Socio-Economic and Ecological Correlates of Leopard-Stock Farmer Conflict in the Baviaanskloof Mega-Reserve, Eastern Cape By
Liaan Minnie
Submitted in fulfilment of the requirements for the degree of Magister Scientiae at the Nelson Mandela Metropolitan University
January 2009
Supervisor: Prof. G.I.H. Kerley Co-Supervisor: Dr. A.F. Boshoff
DECLARATION BY STUDENT
FULL NAME:
______Liaan Minnie_________________________________
STUDENT NUMBER:
_s203010914__________________________________
QUALIFICATION: _______M.Sc._______________________________________
DECLARATION: In accordance with Rule G4.6.3, I hereby declare that the above-mentioned treatise/ dissertation/ thesis is my own work and that it has not previously been submitted for assessment to another University or for another qualification.
SIGNATURE:
___________________________________________________
DATE:
_______11 April 2009__________________________________
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Table of contents Summary .................................................................................................................................. vii List of acronyms .....................................................................................................................viii Acknowledgements ................................................................................................................... ix Chapter 1: Introduction .......................................................................................................... 1 1.1 Biological factors ............................................................................................................. 1 1.1.1 Body size .................................................................................................................... 1 1.1.2 Range size .................................................................................................................. 2 1.1.3 Prey specialization .................................................................................................... 2 1.2 Direct impacts .................................................................................................................. 2 1.2.1 Habitat destruction and reduction in natural prey.................................................... 3 1.3 Indirect impacts ................................................................................................................ 3 1.3.1 Human population growth ......................................................................................... 4 1.3.2 Conservation efforts .................................................................................................. 4 1.4 Carnivore-stock farmer conflict ....................................................................................... 5 1.5 Leopard (Panthera pardus) ............................................................................................... 6 1.5.1 Distribution and status .............................................................................................. 6 1.5.2 Cape mountain leopard ............................................................................................. 6 1.5.3 Diet of leopards in the Baviaanskloof Mega-Reserve ............................................... 8 1.5.4 Leopard-stock farmer conflict in the Baviaanskloof Mega-Reserve ......................... 9 1.6 Rationale and objectives................................................................................................... 9 Chapter 2: The Baviaanskloof Mega-Reserve..................................................................... 11 2.1 Baviaanskloof Mega-Reserve (BMR) ............................................................................ 11 2.2 Baviaanskloof Nature Reserve ....................................................................................... 11 2.3 Climate ........................................................................................................................... 12 2.4 Geology .......................................................................................................................... 13 2.5 Vegetation ...................................................................................................................... 13 iii
Chapter 3: Ecological correlates of leopard-stock interactions in the Baviaanskloof Mega-Reserve ......................................................................................................................... 16 3.1 Introduction .................................................................................................................... 16 3.2 Methods .......................................................................................................................... 17 3.2.1 Subjects .................................................................................................................... 17 3.2.2 Survey Instrument .................................................................................................... 18 i.
Predators of livestock ............................................................................................ 18
ii.
Leopard-stock incidents ......................................................................................... 19
3.2.3 Statistical Analysis................................................................................................... 20 3.3 Results ............................................................................................................................ 20 3.3.1 Predator Comparison .............................................................................................. 21 3.3.2 Leopards .................................................................................................................. 23 3.4 Discussion ...................................................................................................................... 28 3.4.1 Predator comparison ............................................................................................... 28 3.4.2 Characteristics of leopard-stock incidents .............................................................. 29 3.4.3 Predator interactions............................................................................................... 30 Chapter 4: Socio-economic correlates and management of leopard-stock farmer interactions in the Baviaanskloof Mega-Reserve ................................................................ 33 4.1 Introduction .................................................................................................................... 33 4.2 Methods .......................................................................................................................... 34 4.2.1 Surveys Instrument .................................................................................................. 34 i.
Personal information.............................................................................................. 34
ii.
Farming type .......................................................................................................... 34
iii. Management of livestock....................................................................................... 34 iv.
Predator control strategies .................................................................................... 35
v.
Attitudes towards leopards .................................................................................... 35
4.2.2 Statistical analysis ................................................................................................... 35 4.3 Results ............................................................................................................................ 36 iv
4.3.1 Management of livestock ......................................................................................... 36 4.3.2 Predator control strategies ...................................................................................... 39 4.3.3 Attitudes towards leopards ...................................................................................... 42 4.3.4 Socio-demographic composition ............................................................................. 44 4.3.5 Characteristics of livestock ..................................................................................... 45 4.4 Discussion ...................................................................................................................... 45 4.4.1 Socio-demographic composition ............................................................................. 45 4.4.2 Characteristics of livestock ..................................................................................... 45 4.4.3 Management of livestock and predator control strategies ...................................... 46 4.4.4 Attitudes towards leopards ...................................................................................... 47 Chapter 5: Modelling leopard abundance: What can we learn? ...................................... 49 5.1 Introduction .................................................................................................................... 49 5.2 Methods .......................................................................................................................... 51 5.2.1 Distribution of mammal habitat classes .................................................................. 51 5.2.2 Estimation of prey abundance ................................................................................. 52 i.
Modelled abundance .............................................................................................. 52
ii.
Game count data .................................................................................................... 52
5.2.3 Estimation of potential leopard density ................................................................... 53 5.3 Results ............................................................................................................................ 55 5.3.1 Mammal habitat classes .......................................................................................... 55 5.3.2 Potential prey abundance ........................................................................................ 57 5.3.3 Potential leopard density and abundance ............................................................... 57 5.3.4 Comparison of potential leopard densities.............................................................. 59 5.4 Discussion ...................................................................................................................... 60 5.4.1 Potential leopard density and abundance ............................................................... 60 5.4.2 Comparison of potential leopard densities.............................................................. 62 5.4.3 Model limitations and improvements ...................................................................... 64 v
Chapter 6: General discussion .............................................................................................. 65 6.1 Limitations to this study ................................................................................................. 65 6.2 Synthesis of findings ...................................................................................................... 65 6.3 Management recommendations...................................................................................... 67 6.3.1 Linking leopard predation with conservation planning and implementation ......... 67 i.
Conservation planning opportunities ..................................................................... 67
ii.
Withdrawal of livestock......................................................................................... 68
6.3.2 Livestock and predator management....................................................................... 68 i.
Livestock management .......................................................................................... 69
ii.
Livestock guarding animals ................................................................................... 70
iii. Restoration of natural prey base ............................................................................ 70 6.3.3 Leopard conservation .............................................................................................. 71 i.
Education ............................................................................................................... 71
ii.
Incentives ............................................................................................................... 71
iii. Eco-tourism ........................................................................................................... 72 6.4 Further research .............................................................................................................. 73 References ................................................................................................................................ 75 Appendices............................................................................................................................... 84
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Summary
The leopard, Panthera pardus, is particularly threatened outside conservation areas in South Africa. This has been attributed to a reduction in natural habitat, decreasing natural prey populations, and commercial exploitation such as trophy hunting, and most importantly, persecution by stock farmers (Woodroffe 2001). The leopard population in the Baviaanskloof Mega-Reserve (BMR) has undergone a substantial decrease in range and numbers in the past 200 years, resulting in a highly fragmented population in the Baviaanskloof Mega-Reserve, and is regarded as being insecure. There is thus a need to investigate the nature and extent of leopard-stock farmer interactions to provide the foundation for an effective leopard conservation plan. Here I investigated the ecological and socio-economic factors influencing leopard-stock farmer conflict via landowner surveys and estimated potential leopard numbers using a prey-based density model. Leopards are not necessarily the most important causes of livestock mortality in the BMR. On average, leopards killed significantly less livestock (0.7% livestock per year) than black-backed jackals (4.7% per year) and caracal (2.5% per year), yet 67% of farmers had negative attitudes towards leopards. These negative attitudes were not significantly related to stock losses. However, most of the farmers that had negative attitudes towards leopards did not have any stock losses attributed to leopards. Thus if predator-stock conflict is not reduced it will result in the retaliatory killing of leopards. This will have severe consequences for this relatively small population (estimated at 59 – 104 individuals by the prey-based model), which may ultimately lead to the local extinction of these leopards (Woodroffe & Ginsberg 1998). Key words: Panthera pardus; leopard; carnivore; human-predator conflict
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List of acronyms BMR: Baviaanskloof Mega-Reserve BNR: Baviaanskloof Nature Reserve BCR: Baviaanskloof Cluster Reserves ECPB: Eastern Cape Parks Board DEDEA: Department of Economic Development and Environmental Affairs AgriEC: Agricultural Society of the Eastern Cape
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Acknowledgements Firstly, I would like to thank the farmers from the Baviaanskloof, Cockscomb, Steytlerville, Willowmore, and Kareedouw areas. Without your assistance, this project would not have been possible. I would also like to thank Gerrrie Ferreira for providing me with the leopard mortality data for the Baviaanskloof Mega-Reserve. Secondly, I would like to thank Onno Huyser and Tamaryn Allen from the Table Mountain Fund for all their assistance with regards to the funding of this project. I would also like to thank the Table Mountain Fund, the World Wildlife Fund, and the Nelson Mandela Metropolitan University for providing funding for this project, and the Mazda Wildlife Fund for providing transport. Thirdly, I would like to thank the Eastern Cape Parks Board, the Department of Economic Development and Environmental Affairs, the Agricultural Society of the Eastern Cape, the Wilderness Foundation, and “die Baviaans/Kouga Kaapse Bergluiperd Bestuurskomitee” for supporting this project. Fourthly, I would like to thank my supervisors, Prof. G.I.H. Kerley and Dr. A.F. Boshoff who assisted and guided me throughout the whole project. Finally, I would like to thank all my family and friends who supported me throughout the duration of the project.
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Chapter 1: Introduction Humans and carnivores have coexisted for eons (Graham et al. 2005; Woodroffe 2000) and human-carnivore conflict has played a major role in shaping carnivore populations worldwide (Wang & Macdonald 2006). According to Kruuk (2002), human-carnivore conflict over livestock has been in existence since humans domesticated wild ungulates. However, in recent times there has been a dramatic increase in human-carnivore conflict. These conflicts happen because of competition between humans and carnivores for shared, limited resources (Graham et al. 2005). For example, many carnivore species kill prey species that humans hunt, harvest or farm for consumption or recreation, and occasionally they may even kill people (Kaczenskey et al. 2004; Treves 2003). The conflict can be particularly contentious when the predators involved are protected and the resources concerned are of high value to humans (Thirgood et al. 2000). The factors contributing to the increase in human-carnivore conflict vary according to local socio-economic environment and the biological and ecological attributes of the predator involved. These factors can be grouped into three broad categories (1) Biological factors, (2) Direct impacts, and (3) Indirect impacts (Mattson 2004). All these factors are interlinked and equally important in order to assess the severity of humancarnivore conflict. This dissertation will attempt to address these factors in terms of leopardstock farmer conflict in the Baviaanskloof Mega-Reserve (BMR), Eastern Cape, South Africa. The BMR is a World Heritage Site and is situated in the south-western part of the Eastern Cape. This area consists of the Baviaanskloof Nature Reserve as well as the surrounding nonconservation areas. 1.1 Biological factors Biological factors are the attributes of the specific carnivore involved, which will increase its chance of encountering humans, their livestock or compete directly with humans for wild ungulates. According to Mattson (2004), the three biological factors that contribute most to carnivore-stock conflict are body size, range size, and prey specialization. 1.1.1 Body size One of the most important factors governing human-carnivore conflict is the body size of carnivores. According to Mattson (2004), an increase in predator body size is positively correlated with an increase in home range size and prey weight range. This increase in prey size thus determines which predators will be able to take livestock. In other words, large 1
predators such as lions (Panthera leo), spotted hyaenas (Crocuta crocuta), brown hyaenas (Parahyaena brunnea), cheetah (Acinonyx jubatus), African wild dogs (Lycaon pictus) and leopards (Panthera pardus) are more likely to come into conflict with humans because they readily take livestock. Preferred prey weight ranges gives a good indication of whether a carnivore is capable of preying on domestic livestock, and all the large African carnivores have preferred prey weight ranges that incorporate livestock body size (lion, Hayward & Kerley 2005; spotted hyaena, Hayward 2006; leopard, Hayward et al. 2006a; cheetah, Hayward et al. 2006b). 1.1.2 Range size Carnivore range size plays an important role in human-carnivore conflict. Carnivores with a wide-ranging habit are more likely to have home ranges occurring partially outside protected areas (Woodroffe 2000). This thus increases the chance of predators encountering humans and livestock, and inevitably leads to recurrent resource competition with humans (Graham et al. 2005). This conflict with farmers at reserve borders can develop into a potent edge effect leading to local extinctions of carnivore populations, if the reserve is too small to include the entire home ranges of carnivores (Woodroffe & Ginsberg 1998). 1.1.3 Prey specialization Specialized predators are more vulnerable to extinction than generalist predators (Mattson 2004; Hayward & Kerley 2008). This is because specialists cannot switch prey species when the density of their natural prey is reduced. A classic example of this, which is used in most ecology textbooks (Stiling 2002), is the case of the snowshoe hare (Lepus americanus) and the Canadian lynx (Lynx canadensis). Generalists on the other hand are able to adapt by switching to other food sources when there is a reduction in natural prey, for example jackals (Canis spp., Mattson 2004). These carnivores come into conflict with livestock farmers, simply because they are able to switch to domestic livestock when the availability of their natural prey is reduced (Mizutani 1993). All of the African large predators (lion, hyaena, cheetah, African wild dog and leopard) have come into conflict with landowners, and all of them are generalist predators (Graham et al. 2005). This increases the possibility of switching to domestic ungulates for prey. 1.2 Direct impacts Direct impacts are defined as human impacts that have a direct affect on the carnivore population. Many factors should be considered when investigating the anthropogenic impacts 2
involved in human-carnivore conflict. These are the harvesting of body parts, retaliatory killing of carnivores, collisions with motor vehicles, decrease in prey base, destruction of natural habitat, and disease (Mattson 2004). Of these factors, only three are applicable in the BMR. They include destruction of habitat, the reduction in natural prey, and retaliation for depredation. 1.2.1 Habitat destruction and reduction in natural prey Humans alter their natural environment in two main ways: they alter the habitat to create pastures for livestock, and they overexploit the natural vegetation by using it as grazing for livestock, and overexploit herbivores for food or recreational purposes (Breitenmoser 1997). This process of habitat destruction and the reduction in natural prey often go hand in hand. For example, introduced livestock outcompetes the natural herbivores and has a large impact on the vegetation, which decreases the natural prey base of the area (Breitenmoser 1997). The high density of livestock prevents the regeneration of the natural vegetation (Breitenmoser 1997) and consequently decreases the carrying capacity for native prey. In these unnatural settings, carnivores are forced to prey on livestock (Breitenmoser 1997). Thus, the recent increase in carnivore-stock farmer conflict is partially due to the destruction of natural habitat (Treves & Karanath 2003), but also to the overexploitation of the natural prey in the area. According to Mishra (1997), this overexploitation of natural herbivores by humans can reduce the availability of natural prey to predators to such an extent that they are forced to take domestic livestock. 1.3 Indirect impacts Indirect impacts are defined as factors that increase the likelihood of human-carnivore conflict. These factors can be seen as a catalyst for conflict between humans and carnivores. Of these factors, human population growth (Woodroffe 2000) and conservation efforts (Breitenmoser 1997) are two of the most important factors augmenting human-carnivore conflict.
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1.3.1 Human population growth The rate of conflict between carnivores and humans has grown in the last decades and is largely attributable to human population explosion in the last century, which has lead to an increase in urbanization and development into previously secluded carnivore habitats (Graham et al. 2005; Kaczensky et al. 2004; Treves 2003). This in turn increases the frequency of encounters between domestic stock and carnivores (Woodroffe 2001; NaughtonTreves et al. 2003), and hence an increase in the severity of the factors that shape humancarnivore conflict. This is because human population expansion is at the core of carnivore extinctions. According to Woodroffe (2000), there is a significant linear relationship between human density and carnivore extinction. Thus, with an increase in human population there is an increased probability of the local extinction of carnivore populations. This is due to humans modifying the environment in such a way that it becomes hostile towards carnivores (Woodroffe 2000). Large carnivores are very sensitive to this human population explosion, because this increases their chances of encountering humans and livestock. This leads to an increase in the amount of livestock or even humans killed by predators (Woodroffe 2000), which generally results in retaliatory killing of carnivores. 1.3.2 Conservation efforts Conservation efforts within protected areas have led to an increase in predator numbers. These predators ultimately disperse from the protected areas onto the neighbouring farmlands, where conflict inevitably arises. This gives rise to a situation that shares similarities with source-sink dynamics (Larivière et al. 2000). Here, the reserves with their relatively high carnivore densities act as sources and the neighbouring farmlands as sinks. The reason for this is that these reserves often lack adequate fencing. The factors that exemplify this population increase are, successful reintroduction programmes and habitat restoration accompanied by a higher conservation status for the predator in question. This was the case for the ‘Big Three’ (analogous to the African ‘Big Five’), which includes the brown bear (Ursus arctos), wolf (Canis lupus) and the Eurasian lynx (Lynx lynx) populations in the Swiss Alps (Breitenmoser 1998). Here the carnivore decline mirrored human expansion. Wherever humans settled the carnivore population was exterminated due to their threat to livestock and as competitors for game species (Breitenmoser 1998). However, this is not the sole reason for their decline. According to Breitenmoser (1998), the alteration of the natural habitat, reduction in natural prey items and the expansion of agricultural farmlands played important roles. The recovery of the ‘Big Three’ started with the restoration of natural habitats. This, in combination with a 4
retraction of human populations towards city centres, due to industrialization, led to the recovery of the forests (Breitenmoser 1998). This facilitated the immigration of ungulates to these areas, which was also augmented by reintroduction programmes, and ultimately led to an increase in the carnivore population (Breitenmoser 1998). The increases in carnivore populations lead to an increase in carnivore-stock conflict, which in turn leads to the retaliatory killing of lynxes and wolves outside the boundaries of protected areas in the Swiss Alps (Breitenmoser 1998). 1.4 Carnivore-stock farmer conflict According to Graham et al. (2005), livestock depredation by carnivores is one of the main reasons for conflict between carnivores and humans. Several factors play a role in humancarnivore conflict. All of these factors combine to create a unique situation where carnivores compete with livestock farmers for the same resources. In general, farmers that farm next to protected areas generally have the greatest depredation rates. In areas where livestock farming is the predominant landuse, carnivore populations will suffer most from direct persecution due to retaliatory actions by the farmers (Mazzolli et al. 2002). This depredation of livestock by carnivores is exacerbated by habitat destruction and the reduction in natural prey, which forces carnivores to prey on domestic livestock (Mizutani 1993). The conflict arises because carnivores are adapted to take ungulate prey and therefore they will take domestic ungulates when the opportunity arises (Treves & Karanath 2003). The exact reasons why carnivores prey on domestic stock are poorly understood. In some areas, it is thought that it is a learnt behaviour, in other words, predators have learned that livestock are easy prey (Maddox 2003). In this case, there may be the existence of a few “problem individuals” that specifically target livestock as prey. Other factors, such as age and sex of the predator may also play an important role. Saberwal et al. (1994) showed this for lions and Sukumar (1991) for tiger (Panthera tigris) in India. For whichever reason, the fact remains that carnivores prey on domestic livestock, which leads to serious economic losses to farmers due to livestock losses and the increased costs and work effort to adapt farming methods (Kaczensky et al. 2004). According to Treves and Karanath (2003) there is an increase in the frequency and economic cost of the conflict between humans and carnivores in many areas. These perceived economic losses lead to carnivore persecution by farmers (Graham et al. 2005). This effect has lead to the extinction of several carnivore species worldwide (Woodroffe et al. 2005).
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1.5 Leopard (Panthera pardus) 1.5.1 Distribution and status Leopards have the widest geographical range of all felids (Skinner & Chimimba 2005). They occur from the southern parts of Africa through the Middle East to the Far East, and their range extends north as far as Siberia and south as far as Sri Lanka and Malaysia (Mills 2005). Globally, leopards are not considered to be threatened with extinction, and are classified on the IUCN Red List as Near Threatened (Breitenmoser et al. 2008). In a South African context, the two largest leopard populations occur within the Kruger National Park and the surrounding areas (over 1000 individuals) and the Kalahari Gemsbok National Park (over 150 individuals shared between South Africa and Botswana; Mills 2005). In Kwa-Zulu Natal, leopards occur mainly in the north-east with few individuals occurring in the rest of the province (Skinner & Chimimba 2005). They occur throughout the Limpopo Province as well as in Mpumalanga, the North-West Province (there are reported viable populations in the Magaliesberg, Waterberg, and Soutpansberge – Mills 2005), and Gauteng (Skinner & Chimimba 2005). In the Western Cape, they occupy the mountains (Cape Fold Mountains, CFM) and forests of the south and south-western Cape (Stuart 1981). There is no exact estimate of the population size for the CFM leopards, but it is considered very small and extremely insecure (Norton 1986; Turnbull-Kemp in Stuart & Heinecken 1977). According to Stuart (1981), the Cape Mountain leopards attain their highest densities in the Mountain Fynbos of the southwestern, southern portions of the Western Cape as well as eastern and southern part of the Eastern Cape. Although leopards are not considered endangered in a global context, nationally they are considered to be threatened with extinction in the medium term future by the National Environmental Management and Biodiversity Act of 2004. 1.5.2 Cape mountain leopard According to Henley (2000) there is a possibility that the leopards occupying the mountainous areas in the Western and Eastern Cape Provinces are a subspecies distinct from the leopard populations occurring further north. This is primarily based on morphological differences between this leopard and the savanna leopard (Martins & Martins 2006). Firstly, the Cape leopards have a longer, softer and more vividly coloured coat (Henley 2000). Secondly, these leopards tend to be smaller than savanna leopards, with males averaging 31 kg and females 21 kg (Stuart 1981), whereas male savanna leopards average between 58 and 63 kg and females between 32 and 38 kg, depending on the location (Skinner & Chimimba 2005). This 6
differentiation is probably due to the differences in diet (Henley 2000), with the mountain leopards preying on smaller prey (e.g. rodents and small antelope) compared to the savanna leopards. However, there is no genetic evidence to support the taxonomic separation of the “Cape Mountain leopard”. Irrespective of this, several factors make the Cape leopard population unique and of special conservation concern. This population forms the southern extreme of the global distribution of leopards (see Skinner & Chimimba 2005; Figure 1.1) and it has become progressively more isolated from other leopard populations since the early 1900s (Norton 1986; Figure 1.2). The Cape leopard population also occupies a unique biome, namely Fynbos, which has a discrete prey base compared to other more productive systems such as savannas (Henley 2000).
Figure 1.1: The distribution of leopards in Africa (from Skinner & Chimimba 2005).
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Figure 1.2: The patterns of historical range retraction of southern African leopards (from Norton 1986). 1.5.3 Diet of leopards in the Baviaanskloof Mega-Reserve Leopards are opportunistic and prey on a wide range of animals (Bothma & le Riche 1984) and have been known to scavenge when the opportunity arises (Bailey 1993). This together with their secretive and nocturnal habits allows leopards to persist in areas close to human habitation (Ott et al. 2007). Conflict with stock farmers inevitably arises because leopards prefer prey between 10 and 40 kg (Hayward et al. 2006a), which includes livestock. Ott et al. (2007) described the diet of leopards in the Baviaanskloof Nature reserve and adjacent rangelands. Leopards preyed predominantly on small mammals including vlei rat (Otomys irroratus), rock hyrax (Procavia capensis), African wild cat (Felis silvestris), shorttailed gerbil (Desmodillus auricularis), Namaqa rock mouse (Aethomys namaquensis), and multimammate mouse (Mastomys sp.; Ott et al. 2007). The diet also included nine ungulate species including mountain reedbuck (Redunca fulvorufula), bushbuck (Tragelaphus scriptus), grysbok (Raphicerus melanotis), common duiker (Sylvicapra grimmia), steenbok (Raphicerus campestris), grey rhebuck (Pelea capreolus), klipspringer (Oreotragus oreotragus), kudu (Tragelaphus strepsiceros), and the alien nyala (Tragelaphus angasii; Ott et al. 2007). Most importantly, two breeds of domestic stock, Angora goats (Capra hircus) and sheep (Ovis aries) was recorded in the diet (Ott et al. 2007). Although livestock only forms a small part of the leopard’s diet, it still indicates that leopards prey on domestic stock
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in the BMR. This causes economic losses to the farmer and hence the retaliatory killing of leopards. 1.5.4 Leopard-stock farmer conflict in the Baviaanskloof Mega-Reserve Relatively little information is available regarding the effects of retaliatory killing on leopards in the BMR. Most of this information relates to the then Cape Province and does not specify how many leopards were killed in the BMR. For example, Stuart & Heinecken (1977) determined the amount of known leopard mortalities in the then Cape Province between 1952 and 1977. A total of 189 leopards were killed in this period. This translates to an average of 7.3 leopard killed per year. Esterhuizen & Norton (1985) also determined the amount of leopard removed in the then Cape Province from 1977 to 1982. However, they determined the amount of leopard mortalities for each divisional council of the then Cape Province. It was thus possible to determine how many leopards were killed in the BMR. A total of 46 leopards were killed in the BMR over this period (Esterhuizen & Norton 1985). This translates to an average of 7.6 leopards killed per year (Esterhuizen & Norton 1985). More recent records suggest that the amount of leopards killed due to the retaliatory response of farmers is on the decrease. Only four leopards were legally killed in the BMR from 2004 to 2007 (G. Ferreira, DEDEA, pers. comm.). There is thus a substantial decrease from 7.6 leopards per year from 1952 – 1977, to 1.3 leopards per year from 2004 - 2007. However, these figures are likely to be underestimates of the actual leopard mortalities in the BMR. This is because not all leopard kills are reported to the authorities (Martins & Martins 2006). Therefore, the actual number of leopard killed in the BMR and the affect of this on the leopard population cannot be determined. Thus, the possibility still exists that the retaliatory killing of leopards in the BMR can lead to the local extinction of these carnivores, as was the case for many carnivores worldwide (Woodroffe et al. 2005). 1.6 Rationale and objectives The future conservation of carnivore populations depends partially on the understanding of human-predator interactions (Woodroffe 2000). Thus, in order to facilitate carnivore conservation, the major factors that influence carnivore-stock conflict needs to be investigated. This study addresses three broad categories that influence leopard-stock farmer conflict in the Baviaanskloof Mega-Reserve, Eastern Cape, South Africa. Firstly, the ecological factors (Chapter 3) contributing to leopard-livestock interactions are assed. Here, I describe habitat selection of leopards based on livestock losses attributed to leopards, I 9
determine if leopard predation on livestock is focused in areas that border the Baviaanskloof Nature Reserve (BNR), and then I compare the livestock losses attributed to various causes of livestock mortality and assess the effects leopards have on these predators. Secondly, the socio-economic factors (Chapter 4) that influence leopard-stock farmer conflict are examined. Here, I asses the attitudes of farmers towards leopards and the factors influencing these attitudes, and I also assess the effectiveness of the livestock management techniques and predator control strategies employed by farmers in the BMR. Finally, a prey-density based model is used to estimate the potential leopard abundance and density in the Baviaanskloof Nature Reserve (Chapter 5). This information will contribute to reducing leopard-stockfarmer conflict through the drafting and implementation of appropriate management strategies derived from this study.
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Chapter 2: The Baviaanskloof Mega-Reserve The study area is centred around the Baviaanskloof and Kouga Mountains in the Eastern Cape, South Africa, an area that supports a population of leopards. The planning domain of the Baviaanskloof Mega-Reserve (BMR, Boshoff et al. 2008) was used as the study site for this study, as it includes both conservation and non-conservation areas. The BMR has had a long history of leopard-stock farmer conflict and is also the focus for a major conservation initiative, the BMR Project (Boshoff et al. 2001). 2.1 Baviaanskloof Mega-Reserve (BMR) The three major goals of the BMR Project are to (1) conserve the biodiversity of the area, (2) protect its role as a catchment area and a provider of fresh water, and (3) promote sustainable economic development in the Planning Domain (Boshoff 2008). The BMR Planning Domain incorporates the Baviaanskloof Nature Reserve (BNR), Groendal Nature Reserve (GNR), Formosa Nature Reserve (FNR), their sub-sections, and the farming areas bordering these reserves (Figure 2.1; Boshoff 2008). The study area is dictated by the BMR Planning Domain, and incorporates all the farming communities that fall within this planning domain. These farming communities include the areas in and around Willowmore, Steytlerville, Baviaanskloof, Cockscomb, and Kareedouw. The various farming communities in relation to the BNR and the Planning Domain of the BMR are shown in Figure 2.1. The conservation area is bordered predominantly by livestock farmers (northern border of the Baviaanskloof Nature Reserve and the Kareedouw area, south of the Cockscomb section) with other landuse types including irrigated crops (between the Cockscomb and Stinkhoutberg sections and south of the Kouga section), contracted conservancies and private nature reserves (scattered throughout the planning domain; Boshoff 2008). The dominant landuse in these areas is small stock farming and to a lesser extent, cattle farming. 2.2 Baviaanskloof Nature Reserve The Baviaanskloof Nature Reserve (BNR) is managed by the Eastern Cape Parks Board (ECPB) as a protected area. It was proclaimed a World Heritage Site in 2004 because of the significant ecological processes and biodiversity, and threatened species (Boshoff 2008). The BNR forms the core of the BMR and is situated in the western part of the Eastern Cape Province (Figure 2.1) and spans 199 477 ha (Boshoff 2008). It consists of three sections and 11
one sub-section: (1) the Western section (78 274 ha) which forms the northern and western boundaries of the reserve, (2) the Kouga section (39 113 ha) to the south of the reserve, (3) the Cockscomb section (72 617 ha) which makes up the eastern portion of the reserve, and (4) the Welbedacht sub-section (9 473 ha) situated north-west of the western section (Boshoff 2008). The BNR falls within a large protected area network (Baviaanskloof Reserve Cluster – BRC) which includes the Groendal Nature Reserve (43 428 ha) and the Formosa Nature Reserve (25 324 ha; Figure 2.1).
Indian Ocean
Figure 2.1: The location of the Baviaanskloof Mega-Reserve Planning Domain including the Baviaanskloof Nature Reserve, Groendal Nature Reserve, Formosa Nature Reserve, their individual sub-sections, and the planning domain in relation to the surrounding towns and South Africa. 2.3 Climate The BNR is situated in an area that receives rain throughout the year (Buckle 1989), with the driest period occurring from December to February (Teague et al. 1989). The rainfall ranges from 500 to 700 mm per year in the east and the west receives approximately 300 m per year (Teague et al. 1989). There is a marked longitudinal difference in the rainfall, with the Kouga
12
Mountains to the south receiving an average of 547 mm per year and the Baviaanskloof Mountains to the north receiving an average of 451 mm per year (Buckle 1989). The area is characterised by warm summers (maximum temperatures can reach 45°C) and relatively mild winters (temperatures range from 5°C to 31°C; Buckle 1989), with average yearly temperatures of 17°C to 18°C whilst the higher areas have temperatures below 13°C (Teague et al. 1989). The mountain peaks are often covered in snow in winter (Buckle 1989) and frosts occur seldom (Teague et al. 1989). 2.4 Geology According to Rust & Illenberger (1989), most of the valley floor of the BNR is covered by fault-fractured quartzite, Bokkeveld shale and Enon conglomerate. The mountainous areas consist of quartzite and shales of the Table Mountain and Witteberg groups (Rust & Illenberger 1989). This gives rise to acidic, nutrient poor soils that are coarse grained, rocky and shallow (Teague et al. 1989). Deeper soils only occur on the valley floor and the plateaus (Rust & Illenberger 1989), and tend to be less rocky with greater clay content (Campbell 1985). 2.5 Vegetation The Baviaanskloof Mega-Reserve (BMR) occurs within the transition zone between the Cape Floristic Region (CFR), and the south-western part of the Maputuland-Pondoland Subtropical Thicket (Boshoff 2005). This transitional area contains examples of seven of the eight South African biomes, which are, Fynbos, Sub-tropical Thicket, Nama Karoo, Succulent Karoo, Grassland, Savanna, and Forest Biomes (Boshoff 2005). Due to the highly diverse topography, soil types and microclimates (Vlok 1989), the BMR has 69 vegetation types (Figure 2.2), which are dominated by fynbos and sub-tropical thicket elements (Boshoff 2005). Of these vegetation types, 31 are endemic to the area and 16 are near endemic (Boshoff 2005). According to Vlok (1989), the major factors that determine the distribution of these vegetation types are soil type, soil fertility, rainfall, and fire. The Fynbos elements are located on the nutrient poor soils of the mountains (Boshoff 2005), with Wet Mountain Fynbos occurring on the moist (rainfall greater than 800 mm p.a.) upper portions of the steep south facing slopes, Mesic Mountain Fynbos on the mid south facing slopes where the rainfall ranges from 400 to 600 mm p.a., Arid Mountain fynbos on the drier (rainfall between 300 and 400 p.a.) north facing slopes, and Grassy Fynbos on the loamy north facing slopes (Vlok 1989). All the Fynbos types are driven by fire regimes, which are a critical ecosystem process for these vegetation types (Boshoff 2005). 13
The Sub-tropical Thicket elements are found on the deeper, more nutrient rich soils of the valley floor and mountain slopes (Boshoff 2005), with Valley Bushveld occurring on the lower mountain slopes, and Spekboomveld higher up (Vlok 1989). The Subtropical Thicket vegetation types are highly diverse. This is because of the transitional nature of the BMR that gives rise to a large number of Sub-tropical Thicket mosaics, which occurs when the thicket forms clumps within the other vegetation such as Fynbos and Succulent Karoo (Boshoff 2005). The rest of the vegetation types are made up of Nama Karoo and Succulent Karoo elements, which occur on the relatively low rainfall areas to the north and west of the BNR (Steytlerville area), Grassland elements on the foothills, Savanna elements on the alluvial soils of the river floodplains, and Forest elements in riverine areas and sheltered ravines (Vlok 1989).
14
Figure 2.2: Vegetation types occurring within the Baviaanskloof Mega-Reserve Planning Domain. The reserve cluster is indicated by the solid black lines. See http://www.wildernessfoundation.org.za for detailed information. 15
Chapter 3: Ecological correlates of leopard-stock interactions in the Baviaanskloof Mega-Reserve
3.1 Introduction Large predators in South Africa are generally confined to protected areas. However, these areas are seldom large enough to sustain a viable population of wide-ranging predators (Brashares et al. 2001), especially leopards. Leopards have large home ranges that vary from 14.8 km2 (Bailey 1993) to 1370 km2 (Bothma et al. 1997), depending on habitat type and prey availability. For this reason, the bulk (estimated at 87%) of the leopard population in South Africa occurs on privately owned land (Martin & de Meulenaer 1988), where there are proportionately higher densities of domestic ungulates compared to wild ungulates (Mishra 1997). This leads to stock losses, and ultimately results in economic losses to farmers. Farmers in turn attempt to prevent these losses by the retaliatory killing of predators. According to Woodroffe & Ginsberg (1998) this conflict with humans is the leading cause in the decline of carnivore numbers, worldwide. This is also the case for leopards in the Western Cape (Martins & Martins 2006), and probably for the Baviaanskloof leopards as well. The leopard populations of the Cape region have suffered a substantial range retraction, and now persist in the mountainous areas of the Western (Martins & Martins 2006) and Eastern Cape (Skinner & Chimimba 2005). In order for conservation of predators on private lands to be effective, this human-carnivore conflict needs to be resolved and the number of carnivores killed on private lands needs to be minimized (Woodroffe 2001). Several studies have indicated that carnivore-stock conflict is influenced by habitat characteristics such as scrub and woodland cover and topographical features, and prey abundance (lynx predation on livestock, Stahl et al. 2002). Thus, it can be expected that leopard-livestock conflict in the BMR will also be affected by these factors. Therefore, certain properties will have relatively more livestock losses attributed to leopards due to habitat selection and the availability of prey. However, leopards are not the sole depredators of livestock on private lands. Most of the large African predators kill livestock (lion, Patterson et al. 2004; hyaena, Ogada et al. 2003; cheetah, Marker 2002; African wild dogs, Woodroffe et al. 2005), and this behaviour has also been documented in meso-predators (black-backed jackal, Canis mesomelas, Kaunda & Skinner 2003; caracal, Caracal caracal, Melville et al. 2004). Therefore, it is important to assess the extent of leopard predation on livestock and the importance thereof relative to other carnivores. 16
The development of a strategy that maintains leopard populations and their habitats outside protected areas is required. In order for such a conservation strategy to be developed, the factors that play a role in leopard-stock interactions need to be understood. Stock losses attributed to leopards and other carnivores are believed to be high in the areas surrounding the Baviaanskloof Nature Reserve (Boshoff et al. 2008). There are no studies that have quantified stock losses to predators in this area, or the factors involved in livestock depredation. Here the biological factors that contribute to leopard-stock interactions were investigated by gathering information on the distribution and extent of them, via landowner surveys. The habitat selection of leopards in terms of stock losses was examined. This also incorporated a comparison of leopard-stock losses between properties that border the reserve and those that do not. The characteristics of these leopard-stock incidents as well as the authorities involved in the management of these incidents are also described. The stock losses attributed to leopard was compared with those attributed to other carnivores and the effects leopards have on the amount of stock taken by other predators was also investigated. 3.2 Methods 3.2.1 Subjects Through introducing the project via quarterly farmers’ association meetings in the study area, the farmers were familiarised with the project and subjects were recruited for the survey. These farmers’ associations were selected based on their proximity to the BMR. Only the areas that fall within the BMR Planning Domain (Figure 2.1) were sampled, although some farms extended beyond the planning domain. These included the farms in the Baviaanskloof, Cockscomb, Willowmore, Steytlerville and Kareedouw areas. In each area a representative sample of landowners that border the reserve and those that are located further from the reserve was selected. In addition to these farmers’ association meetings, a general launch event was held in February 2008. The aim of this was to formally introduce the farming communities to the project, its supporters and funders. In certain areas, it was not possible to introduce the project at a farmers’ association meeting. Where this was the case, the chairperson of the respective farmers’ association was contacted and asked if he was willing to provide a list and contact details of farmers in the area. Thereafter farmers were contacted telephonically and meetings were set up with individual landowners. The subjects (n = 73) used in the analysis were considered to be a representative sample of the population of farmers occurring in the BMR planning domain. The locations of the participants are shown in Figure 3.1. The dominant landuse in the Hankey area is Citrus farming and a large 17
proportion of the properties on the southern border of the BMR (Joubertinia area) are irrigated croplands, hence of limited relevance to this study. 3.2.2 Survey Instrument Interviews were used to gather information regarding the various aspects of carnivore-stock conflict. These interviews were conducted between October 2007 and November 2008, using a structured questionnaire type approach. Details of the questionnaire are shown in Appendix I. The initial draft questionnaire was tested on five farmers from different areas within the study area, and they were asked to comment on the design and the questions asked. These comments were used to revise the questionnaire. The questionnaires were designed to address two broad issues that play a role in carnivore-stock interactions, namely: ecological and socio-economic correlates of such interactions. In this chapter, I will only be focusing on ecological aspects of carnivore-stock conflict. The socio-economic aspects will be addressed in Chapter 4. Information regarding the ecological factors of carnivore-stock interactions was divided into the following two sections: i. Predators of livestock This section focused on the identification of various livestock predators, the amount of livestock taken by each predator (number and percentage), and the change in patterns of stock losses attributed to these predators for the last decade. The study area’s most prevalent livestock predators, according to the pilot study, were incorporated into this section. These included black-backed jackals, caracals, leopards, black eagles (Aquila verreauxii), stray dogs (Canis familiaris) and baboons (Papio cyanocephalus ursinus). Two other categories, “Unknown” and “Other” were included. The “Unknown” category included information where livestock carcasses could not be found, or the predator responsible for killing it could not be identified. Here, stock losses due to stock theft and natural mortality are also included. The “Other” category allowed for the inclusion of livestock predators that were not mentioned in the questionnaire. Data on the amount of stock taken or percentage stock loss and the change in pattern of stock losses over the last ten years for each predator was collected. Birds of prey, such as black eagles, martial eagles (Polemaetus bellicosus), and corvids (crows and ravens) were grouped together in a single “Birds” category due to the lack of accurate identification by the respondents.
18
Figure 3.1: The farm boundaries of the participants in the survey (n = 73) in relation to the Baviaanskloof Nature Reserve and surrounding towns. Farmers were also asked to identify, on a map, the areas where they lose livestock to leopards. This information was then mapped into a GIS using ArcGIS version 9.2 (ESRI 2006) in order to determine spatial information such as the distribution of leopard predation and possible habitat selection by leopards. This layer was then overlaid onto a Mammal Habitat Class (MHC) layer. MHCs were used as the spatial units, which were obtained from the Sub-tropical Thicket Ecosystem Planning (STEP) project (Vlok & Euston-Brown 2002; Cowling & Heijnis 2001). Habitat selection was determined by comparing the proportional frequency of available area for each MHC with the frequency of occurrence of leopard-stock interactions of each MHC. MHCs were considered selected for when the frequency of use was greater than the proportional area of available habitat, whereas MHCs were avoided when the frequency of use was smaller than the frequency of available habitat. MHCs that were used in proportion to availability were not selected (Neu et al. 1974). ii. Leopard-stock incidents This section specifically focuses on collecting information on leopard-stock incidents and various aspects thereof, as well as the occurrence of leopard signs and tracks on
19
farmlands. Information regarding leopard depredation events such as time of day and season of occurrence, as well as the characteristics of reporting of leopard-stock incidents was collected. The characteristics of reporting include information on the authority involved, type of action taken and effectiveness thereof. 3.2.3 Statistical Analysis Both qualitative and quantitative information was collected via the questionnaires. All variables measured were shown to be distributed non-normally by the Shapiro-Wilk test (Zar 1996), and had unequal variances according to the Levene’s test (Zar 1996). In the case of the quantitative data, an arcsine transformation did not improve on normality. Non-parametric statistical techniques were thus applied (Zar 1996). Quantitative data included percentage stock lost to the various livestock predators and the comparison of leopard-stock losses between farms bordering the BNR and those that did not. Stock losses were compared between predators using a Kruskal-Wallice ANOVA on ranks and a post-hoc Tukey-type test for multiple comparisons. In order to determine if leopards take more stock on farms bordering the Baviaanskloof Nature Reserve compared to those that do not, a comparison of leopard-stock losses between farm locations was made by employing a Mann-Witney U test. For these data sets, respondents were asked to provide an average for the last three years of farming. However, if a range was given (for example, 20 to 30% stock lost to leopards), the arithmetic mean was taken. Stock losses were calculated as the percentage of the total stock number, including all breeds of livestock and not the percentage loss of offspring. Qualitative data consisted of categorical variables (for example, the pattern of stock losses is increasing, decreasing or remains constant), which were analysed using a Pearson’s chi-squared test. Here, log-linear analysis was used to analyse habitat selection and contingency tables were employed for the analysis of categorical variables. The Yates correction factor was used for small degrees of freedom (Zar 1996). Spearman’s rank correlation was also used to determine the relationship between the frequency of seeing leopard signs and tracks, and leopard-stock interactions. All data were analysed using STATISTICA version 8.0 (StatSoft 2007). 3.3 Results A total of 73 farmers provided data for this survey. Respondents managed a total of 267 678 ha. Of these, 34 respondents bordered the Baviaanskloof Nature Reserve while 39 did not.
20
3.3.1 Predator Comparison Most respondents reported that they had stock losses attributed to caracals (91.8% of respondents), followed by black-backed jackals (74.0%) and unknown losses (68.5%, Table 3.1). Only 32.9% of respondents reported a leopard problem. Of the predators assessed, 68.5% of the respondents agreed that the black-backed jackal problem is on the increase (χ2 = 31.4, p = 0.00), trends in all the other predator problems were consistent over time (Table 3.1). Even though most respondents reported caracal, black-backed jackal, and bird problems (Table 3.1), this was not the case when comparing the amount of stock taken by the various predators (Figure 3.2). On average, farmers reported that they lose 12.6% of their livestock per annum. Of the total amount of livestock losses, black-backed jackals were reported to take on average 4.7%, followed by caracal (2.5%) and unknown losses (1.7%). The amount of stock taken by leopards (0.7%) was significantly lower than that of blackbacked jackals (Z = 5.6, p = 0), caracal (Z = 6.16, p = 0), and unknown losses (Z = 3.9, p = 0.006). Stock losses attributed to leopards did not significantly differ from those attributed to birds (Z = 2.78, p = 0.299), baboons (Z = 0.48, p = 0.006), stray dogs (Z = 1.91, p = 0.006), bushpigs (Potamochoerus larvatus; Z = 2.48, p = 1.000), Cape foxes (Vulpes chama; Z = 2.74, p = 0.339), African wild cats (Z = 3.01, p = 0.145), or mongooses (Herpestidae; Z = 3.13, p = 0.097).
21
Table 3.1: Responses of land managers regarding predators of livestock and the change in predation rates over time in the BMR (n = 73). Percentage of Stock loss pattern Variable Response respondents (n) for the last decade Yes
91.8 (67)
Consistent
Black-backed jackals Yes
74.0 (54)
Increase
Unknown
Yes
68.5 (50)
Consistent
Birds
Yes
58.9 (43)
Consistent
Leopards
Yes
32.9 (24)
Consistent
Baboons
Yes
27.4 (20)
Consistent
Stray dogs
Yes
15.1 (11)
Consistent
Bushpigs
Yes
8.2 (6)
Consistent
Cape foxes
Yes
5.5 (4)
Consistent
African wild cats
Yes
2.7 (2)
Consistent
Mongooses
Yes
1.4 (1)
Consistent
6 5 4 3 2 1 Mongooses
African wild cats
Silver jackals
Bushpigs
Stray dogs
Leopards
Baboons
Birds
Unknown
Caracals
0 Black-backed jackals
Average stock loss (% / year)
Caracals
Causes of stock loss Figure 3.2: Comparison of perceived stock losses (percentage of stock) to various predators of livestock in the BMR. Birds include raptors and corvids. 22
3.3.2 Leopards Only 32.9% of respondents (Table 3.1) attributed stock losses to leopards. These respondents were asked to comment on the temporal and seasonal characteristics of leopard depredation events (Table 3.2). Nearly half (45.5%) of respondents, with stock losses attributed to leopards, believe that these incidents occur at night. Most respondents (37.0%) did not know in which season leopards killed the most livestock. However, 30% of respondents believed that most of the leopard attacks occurred in winter. Yet, there was no statistical difference in reported leopard-stock losses between seasons (χ2 = 10.96, p = 0.25). Of the 24 respondents who had stock losses due to leopards, only 10 reported these stock losses, most of who reported to the Department of Economic Development and Environmental Affairs (DEDEA; Table 3.3). However, the majority (58.3%) of respondents experiencing leopard-stock losses did not report these incidents. Eighty percent of those respondents who reported stock losses believed that action was taken by DEDEA. This was in the form of supplying cagetraps for the live capture of leopards, which were then either collared with GPS-collars and released back onto the farm or translocated to other reserves. Respondents could not agree on the effectiveness of the issuing of permits to hunt leopards or setting of cage traps to capture leopards in reducing leopard-stock losses (χ2 = 0.4, p = 0.94). However, 60% of the respondents believe that these actions were either moderately effective or very effective in reducing leopard-stock losses. Leopards took significantly more stock on farms that bordered the BNR (1.2% livestock per year) compared to farms that did not (0.3% livestock per year; U = 414; p = 0.006, Figure 3.3). The areas with leopard-stock interactions are indicated in Figure 3.3. The presence of leopard tracks and signs was strongly related to stock lost to leopards, with a higher frequency of reported leopard problems on farms that reported leopard signs. Only two farmers had leopard problems, but were not aware of any signs or tracks. In contrast, nine farmers reported no stock lost to leopards, but were aware of signs of leopards on their farms. There was no correlation between the frequency of tracks or signs of leopards and the percentage stock lost to leopards (R = 0.14, df = 30, p = 0.52).
23
Table 3.2: Temporal and seasonal characteristics of leopard-stock incidents as reported by land managers in the BMR (Only incorporates land managers that recorded stock losses due to leopards; n = 24). Percentage of each Variable Time
of
day
when
leopard-
stock incidents take place
Response
respondents (count) χ2
Dawn
21.2 (7)
Day
9.1 (3)
Dusk
15.2 (5)
Night
45.5 (15)
Don't know
9.1 (3)
Season
when Spring
14.8 (4)
the
most Summer
18.5 (5)
leopard-stock incidents place
Winter
take Autumn Don't know
29.6 (8)
p
15.030 0.005
10.960 0.250
0.0 (0) 37.0 (10)
There was a significant difference (χ2 = 38.2, p = 0.01 df = 22) between the use and availability of habitat across individual MHCs (Figure 3.4). Seven of the MHCs were preferred. The preferred MHCs had relative frequencies of occurrence ranging from 16.8 for Groot Valley Thicket to 0.4 for Oudtshoorn Broken Veld. Most MHCs (12) had fewer reported leopard-stock losses than predicted by their relative area, and had relative frequencies ranging from -13.7 for Central Valley Thicket with Succulent Karroo to -0.2 for Kromme Fynbos / Renosterveld mosaic and Zuurberg Grassy Fynbos. Of these MHCs, eight had no reported leopard-stock incidents whatsoever. Only three MHCs had leopard-stock losses in proportion to the relative area (relative frequencies close to zero). This included, Steytlerville Broken Veld, Thicket / Valley Thicket with Mountain Karroo, and Kouga Mountain Fynbos.
24
Table 3.3: Characteristics of reporting of leopard-stock incidents by land managers in the BMR (Only incorporates land managers that recorded stock losses due to leopards; n = 24). Percentage of each Variable Report leopardstock incidents
Response
respondents (n)
Always
25.0 (6)
Occasionally 16.7 (4) Never
58.3 (14)
DEDEA a
70.0 (7)
NGO’s
20.0 (2)
Other
10.0 (1)
No one
0.0 (0)
Yes
80.0 (8)
No
20.0 (2)
Don’t know
0.0 (0)
Permit b
40.0 (4)
Cage traps
40.0 (4)
None
20.0 (2)
Very
30.0 (3)
Was the action
Moderate
30.0 (3)
taken effective? ‡
Not
20.0 (2)
Don’t know
20.0 (2)
Agency leopardstock incidents reported to ‡ Was action taken by the agency? ‡ What type of action was taken? ‡
χ2
p
7.000
0.030
11.600 0.009
10.410 0.005
3.600
0.308
0.400
0.940
‡ Only incorporates responses of farmers who report leopard-stock incidents (n = 10); a = Department of Economic Development and Environmental Affairs; b = leopard can only be hunted when issued with a permit
25
-
Figure 3.3: The locations of leopard-stock interactions as reported by landowners in the BMR. Table 3.4: The effects of the presence of leopards-stock interactions on stock losses caused by other predators in the BMR (n = 73). Percentage of each response (count) Leopard
No
problem
problem
χ2
p
Black-backed jackals 17.8 (13)
56.2 (41)
15.5
0.0
Caracals
31.5 (23)
60.3 (44)
6.0
0.0
Stray dogs
8.2 (6)
6.8 (5)
0.0
1.0
Baboons
13.7 (10)
13.7 (10)
0.1
0.8
Bushpigs
2.7 (2)
5.5 (4)
0.2
0.7
Cape foxes
2.7 (2)
2.7 (2)
0.3
0.6
African wild cats
0.0 (0)
2.7 (2)
0.5
0.5
Mongooses
0.0 (0)
1.4 (1)
0.0
1.0
Birds
27.4 (20)
31.5 (23)
0.1
0.8
Predator
leopard
26
Kouga Mountain Fynbos
Thicket / Valley Thicket with Mountain Karoo
Steytlerville Broken Veld
Zuurberg Grassy Fynbos
Kromme Fynbos / Renosterveld Mosaic
Uniondale Inland Renosterveld
Sundays Valley Thicket with Grassy Karoo
Groot Spekboomveld
Arid Thicket with Nama Karoo
Gamtoos Spekboomveld
Humansdorp Grassy Fynbos
Valley / Arid Thicket with Renosterveld & Succulent Karoo
Sundays Valley Thicket
Sundays Arid Thicket
Central Valley Thicket with Succulent Karoo
Oudtshoorn Broken Veld
Baviaans Fynbos Thicket
Baviaans Renoster Thicket
Eastern Valley Thicket with Arid Fynbos
Cockscomb Mountain Fynbos
Baviaanskloof Mountain Fynbos
Groot Valley Thicket
Frequency of occurrence/availability
20
15
10
5
0
-5
-10
-15
Mammal Habitat Class
Figure 3.4: Frequency of leopard-stock interactions in relation to the proportional availability of Mammal Habitat Classes (MHC) on the surveyed properties. Preferred MHCs have a positive frequency of occurence, whereas avoided MHCs have a negative frequency of occurences. MHCs with a zero frequency of occurence are used in proportion to availability. 27
Farms that did not report any leopard problems (Table 3.4) had significantly more stock losses attributed to black-backed jackals (χ2 = 15.5, p = 0.0) and caracals (χ2 = 6.0, p = 0.0). There were, however, no significant differences in stock losses due to the other predators between farms with or without reported leopard problems (Table 3.4). 3.4 Discussion This technique proved to be very useful in determining the insights and opinions of land managers regarding stock losses to various predators. However, the technique does have some limitations or shortcomings, which are inherent in these types of data gathering techniques. The information obtained is based on the opinions and experiences of individual land managers (Lawson 1989). It may thus, suffer from certain biases in the amount of stock lost, and predators involved (Lawson 1989). The interpretation of the results and the conclusions reached must be done with these limitations in mind. 3.4.1 Predator comparison Stock losses to the various predators are not uniform in space and time. They also varied a great deal in terms of the predators involved, and the extent of predation by each predator. When comparing the extent of the predator problems (Table 3.1) to the amount of stock taken by each predator (Figure 3.2), inferences can be made regarding the severity of predator problems. For example, 67% of respondents reported stock losses due to caracals followed by black-backed jackals with 54%. One would thus expect the proportion of stock lost to these predators to reflect this ratio. However, this is not the case. Black-backed jackals were reported as causing 37% of livestock losses per annum, compared to the 20% reportedly lost to caracals. In other words, black-backed jackals take proportionately more livestock than caracals, judging from the frequency of individual farms reporting the problem. This was also the case for leopards and baboons, with baboons reportedly taking proportionately more livestock than leopards. All the other predators took livestock in accordance with the extent of the reported depredation problem. Therefore, black-backed jackals target livestock because they kill more livestock than what would be expected. Stock losses to leopards are believed to be high in the areas surrounding the BMR. However, stock losses attributed to leopards are significantly less than those attributed to blackbacked jackals, caracals, and unknown losses. This corresponds with research elsewhere in 28
Africa (Kolowski et al. 2006; Patterson et al. 2004; Ogada et al. 2003), where stock losses attributed to leopards was significantly lower than the stock losses attributed to other carnivores. Irrespective of the relatively small amount of stock lost to leopards, there is still tremendous focus on leopards as predators of livestock. This is because leopards take relatively large amounts of stock in one incident (according to respondents they can kill up to 30 head of sheep) compared to caracal, for example, which take one or two individuals per incident (den Hertog 2008). Leopards are also a protected species and the major predators of livestock (black-backed jackals and caracals) are not. According to the land managers this is very important, as the other predators can be managed via various techniques (see Chapter 4) and leopards cannot (den Hertog 2008). This indicates the importance of the perceptions of land managers (NaughtonTreves 1997) regarding the threat of various predators (see Chapter 4). These perceptions and attitudes have a large influence on the retaliatory killing of carnivores (Bjerke et al. 1999) and consequently carnivore conservation. Therefore, attitudes need to be assessed in order to conserve carnivores on private lands (Woodroffe & Ginsberg 1998; see Chapter 4). Thus, more attention and research should be focussed on the other predators of livestock, especially blackbacked jackal and caracal, which are the dominant causes of livestock mortality in the BMR. 3.4.2 Characteristics of leopard-stock incidents The responses of farmers regarding the seasonal and temporal characteristics of leopard-stock incidents (Table 3.2) as well as the institutions involved in assisting landowners with leopardstock losses vary greatly (Table 3.3). According to the respondents who had perceived stock losses to leopards, most of these leopard-stock incidents occurred at night. This probably reflects the popular beliefs, that leopards are only active at night (Norton & Henley 1987). Indeed this is the case for leopards in most areas (Kalahari Desert, Bothma & Bothma 2006; Kenya, Hamilton 1981). However, Norton & Henley (1987) showed that the leopards in the Cederberg are mostly active during the day, with peak activity in the late morning and late afternoon. This is probably the case for the Baviaanskloof leopards as well. Respondents of this survey believed that most leopard-stock incidents occurred in winter. The land managers in the Stellenbosch and Cederberg areas also believe that most stock losses occur in winter (Norton & Lawson 1985; Norton & Henley 1987). According to Norton & Henley (1987) this is not the case, which probably holds true for the leopards in the BMR because they occur in a similar habitat as the Cederberg leopards. There is, however, currently no information regarding the activity or hunting patterns 29
of leopards in the BMR. Therefore, these perceptions cannot be confirmed or rejected. This indicates that more research needs to be undertaken regarding the spatial ecology of leopards in the BMR. The majority of land managers with leopard-stock interactions did not report these stock losses to any organisation. These respondents apparently believed that these organisations (Table 3.3) could not assist in reducing stock losses to leopards. However, of the farmers that did report perceived stock losses to leopards, most reported these to the Department of Economic Development and Environmental Affairs (DEDEA). The actions taken by DEDEA included the supply of cage traps and permits for the removal of “problem” leopards. Sixty percent of the respondents that experience leopard predation believed these actions to be either very or moderately effective. This leads one to question the attitudes of land managers towards these organisations because if these actions are effective, why do most farmers not make use of these services? According to den Hertog (2008), who studied the power relations between farmers of the BMR and the organisations involved in leopard-stock incidents, there is a lack of trust between the land managers and the various conservation organisations involved. If the level of trust and cooperation between farmers and conservation organisations are not restored, conservation of carnivores will not be a reality (Marshall et al. 2007). 3.4.3 Predator interactions The influence of habitat selection and inter-specific social dominance has been shown to play an important role in the structuring of carnivore communities (Durant 1998). One would thus expect that these interactions are also present in the areas where land managers lose stock to more than one predator. This was, in fact, the case in the BMR. Most notable is the apparent interaction between leopards, the dominant carnivore in the Baviaanskloof Mega-Reserve, and black-backed jackals and caracal (Table 3.4). The presence of leopards on certain properties influenced the reported predation by caracal and black-backed jackal in such a way that there is a perceived reduction in the amount of stock taken by these two predators. This indicates the possibility of interspecific competition between these carnivores, which may result in ecological separation (caracal and leopards in the mountains of the Western Cape, Norton & Henley 1987; cheetah and lions and hyaenas in Namibia, Marker 1998) or avoidance behaviour (black-backed jackals and leopards in the Kruger National Park; Bailey 1993). However, the exact mechanisms are not known. Thus, the data presented here cannot exclude other possibilities such as availability of 30
natural prey and habitat selection by individual carnivores (Karanath et al, 2000), which may contribute to this observed pattern. There is also a possibility that land managers blame most of their stock losses on leopards (den Hertog 2008), thus skewing the results. It is difficult to determine whether this reduction in stock taken by black-backed jackals and caracal is due to behavioural, social and ecological factors or simply just an artefact of the inconsistencies in identifying the predator involved in stock losses. It is clear that leopards prefer certain habitats above others, in terms of reported stock losses (Figure 3.4). This is probably due to the presence of a core leopard population in the BNR, with individual territories extending onto bordering farms (Norton & Henley 1987). Because of the historical conflict between leopards and farmers, leopards are forced to persist in remote areas, away from contact with farmers (Martins & Martins 2006). This selection of habitat is also evident in Figure 3.4, where the majority of the preferred MHCs occur in the mountainous areas adjacent to the BNR (Figure 3.3) and incorporate steep slopes, river courses, and deep gorges. Radio telemetry data for the leopards in the Baviaanskloof Nature Reserve also supports this observation (Rogers 2008). Topographical characteristics, such as these, play an important role in increasing the risk of livestock predation (Stahl et al. 2002) by leopards. A large proportion of preferred MHCs had a thicket component, which provides a large amount of vegetation cover for leopards. This has been shown to influence the habitat suitability for large felids (Palma et al. 1999), and probably plays an important role in habitat selection by leopards in the BMR. Judging from the location of preferred MHCs on individual properties, these areas are often the most remote portions on the individual properties, situated far from human habitation, and have the least amount of human activity, due to the remote and rugged terrain. Stahl et al. (2002) showed that in the French Jura, the proximity to human habitation plays an important role in lynx predation on livestock, with flocks in remote areas being attacked more regularly. This is probably the case for leopards in the BMR as well. There is thus a suite of factors that may influence habitat selection of leopards in terms of stock losses. However, further research is required to determine this. In conclusion, leopards in the BMR are not the largest causes of livestock mortality. Irrespective of this, most attention is still given to leopard-stockfarmer interactions. These interactions are prevalent in the mountainous areas bordering the BNR. Therefore, the Eastern 31
Cape Parks Board (ECPB), as the Managers of the Baviaanskloof Nature Reserve and with a mandate to conserve species such as the leopard, needs to engage with their neighbours to manage what is fundamentally a shared leopard population. In doing so, the level of trust and cooperation between the ECPB and private landowners will be restored. This is the first and most important step for leopard conservation in the BMR.
32
Chapter 4: Socio-economic correlates and management of leopard-stock farmer interactions in the Baviaanskloof Mega-Reserve
4.1 Introduction According to Woodroffe & Ginsberg (1998), human-carnivore conflict is the most important cause of adult carnivore mortality. This causes potent edge effects in the areas surrounding reserves, which ultimately leads to local extinctions of carnivore populations (Woodroffe & Ginsberg 1998). One of the main reasons for human-carnivore conflict is livestock predation by carnivores (Graham et al. 2005). The loss of livestock represents an economic loss to farmers, not only in terms of direct losses of livestock but also in terms of the increased costs and work effort in adapting farming methods (Sekhar 1999; Kaczensky et al. 2004). Studies documenting the economic value of livestock lost to carnivores are few. However, the resultant economic losses are large enough to make livestock farming adjacent to nature reserve unprofitable. These losses and the lack of involvement of governmental institutions (e.g. compensation schemes, predator management, education, etc.) leave farmers with no other alternative except retaliatory killing of the carnivores (Graham et al. 2005; Mishra 1997). Thus, effective conservation of carnivores requires the resolution of carnivore-stock farmer conflict (Woodroffe et al. 2005). In order to resolve the conflict between farmers and carnivores, the socio-economic factors that influence the attitudes of farmers towards carnivores need to be addressed. One of the major contributing factors is the economic loss endured by livestock farmers, which often results in negative attitudes towards carnivores (Breitenmoser 1998). This has severe consequences in terms of conservation of carnivores within reserves and on privately owned lands (Woodroffe & Ginsberg 1998). The attitudes of land managers towards carnivores and conservation in general vary according to the local socio-economic environment. Several studies (Naughton-Treves et al. 2003; Kaczenskey et al. 2004) on attitudes towards carnivores have shown that variables such as age, gender, education, income, living on a farm, proximity to reserve, religious and cultural factors influence the perceptions and attitudes of land managers to carnivores. Here, the various socio-economic factors that influence the attitudes of farmers in the BMR towards leopards were assessed. The two broad hypothesis tested are that the attitudes of farmers towards leopards are influenced by perceived stock losses, and that the attitudes of 33
farmers are influenced by tourism activities as the leopard may provide an alternate source of income to the farmer. The effectiveness of various livestock management techniques and predator control strategies employed by livestock farmers in the BMR was also assessed. 4.2 Methods 4.2.1 Surveys Instrument Data were collected during the survey of landowners reported in Chapter 3. In addition to questions related to the ecological correlates of carnivore-stock conflict discussed in Chapter 3, respondents were also asked to supply socio-economic information. Information regarding the socio-economic aspects of carnivore-stock interactions was divided into the following five sections (see Appendix 1): i. Personal information This section focused on the socio-demographic characteristics of the respondents. These variables were divided into categories to ease analysis, and included information on property size (small < 1 000 ha; medium 1 001 – 5 000 ha; large > 5 000 ha), the number of years respondents have been farming their properties (experience: low < 6 years; medium 6 – 15 years; high >15), and whether they reside on the farm or in a nearby town (residence). ii. Farming type This section focused on the characteristics of the livestock owned by the respondents, and included information such as the total number of livestock owned, the number of types of livestock (breeds) owned (diversity of livestock: low < 3; medium 3 – 5; high > 5), and the dominant type of livestock owned (dominant livestock). iii. Management of livestock Management of livestock incorporates the stock management strategies used by the farmers to curb stock losses. This section included a set of specific questions addressing the various livestock management techniques such as kraaling stock at night, lambing/kidding in protected areas, use of Anatolian dogs, use of shepherds, use of electric fencing, etc. These questions were very specific (e.g. “Do you have electric fences?” or “When do most leopardstock incidents occur?”), and provided several options from which respondents could select their response. The responses to these questions were assigned numerical values to allow for statistical 34
analysis. This section also incorporated an open-ended question, e.g. “Have you adapted your farming methods due to predation risk?”. The responses to this question where grouped into similar classes e.g. 1 = responses related to lambs/kids, 2 = responses related to ewes, and 3 = responses related to safer lambing areas etc., which facilitated statistical analysis. iv. Predator control strategies This section focused on the various predator control strategies used by respondents in order to reduce livestock predation by carnivores. The techniques used are hunting of predators, cage traps, gin traps, hunting dogs, poison baits/lures, protective collars, and poison collars. Respondents were asked to rate the effectiveness of each technique used (three classes: very effective, moderately affective, or not effective). They were also asked to provide information on frequency of use (Are the predator control techniques used as preventative measures or only when livestock is killed?), and how many leopards were killed per year by each method. v. Attitudes towards leopards Here, the attitudes of respondent towards leopards (“Do you enjoy seeing leopards on your farm?”) were measured as well as the tourism (“Are leopards of value in a tourism operation?”) and ecological significance (“Do leopards control the population size of other “problem species”?”) of leopards to farmers. Finally, respondents were asked if they had any tourism initiatives on their properties. 4.2.2 Statistical analysis All variables measured were shown to be distributed non-normally by the Shapiro-Wilk test, and had unequal variances according to the Levene’s test. In the case of the quantitative data, an arcsine transformation did not improve on normality. Non-parametric statistical techniques were thus applied (Zar 1996). Quantitative data included percentage livestock lost to the various causes of livestock mortality. This was compared to livestock management techniques and predator control strategies in order to assess the effectiveness thereof. This was done via a Mann-Whitney U test when only two categories where compared (e.g. comparing stock losses between respondents staying on the farm and those that reside in town), and a Kruskal-Wallace ANOVA on ranks and a post-hoc Tukey-type test for multiple comparisons. The Z-adjusted p-level was used in cases where the categorical N < 20 (Zar 1996). 35
The attitudes of respondents towards leopards were compared to various variables. These included: the socio-demographic attributes of respondents, the characteristics of their livestock, tourism initiatives, the tourism and ecological usefulness of leopards to farmers, whether farmers would rather farm or practice eco-tourism, and the total stock losses and stock losses attributed to leopards. This was analysed by employing a Pearson’s chi-squared test statistic. Here, log-linear analysis was used to analyse these categorical variables. The Yates correction factor was used for small degrees of freedom (Zar 1996). 4.3 Results 4.3.1 Management of livestock The management technique most widely used by the respondents was lambing in safer areas (70%, Figure 4.1). This was followed by the retraction of all livestock from areas bordering the BNR (23%), kraaling livestock at night and using shepherds (18%), improvement of border fences (15%), using electric fences (13.7%), and finally the use of Anatolian shepherd dogs (11%). A total of 17 respondents removed their livestock from the areas bordering the BNR. The lesser used techniques included changing livestock type (10%), managing nonbreeding adults in areas bordering the BNR (8%), rotation of livestock (7%), restore natural prey of predators (7%), ram permanently with the ewes (4%), farmer spends more time in the veld (4%), lambs checked every day (4%), reduce stock number (1%), reduce flock number (1%), change lambing season (1%), and use smaller camps (1%).
36
Percentage of respondents
80 70 60 50 40 30 20 10 0
Livestock management techniques Figure 4.1: The dominant livestock management techniques used by respondents to reduce livestock predation by carnivores. Livestock management techniques were compared to the various causes of livestock mortality (Table 4.1). Most management responses had no clear relationship with the causes of livestock mortality. The retraction of livestock (Figure 4.2) from the areas bordering the reserve was significantly related to leopard predation (Table 4.1). Stray dog predation had a significant relationship with kraaling livestock at night (Table 4.1). Employing shepherds was significantly related to Cape fox (Vulpes chama) predation, and mongoose predation (Table 4.1). All of the management techniques that had a significant relationship with the causes of livestock mortality were used in response to high predation levels. Thus, none of these techniques was effective in reducing livestock predation by carnivores.
37
Table 4.1: The effectiveness of livestock management techniques used to reduce livestock predation. Management responses
Causes of livestock
Safe lambing
Anatolian
Retraction
Improved
mortality
area a
dogs a
of stock a
fences a
Black-backed
Kraaling stock at night
Shepherd b
b
Electric fence b
440.50 ns
214.00 ns
424.50 ns
226.00 ns
3.58 ns
3.91 ns
1.84 ns
Caracals
492.00 ns
258.00 ns
415.00 ns
338.50 ns
3.88 ns
0.92 ns
0.50 ns
Leopards
471.50 ns
226.00 ns
286.50*
274.00 ns
3.96 ns
1.19 ns
0.91 ns
Stray dogs
440.00 ns
190.50 ns
456.00 ns
293.50 ns
8.04 *
2.46 ns
0.32 ns
Baboons
548.00 ns
231.00 ns
382.00 ns
319.00 ns
4.32 ns
3.56 ns
4.21 ns
Unknown
494.50 ns
192.50 ns
368.00 ns
307.50 ns
4.84 ns
1.04 ns
1.51 ns
Bushpigs
531.00 ns
176.00 ns
425.00 ns
308.00 ns
1.40 ns
0.62 ns
0.18 ns
Cape foxes
531.00 ns
244.00 ns
400.00 ns
255.00 ns
0.90 ns
11.94 **
0.63 ns
546.50 ns
252.00 ns
459.00 ns
315.50 ns
0.44 ns
5.99 ns
0.32 ns
Mongooses
550.00 ns
256.00 ns
467.50 ns
335.50 ns
0.22 ns
8.12 *
0.16 ns
Birds
483.50 ns
219.50 ns
336.50 ns
324.50 ns
1.78 ns
0.56 ns
3.00 ns
All
471.50 ns
245.50 ns
359.00 ns
269.00 ns
0.79 ns
3.44 ns
2.38 ns
jackals
African wild cats
a = Mann-Whitney U test statistic, b = Kruskal-Wallace ANOVA H test statistic. ** Significant at the p < 0.01 level, * Significant at the p < 0.05 level, ns = not significant.
38
Figure 4.2: Areas where farmers have withdrawn their livestock due to leopard predation. 4.3.2 Predator control strategies The most frequently used (24.6%) predator control strategy was hunting of carnivores (Figure 4.3). This is followed by cage traps (20.2%), gin traps (18.7%), hunting dogs (15.8%), poison bait (9%), protective livestock collars (7%), and poison livestock collars (1%). Three percent of respondents did not practice any predator control strategies at all. Of the respondents (n = 6) who did not use any predator control techniques, only one respondent had zero stock losses, three respondents had 4% stock losses and the other two had 49% and 23% total stock losses, respectively.
39
Percentage of respondents
25 20 15 10 5 0
Predator control strategy Figure 4.3: Percentage of respondents that use specific predator control strategies. The predator control techniques were compared to the various causes of livestock mortality in isolation (Table 4.2). Most predator control strategies had no clear relationship with the causes of livestock mortality. Livestock losses attributed to black-backed jackals were significantly affected by hunting (Table 4.2), gin traps (Table 4.2), and poison bait (Table 4.2). Predation by birds had a significant relationship with the use of cage traps (Table 4.2). Total livestock losses were affected by hunting (Table 4.2), cage traps (Table 4.2), gin traps (Table 4.2), and poison baits (Table 4.2). Once again, all the management techniques that had a significant relationship with the causes of livestock mortality were used in response to high predation levels. Thus, none of these techniques was apparently effective in reducing livestock predation by carnivores. Respondents had varied opinions regarding the effectiveness of these predator control strategies. According to the respondents, only hunting was found to be a significantly effective method in controlling or reducing carnivore predation (χ2 = 10.08, p = 0.006). Sixty-six percent (66%) of respondents tend to use these control strategies as preventative measures, whilst 34% of farmers use these methods only when stock is lost. 40
Table 4.2: Results of the statistical analysis of the effectiveness of predator control strategies used to reduce livestock predation. Causes of Predator control strategies livestock
Hunting
Protective
Poison
collar
collar
266.0 **
343.0 ns
16.5 ns
569.0 ns
408.0 ns
434.5 ns
50.0 ns
563.0 ns
560.0 ns
462.0 ns
413.0 ns
47.0 ns
588.0 ns
653.5 ns
605.5 ns
509.5 ns
424.5 ns
46.0 ns
535.0 ns
554.5 ns
566.5 ns
589.5 ns
476.5 ns
406.0 ns
51.0 ns
Unknown
522.0 ns
500.0 ns
585.0 ns
637.5 ns
484.0 ns
362.0 ns
67.0 ns
Bushpig
542.0 ns
632.0 ns
666.0 ns
561.0 ns
498.0 ns
408.0 ns
65.0 ns
Cape fox
529.0 ns
628.0 ns
664.0 ns
605.0 ns
475.0 ns
391.0 ns
67.0 ns
561.5 ns
651.5 ns
630.0 ns
609.0 ns
494.0 ns
420.0 ns
69.0 ns
Mongoose
563.5 ns
635.5 ns
647.5 ns
630.0 ns
503.5 ns
427.5 ns
70.0 ns
Birds
534.0 ns
407.0 **
551.5 ns
519.5 ns
402.0 ns
421.5 ns
28.0 ns
All
394.0 *
455.0 *
421.0 **
555.5 ns
251.5 **
411.0 ns
33.0 ns
Hunting
Cage trap Gin trap
185.5 **
500.5 ns
295.5 **
632.0 ns
Caracal
508.0 ns
516.5 ns
560.0 ns
Leopard
484.0 ns
500.0 ns
Stray dog
562.0 ns
Baboon
mortality Black-backed jackal
African wild cat
dog
Poison bait
** Significant on the p < 0.01 level, * Significant on the p < 0.05 level, ns = not significant.
41
4.3.3 Attitudes towards leopards The majority (67.2%) of respondents had a negative attitude towards leopards (Table 4.3). Thirty-seven percent of farmers did have some form of tourism initiative on their properties. However, the presence of tourism initiatives did not influence the perceptions of farmers towards leopards (χ2 = 0.70, p = 0.402). When respondents were asked if they would rather farm or run ecotourism operations, a significant proportion (56%) of farmers with negative attitudes towards leopards would rather farm (χ2 = 11.58, p = 0.0007). Seventy-four percent of respondents believed that leopards have a tourism value. However, this did not significantly affect the attitudes of farmers towards leopards (χ2 = 3.83, p = 0.147). Forty-nine percent (49%) of land managers believed that leopards do not influence other carnivore species in terms of interspecific social dominance. This had a significant and a negative effect on the attitudes of the respondents (χ2 = 7.62, p = 0.022). The attitudes of respondents were then compared to total stock losses (Figure 4.4) and stock losses attributed to leopards (Figure 4.5). Forty-nine percent of respondents had a negative attitude towards leopards and high total stock loss. However, the attitudes of farmers towards leopards was not affected by the number of total stock lost (χ2 = 5.87, p = 0.118). The reverse was true when the attitudes of respondents towards leopards were compared to the number of livestock losses attributed to leopards. Forty-nine percent of land managers had a negative attitude towards leopards, but had zero stock lost to leopards in the last three years of farming. This relationship was also not significant (χ2 = 2.99, p = 0.393).
42
Table 4.3: The attitude of respondents towards leopards and the relationship of various response variables with attitudes. Percentage of Relationship with attitude Variable Response respondents (n) towards leopards (χ2) Attitude towards leopards
Tourism initiative on farm
Farm or ecotourism
Leopard tourism potential
Leopards control other predators
Positive
32.8% (24)
Negative
67.2% (49)
Yes
37.0% (27)
No
63.0% (46)
Farm
69.9% (51)
Ecotourism
30.1% (22)
Yes
73.9% (54)
No
24.7% (18)
Don’t know
1.4% (1)
Yes
49.3% (36)
No
30.1% (22)
Don’t know
20.6% (15)
n/a
0.70 ns
11.58 **
3.83 ns
7.62 *
** Significant on the p < 0.01 level, * Significant on the p < 0.05 level, ns = not significant.
43
30 20 10 Negative
0 None
Low
Positive Medium
Attitude
Frequency of occurance
40
High
Total stock losses
40 30 20 10 Negative
0 None
Low
Positive Medium
Attitude
Frequency of occurance
Figure 4.4: The affect of total stock losses on the attitudes of respondents towards leopards.
High
Leopard stock losses
Figure 4.5: The affect of stock losses attributed to leopards on the attitudes of respondents towards leopards. 4.3.4 Socio-demographic composition A total of 73 farmers provided data for this survey. Respondents managed a total of 267 678 ha. The average farm size was 3 667 ha (range 34 – 12 680 ha). Property size did not affect the attitudes of respondents towards leopards (χ2 = 2.83, p = 0.243). Most respondents (89%) had farmed on their current properties for more than five years. The amount of years spent farming on the property (experience) did not significantly affect the attitudes of respondents towards 44
leopards (χ2 = 0.65, p = 0.721). Ninety-three percent (93%) of the respondents resided on their farms, whereas 7% stayed in nearby towns. Place of residence did not significantly affect the attitudes of respondents towards leopards (χ2 = 0.20, p = 0.652). 4.3.5 Characteristics of livestock The number of livestock and game owned ranged from 83 to 11 300 animals (mean = 1 917) and had no significant relationship with the attitudes of respondents towards leopards (χ2 = 0.24, p = 0.889). The majority (95.9%) of respondents’ livestock comprised smallstock (sheep and goats). Respondents owned on average three different breeds of livestock (range 1 – 6), which was dominated by Dorper sheep (41.1% of respondents), Angora goats (21.9%), and wool Merino sheep (17.8%). Diversity of livestock did not significantly affect the attitudes of respondents towards leopards (χ2 = 3.45, p = 0.178). However, the dominant livestock on the property was significantly related to the attitudes of respondents towards leopards (χ2 = 16.43, p = 0.022). Respondents who owned predominantly Dorper sheep had a negative attitude towards leopards. 4.4 Discussion 4.4.1 Socio-demographic composition Socio-demographic variables have been shown to affect the attitudes of farmers towards carnivore conservation (Naughton-Treves et al. 2003). None of the measured socio-demographic variables significantly influenced the attitudes of respondents towards leopards. Therefore, the attitudes of respondents in the BMR towards leopards are affected by other factors. 4.4.2 Characteristics of livestock The attitudes of respondents towards leopards were significantly (p = 0.022) affected by dominant livestock. Respondents who predominantly owned Dorper sheep had a negative attitude towards leopards. This is to be expected, as 41% of the respondents own predominantly Dorper sheep, and 67% of respondents had a negative attitude towards leopards. However, leopards do not cause the largest proportion of sheep mortalities (Chapter 3). Therefore, the negative attitudes towards leopards are driven by other factors, which will be highlighted in the sections that follow.
45
4.4.3 Management of livestock and predator control strategies It was not possible to isolate a single, or even a suite of livestock management techniques that significantly reduced the level of predation by certain carnivores. This is because most techniques are used in combination with other techniques. When these techniques were analysed separately few significant associations emerged. This is because livestock management techniques do not affect stock losses due to predators (Graham et al. 2005). These techniques are positively correlated with net primary production instead (Graham et al. 2005). However, the most important finding was that the majority of respondents with high stock losses attributed to leopards withdraw their livestock from the areas bordering the nature reserve. This translates to 14 367 ha (5.4% of surveyed properties) of privately owned land that is not being farmed (Figure 4.2). The presence of leopards may thus reduce the impacts of livestock on the vegetation and consequently assist in the conservation of biodiversity. These areas have been shown to assist in the conservation of mammals on farmlands (Macdonald et al. 2008). However, a landscape-level approach instead of a farm-level approach is required to address biodiversity conservation on farmlands (Macdonald et al. 2008). There is thus the possibility to incorporate these areas into the Baviaanskloof Nature Reserve in order to provide more habitat for leopards. However, this will not necessarily contribute to biodiversity conservation unless these areas correspond with the critical biodiversity areas identified by the Baviaanskloof Mega-Reserve Conservation Plan (see Boshoff et al. 2008). As was the case with the management techniques for livestock, it was not possible to isolate certain predator control strategies that significantly reduced the level of predation by carnivores. However, when these predator control strategies were analysed separately, several significant associations with the causes of livestock mortality were observed (Table 4.2): blackbacked jackal predation was associated with the use of hunting (p < 0.001), gin traps (p < 0.001), and poison baits (p < 0.001); predation by birds was associated with the use of cage traps (p < 0.001); total stock losses was associated with the use of hunting (p < 0.005), cage traps (p < 0.005), gin traps (p < 0.001), and poison baits (p < 0.001). In all these cases, the predation by the relevant predator was greater when the specific technique was applied. These techniques are thus applied as a response to increased predation by carnivores, with 66% of respondents doing so. According to Graham et al. (2005), this is understandable because an increased predation risk to livestock leads to an increase in protective measures used by farmers. It seems that none of these 46
techniques significantly reduces the amount of livestock lost to predators. Even though farmers have been using these techniques for years, they are not succeeding in reducing predator-stock conflict in Natal (Lawson 1989). This is a classic example of the lack of evidence-based management. Sutherland et al. (2004) found that 77% of management decisions made by conservation officials were based on anecdotal evidence such as common sense, personal experience, and hearsay. There is in all probability, a greater proportion of farmers that manage livestock and predators in this fashion. For this reason, the majority of management techniques are ineffective. It is therefore necessary to use techniques that have been proven to prevent livestock losses rather than “cure” it, as well as education and advice on which techniques to use and how to apply them (Lawson 1989). 4.4.4 Attitudes towards leopards The majority (67%) of respondents had a negative attitude towards leopards. One of the most important factors influencing the perceptions of farmers towards carnivores is the threat carnivores pose to the livelihoods of farmers (Maddox 2003). Even though there was no significant relationship between the attitudes of respondents towards leopards and the total amount of stock lost or the stock losses attributed to leopards, an interesting pattern emerges. Respondents with high total stock losses have negative attitudes towards leopards (Figure 4.4). This is however, in no way affected by leopard predation on livestock, because respondents with zero stock losses to leopards still have a negative attitude towards them (Figure 4.5). The hypothesis that farmers with high levels of leopard predation will have a negative attitude towards leopards is therefore not supported. Thus, it is clear that predation by all carnivores plays a major role in the attitudes of farmers towards carnivores, in this case leopards (attitudes towards wolves, Naughton-Treves et al. 2003). Consequently, one can expect that any land manager, who experiences livestock predation by carnivores, will have negative attitudes towards other carnivores, even those that do not pose a threat to their livestock. This begs the question: Why do farmers have negative attitudes towards carnivores that do not kill livestock? This is because a large proportion of farmers that experience livestock losses to predators do not want any other potentially damage causing predators on their property, and they will take steps to prevent these carnivores from settling on their properties (Marker et al. 2003), as was also the case in Kwa-Zulu Natal (Lawson 1989).
47
In addition to this, the attitudes of farmers are also significantly affected by their choice of occupation. The majority of respondents (70%) would rather farm than run an eco-tourism operation. This was significantly (p < 0.01) related to a negative attitude towards leopards. Here, it was also hypothesized that respondents that have some form of tourism on their properties will have a positive attitude towards leopards. This was not the case, as 63% of respondents did not have any form of tourism on their properties and there was also no significant (p > 0.05) relationship between attitudes towards leopards and tourism initiatives. Thus, the hypothesis is therefore not supported (Figure 4.3). Even though most respondents did not have tourism on their properties and would rather farm, 74% still believed that leopards have an economic value in tourism. However, this was not significantly (p > 0.05) related to the attitudes of the respondents (Figure 4.3). This pattern was also evident when respondents were asked if leopards control other predators. Forty-nine percent of respondents believed that leopards influence the population size of other carnivores. However, this was significantly (p < 0.05) related to negative attitudes towards leopards (Figure 4.3). On the other hand, 30% believed that leopards do not influence other carnivores and 21% did not know if leopards influence other carnivores (Figure 4.3). It appears that the tourism potential of leopards is undervalued by respondents. Although community based conservation and tourism schemes are important to conservation of carnivores on private lands (Thavarajah 2008), it is not the sole solution to leopard-stock farmer conflict in the BMR. The fact that most farmers do not know what ecological role leopards play in the ecosystems and the benefits they provide for livestock farming, indicates the necessity of extensive education programmes in the BMR. However, the most important way to change the attitude of farmers towards carnivores is through financial incentives and compensation schemes (Thavarajah 2008). Even though this will not reduce carnivore-livestock conflict, it will increase the tolerance of farmers towards carnivores (Hemson 2003), and substantially improve their attitudes towards carnivores.
48
Chapter 5: Modelling leopard abundance: What can we learn?
5.1 Introduction Due to the fact that the management and monitoring of biodiversity is notoriously difficult and expensive, shortcuts such as ‘indicator’, ‘umbrella’, ‘keystone’, and ‘flagship’ species are commonly used to achieve biodiversity conservation targets (Simberloff 1998). According to Simberloff (1998) the ‘umbrella’ species (a species that has such a wide range, that the conservation of this species will encompass the conservation of many other species) seems to be the best approach. For this purpose, large carnivores, which can be seen as indicators of species richness (Gavashelishvili & Lukarevskiy 2008), are often employed as surrogates for biodiversity conservation. This is because they may regulate the numbers of their prey and consequently alter the structure and function of ecosystems (Estes et al. 1998; Terborgh et al. 1999). Even in ecosystems where prey abundance is regulated by bottom-up effects, such as rainfall, the interactions of carnivores with their prey play an important role in influencing population dynamics, behaviour, and evolution (Mills 2005). Thus, these intricate relationships between predators, prey, and their environment are undoubtedly linked to the functional component of biodiversity (Mills 2005; Miller et al 2001), and provides the basis for the use of predators as conservation surrogates. Thus, the leopard, which is the largest remaining carnivore in the BMR (Henley 2000), can be employed as a surrogate for biodiversity conservation (Gavashelishvili & Lukarevskiy 2008). Population size estimates are essential for ecological theory and wildlife management (Norton 1986; Smallwood 1997), and should be central to the development of conservation strategies (Smallwood 1999). There is a serious lack of information regarding the distribution and abundance of leopards in the Baviaanskloof Reserve Cluster (BRC), however the population is thought to be small and extremely insecure (Norton 1986; Stuart & Heinecken 1977). This gap in information urgently needs to be addressed in order to assist in leopard conservation (Gros et al. 1996). A lack of information on leopard numbers constrains our ability to understand the factors (e.g. retaliatory killing of leopards) shaping this community. This undermines the effective conservation of these felids. Several methods for the determination of carnivore abundance exist, each with their own advantages and limitations. 49
The first involves relating carnivore density to the density of signs of carnivores such as tracks (mountain lions, Felis concolor, Smallwood & Fitzhugh 1995; lions, Panthera leo, leopards, Panthera pardus, and wild dogs, Lycaon pictus, Stander 1998), and scat. This non-invasive technique does not require direct observations of the focal species. However, the relationship between the density of these signs and the population density is rarely known (Caughley 1977). The second set of techniques involves transect/grid based ground and aerial animal counts. This method generally underestimates densities because of the fact that these carnivores are often well concealed, camouflaged, mostly nocturnal, or occur at very low densities (Mills 1997). Furthermore, the use of aircrafts in aerial censuses can be very expensive. The third method involves mark-and-recapture as the basis for population estimates. This can be accomplished via physically marking individuals and releasing them back into the population, using genetic microsatellites (European badgers, Meles meles, Miller et al. 2005) or by using camera traps where the individuals are distinguished based on unique physical features (tigers, Panthera tigris, Karanath & Nichols 1998). Here, the Lincoln-method is used to estimate the number of individuals in the population. This can be a very useful technique if the assumptions (equal catchability, closed population, and random mixing of marked individuals in the population) are met. Nevertheless, the assumptions are rarely met (Mills 1997). The final set of methods incorporates a modelling process, whereby predator density is determined via the use of certain habitat attributes (tigers, Panthera tigris, Ranganathan et al 2008). This method relies heavily on the possibility of identifying the limiting resources for carnivore species, estimating the abundance and distribution thereof, and relating it to the abundance of the focal carnivore (Karanth et al. 2004). It is, however, notoriously difficult to develop such relationships in practice (Karanth et al. 2004). Several methods for the modelling of predator abundance do exist, including the relation of prey availability to predator density. The reason for this being that predators seem to be limited by prey resources, thus, prey availability is the fundamental determinant of the abundance of predators (Carbone & Gittleman 2002). There have been several studies documenting this relationship between prey biomass and predator biomass or abundance (Karanth & Nichols 1998; Karanth et al. 2004; Carbone & Gittleman 2002; Hayward et al. 2007; Gros et al. 1996; Ranganathan et al. 2008). Most of these studies of spatial distribution and abundance commonly employ either large-scale game counts or meta-analysis of several studies in order to make inferences regarding predator densities. 50
Here, a model is presented that utilises an estimate of potential prey availability, as well as game counts, to determine the potential abundance of leopards in the BRC. Firstly, the relationship between leopards and the available prey was used to estimate the density of leopards that could be supported in the BRC. Secondly, the methods of Boshoff et al. (2001), Hayward et al. (2007), Carbone & Gittleman (2002), and Norton & Henley (1987) was used to determine the density of leopards in the BRC, and these results were compared to the results of the model presented here. Thirdly, the BRC leopard density estimate was compared to the density estimates of other southern African leopard populations. Finally, the limitations, improvements, and conservation applications of the model is highlighted. 5.2 Methods This approach of estimating potential leopard abundance comprised of the estimation of the potential prey abundance based on Boshoff et al. (2001) and direct counts, and then the estimation of leopard abundance based on Hayward et al. (2007). This was undertaken in three steps: (1) determination of the distribution and extent of Mammal Habitat Classes (MHC) within the BRC, (2) determination of potential prey abundance for each MHC, and (3) calculation of potential leopard abundance using a model that predicts potential leopard density as a function of potential prey abundance. 5.2.1 Distribution of mammal habitat classes In order to determine the herbivore distributions and potential abundance in the BRC, MHCs were used as the spatial units for this analysis. These MHCs, which are the planning units for the Subtropical Thicket Ecosystem Planning (STEP) project, were defined according to various biological and environmental characteristics, including, vegetation type and structure, rainfall, geology and altitude (Cowling & Heijins 2001). They were obtained from the STEP project (Vlok & Euston-Brown 2002). ArcGIS 9.2 (ESRI 2006) was used to determine which MHCs occurred within the BRC. This was done by overlaying the BMR reserve and boundary layer, obtained from the BMR Project Management Unit (A. Skowno, unpubl. data), over the MHC layer, and extracting the boundaries of the various MHCs, as well as their extent.
51
5.2.2 Estimation of prey abundance i. Modelled abundance The potential herbivore distributions were calculated for each MHC. Firstly, a model developed by Boshoff et al. (2001; hereafter referred to as the ‘prey model’) was used. This method consists of a simple spreadsheet model that incorporates adjusted agricultural stocking rates based on Large Stock Units (LSUs; see Meissner et al. 1983), forage availability, and metabolic requirements of mammal species (see Boshoff et al. 2001 for details of the model). Only the 15 mammal species, with the exception of baboons, with a mass greater than ca. 2 kg that naturally occur within the BRC were incorporated in the model (Table 5.1). Baboon numbers were not calculated by using the Boshoff et al (2001) model, as it only caters for herbivore species. Thus, potential baboon numbers were calculated using the home range size of troops occurring in similar habitats; the data from de Vore & Hall (1965), who worked in the Cape of Good Hope Nature Reserve, was used. The number of individuals per troop was plotted against the home range size of each troop. The linear regression equation obtained (y = 0.412x + 0.646; where y is range size and x is number of individuals) was then used to determine the potential numbers of baboons occurring in the BRC, assuming that there is no levelling off of home range size with an increase in number of individuals. ii. Game count data Game count data from a section of the BRC was used as an estimate of herbivore density (Venter et al. 2008). These counts were obtained by flying 300 m wide transects that were 900 m apart, in order to identify areas with potentially high animal densities, and covered an area of 55 554 ha (Venter et al. 2008). The high-density areas were then re-sampled by flying 300 m wide transects, and covered an area of approximately 27 000 ha. All transects were flown at a height of 30 m and at an average speed of 32 knots (Venter et al. 2008). These transects where flown via helicopter in triplicate over a period of 9 days, recording the incidence of all wildlife species, their location and their abundance (Venter et al. 2008). The resulting density estimates were then extrapolated to the entire BRC and were used to estimate potential leopard abundance.
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Table 5.1: The body mass of herbivore species with a body mass greater than 2 kg, together with baboons, occurring in the Baviaanskloof Reserve Cluster. Mean body
Herbivore
Species
Baboon, Chacma*
Papio cyanocephalus ursinus
12
Buffalo, African
Syncerus caffer caffer
432
Bushbuck*
Tragelaphus scriptus
46
Bushpig
Potamochoerus porcus
46
Duiker, Common*
Sylvicapra grimmia
16
Eland
Tragelaphus oryx
345
Grysbok, Cape*
Raphicerus melanotis
7
Hartebeest, Red
Alcelaphus buselaphus
95
Klipspringer*
Oreotragus oreotragus
10
Kudu*
Tragelaphus strepsiceros
135
Reedbuck, Mountain*
Redunca fulvorufula
23
Rhebok, Grey*
Pelea capreolus
7
Rhino, Black
Diceros bicornis
800
Steenbok*
Raphicerus campestrus
8
Zebra, Cape mountain
Equus zebra zebra
179
mass
* indicates species used in the determination of potential leopard abundance 5.2.3 Estimation of potential leopard density The potential prey density data was used to determine potential leopard abundance in the BRC. Calculation of potential leopard density followed the method developed by Hayward et al. (2007). The prey density (#.km-2) data was converted to biomass (kg.km-2) by using ¾ of adult female body mass in order to account for sub-adults and young that is preyed upon (Schaller 1972). These mean female body mass estimates where obtained from Stuart & Stuart (2000) and Skinner & Chimimba (2005) and were converted to ¾ adult female body mass. Hayward et al. (2007) developed regression equations relating predator biomass to the biomass of prey falling within the predators’ preferred prey weight range (Pw; 10 – 40 kg) as well as for significantly preferred prey species (Ps; bushbuck, common duiker, and impala). The 53
regression equations for Ps (y = -2.455 + 0.456x; where y = potential leopard abundance and x = log10 of prey biomass) and Pw (y = -2.248 + 0.405x) were used in order to determine potential leopard abundance in the BRC. Hayward et al. (2006a) found that leopards significantly prefer bushbuck, common duiker, and impala. However, this analysis only incorporated data from bushveld and savannah ecosystems. For this reason, the Ps estimate was expanded to incorporate all prey items (actual prey; Pa) occurring in the diet of leopards in the BRC. The data from Ott et al. (2008), who described the diet of leopards in the BMR, was used to determine the Pa. They found that the dominant prey items occurring in the diet consists of 60% native ungulates, 20% rodents, and 12.5% rock hyrax (Table 5.2). All the small mammals (i.e. rodents and rock hyrax), carnivores, exotic species (nyala), and domestic stock were excluded from the analysis due to the lack of data regarding their potential distribution and numbers in the MHCs. Thus, the prey species that formed part of the diet of leopards in the BRC were used in the determination of potential leopard abundance, these included mountain reedbuck, bushbuck, Cape grysbok, common duiker, steenbok, klipspringer, kudu, and grey rhebok. Baboons were also included in the initial analysis even though they do not for part of the Baviaanskloof leopard’s diet, according to Ott et al. (2008). The resultant density and abundance estimate was then compared to the estimates of Boshoff et al. (2001), Norton & Henley (1987), and Carbone & Gittleman (2002). These models were not developed specifically for the BRC, they were however applied to the BRC in order to make comparisons with our model. Boshoff et al. (2001) determined the potential abundance of leopards in the Cape Floristic Region, which resulted in an estimate of 2 individuals per 200 km2. Norton & Henley (1987) used home range analysis to estimate the densities of leopards in the southern Cape, which resulted in an estimate of 6 – 9 individuals per 100 km2. These two estimates were simply extrapolated to the size of the BRC. Carbone & Gittleman (2002) developed an equation that relates prey biomass to carnivore density. The prey biomass estimate of the BRC was then used to estimate leopard density in the BRC.
54
Table 5.2: Occurrence of indigenous prey items in the diet of leopards in the BMR (from Ott et al. 2008). Prey species
Frequency
Common name
Scientific name
occurrence (%)
Rodents
Class Rodentia
20.0
Reedbuck, Mountain
Redunca fulvorufula
17.5
Bushbuck
Tragelaphus scriptus
15.0
Hyrax, Rock
Procavia capensis
12.5
Grysbok, Cape
Raphicerus melanotis
10.0
Duiker, Common
Sylvicapra grimmia
5.0
Steenbok
Raphicerus campestrus
5.0
Birds
Class Aves
5.0
Wild Cat, African
Felis silvestris
2.5
Klipspringer
Oreotragus oreotragus
2.5
Kudu
Tragelaphus strepsiceros
2.5
Rhebok, Grey
Pelea capreolus
2.5
of
5.3 Results 5.3.1 Mammal habitat classes Twenty-six MHCs were identified in the study area (Table 5.3) and ranged in size from 8 ha for Central Valley Thicket with Succulent Karoo to 83 501 ha for Baviaanskloof Mountain Fynbos.
55
Table 5.3: The 26 Mammal Habitat Classes (MHC) used as the spatial units for the leopard density model, and their respective sizes in hectares (reflecting the extent of the MHCs in the Baviaanskloof Reserve Cluster). Mammal Habitat Class (MHC)
Size (ha)
Afromontane Forest / Thicket Forest
9 032
Baviaans Fynbos Thicket
5 348
Baviaans Renoster Thicket
4 872
Baviaanskloof Mountain Fynbos
83 501
Central Valley Thicket with Succulent Karoo
8
Cockscomb Mountain Fynbos
44 992
Eastern Valley Thicket with Arid Fynbos
760
Eastern Valley Thicket with Succulent Karoo
1 003
Gamtoos Valley Thicket
3 795
Groot Spekboomveld
26
Groot Valley Thicket
19 183
Humansdorp Grassy Fynbos
3 322
Knysna Afromontane Forest
4 127
Kouga Mountain Fynbos
57 451
Kromme Fynbos / Renosterveld Mosaic
591
Langkloof Fynbos / Renosterveld Mosaic
680
Oudtshoorn Broken Veld
400
Steytlerville Broken Veld
179
Sundays Thicket
1 835
Sundays Valley Thicket
128
Sundays Valley Thicket with Grassy Karoo
1 069
Thicket / Valley Thicket with Fynbos
1 051
Thicket / Valley Thicket with Grassy Fynbos
3 901
Tsitsikamma Mountain Fynbos
21 028
Uniondale Inland Renosterveld
5 221
Valley / Arid Thicket with Renosterveld & Succulent Karoo
76
Total
273 579 56
5.3.2 Potential prey abundance The Cape grysbok had the highest potential biomass with 86.9 kg per km2 from the prey model outputs, compared to the grey rhebuck, which has the lowest potential biomass, with 2.6 kg per km2 (Table 5.4). The potential contribution of each species to support potential leopard abundance thus varies in accordance with their biomass estimates. When comparing the potential biomass estimates, the total game count biomass estimate for the BRC (155.7 kg) is several orders of magnitude smaller than the total prey model estimate for the BRC (9.5 x 105 kg). It ranges from 0 to 2.00 x 10-2 kg per km2 for the game count, compared to 2.62 – 86.85 kg per km2 for the prey model estimate (Table 5.4). This substantial difference persists for all the species involved. The most extreme differences occur between the game count and prey model estimates for grey rhebuck, steenbok and Cape mountain zebra. These three species were not recorded in the game count and consequently have a estimated biomass of zero for the game count data. 5.3.3 Potential leopard density and abundance The prey species (Ps) and prey weight (Pw) models, following Hayward et al (2007) resulted in potential leopard densities of 0.0003 – 0.215 individuals per km2 and 0.0005 – 0.0312 individuals per km2 respectively (Table 5.5). The Ps method was then adapted to incorporate all the prey items (actual prey; Pa) occurring in the diet of leopards in the BRC, which resulted in an estimate that ranges from 0.0007 - 0.0381 individuals per km2 (Table 5.5). The substantial difference in the potential prey biomass estimates of the prey model and the game count, together with the differences in the leopard models results in a huge range of potential leopard density estimates for the BRC (0.0003 – 0.0381 #/km2; Table 5.5).
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Table 5.4: Comparison of potential wildlife densities and corresponding biomass determined by a prey-abundance model and estimated by a game count in the Baviaanskloof Reserve Cluster. Estimated Density Estimated Biomass Species
(#/km2)
(kg/km2)
Model†
Count‡
Model† Count‡
Baboon, Chacma a
2.43
1.09 x 10-4
29.12
1.31 x 10-3
Buffalo, African
0.02
4.62 x 10-5
7.99
1.99 x 10-2
Bushbuck b c
0.75
6.35 x 10-5
34.28
2.92 x 10-3
Bushpig
0.34
1.48 x 10-6
15.75
6.81 x 10-5
Duiker, Common a b c
1.21
9.01 x 10-6
19.29
1.44 x 10-4
Eland
0.10
1.56 x 10-5
33.16
4.36 x 10-3
Grysbok, Cape c
12.41
4.20 x 10-6
86.85
2.92 x 10-5
Hartebeest, Red
0.09
6.53 x 10-5
8.36
6.20 x 10-3
Klipspringer a c
1.49
2.11 x 10-5
14.85
2.11 x 10-4
Kudu c
0.07
1.48 x 10-4
9.75
2.00 x 10-2
Reedbuck, Mountaina c
0.22
2.77 x 10-5
5.00
6.36 x 10-4
Rhebuck, Grey c
0.35
0.00
2.62
0.00
Rhino, Black
0.05
n/a
43.05
n/a
Steenbok c
1.76
0.00
14.06
0.00
Zebra, Cape mountain
0.13
0.00
23.13
0.00
347.26
5.69 x 10-2
Total biomass
† Estimates obtained from the adapted herbivore model of Boshoff et al. (2002). ‡ Estimates obtained from game counts (Venter et al. 2008). a Refers to prey used in the Pw calculation of potential leopard density b Refers to prey used in the Ps calculation of potential leopard density c Refers to prey used in the Pa calculation of potential leopard density n/a Omitted due to security reasons.
58
Table 5.5: Potential leopard density (#/km2) and population size (in parenthesis) estimated by the three prey-based models, and the estimated biomass used to determine this. Prey-based model Biomass (kg/km2) Herbivore model Game count Prey species (Ps)
53.57
0.0215 (59)
0.0003 (1)
Prey weight (Pw)
68.26
0.0312 (86)
0.0005 (1)
Actual prey (Pa)
186.70
0.0381 (104)
0.0007 (2)
5.3.4 Comparison of potential leopard densities Our estimate of 59 - 104 individuals (Table 5.5) was then compared to those of Boshoff et al. (2001), Norton et al. (1984), and Carbone & Gittleman (2002), with their estimates being 27, 124, and 164 - 246 individuals respectively (Table 5.6). Table 5.6: Comparison of the potential leopard abundance (total number of individuals) and potential leopard density (number of individuals per km2) in the BRC, using several carnivore density estimates. Potential leopard Potential leopard Reference density (#/km2) abundance (total #) This study*
0.022 - 0.038
59 - 104
Boshoff et al. 2001†
0.010
27
Carbone & Gittleman 2002*
0.046
124
Norton & Henley 1987‡
0.060 - 0.090
164 - 246
* Models using prey biomass to estimate leopard abundance † Estimate based on broad habitat requirements ‡ Estimate based on home-range analysis The published potential leopard densities of several southern African areas are shown in Table 5.7. These estimates were determined by examining populations that occur in a wide variety of habitats and by employing various techniques. The estimates range from a minimum of 0.002 individuals per km2 in Mountain Fynbos to a maximum of 0.303 individuals per km2 in woodlands. There is a large range of estimates as well as a large overlap between estimates. When comparing average densities the estimate of 0.030 individuals per km2 in this study is comparable to Bailey’s estimate of 0.035 individuals per km2. The average density estimates of 59
Martins & Martins (2006), Stander (1998), Bothma & le Riche (1984), and Mills (1984) are lower than the present study, and those of Norton & Henley (1987), and Stuart & Stuart (1991) are higher. 5.4 Discussion 5.4.1 Potential leopard density and abundance The differences in the abundance and biomass estimates between the prey model and the game count (Table 5.4) resulted in a large range of potential leopard densities (Table 5.5). This discrepancy is due to the general inaccuracies of the game count. This because game counts are based on raw count data that has an unknown relationship with true animal density, the spatial units are not conducive to extrapolation to the entire reserve (Karanath et al 2004), and are generally biased towards animals with a larger body size (Mills 1997), as can be seen in Table 5.4. The leopard’s diet in the BMR also consists mostly of smaller mammals (Table 5.2), which are likely to be under represented in the game count estimate (Norton-Griffiths 1978). When incorporating the game count data, it results in an estimate of one or two individuals. This estimate is incorrect because at least eight leopards have already been collared by a local NGO for the purpose of radio-telemetry (Rogers 2008) in the BMR. This highlights the importance of a limiting factor such as prey density, and the accurate measurements thereof for the prediction of leopard densities. The importance of the relationship between prey biomass and predator biomass has also been documented by several other studies (Carbone & Gittleman 2002). For this reason, the game count estimates of prey biomass were not included in the determination of potential leopard density and abundance. However, if the game count data was more accurate or supplemented with ground based techniques such as survey transects, it would have been conducive to more accurate predictions of potential leopard abundance. By excluding the game count estimates of prey abundance, we arrive at a potential leopard density of 0.022 – 0.038 individuals per km2 (59 – 104 individuals in the BRC). It must however, be stressed that our model does not precisely predict the actual population size of leopards in the BRC. However, it does give a broad estimation of the potential leopard densities and population sizes, and identifies areas where research needs to be focussed.
60
Table 5.7: Comparison of a selection of leopard density estimates (average densities in parenthesis) for different habitat types in southern Africa Estimated leopard Study area Habitat type Methods Source density (#/km2) Mountain
0.022 – 0.038
Fynbos
(0.030)*
Mountain
0.002 – 0.004
Fynbos
(0.003)
Mountain
0.060 – 0.090
Fynbos
(0.075)
Mountain
0.040 – 0.060
Fynbos
(0.050)
Kaudom GR, Namibia
Woodland
(0.013)
Kruger NP, SA
Woodland
Kalahari Gemsbok NP,
Semi-desert &
SA
Tree savanna
Kalahari Gemsbok NP,
Semi-desert &
SA
Tree savanna
Baviaanskloof MR, SA Cederberg WA, SA Cederberg WA, SA Cederberg WA, SA
Prey-based model
This study
Radio-tracking
Martins & Martins (2006)
Radio-tracking
Norton & Henley (1987)
Spoor counts
Stuart & Stuart (1991)
Radio-tracking
Stander (1998)
Radio-tracking
Bailey (1993)
(0.006)
Spoor counts
Bothma & le Riche (1984)
(0.011)
Radio-tracking
Mills (1984)
0.006 – 0.303 (0.035)
* Indicates potential leopard density MR = Mega-Reserve; SA = South Africa; WA = Wilderness Area; GR = Game Reserve; NP = National Park
61
5.4.2 Comparison of potential leopard densities A comparison of this result to other techniques applied to the BRC showed that there is a wide range of estimates and techniques used to estimate potential leopard abundance (Table 5.6). The Carbone & Gittleman (2002) model incorporated many carnivores across various habitat types, and is a general model (Carbone & Gittleman 2002), which is not specifically geared towards determining leopard abundance. This model has been used to estimate carnivore densities successfully (Carbone & Gittleman 2002). However, this estimate is in all probability much higher than the actual densities of leopards in the BRC. The Boshoff et al. (2001) estimate, which forms the lower limit of the range of estimates, was based on a literature review that incorporates information on leopard densities, social structures, breeding units, territory sizes and home ranges (Boshoff et al. 2001). This information was then applied to the CFR, which was treated as a single homogenous unit. In other words, it does not take into account the variation in potential leopard abundance according to habitat type and prey abundance. The Norton & Henley (1987) estimate, which forms the upper limit of the range, was determined by the home-range analysis of leopards in the mountainous areas of the southern Cape (Norton & Henley 1987). However, the accuracy of this estimate is questionable because of its small sample size (n=3), and the short duration of their study (Martins & Martins 2006). It may thus, not be applicable to the BRC. Therefore, this model provides a more accurate prediction of potential leopard densities for two reasons. Firstly, it is based on the method of Hayward et al. (2007), which accurately predicts leopard densities (Hayward et al. 2007). Secondly, the Hayward model is improved by incorporating the potential prey of leopards in the BRC. Comparing the various leopard densities in southern African regions also produces interesting results (Table 5.7). The estimates for the mountainous Fynbos areas of the CFR range from 0.002 to 0.060 individuals per km2 compared to 0.006 – 0.011 individuals per km2 for semideserts / tree savannas, and 0.006 – 0.303 individuals per km2 for woodlands. There is overlap between these various estimates to a certain extent, with semi-deserts having the lowest average density (0.009/km2), followed by mountain fynbos (0.027/km2) and finally wooded savannas (0.107/km2). These differences in leopard densities between various habitat types are due to the productivity of the habitat, which in turn influences prey abundance and distribution (Mizutani 1998). Prey density and distribution emerges as the most important limiting factor (Bailey 1993). This can account for the higher densities of leopards in Fynbos, which is considered to support 62
low densities of large herbivores (Venter et al. 2008), compared to dryer areas such as semideserts. Leopards in the BRC prey mostly on small mammals such as rodents, and small antelope (Ott et al. 2008), which are non-nomadic in fynbos. In dry areas, the nomadic nature of prey items can result in seasonal prey scarcity, which necessitates large home ranges and consequently much lower densities (Bothma & le Riche 1984). This is the case for the leopard population in the Kalahari Gemsbok National Park, with densities as low as 0.006 individuals per km2 (Bothma & le Riche 1984). Inter specific social dominance (Durant 1998) and competition (Bailey 1993) plays an important role in structuring carnivore communities. The fact that leopards are the dominant predators in the reserves of the CFR (Henley 2000) might explain the higher densities in the BRC than in dryer areas, where competition with other predators and inter specific social dominance may result in lower leopard densities. These differences between habitat types are expected. However, one would expect similar results comparing population estimation techniques within comparable habitats. This is however, not the case. Comparing the leopard densities estimates of the Cederberg Wilderness Area highlights the incongruent nature of these various techniques (Table 5.7). The situation seems even more confounded by the difference in estimated leopard densities whilst using the same technique. Take for example the estimates of Martins & Martins (2006), and Norton & Henley (1987) who both determined the potential leopard abundance via radio tracking and home range analysis. The respective estimates of 0.002 – 0.004 individuals per km2 and 0.019 – 0.031 individuals per km2 differ by an order of magnitude. These widely different estimates reflect the various approaches and methods used to determine leopard densities as well as the habitat type in question, and highlight the fact that there is a serious lack of knowledge regarding the estimation of potential leopard abundance. The application of these techniques to leopard conservation can produce varying results, which will ultimately negatively affect leopard conservation. There is a need to identify techniques that will accurately predict leopard densities in the CFR. Our model provides a platform for such a technique.
63
5.4.3 Model limitations and improvements The model does not exactly predict the density of leopard in the BRC. It does provide a range of potential leopard densities and identifies areas where the lack of knowledge prevents the accurate prediction of leopard densities. These are: (1) behavioural processes such as territoriality, intraspecific competition, habitat selection, and dominance, which can be obtained from home range analysis, and (2) incorporating accurate information on prey densities, including rodents and other small mammals, as this forms a major portion of the leopard diet (Ott et al 2007). Finally, the ideal would be to test the improved model predictions on a population of leopards with a known population size (Hayward et al. 2007). An example of such improvements on the model does exist. Here, we incorporated habitat selection for illustrative purposes only. Our estimate of 59 - 104 individuals for the BRC includes all 26 MHCs occurring within the BRC. However, there is some preliminary data from the BMR (Rogers 2008), that suggests that leopards move mostly in gorges and rivers, only emerging when they move between two gorges and rivers, or for the occasional hunt. It therefore, seems pertinent that the model can be further refined to incorporate various habitat selection scenarios. For this reason, the overall potential leopard density was applied to each of the MHCs in the BRC and only the MHCs occurring in the gorges and rivers where incorporated into the model. This results in an estimate of 10 - 17 individuals for the BRC. This estimate is in all probably a more accurate reflection of the actual leopard population size in the BRC as opposed to the potential leopard densities that can be sustained by the estimated prey base, presented here. If this is the case, this population is extremely small. The BRC therefore needs to be expanded via the purchase of more conservation land or contractual agreements with neighbouring landowners in order to provide additional habitat for leopards (Henley 2000). In conclusion, the actual number of leopards in the BRC is probably much lower than the upper limit of 104 individuals. This can be attributed to the discontinuous nature of the cluster of reserves intersected by areas of non-conservation landuses. These hostile environments effectively create island populations. This can ultimately result in a potent edge effect, whereby conflict with landowners may lead to the local extinction of these leopards (Woodroffe & Ginsberg 1998).
64
Chapter 6: General discussion
6.1 Limitations to this study When interpreting the findings of this questionnaire survey, it must be kept in mind that these are opinion surveys and they do not reflect an objective examination by researchers (Lawson 1989). Rather, the data reflects the information that the respondent’s choose to provide. The data may thus suffer from certain biases inherent in this type of research. It may be that some respondents artificially inflate their stock losses hoping that this will motivate conservation authorities to assists in alleviating carnivore-livestock conflict (Lawson 1989; Holmern et al. 2007). Since these stock losses were based on the farmers’ identification of the predator involved, the possibility exists that respondents that did not accurately identify the culprit, and reported stock losses might not accurately reflect the actual cause of predation or the severity thereof (Lawson 1989). Respondents may also wrongly accuse certain predators of killing livestock that died of natural causes, because of lack of vigilance in determining the actual cause of death or prejudices towards these carnivore species (Rasmussen 1999), or the desire to shift the responsibility for their stock losses from themselves. Most farmers in the BMR do not receive any compensation for livestock losses attributed to carnivores. Some farmers that form part of the Baviaanskloof Farmers Association receive limited compensation for leopard-stock losses from a local NGO. Therefore the reporting of stock losses attributed to other predators is unlikely to be biased. There is also no outreach programme currently employed by the Eastern Cape Parks Board, and therefore farmers do not gain anything by overinflating their livestock losses (Holmern et al. 2007). Thus, despite the flaws pointed out previously, these results are considered valid, and provide useful insights into carnivore-livestock conflicts. 6.2 Synthesis of findings The most import result from this study is that leopards are not necessarily the most important causes of livestock mortality in the BMR. On average, leopards killed significantly less livestock (0.7% livestock per year) than black-backed jackals (4.7% per year) and caracal (2.5% per year). So why does so much attention fall on leopards? The two major reasons for this are: (1) leopards kill relatively large numbers of livestock in one incident (den Hertog 2008), and (2) leopards in 65
South Africa are a protected species and legally cannot be lethally controlled by land managers without a permit from DEDEA, whereas the other predators of livestock can be controlled in this fashion. Irrespective of the relatively small amounts of livestock losses attributed to leopards, most (67%) respondents in this survey had negative attitudes towards leopards. It was found that these negative attitudes are not driven by the amount of stock lost to leopards, as was originally hypothesised, but are influenced by the total amount of stock lost. Thus, in order to change the attitudes of farmers in the BMR, livestock predation by all predators has to be reduced. This requires cooperation between ECP, DEDEA, and the farmers in order to implement appropriate and ecologically acceptable predator control strategies and livestock management techniques, since the techniques employed by the farmers do not appear to reduce predation by predators, according to the data provided by landowners. In other words, livestock losses in the BMR cannot be reduced by simply focussing on specific predators or causes of livestock mortality, a holistic predator management plan is required. However, this will only happen if the relationship between DEDEA and the farmers is improved. This study shows that most farmers do not make use of the predator control strategies provided by DEDEA, even though those who use these services deem them as being either moderately or very effective. For whatever reason, this leads one to question the level of trust and cooperation between farmers and DEDEA. If this relationship between conservation authorities and farmers is not restored and effective management techniques put in place to reduce stock losses, the negative attitudes towards leopard will remain. This may result in further killing of leopards and other carnivores, because most respondents will take management steps to prevent these predators from settling on their properties (Marker et al. 2003). These retaliatory killings may have severely negative effects on the BMR leopard population. Further reducing this relatively small population, can result in a potent edge effect, which may lead to the local extinction of these leopards (Woodroffe & Ginsberg 1998). Leopard predation is much higher on properties that border the Baviaanskloof Nature Reserve directly. When comparing these predation incidents to the relative available habitat, intriguing results emerge. It appears that leopards prefer the mountainous area, based on stock losses. Several reasons for this are mentioned (e.g. presence of thicket vegetation which provides cover to the leopards for hunting purposes), however no data were collected to support any of 66
these. Farmers responded by withdrawing their livestock from these area. Therefore, these areas can be important in conservation terms, and have been shown to assist in mammal conservation (Macdonald et al. 2008), but not necessarily biodiversity conservation. However, if these areas correspond with the critical biodiversity areas identified by the Baviaanskloof Mega-Reserve Conservation Plan (see Boshoff et al. 2008), the influence of leopards can assist in biodiversity conservation by reducing the vegetation impacts of livestock in these areas. The areas that are not being farmed can effectively be seen as an extension of the Baviaanskloof Nature Reserve. These areas are also important in terms of predator interactions. When comparing stock losses attributed to leopards to the other predators of livestock, it produces novel results. In areas with leopard-stock interactions, there is significantly less predation by black-backed jackal and caracal. This indicates the possibility of interspecific competition between these carnivores, which may result in ecological separation (caracal and leopards in the mountains of the Western Cape, Norton & Henley 1987; cheetah and lions and hyaenas in Namibia, Marker 1998) or avoidance behaviour (black-backed jackals and leopards in the Kruger National Park; Bailey 1993). However, the exact mechanisms producing these trends are not known. These findings can assist in the education of land managers regarding the nature and extent of carnivore predation on livestock and may also assist in improving their attitudes towards leopards. 6.3 Management recommendations This study provides valuable insights into the ecological and socio-economic factors that influence carnivore-stock farmer conflict in the BMR, with particular reference to leopard-stock farmer conflicts. Understanding these factors plays an important role in the conservation of leopards and other carnivores in the BMR. Even though leopards are not considered endangered or threatened in South Africa, this study shows that the regional extinction of leopards is a real possibility. Therefore, there is a need for a regional approach to leopard conservation, as a national approach might overlook the critical issues linked to the regional survival of leopard populations, such as the BMR leopard population. Combining the information 6.3.1 Linking leopard predation with conservation planning and implementation i. Conservation planning opportunities The spatial data presented in this study shows that leopard impacts on livestock vary across the landscape and in different habitat types. This provides the basis for a conservation 67
planning approach in which ‘leopard hotspots’ could be identified. These ‘hotspots’ reflect areas that may represent agricultural challenges due to high stock losses attributed to leopards. The problem areas can also be viewed as conservation opportunities as they are areas of high leopard activity. Therefore, by developing these identified ‘hotspots’ into conservation planning layers and incorporating them into the protected areas network, the problem of leopard-stock farmer conflict on a local scale will be reduced and the potential leopard habitat will also be expanded. This will assist in the conservation of the BMR leopard population. ii. Withdrawal of livestock This study has identified tracts of privately owned land where agricultural activity has been ceased due to the threat of leopard predation. These areas should be viewed as voluntary conservation areas. These areas should be linked to the conservation agencies, which in turn, should support and assist the landowners in the management of these areas. These areas may also provide incentives to the landowners via the new property tax bill, whereby landowners may receive tax rebates if portions of their properties are managed as conservation areas. This will assist in the conservation of leopards on a local scale, by providing additional habitat and reducing leopard-stock farmer conflict. 6.3.2 Livestock and predator management The majority of livestock management techniques and predator control strategies employed by farmers in the BMR are not 100% effective in reducing livestock losses to carnivores, according to the data provided by the farmers. This is because livestock management techniques do not affect stock losses due to predators (Graham et al. 2005). These techniques are positively correlated with net primary production instead (Graham et al. 2005). The fact that these techniques are being used, irrespective of efficacy, indicates that farmers base their management decisions on anecdotal evidence such as common sense, personal experience, and hearsay. Provision of alternative and effective management techniques is a major component of carnivore conservation strategies (Marker-Kraus et al. 1997). There is thus a need for the use of holistic predator management techniques that have been proven to reduce or prevent stock losses to predators in the BMR (evidence-based management; Sutherland et al. 2004). At the moment, none of the available techniques for livestock and predator management have been verified by independent research or has been proven to reduce or prevent stock losses to predators in the 68
BMR. However, there are several other techniques, not extensively employed by farmers in the BMR, which have been shown to reduce livestock depredation by carnivores, elsewhere. Some of these are: i. Livestock management Livestock management is a very broad category and include any management decision or intervention related directly to livestock. Several techniques have been proven to reduce livestock losses to predators. These include: •
The synchronisation of calving or lambing seasons between farms (Marker 2002). This reduces year-round availability of calves, lambs and kids, which form the largest proportion of livestock consumed by predators.
•
Timing the lambing and calving season so that it does not overlap with the breeding season of carnivores; Lawson (1989) suggested that black-backed jackal pups are born in winter and therefore more livestock is taken in winter when there are more pups to feed.
•
Changing livestock breeds to indigenous breeds that have better anti-predator responses, such as native cattle (Marker 2002, Middleton in Rasmussen 1999). Several respondents to this survey suggested that Damara sheep have a better grouping behaviour and are more vigilant for predators.
•
Lambing and calving in corrals (Marker 2002).
•
Kraaling livestock at night (Ogada et al. 2003; Holmern et al. 2007). This technique did not reduce livestock losses in the BMR. However, by improving these corrals (creating visually closed corrals) there may be a reduction in the amount of livestock lost to predators (Rasmussen 1999), especially leopards.
•
The use of protective livestock collars. Some initial evidence from the farmers in the Baviaanskloof Agricultural Society indicates that these collars reduce stock losses substantially (80 – 100%). This result differs from that of this study, because these collars were not extensively used when this survey was done. Therefore, protective livestock collars seem to be one of the most effective techniques in reducing livestock predation by leopards and caracal.
69
ii. Livestock guarding animals There is a wide variety of livestock guarding animals available (Llamas sp, Alpaca sp, Anatolian shepherd dogs, and donkeys). The most widely used animal is the Anatolian shepherd dog. The effectiveness of these Anatolian Shepherds in reducing livestock predation by carnivores has been widely proven (Marker 2002; Rigg 2004). According to Marker (2002), farmers with these dogs reported a decrease in livestock losses of almost 90%. The use of Anatolian shepherd dogs in the BMR is a relatively recently adopted technique, and consequently most dogs are still in the training phase. For this reason, these dogs did not significantly reduce the amount of stock lost to predators during this survey. However, one farmer that had working dogs had a total stock loss of only 3% per year compared to the average stock losses of 13% per year. With proper education and training regarding Anatolian dog management and use (Marker 2002), it is a possibility to use these dogs in the BMR. However, these dogs require, food, veterinary care and might not be as cost effective as other techniques (e.g. livestock collars). Therefore, proper research as to the effectiveness of these animals in reducing livestock losses in required. iii. Restoration of natural prey base Several studies have shown that there is a correlation between low natural prey availability and high predation rates on domestic livestock (Lawson 1989; Woodroffe et al. 2005, Kolowski & Holekamp 2006; Holmern et al 2007). According to Marker (2002), farmers who maintain the natural prey base of carnivores, have lower predation rates on their livestock. Reasons for this are that predators hunt and kill prey that are the most effectively located. This is because livestock management techniques do not affect stock losses due to predators (Graham et al. 2005). These techniques are positively correlated with net primary production instead (Graham et al. 2005), and many carnivore species prefer to prey on natural prey (Graham et al. 2005), which is also the case for leopards in the BMR (Ott et al. 2007). This is because leopards have a preferred prey weight range of 10 – 40 kg (Hayward et al. 2007), which excludes most adult livestock. Five respondents in this survey are employing this technique, three of which have low total stock losses (1 -3% per year), whilst the other two have high total stock losses (> 7% per year). Even though there was no difference in stock losses between farmers who employed this technique and those who did not, this technique shows great potential in reducing stock losses to 70
carnivores in the BMR. However, it may take several years for the prey base to be restored, depending on the degree of habitat degradation. Therefore farmers are encouraged to actively restore the natural habitat and thereby restore the natural prey base of carnivores. As showed in this study, no single technique will be effective in reducing or preventing livestock depredation. Thus, a combination of these techniques is required to significantly reduce livestock losses to carnivores (Ogada et al. 2003). 6.3.3 Leopard conservation In order for the conservation of leopards in the BMR to be effective, there should be a level of cooperation between ECPB as managing authority of the Baviaanskloof Nature Reserve and their neighbours (the majority are livestock farmers). This is because the leopard population in the BMR is fundamentally a shared population, with individual leopards moving freely between conservation areas and privately owned land (Rogers 2008). The first step to accomplishing this is to restore the trust between these two parties. In order to achieve this, a three-pronged strategy is required: i. Education The majority of farmers in the BMR either believe that leopards do not control other predators, or they do not know if leopards control other predators. However, here I have shown that leopards reduce the amount of stock lost to black-backed jackal and caracal. Thus, farmers need to be educated regarding the ecological role carnivores play in an ecosystem as well as the benefits of having leopards on their properties. This should significantly improve their attitudes towards carnivores (Woodroffe et al. 2005; Holmern et al. 2007) and consequently conservation. ii. Incentives Because attitudes towards leopards are driven by the financial losses due to livestock depredation, the only clear way to change the attitudes of farmers is to provide financial incentives or compensation for stock losses (Thavarajah 2008). According to respondents of this survey, there two major complications with compensation schemes. Firstly, farming operations are extensive and it is not always possible to inspect all the flocks daily. The majority of farmers take approximately one week to inspect all their livestock. If some livestock are missing, it is thus often too late to identify the cause of mortality, as the carcass has already started 71
decomposing or it may have been scavenged upon by other predators, especially bushpig. Secondly, the terrain is very rugged and the vegetation very dense. Therefore, it is not always possible to locate the carcasses. Thus, the causes of mortality for only a small proportion of livestock losses can be identified. Therefore, governmental institutions (DEDEA) often underestimate the actual stock losses and the economic implications thereof. The establishment of such a scheme is indeed difficult in the BMR. However, the responsibility of an effective conservation scheme falls both on the farmers and on the DEDEA. •
Farmers need to be more vigilant and need to change their management practices in such a way that livestock losses can be detected quickly and efficiently. This includes the withdrawal of livestock from areas with high leopard predation (this study). These areas will effectively be “conservation area” and the South African Government is planning on passing a bill where any conservation land receives tax rebates. Therefore, farmers that are already withdrawing livestock from certain portions of their property in response to leopard predation, can attain incentives for the ‘unused land’ by setting these tracts of land aside as conservation areas. Farmers are also encouraged to report all stock losses to DEDEA in order to obtain an accurate measure of stock losses.
•
DEDEA needs to assign environmental officers to all the areas that fall within the planning domain in order to assist in verification of the causes of mortality and the submission of claims to DEDEA. Therefore, the onus is on DEDEA and the Agricultural Union of the Eastern Cape (AgriEC) to establish a predator programme that accurately records stock losses in the BMR. DEDEA should be the authority that is responsible for securing funding and for compensation payments to farmers.
iii. Eco-tourism At the moment, farmers undervalue the tourism potential of leopards in the BMR. In order to change their attitudes towards carnivores and leopards in particular, they need to see the financial benefits of eco-tourism. Even though eco-tourism potential and opportunities did not significantly influence attitudes towards leopards, respondents that practised some form of tourism had positive attitudes towards leopards. Community based conservation schemes have 72
been widely used to change attitudes towards wildlife and assist in conservation (see Hackel 1999 for a review). However, I do not believe that this will be an effective strategy in increasing the tolerance of farmers towards carnivores. This is primarily because most farmers would rather farm than run a tourism operation. Therefore, tourism ventures need to be used as a component of a larger predator management scheme. 6.4 Further research This study only focused on a small portion of the factors that play a role in carnivore-livestock conflict in the BMR. Thus, there is a large amount of research to be done regarding this issue, especially in the BMR. However, during the course of my research it became apparent that there are several areas that require further research attention. •
Ecological and behavioural information on the dominant predators of livestock in the BMR (black-backed jackals and caracal), as well as leopards, needs to be collected and analysed. This will assist in identifying the ecological factors (prey preference, habitat use on private lands, habitat preferences, etc.) that play a role in livestock predation as well how to prevent these losses in the BMR.
•
Effective livestock and holistic predator management techniques should be determined. This can be done via long-term trial experiments that determine the effectiveness of techniques in the BMR. This will assist in determining which techniques are effective in reducing livestock predation by carnivores in the BMR.
•
Information regarding the behavioural processes (territoriality, intra-specific competition, habitat selection, and dominance) of leopards in the BMR as well as their interactions with other carnivores (social-dominance, inter-specific competition, etc.) needs to be collected. More accurate information regarding the densities and biomass of rodents and other small mammals should be collected, as this forms a major portion of the leopard diet (Ott et al 2007). This will assist in the improvement of the leopard-model presented here, which will give a more accurate prediction regarding the population status of the Baviaanskloof leopard population. In addition to this the population size of leopards must be verified using techniques such as genetics or photo surveys. 73
•
The connections between the BMR leopard population and other, nearby populations need to be assessed. These corridors will allow the flow of genes between the various leopard populations, and are important for the long term conservation of leopards.
•
There is a need to predict the movements of leopards in the BMR in order to assist in predator control as well as the development of eco-tourism.
Addressing these various issues will improve our understanding of the various factors that influence the BMR leopard population and will significantly contribute to the reduction in carnivore-stock farmer conflict and assist in effective conservation of carnivores in the BMR.
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Appendices Appendix 1: Questionnaire used to survey the farmers in the Baviaanskloof Mega-Reserve. Leopard-stock farmer interactions survey Centre for African Conservation Ecology Nelson Mandela Metropolitan University Leopards are opportunistic predators and hunt the available prey. Due to this there usually exists conflict between farmers and leopards because leopards can take small-stock which can lead to large economic losses to farmers. This might be motivation to farmers to prosecute the leopards. On the other hand, leopards are very important to various ecological processes and as part of the big five, they are also very important to ecotourism. It is, thus very important that leopard-stock interactions should be investigated in order to understand the various processes involved and to determine what the actual economic value of the stock lost due to leopard depredation is. This information is vital to the understanding of leopard-stock conflicts in and around the Baviaanskloof Mega Reserve (BMR) as it will be the basis of the development of a leopard management programme for the BMR which will include information from not only conservations staff but also farmers. This questionnaire survey is therefore aimed at landowners within the Baviaanskloof Planning Domain. (BPD)Your participation will be invaluable in providing information for this project, as well as assisting in developing an understanding of the leopard-stock conflicts in the BPD. Please note that this form can be provided electronically by emailing me at
[email protected]. Any queries can also be directed to this address. I will be providing feedback on this survey to the participants on the completion of this project. Many thanks for your support. Liaan Minnie 1.
Personal Details Email Cell no.
Name Tell no. Farm name(s)
1)
2)
3)
Farm size(s)
1)
2)
3)
Years occupied
1)
2)
3)
Residential Farm 2.
Farming Type (mark with an X)
What animals do you farm?
Percentage contribution of farm stock: 815, how much?
Jackals
%
Caracals
%
Leopards
%
Black eagles
%
Stray dogs
%
Baboons
%
Unknown
%
Has this pattern changed? Increase
Decrease
Other % (specify) Rank in order of abundance i.e. from most abundant (1) to least abundant (7) on your farm. Black Jackals Caracal Leopards Stray dogs Baboons eagles 5. Leopard-stock incidents (mark with an X) a) Incidents If >5, How many leopard incidents do you have per 0 1 2 3 4 5 many? month? Where do these incidents occur (Indicate on Map GPS S E map or write in GPS points)? When do you think most of these incidents Dawn Day Dusk occur?
Same
Other (as specified) how
Night
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In what season do you think these incidents occur? Which season has the largest number of incidents? How often do you report these incidents?
Summer
Spring
Winter
Autumn
Summer
Spring
Winter
Autumn
Never
Occasionally
Always
To whom do you report these incidents? To your knowledge, was action taken by these individuals/institutions? What type of action was taken by these individuals/institutions?
How effective were these actions?
Yes
No
Very
Moderate
Low
Ineffective
b) Control Actions – Control measures used to decrease leopard depredation. How effective is it? How many leopards caught per year? What type of control do you use? Very Moderate Not 0 1 2 3 4
If >4, many?
Cage traps Gin traps Poison bait/lure Toxic collars Protective collars Hunting Guard dogs None How often are the control methods used? Where are the control actions used (Indicate on map or write in GPS points)? How often are cages, traps, baits and lures checked?
Preventative measure
Only when Stock lost
Map
S
Once daily
GPS
Once weekly
E Once monthly
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how
