LIMPOPO LEOPARD PROJECT

ESTABLISHING A PROVINCIAL FRAMEWORK TO ENABLE ADAPTIVE MANAGEMENT OF LEOPARDS IN

LIMPOPO SOUTH AFRICA

PROGRESS REPORT YEAR 2014

2 LIMPOPO LEOPARD PROJECT YEAR 2014

PROJECT BACKGROUD

Global biodiversity is under increasing threat (Brooks et al. 2006), with many species facing extensive range

contractions and extinctions (Laliberte and Ripple 2004, Cardillo et al. 2005, Bates et al. 2014). Conservation success

depends on understanding the environmental factors that support species persistence (Karanth et al. 2010),

particularly in human-dominated landscapes where widespread habitat fragmentation has impacted species

distribution patterns (Sanderson et al. 2002a, Karanth et al. 2010). Large, terrestrial mammals play a fundamental

role as ecosystem engineers either through their effect on prey populations or by altering vegetation structure and

species composition (Morrison et al. 2007). Life-history traits (Brashares 2003), large body size (Cardillo and

Bromham 2001), and specialized habitat requirements (Fischer and Lindenmayer 2007) increase the susceptibility of

terrestrial mammal species to local extirpation and extinction as a result of anthropogenic impact (Karanth et al.

2009), which has forced 25 % of global terrestrial mammal species to near extinction (Ceballos et al. 2005). Large,

terrestrial mammals are now among the world’s most threatened taxa (Channell and Lomolino 2000) – with over 79

% of the world’s land surface having lost its full complement of large mammalian assemblages (Morrison et al.

2007).

Mammalian carnivores are one of the most vulnerable guilds (Schipper et al. 2008, Estes et al. 2011), primarily due

to their volatile relationship with people and their perceptions of predators (Woodroffe et al. 2005). Mammalian

carnivores are particularly sensitive to the expansion of human populations into wild habitats (Woodroffe 2000), and

as a result, conflict between people and predators remains the greatest threat to large carnivores globally

(Woodroffe and Ginsberg 1998). Accurately documenting the change in carnivore distribution has become a priority

for conservation authorities (Ray et al. 2005). However, there is a lack of basic information on carnivore abundance

and distribution (Friedmann and Daly 2004, Long et al. 2008), particularly at regional and sub-continental scales

(Karanth et al. 2009). This deficit is primarily due to the difficulty in obtaining data on wide-ranging, and often

nocturnal and secretive species (Thorn et al. 2011b). As a consequence, large-scale carnivore management decisions

are seldom supported by science-based evidence (Sutherland et al. 2004). Given the rapid decline of global

biodiversity (Sala et al. 2000), conservation planning requires a systematic and adaptive approach (Margules and

Pressey 2000, Westgate et al. 2013) where current and future management decisions are furnished with evidence

gathered from previous management practices (Westgate et al. 2013). Such an approach aims to improve

management of critical habitats by learning from management outcomes (Williams et al. 2009, Biggs et al. 2011),

but can only be implemented where management actions are appropriately scaled to the ecological system of

interest (Delsink et al. 2013, Guerrero et al. 2013).

Detecting population change forms a central component of wildlife management (Caughley and Sinclair 1994).

However, conservation practitioners require reliable and efficient methods of monitoring population trends at large

spatial scales to ensure informed decision-making (Barea-Azcón et al. 2006). Numerous coarse- and fine-scale

population estimator methods exist, including aerial surveys (Kingsford and Porter 2009), live trapping (Flowerdew

et al. 2004), camera-trapping (Rich et al. 2014), sign surveys (Ausband et al. 2014), harvest effort (Gese 2001), trophy

quality (Croes et al. 2011), and occupancy (Karanth et al. 2009). Although population estimator methods are suitable

for the management and conservation of wildlife, little is known of how one relates to the other and how they can

be applied within a management framework (Choate et al. 2006). Large carnivores are vital to biodiversity at a global

scale through their role as keystone species (Miller et al. 2001, Estes et al. 2011), but also present great challenges

for conservation and management (Ray et al. 2005). Enumeration of large carnivores is a particularly difficult task

(Obbard et al. 2010) due to their low densities, wide-ranging distribution and elusive nature (Hunter and Barrett

2011). Yet large carnivore monitoring is essential, particularly due the widespread degradation of suitable habitat for

predators (Ray et al. 2005).

Landscape degradation, fragmentation and the loss of connectivity has led to the global population decline of

numerous mammalian species (Ceballos and Ehrlich 2002), of which large carnivores are the most severely impacted

(Crooks et al. 2011). The combination of large body size, large area requirements, low densities, slow population

growth rates, and anthropogenic threats have resulted in widespread extirpation or localized extinction of many

large carnivore species across their historic geographical range (Cardillo et al. 2004, Cardillo et al. 2005). Across

Africa, carnivores have experienced an average range loss of 35.8%, where only 14% of the total land area is

currently comprised of intact medium and large felid communities (Ray et al. 2005). The decline or disappearance of

large carnivores can generate negative, cascading effects with system-level impacts due to their essential role as

top-down regulators (Terborgh et al. 2001, Estes et al. 2011). Because large carnivores act as indicators of ecosystem

health (Dalerum et al. 2008), they can be effective focal species on which to evaluate fragmentation and

connectivity across large spatial scales (Crooks and Sanjayan 2006).

Land-use change is a significant form of global pressure affecting biodiversity (Sala et al. 2000, Zebisch et al. 2004).

Transformation of land and how land is managed are key drivers of biodiversity loss at global, national and local

scales (Haines-Young 2009), and forms a central component of global environmental and sustainability research

(Turner et al. 2007). Across southern African, legislative changes have triggered a rapid shift from livestock to game

ranching (Cloete et al. 2007, Lindsey et al. 2009b). Over the past three decades, South Africa’s game ranching

industry has grown to comprise over 9000 ranches (NAMC 2006) and encompasses approximately 16.8% of the

country’s land surface (FAOSTAT 2014). Game ranching is heralded as a conservation success across South Africa

(Lindsey et al. 2009a) due to the positive consequences resulting from well-managed properties, sustainable job

opportunities and training, economic development, maintenance of stable gene pools, wildlife reintroductions, and

the fostering of endangered species (Flack 2003). However, there is a general lack of information regarding the

ecological impact of game ranching across South Africa, particularly for large carnivores (Lindsey et al. 2009b).

Furthermore, habitat fragmentation, as a result of erecting perimeter game fencing, restricts movement of wildlife

populations (Woodroffe et al. 2014), which can lead to inbreeding and overstocking, and prevent immigration and

emigration (Bond et al. 2004, Lindsey et al. 2009b, Packer et al. 2013).

4 LIMPOPO LEOPARD PROJECT YEAR 2014

In this thesis, I use leopard Panthera pardus—as a model large carnivore—in Limpopo Province, South Africa, to

investigate and address some of the fundamental components that underpin wildlife management and conservation

in a landscape dominated by people. Leopard are the world’s most wide-ranging, and persecuted felid (Hunter et al.

2013). Twelve African countries are permitted to export a quota of leopard skins procured through trophy hunting

(Balme et al. 2010). While trophy hunting is regulated, there is little scientific input on the allocation of harvest

quotas or the implementation of hunting practices (Balme et al. 2010). Accordingly, the biological sustainability of

leopard hunting remains largely unknown (Packer et al. 2009). Leopards are also frequently killed—both legally and

illegally—for their role as predators of livestock, game species, and occasionally people (Hunter et al. 2013). Human-

wildlife conflict is a major concern for biodiversity conservation (Woodroffe et al. 2005) and large felids such as lion

Panthera leo (Ogada et al. 2003, Holmern et al. 2007), leopard (Ogada et al. 2003, Thorn et al. 2013), jaguar

Panthera onca (Zimmermann et al. 2005) and tiger Panthera tigris (Miquelle et al. 2005) are frequently implicated in

conflict events centered around livestock and game depredation (Sillero-Zubiri and Laurenson 2001). In addition,

illegal practices such as cage trapping, poisoning, shooting and snaring constitute a significant portion of leopard

mortality in Limpopo, and throughout South Africa (Ray et al. 2005, Swanepoel 2009, St John et al. 2012). Poaching

leopard and the illegal trafficking of their skins for cultural regalia represents another significant threat to the

species (Hunter et al. 2013). Even though a large proportion of Limpopo is considered suitable leopard habitat (63%;

which comprises 32% of suitable leopard habitat in South Africa), there are uncertainties regarding leopard

population viability (Daly et al. 2005, Swanepoel et al. 2013). Given the tenacious persistence of leopard in human-

dominated landscapes they present an ideal opportunity to assess the effects of human-mediated disturbance on

large carnivores.

REPORT SUMMARY FOR 2014

This has been an extremely successful year for the Limpopo Leopard Project. Aside from camera-trapping six study

sites across Limpopo, we included an additional study site (called Lajuma), which comprises privately owned game

farms nestled within the western Soutpansberg Mountains. All seven camera-trapping surveys are now finished, and

I am busy capturing the data and running analyses. The occupancy survey was conducted in November, with great

success—about 750 respondents took part this year. The Limpopo Department of Economic Development,

Environment and Tourism (LEDET; Limpopo’s conservation authority) have really worked hard this year to adopt our

new leopard trophy hunting regulations. Hunting outfitters have been somewhat disgruntled, but for the most part,

they have been very welcoming of the scientific approach to sustainable hunting we have put forward. LEDET have

now committed to implement our recommendations from 2015-onwards. Scientific data from trophy hunted

leopard, also known as hunt return forms, are finally being completed and submitted to a very high standard (all

forms now have to be completed online). The Limpopo Hunters Liaison Forum (the organization that represents all

of Limpopo’s leopard hunters) have been very supportive of this research. I currently have one paper (Chapter 1) in

review, and another paper (Chapter 2) is currently being written.

SUMMARY LINE

Limpopo Leopard Project – establishing a provincial framework to enable adaptive management of leopards across

Limpopo province, South Africa.

PROGRESS REPORT

CHAPTER 1 – THE IMPORTANCE OF REFUGIA, ECOLOGICAL TRAPS, AND SCALE FOR THE

MANAGEMENT OF A THREATENED LARGE CARNIVORE

Introduction – Large-scale management decisions are seldom supported by science-based evidence (Sutherland et

al. 2004). Given the rapid decline of global biodiversity (Sala et al. 2000), conservation planning requires a systematic

and adaptive approach where the implementation of scientifically justified management zones feature prominently

(Margules and Pressey 2000, Westgate et al. 2013). Understanding the spatio-temporal dynamics that underpin the

distribution of animal populations within and across management zones, and how these are influenced by ecological

and anthropogenic factors, is key to effective conservation planning (Hansen 2011, Delsink et al. 2013). Habitat

quality is one factor affecting how animals interact with their environment (Pearson et al. 2011), and is a commonly

explored theme in ecological studies (Turner et al. 2001, Battin 2004). High-quality habitats generally yield fitness

benefits through increased opportunities for survival and reproduction, whereas low-quality habitats carry fitness

costs due to increased mortality or reduced reproduction (Franklin et al. 2000, Delibes et al. 2001). This conceptual

framework forms the basis of source–sink theory (Pulliam 1988) and is considered a mechanistic foundation for

landscape ecology (Wiens et al. 1993). Subsequent refinement of the source–sink model has enabled the inclusion of

two essential concepts. First, habitats that exhibit relatively high survival due to the low risk of human-mediated

mortality (Naves et al. 2003) but low reproduction due to suboptimal habitat are considered ‘refugia’ (Stoner et al.

2013). In contrast, ‘ecological traps’ are characterized by high-quality habitat that exhibits reduced survival

(Schlaepfer et al. 2002, Sánchez-Mercado et al. 2014), often due to human activity such as over-hunting or

retaliatory killing (Delibes et al. 2001, Naves et al. 2003, Hansen 2011). These scenarios can lead to maladaptive

habitat selection by animals, which may threaten their long-term persistence (Schlaepfer et al. 2002, Battin 2004,

Gilroy and Sutherland 2007, Roever et al. 2013).

Identifying refugia and ecological traps is critical to enable conservation practitioners to focus resources in areas of

concern (Naves et al. 2003, Stoner et al. 2013). Although a number of empirical studies have demonstrated the

existence of such areas (e.g., Woodward et al. 2001, Weldon & Haddad 2005, van der Meer 2011), few have done so

at the spatial scales required to inform management (Robertson and Hutto 2006). Scale mismatching (i.e., where the

implementation of conservation research and actions do not reflect the scale of the conservation problem) occurs

frequently in natural resource management, resulting in inefficiencies, a loss of system components, and failure to

achieve management objectives (Cumming et al. 2006, Guerrero et al. 2013). Many of the problems arising in

6 LIMPOPO LEOPARD PROJECT YEAR 2014

conservation are a consequence of the mismatch between the scale of the management intervention and the scale

of the ecological processes being managed (Delsink et al. 2013).

The leopard (Panthera pardus) is the world’s most persecuted large felid (Hunter et al. 2013), and while the trophy

hunting of leopard is regulated, there is little scientific input on the allocation of harvest quotas or the

implementation of hunting practices (Balme et al. 2010). In addition, human-carnivore conflict is a major concern for

biodiversity conservation (Woodroffe et al. 2005), and like other large felids (Ogada et al. 2003, Miquelle et al. 2005,

Zimmermann et al. 2005, Holmern et al. 2007), leopards are frequently implicated in conflict centered around

livestock and game depredation (Hunter et al. 2013, Thorn et al. 2013)—often leading to legal retaliatory killing of

putative problem leopards. Most range states lack official guidelines on how to effectively manage problem leopards

(Friedmann and Traylor‐Holzer 2008, Balme et al. 2010), and as a result many leopards are killed based on little

evidence (Balme et al. 2009b).

Using trophy hunting and problem leopard permit records, we explored the distribution of refugia and ecological

traps at three geographical scales in Limpopo Province, South Africa (hereafter ‘Limpopo’). We investigated the

potential for maladaptive habitat selection and evaluated the sustainability of leopard trophy hunting by using

trophy hunting permits alone, and then in combination with problem leopard permits to assess the compounding

effect of legal retaliatory killing. Finally, we propose an adaptive, science-based regulatory framework aimed at

improving leopard management practices in Limpopo, but which has broader applicability for the management of

other large carnivores exposed to trophy hunting or population control.

Progress – This manuscript has been submitted to Biodiversity and Conservation (currently under review).

CHAPTER 2 – THE CONSERVATION COSTS OF GAME RANCHING

Introduction – Land-use change is a significant form of global pressure affecting biodiversity (Sala et al. 2000,

Zebisch et al. 2004). Transformation of land and how land is managed are key drivers of biodiversity loss at global,

national and local scales (Haines-Young 2009), and forms a central component of global environmental and

sustainability research (Turner et al. 2007). Across sub-Saharan Africa, legislative changes during the colonialist-

period established centralized control over wildlife populations to mitigate their decline caused by over-hunting and

disease outbreaks (Bond et al. 2004). This control limited commercial and subsistence use of wildlife, which

prevented landowners from deriving any wildlife-based income (Lindsey et al. 2009b)—effectively diminishing the

value of wildlife and making them a financial burden to landowners (Murombedzi 2003). As a result, wildlife

populations continued to decline due to persecution, competition with livestock, poaching and neglect (Lindsey et

al. 2009b). During the 1960s and 1970s, legislative policies were modified across several southern African countries

(e.g., Namibia, South Africa, Zimbabwe), which devolved user rights of wildlife to the landowner (Lindsey et al.

2009a). These changes allowed landowners to derive financial benefits from wildlife occurring on their properties

through live animal sales, hunting and ecotourism (Bond et al. 2004), which triggered a rapid shift from livestock to

game ranching across large areas of southern Africa (Cloete et al. 2007, Lindsey et al. 2009b).

Over the past three decades, South Africa’s game ranching industry has grown to comprise over 9000 ranches

(NAMC 2006) and encompasses approximately 16.8% of the country’s land surface (FAOSTAT 2014). Game ranching

is heralded as a conservation success across South Africa (Lindsey et al. 2009a) due to the positive consequences

resulting from well-managed properties, sustainable job opportunities and training, economic development,

maintenance of stable gene pools, wildlife reintroductions, and the fostering of endangered species (Flack 2003).

Restocking of game ranches resulted in extensive reintroductions of wildlife populations (Lindsey et al. 2009b),

which increased the abundance and distribution of wildlife on private land to levels far greater than that on state-

owned property (NAMC 2006). Wildlife reintroductions have facilitated the recovery of endangered species such as

African wild dog Lycaon pictus (Gusset et al. 2007b), bontebok Damaliscus pygargus dorcas, white rhinoceros

Ceratotherium simum, and black wildebeest Connochaetes gnu (Flack 2003, Lindsey et al. 2009b). Furthermore,

game ranching enables the conservation of watersheds and indigenous vegetation and facilitates the recovery of

degraded lands (Bond et al. 2004, Lindsey et al. 2009b). From an economic perspective, the land-use shift towards

game ranching has generated lucrative wildlife subsectors such as recreational hunting (ZAR 3 100 million per

annum), game capture activities (ZAR 750 million), trophy hunting (ZAR 510 million), taxidermy (ZAR 200 million),

live animal sales (ZAR 94 million), and meat production (ZAR 42 million) (NAMC 2006).

There is a general lack of information regarding the ecological impact of game ranching across South Africa (Lindsey

et al. 2009b). However, some negative consequences include: (1) the hybridization of subspecies (e.g., bontebok and

blesbok Damaliscus pygargus phillipsi) to create new varieties of hunting trophies that endanger the genetic purity

of natural game, (2) genetic manipulation of closely related species are employed to breed larger specimens and

‘freak’ animals (e.g., aberrant colour variants) to offer as trophy animals or tourist attractions, (3) inbreeding of rare

game varieties (e.g., roan and sable antelope) by breeders lacking the necessary expertise, (4) introduction of

extralimital (i.e., species that do not occur naturally within the given geographical area) species—such as springbok

Antidorcas marsupialis in South Africa’s West Coast and Cape Mountain zebra Equus zebra zebra in the Saldanha

dune fields—can lead to inbreeding, hybridization (e.g., waterbuck Kobus ellipsiprymnus

and lechwe Kobus leche), competition, physical abnormalities, and destruction of habitat, (5) introduction of alien

plant species, such as the conversion of natural fynbos in the Western Cape into grassland for grazing, and (6)

unregulated relocation of animals, which can lead to genetic contamination and the transmission of parasites and

diseases (Hamman et al. 2003). Furthermore, habitat fragmentation, as a result of erecting perimeter game fencing

(Packer et al. 2013), restricts movement of wildlife populations (Woodroffe et al. 2014), which can lead to

inbreeding and overstocking, and prevent immigration and emigration (Bond et al. 2004, Lindsey et al. 2009b).

The land-use shift towards game ranching has significantly increased the area of land used for wildlife production

(NAMC 2006), which increases interactions between financially valuable game species or infrastructure (e.g., electric

fencing, water pumps) and free-ranging, large mammals (Osborn and Parker 2003, Osborn and Hill 2005). These

8 LIMPOPO LEOPARD PROJECT YEAR 2014

interactions can ultimately lead to human-wildlife conflict, which often undermines the objectives of sustainable use

and wildlife conservation initiatives (Gusset et al. 2009), and is regarded a major concern for conservation globally

(Woodroffe et al. 2005). Human-wildlife conflict is closely linked to the perceived financial loss of revenue through

property damage and stock depredation (Woodroffe et al. 2005, Thorn et al. 2013). In South Africa, the trend

towards higher value and artificially rare game species—though appearing important for short-term economic

development (NAMC 2006)—may increase conflict between large carnivores and ranchers (Lindsey et al. 2005,

Lindsey et al. 2009b). Large carnivores such as leopard Panthera pardus, cheetah Acinonyx jubatus, African wild dog

and brown hyaena Hyaena hyaena are ecologically vital—though not financially valuable—to their ecosystems as

keystone species and act as biodiversity indicators (Dalerum et al. 2008), but are frequently implicated in human-

carnivore conflict across South Africa (Gusset et al. 2007a, Lagendijk and Gusset 2008, Thorn et al. 2012, Thorn et al.

2013),

Aside from illegally killing large carnivores (St John et al. 2012), South African landowners can apply for a permit to

destroy a problem animal (defined as an animal that has caused significant property damage, killed an excessive

number of livestock or threatened the lives of people; Linnell et al. 1999) . Within South Africa, Limpopo province

has the highest incidence of problem animal complaints (Lindsey et al. 2011) and the highest density of game

ranches of any province (van der Waal and Dekker 2000, Carruthers 2008). Previous research has demonstrated that

leopard account for the majority of human-carnivore conflict in Limpopo (Thorn et al. 2013), which makes the

leopard an ideal candidate for investigating the impact of the game ranching industry on large carnivores in South

Africa. In this paper, we categorized problem animal permits (PAPs; N = ±2000) issued between January 2003 and

December 2012 by the nature of the complaint (e.g., livestock depredation, game depredation, infrastructure

damage, crop damage, threat to people) and investigated how PAPs varied over space and time. We then evaluated

the spatial relationship between PAPs and game ranches across Limpopo. Using Limpopo’s game auction records

from 2003 to 2012, we assessed the trend in game sales (average annual turnover, average annual sold, average

annual price) and evaluated which game species contribute the most to Limpopo’s game ranching industry, both

numerically and financially, over time. Using two contrasting Limpopo administrative districts (Waterberg District

and Capricorn District) we assessed the trend in breeding aberrant colour variants and extralimital game species,

and how these relate, both spatially and temporally, to PAPs.

Progress Report – I am currently writing this paper (intended submission date: March 2015).

CHAPTER 3 – MULTI-SCALE EVALUATION OF LEOPARD MONITORING TECHNIQUES

Introduction – Detecting population change forms a central component of wildlife management (Caughley and

Sinclair 1994). Conservation practitioners require reliable and efficient methods of monitoring population trends at

large spatial scales to ensure informed decision-making (Barea-Azcón et al. 2006). Typical population estimator

methods (i.e., involving direct observations) include aerial surveys (Kingsford and Porter 2009), live trapping

(Flowerdew et al. 2004), and camera-trapping (Rich et al. 2014). However, given the effort and resources required

(Balme et al. 2009a), these methods are often only feasible at small scales (Barea-Azcón et al. 2006). In contrast,

measuring indices of population change, such as sign surveys (Ausband et al. 2014), harvest effort (Gese 2001),

trophy quality (Croes et al. 2011), and occupancy (Karanth et al. 2009), provide a way of monitoring at scales large

enough to inform management (Yoccoz et al. 2001). Although population estimators and population indices are

suitable for the management and conservation of wildlife, little is known of how one relates to the other (Choate et

al. 2006). When comparing the efficiency at detecting mammal species richness and abundance, Silveira, Jácomo &

Diniz-Filho (2003) found that track counts performed better than camera-trapping and direct faunal counts. In the

Mediterranean basin, scent stations and sign surveys were more efficient methods, both economically and

logistically, at detecting carnivore species than the use of camera-trapping and live trapping when conducted at

large spatial scales (Barea-Azcón et al. 2006). When sampling bat species in Catalonia, Flaquer, Torre & Arrizabalaga

(2007) suggest the use three survey methods (bat detectors, mist nets and roost surveys) when assessing species

richness to prevent underrepresenting bat communities.

Identifying methodological ‘best practice’ between the need for rigour and program sustainability is at the forefront

of conservation management (Brashares and Sam 2005). Monitoring methods that are the most accurate, and thus

the most desirable, are often the least economical (Danell and Andren 2010). Therefore, a compromising trade-off

between monitoring cost and reliability is often warranted (Field et al. 2005). The interchangeable relationship

among monitoring precision, monitoring power and the frequency of monitoring intervals are three crucial

components to consider when devising optimal management strategies (Gerrodette 1987, Brashares and Sam 2005,

Hauser et al. 2006, Danell and Andren 2010). A monitoring program that infers the lowest cost, but still facilitates

reliable management decisions, is essential for a sustainable monitoring framework (Danell and Andren 2010).

Evaluating the statistical power and precision of monitoring estimates is important during the design and

implementation of a monitoring framework as it avoids wasted time and effort on activities that are unlikely to yield

useful results (Gerrodette 1987). The precision, or reliability, of monitoring estimates is directly related to how

frequently monitoring surveys are required (Danell and Andren 2010). Furthermore, monitoring intervals have been

shown to be less important to monitoring performance than monitoring precision (Danell and Andren 2010).

Similarly, an adaptive monitoring approach that considers the current state of the ecological system has been shown

to outperform fixed-interval monitoring (e.g., annual surveys) when deciding on how frequently to conduct

economically costly surveys (Hauser et al. 2006).

Large carnivores are vital to biodiversity at a global scale through their role as keystone species and top-down

regulation of lower trophic levels (Miller et al. 2001, Estes et al. 2011), but also present great challenges for

conservation and management (Ray et al. 2005). Enumeration of large carnivores is a particularly difficult task

(Obbard et al. 2010) due to their low densities, wide-ranging distribution and elusive nature (Hunter and Barrett

2011). These difficulties magnify when we consider the large spatial scales at which large carnivores need to be

monitored (Barea-Azcón et al. 2006). Capture-recapture techniques using camera-traps have become a highly

effective and rigorous method used to count large carnivores (Karanth et al. 2004, Balme et al. 2009a, O'Connell et

al. 2011), but although camera-trapping must be conducted at scales large enough to ensure unbiased population

10 LIMPOPO LEOPARD PROJECT YEAR 2014

estimates (Tobler et al. 2008), these scales are often too small to inform wider population management (Beausoleil

et al. 2013). In contrast, occupancy modeling techniques have shown to be very useful at monitoring large carnivore

populations at provincial (Thorn et al. 2011a, Rich et al. 2013, Ausband et al. 2014) and national scales (Karanth et al.

2009, Karanth et al. 2010). Occupancy modeling relies on data that are often cheaper and easier to obtain than

demographic data (Thorn et al. 2010). Similarly, for carnivores that undergo harvest, catch-per-unit-effort and

trophy quality can be used to monitor population trends (Gese 2001), but their relationship to true population size

has cast doubt (Robinson and DeSimone 2011, Chomba et al. 2014).

This information is vital for scientific authorities (e.g., South African National Biodiversity Institute), particularly for

monitoring and reporting (e.g., non-detrimental findings) on the state of biodiversity and species persistence.

Sustainable use of wildlife resources is an integral component of biodiversity management and economic

development but requires accurate monitoring of population trajectories. To address these factors in Limpopo

Province, South Africa, we evaluate the performance (power and precision) and comparability of population

monitoring techniques at disparate scales using camera-trapping data, public observations (occupancy), catch-per-

unit-effort, and trophy quality of leopard Panthera pardus collected over a three-year survey period. In addition to

monitoring performance, we assessed and compared the optimum monitoring intervals, annual cost and effort

required for each monitoring technique.

Progress Report – The occupancy questionnaire has been completed for 2015. Approximately 750 respondents

participated. The data are still being captured, and once complete, I will then being analyses using PRESENCE. All

seven study sites across Limpopo have now been surveyed using camera-traps. In the future, I hope to include an 8th

study site on farmland within the springbok flats area of Limpopo. Hunt return forms are now being completed to a

very high standard, however, I am currently following up on all the forms from 2013 that were not submitted, of

which there were quite a few. The Limpopo Hunters Liaison Forum (LHLF) are assisting me in collecting these

outstanding forms. During a number of meetings with the LHLF, many expressed that they felt completely left out of

the data collection process. To rectify this, I have set up a website (www.limpopoleopardproject.com) where hunters

and other members of the public can easily upload their own camera-trap images (with GPS/date/time) of leopard

photographed on their properties. I can then use these photos as presence data within the occupancy models. We

aim to use all these data within a monitoring strategy evaluation (MSE) framework. To develop my skills, I am visiting

Imperial College London for four months in 2015 to work with experts in terrestrial MSE methods.

CHAPTER 4 – OCCUPANCY MODELING: FACTORS AFFECTING LEOPARD DISTRIBUTION AND

ABUNDANCE IN LIMPOPO

Introduction – Global biodiversity is under increasing threat (Brooks et al. 2006), with many species facing extensive

range contractions and extinctions (Laliberte and Ripple 2004, Cardillo et al. 2005, Bates et al. 2014). Conservation

success depends on understanding the environmental factors that support species persistence (Karanth et al. 2010),

particularly in human-dominated landscapes where widespread habitat fragmentation have impacted species

distribution patterns (Sanderson et al. 2002a, Karanth et al. 2010). Quantifying the relationships between species

distribution and abiotic and biotic variables is a cornerstone of ecological research (Rushton et al. 2004), and is

particularly relevant for vulnerable species, where understanding the determinants of animal distribution is a vital

precursor for effective conservation management (Rushton et al. 2004).

Large, terrestrial mammals play a fundamental role as ecosystem engineers either through their effect on prey

populations or by altering vegetation structure and species composition (Morrison et al. 2007). Life-history traits

(Brashares 2003), large body size (Cardillo and Bromham 2001), and specialized habitat requirements (Fischer and

Lindenmayer 2007) increase the susceptibility of terrestrial mammal species to local extirpation and extinction as a

result of anthropogenic impact (Karanth et al. 2009), which has forced 25 % of global terrestrial mammal species to

near extinction (Ceballos et al. 2005). Large, terrestrial mammals are now among the world’s most threatened taxa

(Channell and Lomolino 2000) – with over 79 % of the world’s land surface having lost its full complement of large

mammalian assemblages (Morrison et al. 2007).

Mammalian carnivores are one of the most vulnerable guilds (Schipper et al. 2008, Estes et al. 2011), primarily due

to their volatile relationship with people and their perceptions of predators (Woodroffe et al. 2005). Mammalian

carnivores are particularly sensitive to the expansion of human populations into wild habitats (Woodroffe 2000), and

as a result, conflict between people and predators remains the greatest threat to large carnivores globally

(Woodroffe and Ginsberg 1998). Accurately documenting the change in carnivore distribution has become a priority

for conservation authorities (Ray et al. 2005). However, there is a lack of basic information on carnivore abundance

and distribution (Friedmann and Daly 2004, Long et al. 2008), particularly at regional and sub-continental scales

(Karanth et al. 2009). This deficit is primarily due to the difficulty in obtaining data on wide-ranging, and often

nocturnal and secretive species (Thorn et al. 2011b). The status of carnivore populations can be characterized by

abundance estimates (Gese 2001), but accurate records of animal encounters at large spatial scales are unfeasible

and unsustainable for long-term monitoring programs (Barea-Azcón et al. 2006). An alternative state variable to

abundance is the proportion of area occupied by a species (MacKenzie and Nichols 2004)—henceforth referred to as

“occupancy”.

Occupancy modeling requires detection/non-detection data (MacKenzie et al. 2006). Imperfect detection (i.e., false

absence or presence of a species) and spatial or temporal variations in detection probability are corrected for using

an information theoretic approach (MacKenzie et al. 2002, MacKenzie et al. 2006), which produces unbiased

maximum likelihood estimates (MacKenzie et al. 2006). Occupancy modeling provides a flexible framework that

enables occupancy to be modeled as a function of covariates to infer relationships between observed patterns and

the underlying processes (MacKenzie et al. 2002, Thorn et al. 2011a). The use of covariates can provide valuable

information about the factors that influence habitat use by a species and enables estimation of occupancy for

unsampled areas (MacKenzie et al. 2006, Zeller et al. 2011). Occupancy modeling has been used extensively at

assessing patterns and determinants of occurrence for a range of species (Thorn et al. 2011a), such as African

12 LIMPOPO LEOPARD PROJECT YEAR 2014

elephant Loxodonta africana (Martin et al. 2010), tiger Panthera tigris (Hines et al. 2010), jaguar Panthera onca

(Zeller et al. 2011), gray wolf Canis lupis (Rich et al. 2013), and brown hyaena Hyaena hyaena (Thorn et al. 2011a).

In this paper, we use questionnaire data collected over a three-year period in Limpopo province, South Africa to

model the occurrence and assess the factors that influence the province-wide distribution of leopard Panthera

pardus—a wide-ranging, large carnivore that undergoes harvest, intense illegal persecution and state-sanctioned

population control (Lindsey et al. 2011). Due to their resilience in the face of anthropogenic pressure (Nowell and

Jackson 1996), leopard are often afforded low conservation priority (Balme et al. 2010), yet they have been

eradicated from 37% of their historic African range (Ray et al. 2005). Limpopo Province comprises the most suitable

leopard habitat across South Africa (Swanepoel et al. 2013), but is also a major hotspot for human-mediated leopard

mortality (Lindsey et al. 2011, Pitman et al. submitted). The trade in leopard products, such as trophies and skins for

cultural regalia (Hunter et al. 2013), require justification through non-detriment finding assessments undertaken by

the South African National Biodiversity Institute (Lindsey et al. 2011). However, assessing the scale and impacts of

consumptive utilization of leopards requires current data that are often not available. In addition, Limpopo

Province’s conservation authority—the Limpopo Department of Economic Development, Environment and

Tourism—require accurate province-wide data on leopard distribution and abundance to enable informed decision-

making. Furthermore, significant growth in the game ranching industry in Limpopo province (NAMC 2006) may

increase conflict between ranchers and large carnivores (Lindsey et al. 2005). Although the game ranching industry is

important for economic development (NAMC 2006), it may cause further declines of carnivore populations (Lindsey

et al. 2013), which could negatively affect the tourism industry (Maciejewski and Kerley 2014). To ensure leopard

population persistence and sustainable use, effective management is necessary (Balme et al. 2013), but can only be

achieved through a landscape-scale understanding of leopard distribution patterns and the factors that underpin the

likelihood of occupying an area.

Progress Report – The province-wide occupancy survey for 2014 was completed in November.

CHAPTER 5 – RESOURCE USE AND LANDSCAPE CONNECTIVITY: ASSESSING THE PERMEABILITY OF

LEOPARD HABITAT ACROSS LIMPOPO

Introduction – Conserving landscape connectivity is a vital component of biodiversity conservation (Beier and Noss

1998, Crooks and Sanjayan 2006). Due to global habitat fragmentation (Crooks et al. 2011), connectivity

conservation is increasingly being used in range-wide priority-setting exercises (Crooks and Sanjayan 2006, Zeller

2007, Rabinowitz and Zeller 2010). Landscape connectivity is essential for natural ranging behavior and dispersal of

animals (Crooks et al. 2011), helps to maintain the continuity of ecological processes and allows populations to

respond to long-term environmental change (i.e., climate change) by shifting distributions (Crooks et al. 2011). For

small populations, landscape connectivity can increase the likelihood of persistence by facilitating movement among

habitat patches to mitigate the negative effects of demographic and environmental stochasticity (Hilty et al. 2006,

Rabinowitz and Zeller 2010).

Landscape fragmentation and the loss of connectivity can compromise the genetic integrity of populations and

reduce fitness (Frankham et al. 2002, Crooks and Sanjayan 2006)—ultimately leading to increased extinction risk

(Frankham 2005). Landscape fragmentation has led to the global population decline of numerous mammalian

species (Ceballos and Ehrlich 2002), of which large carnivores are the most severely impacted (Crooks et al. 2011).

The decline or disappearance of large carnivores can generate negative, cascading effects with system-level impacts

due to their essential role as top-down regulators (Terborgh et al. 2001, Estes et al. 2011). In a study assessing the

trophic relationships between carnivores and herbivores across North America and Eurasia, Ripple & Beschta (2012)

found that large carnivores, in particular gray wolves Canis lupus and bears Ursis spp., significantly limited the

densities of large mammalian herbivores. Because large carnivores act as indicators of ecosystem health (Dalerum et

al. 2008), they can be effective focal species on which to evaluate fragmentation and connectivity across large

spatial scales (Crooks and Sanjayan 2006). The combination of large body size, large area requirements, low

densities, slow population growth rates, and anthropogenic threats have resulted in widespread extirpation or

localized extinction of many large carnivore species across their historic geographical range (Cardillo et al. 2004,

Cardillo et al. 2005). Across Africa, carnivores have experienced an average range loss of 35.8%, where only 14% of

the total land area is currently comprised of intact medium and large felid communities (Ray et al. 2005).

Leopards Panthera pardus have undergone marked range loss across North Africa, West Africa, North-East Africa,

and South Africa, yet they remain the world’s most wide-ranging large felid (Hunter et al. 2013). Leopards are

remarkably tolerant of human disturbance, and can often persist within close proximity to human settlements

(Hunter et al. 2013), but experience intense anthropogenic pressure through trophy hunting (Packer et al. 2009,

Balme et al. 2010), state-sanctioned population control (Pitman et al. submitted), illegal killing (St John et al. 2012),

and prey loss due to bush meat hunting (Henschel et al. 2011). Previous research has demonstrated that

approximately 20% of South Africa’s land mass comprises suitable—although severely fragmented—leopard habitat

(Swanepoel et al. 2013). The main indicators of habitat fragmentation were attributed to human impact (as a result

of small ruminant and cattle density), normalized difference vegetation index (reflecting vegetation productivity and

bioclimatic variables) and surface ruggedness. Within South Africa, Limpopo province has the greatest capacity to

support viable leopard populations (Swanepoel et al. 2013), but these leopards are also the most persecuted

(Lindsey et al. 2011), often as a result of putative depredation on livestock and game species. Furthermore, human-

mediated leopard mortality is spatially clustered across Limpopo province (Pitman et al. submitted), which further

exacerbates the consequences of habitat fragmentation because leopards are unable to mitigate conflict due to the

disruption in dispersal ability.

For leopard, functional connectivity through natal dispersal has been shown to correspond to structural connectivity

(Fattebert 2014), indicating that dispersing individuals favour suitable habitat and that poor quality habitats could

impede population connectivity (Ricketts 2001, Fattebert 2014). The Kruger National Park (KNP) ecosystem to the

14 LIMPOPO LEOPARD PROJECT YEAR 2014

east of Limpopo Province comprises a major leopard source population (Daly et al. 2005) that could theoretically

seed nearby leopard habitats that are currently exposed to high levels of human-mediated mortality (i.e., ecological

traps). Aside from the KNP ecosystem, 35% of Limpopo Province comprises refuge areas (i.e., refugia) where birth

rates exceed known human-mediated mortality (Pitman et al. submitted). For the most part, these refugia are

geographically isolated from one another, and from the KNP ecosystem (Pitman et al. submitted). Structural

connectivity among these source populations is entirely unknown at the landscape-scale. Given the importance of

Limpopo Province for leopard conservation (Lindsey et al. 2011, Swanepoel et al. 2013), and other large carnivores

(Thorn et al. 2011b), an assessment of landscape connectivity and the identification of habitat corridors is vital and

should form a fundamental component for informed decision-making (Sanderson et al. 2002b). This article describes

the evaluation of habitat connectivity, identification of potential leopard corridors among refuge areas and the KNP

ecosystem, and delineation of contiguous leopard range across Limpopo Province by incorporating resource

selection functions and least-cost path analysis (Di Minin et al. 2013). Such an approach will provide conservation

authorities (e.g., the Limpopo Department of Economic Development, Environment and Tourism; LEDET) and

scientific authorities (e.g., the South African National Biodiversity Institute; SANBI) quantitative data on leopard

population connectivity necessary for biodiversity management and conservation.

Progress Report – This chapter links in with data/progress derived from Chapter 1–3.

A B C

D E

F

SUMMARY DATA

Camera-trapping – The LLP’s camera-trapping activities (Fig. 1) began in April 2013. This survey method has been

highly successful (Table 1), resulting in robust leopard density estimates (Table 2) at key surveillance sites.

Figure 1. Leopard capture frequencies recorded at camera-trap stations during surveys conducted at Welgevonden (A), Wonderkop (B), Atherstone (C), Timbavati (D), Makalali (E), and Venetia (F) in Limpopo, South Africa. Our seventh study site (Lajuma) is still being analyzed.

Table 1. Results of camera-trap surveys undertaken at surveillance sites in Limpopo, South Africa during 2013-2014. (Note: TBC “to be confirmed” entries are still being captured and analysed).

SURVEILLANCE SITE YEAR NO.

STATIONS

AREA SURVEYED

(KM2)

SAMPLING EFFORT (TRAP

DAYS)

LEOPARD CAPTURES

INDIVIDUAL CAPTURES

Welgevonden Private Game Reserve

2013 51 164 2694 169 21

2014 40 228 1948 177 29

Wonderkop Nature Reserve 2013 52 217 2652 54 17

2014 40 217 TBC TBC TBC

Atherstone Nature Reserve 2013 50 173 2600 141 20

2014 40 220 2154 80 21

16 LIMPOPO LEOPARD PROJECT YEAR 2014

Timbavati Game Reserve 2013 40 189 1960 123 35

2014 40 189 TBC TBC TBC

Makalali Game Reserve 2014 50 228 2500 116 28

Lajuma 2014 40 220 TBC TBC TBC

Venetia-Limpopo Nature Reserve 2014 40 206 2000 70 21

Table 2. Spatially-explicit capture-recapture model parameters estimating leopard population density from camera-trap surveys undertaken at surveillance sites in Limpopo, South Africa during 2013-2014. (Note: TBC “to be confirmed” entries are still being captured and analysed).

SURVEILLANCE SITE YEAR SIGMA LAMBDA PSI N SUPER DENSITY 100 KM-2 (± SD)

Welgevonden Private Game Reserve 2013 3.4 0.03 0.33 75.71 3.2 ± 0.7

2014 3.03 0.02 0.48 144 5.44 ± 1.0

Wonderkop Nature Reserve 2013 3.09 0.01 0.48 78.96 2.99 ± 0.8

2014 TBC TBC TBC TBC TBC

Atherstone Nature Reserve 2013 1.87 0.02 0.42 154.43 6.2 ± 1.4

2014 3.01 0.01 0.47 113 4.4 ± 1.0

Timbavati Game Reserve 2013 2.01 0.02 0.72 277.96 11 ± 1.8

2014 TBC TBC TBC TBC TBC

Makalali Game Reserve 2014 3.19 0.01 0.44 135.56 5.1 ± 1.1

Lajuma 2014 TBC TBC TBC TBC TBC

Venetia-Limpopo Nature Reserve 2014 3.36 0.01 0.48 110.21 4.4 ± 1.1

Occupancy – In 2013, we conducted 1020 face-to-face interviews over a 10-week period. The proportion of bush

cover (BUSH) was positively correlated with leopard occupancy probability, whilst human population density

(PEOPLE_KM2) and the proportion of recently cultivated land (CULTIV_RECENT) were negatively correlated with

leopard occupancy probability (Fig. 2a). Leopard detection probability increased whenever the proportion of dense

(DENSE_BUSH) and open bush (OPEN_BUSH) increased. In 2014, we conducted 750 telephonic interviews over a 4-

week period (using the same respondents from 2013). Human population density (PEOPLE_KM2) was negatively

correlated with leopard occupancy probability (Fig. 2b). Leopard detection probability increased whenever the

proportion of dense (DENSE_BUSH) and open bush (OPEN_BUSH) increased, and whenever the proportion of

grassland (GRASSLAND) and environmental vegetation index (EVI_MEAN) decreased. There is quite a marked change

in occupancy probability from 2013 to 2014. A number of factors may be at play here. For instance, we might be

detecting a degree of social desirability bias between survey techniques; face-to-face interviews might generate

more false positives as respondents are keen to engage in conversation about leopard, whereas telephonic

interviews might be more realistic or perhaps generate more false negative responses. We also lost 25% of our

respondents in 2014, mostly due to incorrect contact details, change of details, death, or relocation (outside of

Limpopo Province). In 2015, I will be conducting both telephonic (N = 750) and face-to-face (N = 500) interviews in

order to compensate for the annual loss of respondents.

Monitoring leopard mortality – In many developing countries, conservation authorities lack the human and financial

resources to accurately and consistently monitor wildlife populations (Daly et al. 2005, Rodríguez et al. 2005),

particularly cryptic species such as leopards which range widely and occur mainly outside of formally protected

areas (Friedmann and Traylor‐Holzer 2008, Swanepoel et al. 2013). As a result, carnivore management is rarely

underpinned by strong science (Ray et al. 2005). The LLP monitors annual leopard mortality at the provincial scale to

identify areas that require focused conservation effort resulting from over-exploitation of leopard populations. We

Figure 2. Estimated probability of

leopard Panthera pardus occupancy

for Limpopo province, South Africa for

2013 (a), and 2014 (b).

a)

b)

18 LIMPOPO LEOPARD PROJECT YEAR 2014

use historical trophy hunting and problem-animal-control permit records (Fig. 3) to identify refugia (i.e., habitats

that exhibit relatively high survival but low reproduction) and ecological traps (i.e., high-quality habitat that exhibits

reduced reproduction and survival) among leopard populations at three geographical scales (i.e., catchment,

municipality, district) in Limpopo Province.

Harvest composition – Hunt return forms are now being submitted to a very high standard, but the data are still

being processed. Therefore, I present data from earlier in the year only. Over half of the hunt return forms

submitted to the LEDET lacked basic data (e.g., date, location, sex) about the hunt (Fig. 4). The remaining hunt return

forms contained some data, however, not one hunt return form was fully completed. One of the major issues was

that hunting outfitters did not fully submit all 10 mandatory photos – these photos are needed to determine the age

and sex class of each hunted leopard. Even though 48% of hunt return forms had photos attached (Fig. 5), none of

these comprised all 10 mandatory photos. Estimating trophy quality can only be conducted once all photos, of all

hunted leopard, are collected. A quarter of hunt return forms did not specify whether a male or female was hunted

– nor did the hunting outfitter provide sufficient photos to determine this retrospectively (Fig. 6). However, it is

encouraging to see that over half the hunted leopards are males (bear in mind that not all hunting outfitters

provided hunt return forms). Ideally, we would like to see hunts comprising only males above the age of 7 years old

(currently 16%; Fig 7). Although it is encouraging to see that 62% of all recorded hunts comprised non-subadult

males.

Figure 3. Distribution of leopard (Panthera

pardus) mortality events (N = 757) from

January 2007 to December 2012 across

Limpopo Province, South Africa.

Figure 4. Percentage of data

provided by hunting

outfitters using hunt return

forms for Limpopo Province,

South Africa during 2011–

2013.

Figure 5. Percentage of

hunt return forms that

had some, but not all,

leopard photos for

Limpopo Province, South

Africa during 2011–2013.

PROJECT LEADERS AND OTHER STAFF

Ross Tyzack Pitman, BSc Hons – PhD student and lead investigator

Guy Balme, Ph.D. – Supervisor and Director of Panthera’s Leopard Program

Luke Hunter, Ph.D. – Supervisor and President of Panthera

Rob Slotow, Ph.D. – Supervisor and Deputy Vice-Chancellor and Head of College, University of KwaZulu-Natal

Vino Ndou – UNISA student and LLP assistant (Occupancy survey)

Dipolelo Mashabela – UNISA student and LLP assistant (Occupancy survey)

PARTNERS

Limpopo Department of Economic Development, Environment and Tourism

University of KwaZulu-Natal

Wildlife and Ecological Investments

Siyafunda Conservation

Galagos Wildlife Conservation

Durham University (Primate & Predator Project)

PROJECT DURATION

Funding start date – 20 January 2013

Project start date – 23 April 2013

Projected end date – December 2015 and onwards as part of a long-term monitoring program

Figure 6. Sex class distribution of

harvested leopards for Limpopo Province,

South Africa during 2011–2013.

Figure 7. Sex and age class distribution of

harvested leopard in Limpopo Province,

South Africa during 2011–2013.

20 LIMPOPO LEOPARD PROJECT YEAR 2014

APPROVED BUDGET

See attached budget

GOALS FOR 2015

I aim to have submitted Chapter 2 by March 2015

Develop Monitoring Strategy Evaluation (MSE) models at Imperial College London with Professor E.J.

Milner-Gulland

Develop a leopard education and identification course for hunting outfitters across Limpopo Province

Continue normal fieldwork activities (camera-trapping, questionnaire surveys, trophy monitoring)

Further improve hunting regulations

EXPLORATORY ACTIVITIES

No exploratory activities were conducted.

CONSERVATION ACCOMPLISHMENTS

The Limpopo Leopard Project has succeeded in implementing new trophy hunting regulations for Limpopo. New

regulations are to come into effect in 2015. These recommendations include:

1. LEDET’s leopard management units will be reduced to the catchment-scale—a much smaller scale than the

status quo.

2. Account for problem leopard offtake in the determination of hunting quotas.

3. Divide Limpopo Province into hunting zones by implementing a sustainable offtake rate (i.e., 3.6 % of the

estimated population; Fig. 8).

4. Assist quota allocations by employing alternative measures such as age-based hunting.

5. No hunting of female leopards.

6. Develop and implement official guidelines for problem leopard control to assist in mitigating human-

carnivore conflict.

7. Continue the mandatory completion of hunt return forms.

8. Withhold export permits when hunting outfitters hunt female leopards or when hunt return forms are not

fully completed and submitted.

The abundance of damage-causing animal (DCA; problem animal control) permits, and their allocation, constitute a

major concern for Limpopo’s leopard populations. Limpopo currently issues three-times more DCA permits per year

than any other province in South Africa (Lindsey et al. 2011). Reducing the number of leopards killed by lethal

control would release significant pressure on the provincial leopard population. Problem leopard complaints in

Limpopo are almost exclusively attributed to livestock and game depredation (LEDET unpublished data). To

appropriately deal with the issue of problem animal control, the LEDET require official guidelines on how to manage

problem animals. Some basic considerations include:

1. Stock depredation events should be inspected within 24 h.

2. Problem animal permits should not be awarded for the depredation of wild game.

3. Camera-traps should be used to photographically identify the offender.

4. A problem animal permit should only be awarded once the same leopard is responsible for at least three

depredation events over a two-month period (Ferguson 2006).

LIST OF PUBLICATIONS

Figure 8. Distribution of hunting zones (N = 53) for 2015 across Limpopo Province, South Africa. Each contiguous shade of

grey depicts a single hunting zone where ONE leopard can be sustainably removed per year. Black zones are permanently

restricted from hunting because these areas cannot sustain the removal of any leopard at any time. CITES permits are linked

to a particular hunting zone, and cannot be transferred to another zone.

22 LIMPOPO LEOPARD PROJECT YEAR 2014

Pitman, R.T., Swanepoel, L.H., Hunter, L., Slotow, R., Balme, G. (in review) The importance of refugia, ecological

traps, and scale for the management of a threatened large carnivore. Biodiversity and Conservation

FINAL FINANCIAL REPORT

See attached budget.

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