599
0.7
0.2
1015
0.8
0.1
642
0.6
0.2
1104
0.6
0.1
1453
0.5
0.2
1092
0.3
0.1
344
1.7
0.0
668
0.9
0.0
250
5.2
(continued on next
1456
1623
526
408
1677
2152
1044
1679
1361
2472
808
788
1336
845
1453
1912
1437
453
879
329
Zebra
309
1.3
1.6
510
0.6
0.8
568
0.4
0.5
184
5.4
0.2
143
7.0
0.1
587
1.7
0.1
753
0.7
0.6
365
1.4
1.5
588
0.5
0.4
476
0.8
0.4
865
0.3
0.3
283
2.8
1.3
276
1.1
0.8
468
2.1
0.5
296
1.0
0.6
509
0.8
0.8
669
0.6
0.7
503
0.6
0.3
159
3.8
0.1
308
2.0
0.5
115
8.7
page)
928
B I O L O G I C A L C O N S E RVAT I O N
1 4 2 ( 2 0 0 9 ) 9 0 9 –9 2 9
Table A1 – Continued
Area (km2)
Offtake
R4
Quota
Offtake
RU1
Quota
Offtake
U1
Quota
Offtake
U2
Quota
Offtake
U3
Quota
Offtake
U4
Quota
Offtake
Y1
Quota
Offtake
384
1691
368
519
773
780
863
Leop.
Lion
Oribi
Reedb.
Sable
Steinb.
Suni
Warth.
Waterb.
Wilbst.
Zebra
0.4
31
9.8
0.0
135
3.7
1.3
29
17.0
0.0
42
9.6
0.0
62
6.5
1.0
62
6.4
1.7
69
7.2
2.3
0.3
42
9.5
1.6
186
2.7
0.8
40
9.9
0.2
57
7.0
0.5
85
4.7
0.2
86
5.8
2.0
95
5.3
0.7
0.0
61
0.0
0.0
271
0.0
0.0
59
0.0
0.0
83
0.0
0.0
124
0.0
0.0
125
3.2
0.0
138
0.0
0.0
0.3
42
4.7
0.5
186
2.2
0.7
40
9.9
0.2
57
7.0
0.7
85
4.7
0.6
86
4.7
1.5
95
6.3
0.5
0.4
27
7.4
0.0
118
3.4
0.9
26
7.8
0.8
36
5.5
0.3
54
7.4
0.6
55
7.3
0.4
60
5.0
1.2
0.0
61
0.0
0.0
271
0.0
0.0
59
6.8
0.0
83
4.8
0.0
124
3.2
0.0
125
0.0
0.0
138
0.0
0.0
0.0
61
0.0
0.0
271
0.7
0.0
59
6.8
0.0
83
4.8
0.0
124
3.2
0.0
125
1.6
0.0
138
0.0
0.0
0.0
196
2.6
0.0
862
0.9
0.0
188
4.3
0.0
265
3.0
0.0
394
1.5
0.0
398
2.0
0.0
440
0.9
0.0
5.7
31
6.5
1.6
135
3.0
2.4
29
23.8
0.0
42
16.9
1.0
62
11.3
1.6
62
8.0
4.0
69
11.6
5.5
0.0
292
2.1
0.1
1285
0.6
0.0
280
5.4
0.0
394
3.8
0.1
587
1.7
0.1
593
1.3
0.3
656
1.8
0.2
1.6
134
4.5
0.5
592
1.7
0.5
129
4.7
0.2
182
3.3
0.1
271
3.7
0.4
273
3.7
1.2
302
2.6
1.4
a Top row shows percentage of species’ populations that could be removed while maintaining positive growth rates based on the tailored
models; second row gives estimated densities of each species in the whole Selous GR. Third row gives estimated total numbers of each species
in the Selous GR; fourth row, percentage of estimated population allowed by hunting quotas averaged between 1988 and 1997; fifth row, actual
percentage of estimated population killed averaged over those years. Below, these same 3 variables are shown for 43 of the 47 Selous hunting
blocks leased to hunting safari companies during the period 1988–1997 listed down the left hand side (excluding blocks B1, LU1, LU4, and Z1;
note, KY1/Gonabis were combined for purposes of analyses). Block areas (from Baldus and Cauldwell, 2004) are listed in km2 in the second
column. There were no data on elephant quotas; instead kill data come from Tanzania Wildlife Authority Budget reports years 1988–1992 (E.
Severre, pers comm.). Quotas or kills were divided by block population and multiplied by 100 to obtain population percentages. Those that
exceed calculated sustainable offtake are shown in bold.
R E F E R E N C E S
Adams, W., 2004. Good hunting. In: Adams, M. (Ed.), Against
Extinction. Earthscan, London, pp. 19–23.
Allee, W.C., 1931. Animal Aggregations. University of Chicago
Press, Chicago.
Arcese, P., Hando, J., Campbell, K., 1995. Historical and presentday anti-poaching efforts in Serengeti. In: Sinclair, A.R.E.,
Arcese, P. (Eds.), Serengeti II: Dynamics, Management and
Conservation of an Ecosystem. University of Chicago Press,
Chicago, pp. 506–533.
Baldus, R.D., 2006. The crucial role of governance in ecosystem
management – results and conclusions of the Selous
Conservation Programme/Tanzania 1987–2003. In: Managing
Africa’s Natural Ecosystems, Serengeti Conference
Proceedings, May 2006.
Baldus, R.D., Cauldwell, A.E., 2004. Tourist hunting and it’s role in
development of wildlife management areas in Tanzania.
Unpublished Report, Dar es Salaam.
Bertram, B.C.R., 1975. Social factors influencing reproduction in
wild lions. Journal of Zoology 177, 463–482.
Bond, I., 2001. CAMPFIRE and the incentives for institutional
change. In: Hulme, D., Murphee, M. (Eds.), African Wildlife and
Livelihoods: The Promise and Performance of Community
Conservation. James Currey, Oxford, pp. 227–243.
Borgerhoff Mulder, M., Coppolilllo, P., 2005. Conservation: Linking
Ecology. Economics and Culture. Princeton University Press,
Princeton.
Breden, F., Hausfater, G., 1990. Selection within and between
social groups for infanticide. American Naturalist 136,
673–688.
Caro, T., 2005. The status of wildlife in Tanzania. Report to the
Ministry of Tourism and Natural Resources, COSTECH,
Wildlife Division, TANAPA and TAWIRI. Unpublished Report.
Caro, T., 2008. Decline of large mammals in the Katavi-Rukwa
ecosystem of western Tanzania. African Zoology 43, 99–116.
Caro, T., Baldus, R.D., 2006. The effects of hunting on wildlife
management. Miombo 28, 4–6.
Caro, T.M., Pelkey, N., Borner, M., Campbell, K.L.I., Woodworth,
B.L., Farm, B.P., ole Kuwai, J., Huish, S.A., Severre, E.L.M., 1998a.
Consequences of different forms of conservation for large
mammals in Tanzania: preliminary analyses. African Journal
of Ecology 36, 303–320.
Caro, T.M., Pelkey, N., Borner, M., Severre, E.L.M., Campbell, K.L.I.,
Huish, S.A., ole Kuwai, J., Farm, B.P., Woodworth, B.L., 1998b.
The impact of tourist hunting on large mammals in
Tanzania: an initial assessment. African Journal of Ecology 36,
321–346.
Caro, T.M., Rejmanek, M., Pelkey, N., 2000. Which mammals
benefit from protection in East Africa? In: Entwistle, A.,
Dunstone, N. (Eds.), Priorities for the Conservation of
Mammalian Diversity: Has the Panda had its Day? Cambridge
University Press, Cambridge, pp. 221–228.
Cauldwell, A.E. 2004. Analysis of hunting data of the Selous game
reserve. Unpublished Report.
Clutton-Brock, T.H., 1991. Parental Care. Princeton University
Press, Princeton, NJ.
B I O L O G I C A L C O N S E RVAT I O N
Creel, S., Creel, N.M., 1996. Limitation of African wild dogs by
competition with larger carnivores. Conservation Biology 10,
526–538.
Creel, S., Creel, N.M., 1997. Lion density and population structure
in the Selous Game Reserve: evaluation of hunting quotas and
offtake. African Journal of Ecology 35, 83–93.
Creel, S., Creel, N.M., 2002. The African Wild Dog. Princeton
University Press, Princeton.
Deines, A., Peterson, E., Boeckner, D., Boyle, J., Keighley, A., Kogut,
J., Lubben, J., Rebarber, R., Ryan, R., Tenhumberg, B., Townley,
S., Tyre, A.J., 2007. Robust population management under
uncertainty for structured population models. Ecological
Applications 17, 2175–2183.
Eltringham, S.K., 1984. Wildlife Resources and
Economic Development. John Wiley & Sons, Chicester,
UK.
Estes, R.D., 1991. The Behavior Guide to African mammals.
University of California Press, Berkeley, CA.
Festa-Bianchet, M., 2003. Exploitative wildlife management as a
selective pressure for life-history evolution of large mammals.
In: Festa-Bianchet, M., Apollonio, M. (Eds.), Animal Behavior
and Wildlife Conservation. Island Press, Washington, DC, pp.
191–210.
Gillingham, S., Lee, P.C., 1999. The impact of wildlife-related
benefits on the conservation attitudes of local people around
the Selous Game Reserve, Tanzania. Environmental
Conservation 26, 218–228.
Grange, S., Duncan, P., Gaillard, J.-M., Sinclair, A.R.E., Gogan, P.J.P.,
Packer, C., Hofer, H., East, M., 2004. What limits the Serengeti
zebra population? Oecologia 140, 523–532.
Greene, C., Umbanhowar, J., Mangel, M., Caro, T., 1998. Animal
breeding systems, hunter selectivity, and consumptive use in
wildlife conservation. In: Caro, T. (Ed.), Behavioral Ecology and
Conservation Biology. Oxford University Press, New York, pp.
271–305.
Holmern, T., Muya, J., Roskaft, E., 2007. Local law enforcement and
illegal bushmeat hunting outside the Serengeti National Park,
Tanzania. Oryx 36, 364–372.
Hurt, R., Ravn, P., 2000. Hunting and its benefits: an overview of
hunting in Africa with special reference to Tanzania. In: Prins,
H.H.T., Grootenhuis, J.G., Dolan, T.T. (Eds.), Wildlife
Conservation by Sustainable Use. Kluwer, London, pp. 295–
314.
Kibonde, B., 2006. Selous Game Reserve turns 110 years. Tanzania
Wildlife, Kakakuona Magazine July–September 42, 35–43.
Kingdon, J., 1997. The Kingdon Guide to African mammals.
Academic Press, San Diego, CA.
Leader-Williams, N., Kayera, J.A., Overton, G.L. (Eds.). 1996. Tourist
Hunting in Tanzania. IUCN Species Survival Commission.
Occasional Paper No. 14.
Lewis, D.M., Alpert, P., 1997. Trophy hunting and wildlife
conservation in Zambia. African Journal of Ecology 35, 83–
93.
Lewis, D., Jackson, J., 2005. Safari hunting and conservation on
communal land in southern Africa. In: Woodroffe, R.,
Thirgood, S.J., Rabinowitz, A. (Eds.), People and Wildlife:
Conflict or Coexistence? Cambridge University Press,
Cambridge, pp. 239–252.
Lindsey, P.A., Alexander, R., Frank, L.G., Mathieson, A., Romanach,
S.S., 2006. Potential of trophy hunting to create incentives for
wildlife conservation in Africa where alternative wildlifebased land uses may not be viable. Animal Conservation 9,
283–291.
Lindsey, P.A., Roulet, P.A., Romanach, S.S., 2007. Economic and
conservation significance of the trophy hunting industry
in sub-Saharan Africa. Biological Conservation 34,
455–469.
1 4 2 ( 2 0 0 9 ) 9 0 9 –9 2 9
929
Milner, J.M., Nilsen, E.B., Andreassen, H.P., 2007. Demographic
side effects of selective hunting in ungulates and carnivores.
Conservation Biology 21, 36–47.
Milner-Gulland, E.J., 1994. A population model for the
management of the Saiga antelope. Journal of Applied Ecology
31, 25–39.
Nowak, R.M. (Ed.), 1999. Walker’s Mammals of the World, sixth ed.
Johns Hopkins University Press, Baltimore, Maryland.
Nshala, R., 1999. Granting hunting blocks in Tanzania: the need
for reform. Policy Brief No. 5. Lawyers’ Environmental Action
Team, Dar es Salaam, Tanzania.
Packer, C., Herbst, L., Pusey, A.E., Bygott, J.D., Hanby, J.P., Cairns,
S.C., Borgerhoff Mulder, M., 1988. Reproductive success of
lions. In: Clutton-Brock, T.H. (Ed.), Reproductive Success.
University of Chicago Press, Chicago, pp. 363–383.
Pelkey, N., Stoner, C.J., Caro, T.M., 2000. Vegetation in Tanzania:
assessing long term trends and effects of protection using
satellite imagery. Biological Conservation 94, 297–309.
Price, S.A., Gittleman, J.L. 2007. Hunting to extinction: biology and
regional economy influence extinction risk and the impact of
hunting in artiodactyls. Proceedings of the Royal Society of
London 274, 1845–1851.
Regan, H.M., Ben-Haim, Y., Langford, B., Wilson, W.G., Lundberg,
P., Andelman, S.J., Burgman, M.A., 2005. Robust decisionmaking under severe uncertainty for conservation
management. Ecological Applications 15, 1471–1477.
Reynolds, J.D., Mace, G.M., Redford, K.H., Robinson, J.G. (Eds.), 2001.
Conservation of Exploited Species. Cambridge University
Press, Cambridge.
Rowe, S.R., Hutchings, J.A., 2003. Mating systems and the
conservation of commercially exploited marine fish. Trends in
Ecology and Evolution 18, 567–572.
Spong, G., Hellborg, L., Creel, S., 2000. Sex ratio of leopards taken
in trophy hunting: genetic data from Tanzania. Conservation
Genetics 1, 169–171.
Stephenson, J. 1990. A Conservation Policy and Management Plan
for the Selous National Game Reserve. For the Selous
Conservation Programme and the Wildlife Division, Ministry
of Natural Resources and Tourism. 110pp.
Stoner, C.J., Caro, T., Mduma, S., Mlingwa, C., Sabuni, G., Borner,
M., 2007. Assessment of effectiveness of protection strategies
in Tanzania based on a decade of survey data for large
herbivores. Conservation Biology 21, 635–646.
Stuart, C., Stuart, T., 2001. Field Guide to Mammals of Southern
Africa. Struik Publishers, Cape, Town South Africa.
Tanzania Wildlife Conservation Act 1974, 2002. Regulations.
Government Notice No. 543.
Taylor, V.J., Dunstone, N. (Eds.), 1996. The Exploitation of Animal
Populations. Chapman and Hall, London.
UNEP-WCMC Protected Areas Programme – Selous Game Reserve,
<http://www.unep-wcmc.org/sites/wh/selous.html> (accessed
12.10.2008).
Waltert, M., Meyer, B., Shanyangi, M.W., Balozi, J.J., Kitwara, O.,
Qolli, S., Krischke, H., Muhlenberg, M., 2008. Foot surveys of
large mammals in woodlands of western Tanzania. Journal of
Wildlife Management 72, 603–610.
Whitman, K., Starfield, A.M., Quadling, Q.S., Packer, C., 2004.
Sustainable trophy hunting on African lions. Nature 428, 175–
178.
Whitman, K., Starfield, A.M., Quadling, Q.S., Packer, C., 2007.
Modeling the effects of trophy selection and environmental
disturbance on a simulated population of African lions.
Conservation Biology 21, 591–601.
Young, C.R., Towbin, P., submitted for publication. Behavioral
ecology meets management: effects of infanticide, parental
care and incidental take on sustainability of hunted
populations. Theoretical Population Biology.