Introduction
Human–wildlife conflict is defined by Conover (Reference Conover2002) as any action by humans or wildlife that has an adverse impact on the other. Carnivores in particular come into direct or indirect conflict with humans by posing a threat to human life and/or economic stability (Conover, Reference Conover1994; Sillero-Zubiri & Laurenson, Reference Sillero-Zubiri, Laurenson, Gittleman, Funk, Macdonald and Wayne2001; Woodroffe, Reference Woodroffe, Gittleman, Funk, Macdonald and Wayne2001; Ogada et al., Reference Ogada, Woodroffe, Oguge and Frank2003; Treves & Karanth, Reference Treves and Karanth2003; Thirgood et al., Reference Thirgood, Woodroffe, Rabinowitz, Woodroffe, Thirgood and Rabinowitz2005). Despite intensive conservation efforts, carnivore species overall are on the decline and population extinctions continue (Sillero-Zubiri & Laurenson, Reference Sillero-Zubiri, Laurenson, Gittleman, Funk, Macdonald and Wayne2001; Woodroffe, Reference Woodroffe, Gittleman, Funk, Macdonald and Wayne2001). Yet carnivore species play a pivotal role in ecosystem function, making their conservation a priority (Gittleman et al., Reference Gittleman, Funk, Macdonald, Wayne, Gittleman, Funk, Macdonald and Wayne2001; Sillero-Zubiri & Laurenson, Reference Sillero-Zubiri, Laurenson, Gittleman, Funk, Macdonald and Wayne2001; Treves & Karanth, Reference Treves and Karanth2003).
Human–carnivore conflict is associated with a complex set of factors, including attitudes and perceptions (Sillero-Zubiri & Laurenson, Reference Sillero-Zubiri, Laurenson, Gittleman, Funk, Macdonald and Wayne2001; James, Reference James2002; Dickman, Reference Dickman2005). In general, attitudes refer to the degree of positive or negative feelings people associate with some psychological object such as a symbol, phrase, institution, ideal or person (Thurstone, Reference Thurstone1946). Thus, positive attitudes reflect what people ‘like’ and negative attitudes are things people ‘dislike’; these can be captured by asking people directly how they feel (Edwards, Reference Edwards1994). In addition to this affective component that captures people's feelings, attitudes also contain a cognitive component that captures an attribute or belief about a particular object (Thurstone, Reference Thurstone1928). When both of these attitude components match, they accurately predict human behaviour (Miller & Tesser, Reference Miller and Tesser1986).
Attitudes towards carnivores have been studied and linked to demographic factors such as age, sex, level and source of income, religious beliefs and culture (Kellert, Reference Kellert1985; Kellert & Berry, Reference Kellert and Berry1987; Sillero-Zubiri & Laurenson, Reference Sillero-Zubiri, Laurenson, Gittleman, Funk, Macdonald and Wayne2001; Dickman, Reference Dickman2005; Romaňach et al., Reference Romaňach, Lindsey and Woodroffe2007; Røskaft et al., Reference Røskaft, Händel, Bjerke and Kaltenborn2007). Although a useful starting point, demographic perspectives on attitudes fail to specify deeper mechanisms of environmental attitudes generally, which have been shown to contain cognitive and affective components (Hines et al., Reference Hines, Hungerford and Tomera1987; Stern et al., Reference Stern, Dietz and Kalof1993, Reference Stern, Dietz, Kalof and Guagnano1995; Gagnon Thompson & Barton, Reference Gagnon Thompson and Barton1994; Dietz et al., Reference Dietz, Stern and Guagnano1998). Attitudes towards carnivores are partly based on the degree to which carnivores clash with human interests and partly on inherent human prejudices (Bjerke & Kaltenborn, Reference Bjerke and Kaltenborn1999; Lindsey et al., Reference Lindsey, du Toit and Mills2005). For instance, Sillero-Zubiri & Laurenson (Reference Sillero-Zubiri, Laurenson, Gittleman, Funk, Macdonald and Wayne2001) found that predation by carnivores on livestock was a prevalent predictor of human–carnivore conflict. However, attitudes towards carnivores are not always directly associated with carnivore predation behaviour and must take into account human feelings towards, and beliefs about, carnivores. Kellert (Reference Kellert1985) found that even when wolves caused little livestock depredation, sheep and cattle farmers maintained negative attitudes towards wolves. Studies concur that farmers worldwide generally believe large carnivores have no place on farmland, and fail to appreciate their ecological role (Kellert, Reference Kellert1985; Conover, Reference Conover1994; Oli et al., Reference Oli, Taylor and Rogers1994). Equally, in Africa, local people such as domestic stock farmers, pastoralists and much of the rural population view carnivores as a nuisance and see little ecological, aesthetic or financial value in them (Marker et al., Reference Marker, Kraus, Barnett and Hurlbutt1996; Stander et al., Reference Stander, Llau, Lui, Dabe, Dabe and Penzhorn1997; Dickman, Reference Dickman2005).
In Namibia 90% of the 3,000 strong cheetah Acinonyx jubatus population survives on privately owned farmland in the north-central cattle-ranching region (Marker, Reference Marker2002). In addition, carnivores such as the leopard Panthera pardus, brown hyaena Hyaena brunnea, jackal Canis mesomelas, caracal Felis caracal and, in some cases, lion Panthera leo, spotted hyaena Crocuta crocuta and African wild dog Lycaon pictus share this farmland (Marker et al., Reference Marker, Kraus, Barnett and Hurlbutt1996; Hanssen & Stander, Reference Hanssen and Stander2004). Research into human–carnivore conflict on freehold farmland in Namibia has focused mainly on formerly advantaged commercial farmers (Marker et al., Reference Marker, Kraus, Barnett and Hurlbutt1996; Marker & Schumann, Reference Marker, Schumann and Penzhorn1998; Marker, Reference Marker2002; Schumann, Reference Schumann2006; Schumann et al., Reference Schumann, Watson and Schumann2008). While these farmers were the majority freehold landowners until Namibia's independence in 1990, land reform initiatives since then have led to a drastic demographic change in the farming community.
Formerly disadvantaged Namibians have moved onto freehold farmland, aided by the Affirmative Action Loan Scheme. Many of these farmers have no formal agricultural training and are hampered by a lack of skills and knowledge necessary to run a commercial operation (Vigne & Motinga, Reference Vigne and Motinga2005). Although several assessments of agricultural training needs have been carried out for these farmers (Blackie, Reference Blackie1999; Desert Research Foundation of Namibia, 2005; Vigne & Motinga, Reference Vigne and Motinga2005), none have addressed human–carnivore conflict issues and nothing is known about their attitudes towards carnivores. Successful resource management is becoming increasingly dependent upon knowledge about how conflicts are constructed, and this entails identifying attitudes and beliefs held by various interest groups (Kaltenborn et al., Reference Kaltenborn, Bjerke and Strumse1998). Taking the aspirations and needs of specific cultural groups into account facilitates the development of appropriate human–carnivore conflict management strategies (Sillero-Zubiri & Laurenson, Reference Sillero-Zubiri, Laurenson, Gittleman, Funk, Macdonald and Wayne2001; Treves & Karanth, Reference Treves and Karanth2003; Dickman, Reference Dickman2005). Understanding attitudes towards carnivores is thus one of the first steps towards mitigating human–carnivore conflict to ensure the survival of carnivores on freehold farmland.
Our aim here is to investigate the attitudes of emerging commercial farmers in Namibia and how these affect human–carnivore conflict. We begin by assessing the attitudes of farmers towards carnivores by measuring both affective and cognitive components. Next, we identify how farmers’ perceptions of human–carnivore conflict relate to their behaviour (actions). Finally, we determine how affective and cognitive components of farmers’ attitudes are associated with the level of carnivore removal.
Study area
The study area comprises the north-central freehold farmland in Namibia (Fig. 1). Mean annual rainfall is 467 mm and temperatures vary from < 0°C in winter to > 50°C in summer (Marker, Reference Marker2002). Vegetation is characterized by thorn bush, highland and camel thorn savannah (Byers, Reference Byers1997), much of which is encroached by bush because of the suppression of veld fire, the absence of megaherbivores, and overgrazing and poor livestock management (Lange et al., Reference Lange, Barnes and Motinga1997). The northern limits of the study area merge with mountain savannah and Karstveld around Tsumeb, Grootfontein and Otavi. Highland savannah in the south of the study area covers the Khomas Hochland and Windhoek bergland up to Rehoboth (Byers, Reference Byers1997; Strohbach-Fricke, Reference Strohbach-Fricke and Tarr1997). In these areas cattle are raised for beef production, with sheep, goats and wildlife supplementing incomes (Erb, Reference Erb2004).
Fig. 1 The locations of respondents' farms and protected areas in the north-central freehold farmland of Namibia.
Our study area falls within a key livestock production area that is also regarded as a key area for wildlife (Krugmann, Reference Krugmann2001; Erb, Reference Erb2004), including the full guild of Namibia's large carnivores (Marker et al., Reference Marker, Kraus, Barnett and Hurlbutt1996; Hanssen & Stander, Reference Hanssen and Stander2004). Wildlife resource management outside communal and protected areas on freehold farmland is the domain of the Ministry of Environment and Tourism, sub-division Wildlife Utilisation and Permit Control, with the focus on administering wildlife quotas, live sales and other consumptive uses (Erb, Reference Erb2004).
Methods
Sample and descriptive statistics
For the purpose of this study the term emerging commercial farmer incorporates all formerly disadvantaged farmers on freehold land and excludes communal farmers living on government land. A random sample of 82 emerging commercial farmers was surveyed. Emerging commercial farmers comprise several cultural groups, identified here by respondents’ home language (most commonly spoken while growing up): Herero (47.6%), Ovambo (20.7%), Damara (18.3%), Afrikaans (8.5%) and other languages (4.9%). The majority of respondents were male (90.2%). Female respondents were farm owners or represented their fathers or husbands. Where possible we interviewed the farm owner (64.6%), but in some instances a representative such as the farm foreman (19.5%) or a relative sharing the farming responsibilities (15.9%) was questioned. Farmers had spent a mean of 6.2±SD 4.6 years (range 1–24) living on their farms. Mean farm size was 4,682±SD 2,066 ha (range 304–11,000). The farms are in eight regions of 11 districts, with the majority of farms in the Grootfontein district. One farm is in the Rundu district and, although on communal land, is a demarcated fenced farm to which the owner has title deeds.
Many of the emerging commercial farmers (48.8%) acquired their farms through the market-based Affirmative Action Loan Scheme model whereby the Namibian government provides financial support to allow people to buy farms, thus encouraging the emergence of African entrepreneurs (Sachikonye, Reference Sachikonye and Hunter2004). Vigne & Motinga (Reference Vigne and Motinga2005) reported the majority of Affirmative Action Loan Scheme farmers they surveyed were aged 36–50 and that most such farmers sold small stock to maintain cash flow but indicated they were attempting to move towards an ox-cow production system. Some 98.8% of farmers in our study rated cattle as an important source of cash income, followed by goats (84.8%) and sheep (75.6%), and 53.3% of the farmers rated employment off the farm as an important source of cash income. Most farmers practised a mixed livestock farming strategy (84.1%) comprising on average 41.0% cattle, 35.2% goats and 23.8% sheep.
Survey methodology
Interviews were conducted during 2006 by BS or by one of four staff members of a local NGO, using a questionnaire. To refine survey items a pilot survey was carried out. Farmers were accessed at training courses, information days and agricultural shows. The results described here are part of a larger study conducted on the needs of emerging commercial farmers in Namibia in relation to human–carnivore conflict. We used a Likert (sliding) scale to assess farmers’ attitudes, perceptions and behaviours (Dillman, Reference Dillman1991; Foddy, Reference Foddy1993). We assessed the farmers’ ability to identify carnivores by showing them colour photographs of eight carnivores found on Namibian farmland. Farmers were asked to name carnivores in English or their own language.
Operationalization of variables
To assess attitudes towards carnivores we followed similar approaches to earlier research (Kaltenborn et al., Reference Kaltenborn, Bjerke and Strumse1998; Røskaft et al., Reference Røskaft, Händel, Bjerke and Kaltenborn2007). We measured affective and cognitive attitudes towards carnivores by asking farmers to indicate how much they agreed or disagreed on a scale of 1–5 (1=strongly disagree, 5=strongly agree) with four statements (Table 1).
Table 1 The four measurement items relating to respondents’ attitudes towards carnivores. In a principal component analysis with Varimax rotation items pertaining to affective and cognitive aspects of attitude loaded together on one factor, with positive and negative attitudes in opposing directions.
We measured farmers’ perceptions of the level of carnivore conflict that existed on their farms. Several items were used to identify how much farmers agreed or disagreed on a five-point Likert scale with statements such as: ‘When several livestock are killed, I know I have a carnivore problem’ and ‘When carnivores are seen, I know I have a carnivore problem’.
We measured farmers’ intended behaviour by assessing when they would be likely to take action to remove carnivores from their farmland. Using the same scenarios as above, in this way facilitating the comparison of the perceived level of conflict versus farmers’ behaviour in the form of removing carnivores, we asked farmers to indicate how strongly they agreed or disagreed with statements such as: ‘I attempt to remove a carnivore after several livestock kills are found’.
For the regression analysis additional survey items were used. The dependent variable in the first set of regressions was the level of carnivore conflict, reported by farmers on a scale from 1 (‘carnivores are no problem’) to 5 (‘carnivores are a very big problem’). The dependent variable in the second set of regressions was the level of carnivore removal, measured as the sum of the total number of carnivores removed from the farm in the preceding year, as reported by farmers. Regressions included a number of control variables such as length of time on the farm (years), location (longitude and latitude), farm size (in 1,000s of ha), carnivore trend (based on the farmer's perception of increase or decrease in carnivores since owning the farm), and attitude towards carnivores (aggregated measure based on the four survey items capturing farmers’ attitudes towards carnivores). In the regressions including livestock loss, we included additional independent variables of interest: the size of the herd (number of livestock), whether or not the type of livestock (goats, sheep, cattle) was a source of cash income, and total loss of livestock measured as the number of livestock lost (goats, sheep, cattle, calves) in the preceding year.
Data analysis
Data were analysed using SPSS v. 12.0 (SPSS Inc., Chicago, USA). Missing and non-applicable responses were dropped from the analysis. To determine percentages, responses such as ‘very important’ and ‘important’ were combined as ‘important’, and ‘strongly agree’ and ‘agree’ were combined as ‘agree’. The same approach was taken for negative responses. We tested for normality of variables and used the Kolmogorov–Smirnov test and non-parametric statistics where the assumptions of normality were violated. To compare distribution of data between categories we used χ2 tests. Correlations between and within questions containing non-parametric ordinal and nominal data with non-normal distributions and unequal variances were examined using Spearman's ρ.
Principal component analyses were used to explore the structure of the data for common themes, using Varimax rotation, and loadings were assessed above a 0.50 cut-off point typically used in social science research (Bartholomew et al., Reference Bartholomew, Steele, Moustaki and Galbraith2002). The original Likert-scale responses were used to allow for maximum variance and detail. We used factor analysis as a Harman's single factor test of common method bias (Podsakoff et al., Reference Podsakoff, Mackensie and Lee2003). As multiple factors emerged from the data we conclude that common method bias did not overly influence our analyses.
We analysed the dynamics between farmers’ attitudes and actions by investigating factors related to the actual (reported), rather than perceived, levels of human–carnivore conflict and carnivore removal. One important factor related to loss of livestock to carnivores is the impact of losses based on the type of livestock farmed. We calculated the percentage of livestock loss to carnivores across different types of livestock, and compared these to the percentage of livestock lost to all causes.
Multiple regression analysis was conducted using ordinary least squares regression. We compared regression models for goat, sheep and cattle farmers for the impact of independent variables of interest (herd size, livestock as a source of cash income and number of losses) against a base model that only included control variables. All the regression equations were statistically significant. We excluded a few outliers in the regressions for actual level of carnivore removals but also checked that the results held via a robustness test that included these outlier observations.
Results
Namibian emerging commercial farmers’ attitudes towards carnivores
The majority of emerging commercial farmers (52.4%) reported that carnivores are a ‘big’ or ‘very big’ problem. Carnivores were perceived as the greatest cause of livestock losses (31.0%), above disease (19.0%), poisonous plants (18.0%), theft (17.0%) or birthing problems (10.0%). This is not surprising given that 86.4% of farmers reported livestock losses to carnivores. Farmers appeared familiar with carnivores, identifying species with 86–100% accuracy, with the exception of spotted and brown hyaenas, which were only correctly identified in half of the cases. When asked if they liked having carnivores on their farms, 39.0% responded negatively versus 28.1% positively (χ2=13.24, df=4, P=0.010).
Some 40.8% of farmers were keen to have all carnivores removed from their farmland (χ2=11.28, df=4, P=0.024), and 32.1% of respondents believed the only way to reduce livestock loss is by removing all carnivores but this result is not statistically significant (χ2=5.11, df=4, P=0.276). In contrast, farmers who viewed carnivores as having an ecological role on their farms (48.0%; χ2=13.85, df=4, P=0.008) were less likely to want all carnivores removed from farmland (Spearman's ρ=−0.606, P=0.010). We assessed whether these attitudes towards carnivores were measuring the same thing, via a principal component analysis. The results (Table 1) show that all four items, whether affective or cognitive, captured one underlying attitude, as all four load together onto a single component. All loadings are well above the 0.5 cut-off point. Attitudes that were positive versus negative loaded in opposite directions, as a bipolar factor. Thus farmers who had a negative attitude towards carnivores wanted them removed from their land, believed the only way to reduce livestock losses is by removing carnivores, did not believe carnivores played an ecological role and disliked having carnivores on their farm. This suggests that, taken together, these items appropriately capture attitude towards carnivores.
Perceived levels of human–carnivore conflict and intended action
Some 75.8% of farmers stated they had a carnivore problem after several livestock kills were made, and 42.7% said they had a problem when one livestock kill was made, or when livestock returned home without offspring (44.0%). Some 45.2% of farmers said they had a carnivore problem when game was killed on their farm, 56.1% of farmers stated carnivore problems were present when they sighted carnivore tracks, and 54.9% said they had a problem when sighting a carnivore.
In all presented scenarios there is a strong correlation between the perception of having a carnivore problem and the reported intention to remove carnivores. For example, 70.3% of farmers said they would be more likely to remove carnivores when several livestock were killed and less likely to do so when game was killed (40.3%). There are significant and positive correlations between the perception of a problem and action, as farmers stated they would remove carnivores when one livestock was killed (46.9%), livestock returned without offspring (42.7%), carnivores were sighted (50.0%) or carnivore tracks were seen (42.7%). The only exception was when several livestock were killed. Although this was most likely to result in farmers taking action, the correlation coefficient was not significant. We investigated these results and found they appeared to be affected by several outliers: six farmers said they would not take action even when several livestock were killed.
We tested to see if farmers distinguished between the perceived level of conflict and subsequent intention to take action, via a principal component analysis (Table 2). The level of conflict loads together with the intention to take action, suggesting that farmers view the problem and the solution as part of the same issue. In addition, it shows that farmers perceived sightings (carnivores, tracks), livestock loss and game loss as three separate issues. For example, items related to sighting a carnivore or carnivore tracks loaded together with the intention to take action. Similarly, sighting game killed and the intention to take action loaded onto a single factor. The link between the perceived level of conflict and likelihood to take action is less clear in the case of livestock loss. Farmers distinguished between level of conflict when livestock are killed (Component 4), and the intention to take action when livestock are killed or return without their offspring (Component 2).
Table 2 Principal component analysis of the relationships between perceived levels of carnivore conflict and likelihood to remove carnivores. All four factors had Eigenvalues > 1 and a visual assessment of the scree plot confirmed that all components should be considered in the analysis. The four factors explained 68.3% of the variance. See text for further details.
Predictors of reported human–carnivore conflict and carnivore removal
Although there was a difference in mean herd size for cattle (150±SD 68) and small stock (216±SD 124), carnivore predation had a greater effect on small stock than on cattle. Of all causes of cattle loss, 21.1% could be attributed to carnivores. The impact of carnivores on loss of small stock was much greater: 55.6% of all goat loss and 54.8% of all sheep loss was attributed to carnivores. The difference in the impact of losses (whether to carnivores or other causes) was statistically significant and much greater for small-stock loss than cattle loss (Table 3).
Table 3 One-way Scheffe test comparing the percentage of livestock loss to carnivores and livestock loss to all causes between cattle, goats and sheep. The difference in the percentage of loss between types of livestock is indicated. Standard errors are given in parentheses.
*P<0.05; **P<0.01; ***P<0.001
Because the impact of losses was felt more severely by small-stock farmers we expected that human–carnivore conflict levels and removal of carnivores would differ between small-stock and cattle farmers. We investigated these relationships via regression analysis. For actual levels of human–carnivore conflict the base model (Regression 1) explains 26.6% of variance and demonstrates that a negative attitude was significantly associated with carnivore conflict (Table 4). The variance explained increased to 46.1% for goat farmers, 39.6% for sheep farmers and 31.0% for cattle farmers. An increase in carnivore trend is positively associated with a negative attitude in the base model (Regression 1). However, this significant association disappears when other factors are accounted for (Regressions 2–4). There is a negative association between level of conflict and attitudes towards carnivores. In the case of goats having a smaller herd is significantly associated with the level of human–carnivore conflict. Livestock loss, particularly of small stock, is strongly associated with higher levels of human–carnivore conflict (Regressions 2 and 3) but loss of calves is not.
Table 4 Multiple regression analysis of factors influencing actual level of human-carnivore conflict, comparing regressions for goat, sheep and cattle farmers to the base regression that only included control variables. Regression 4 includes loss of calves as they are more susceptible to predators than adult cattle. Standard errors are given in parentheses.
Two tailed t-tests: *P<0.05; **P<0.01; ***P<0.001
For the actual number of carnivores removed (Table 5) the variance explained by the regressions is lower than in the regressions for levels of human–carnivore conflict. The R 2 of the base model (Regression 1) is low but this increases substantially in Regressions 2–4, especially in the case of goat farmers. Goat loss is the only significant predictor of carnivore removal, and no other variables significantly predict actual levels of carnivore removal.
Table 5 Multiple regression analysis of factors influencing actual levels of removals of carnivores, comparing regressions for goat, sheep and cattle farmers to the base regression that only included control variables. Five outliers were excluded from the regression. Standard errors are given in parentheses.
Two tailed t-tests: ***P<0.001
Discussion
We found that overall the attitudes of the emerging commercial farmers do not differ markedly from other categories of farmers (Conover, Reference Conover1994; Kellert et al., Reference Kellert, Black, Rush and Bath1996; Marker, Reference Marker2002). Negative attitudes towards carnivores prevail, with many farmers expressing the desire to have all carnivores removed from farmland. These negative attitudes were often associated with the perception of carnivores being a problem. In addition, there was a significant negative relationship between attitudes towards carnivores and level of conflict, indicating that when farmers have a more negative attitude towards carnivores they are also likely to perceive a higher level of carnivore conflict.
We also found that the perception of a problem seemed a sufficient motivator for farmers to want to remove carnivores from their land. In many cases simply seeing a carnivore or its tracks was perceived as a problem and farmers indicated they would take action against carnivores. Studies elsewhere corroborate this. Kellert et al. (Reference Kellert, Black, Rush and Bath1996) and Dickman (Reference Dickman2005) found that attitudes towards carnivores are overshadowed by the perception of a problem and that this determines peoples' actions. Nonetheless, livestock losses, in particularly goat losses, were significant predictors of actual conflict. Our results are consistent with other results showing that human–carnivore conflict intensifies with livestock loss (Conover, Reference Conover1994; Oli et al., Reference Oli, Taylor and Rogers1994; Sillero-Zubiri & Laurenson, Reference Sillero-Zubiri, Laurenson, Gittleman, Funk, Macdonald and Wayne2001).
However, while livestock loss and negative attitudes towards carnivores predict higher levels of human–carnivore conflict, they did not predict actual removal of carnivores reported by farmers, except in the case of goat losses. This suggests that while farmers report their intention to remove carnivores they are not actually likely to remove them. When taking this into account together with the lack of correlation of several livestock killed and removing carnivores, we speculate that farmers who lose several livestock to carnivores lack the skills to manage livestock effectively, including the option to remove carnivores from their land. Verification of this could substantiate the need for training or provide further insights into conflict issues.
Perceived loss of livestock attributed to carnivores may be higher than the actual loss experienced by emerging commercial farmers, especially as they generally have little knowledge of carnivore behaviour and ecology and are not able to verify correctly the cause of livestock loss (Schumann & Fabiano, Reference Schumann and Fabiano2006). Other studies confirm the tendency of farmers to exaggerate losses or attribute losses to carnivores regardless of whether or not the loss is a verified carnivore depredation (Oli et al., Reference Oli, Taylor and Rogers1994; Marker et al., Reference Marker, Kraus, Barnett and Hurlbutt1996; Rasmussen, Reference Rasmussen1999). This suggests that carnivores may be removed pre-emptively as a result of perceived cause of losses rather than identifying whether such losses are related to carnivore depredation. Animals perceived as incompatible with agricultural activities are often too easily condemned as problem animals when the real cause of the conflict is inappropriate livestock management (Bothma & Glavovic, Reference Bothma, Glavovic, Fuggle and Rabie1992; Marker et al., Reference Marker, Kraus, Barnett and Hurlbutt1996; Schumann, Reference Schumann2006).
When livestock management practices are applied appropriately they often reduce livestock loss to carnivores. Indiscriminate removal tends to be counter-productive because it disrupts carnivore populations and actually increases the risk of further livestock loss (Marker et al., Reference Marker, Kraus, Barnett and Hurlbutt1996; Ogada et al., Reference Ogada, Woodroffe, Oguge and Frank2003). Combining general knowledge training with management training is a potentially effective approach as people who are more knowledgeable about carnivores tend to be more tolerant (Caro et al., Reference Caro, Borgerhoff Mulder and Moore2003; Treves & Karanth, Reference Treves and Karanth2003). Our study shows that farmers who understood that carnivores play an ecological role had a more favourable attitude and were less likely to want all carnivores removed from their farms, and farmers that viewed carnivores more positively also perceived lower levels of conflict.
However, studies of formerly advantaged commercial farmers in Namibia found that even where farmers expressed tolerance towards large carnivores and recognized their ecological role, this did not necessarily result in lower removals of carnivores (Schumann et al., Reference Schumann, Watson and Schumann2008). Lindsey et al. (Reference Lindsey, du Toit and Mills2005) and Schumann et al. (Reference Schumann, Watson and Schumann2008) found that farmers who were members of conservancies were much more in favour of having a variety of carnivores on their land than non-conservancy members. This suggests that involvement with and education about conservation could nurture positive attitudes by reducing the perception of carnivore problems and thereby human–carnivore conflict.
We found that goat losses are not only a strong predictor of human–carnivore conflict but they are also a strong predictor of carnivore removals. Goat farmers appear to be more sensitive to livestock losses given that the loss of goats, especially, accounts for very negative attitudes towards carnivores, resulting in both higher levels of conflict and higher carnivore removals. This may be because goats are often the starting point of farm production and are an important source of income (Vigne & Motinga, Reference Vigne and Motinga2005). In the case of goats, having a smaller herd is significantly associated with the level of conflict with carnivores. Similarly, other studies have found that farmers with larger herd sizes were more able to absorb economic loss caused by livestock losses and were less inclined to have a negative attitude towards carnivores (Cozza et al., Reference Cozza, Fico, Battistini and Rogers1996; Dickman, Reference Dickman2005; Thirgood et al., Reference Thirgood, Woodroffe, Rabinowitz, Woodroffe, Thirgood and Rabinowitz2005).
Cattle and calf losses did not appear to influence carnivore conflict or removal. This was unexpected as most emerging commercial farmers are weaner-calf producers (Vigne & Motinga, Reference Vigne and Motinga2005) and cow–calf operators typically experience more conflict than ox producers, given the vulnerability of calves to predation (Marker et al., Reference Marker, Kraus, Barnett and Hurlbutt1996). Presumably this could change as emerging farmers move away from their dependence on small stock as a source of cash income to cattle production. Human–carnivore conflict mitigation strategies therefore need to be developed for emerging commercial farmers, not only emphasizing how to manage losses of small stock to reduce conflict but also livestock management of cattle as farmers diversify.
The impact of livestock losses on emerging commercial farmers is much greater than on formerly advantaged commercial farmers. In the case of formerly advantaged farmers 61% of their farms are > 7,000 ha and 13% have a farm > 15,000 ha (Marker et al., Reference Marker, Kraus, Barnett and Hurlbutt1996). The mean farm size of the emerging commercial farmers in our study was 4,600 ha, with 90% of farms < 7,000 ha. Formerly advantaged farmers have a mean cattle herd of 800 and small stock herd size of 597 (Marker et al., Reference Marker, Kraus, Barnett and Hurlbutt1996) compared to the mean of 150 cattle and 216 small stock of emerging commercial farmers in our study. The latter lose 2.0% of cattle to carnivores compared to 1.1% for formerly advantaged farmers, and 9.0% of small stock compared to 6.5% for formerly advantaged farmers. In addition, mean loss data do not reflect the true extent of the impact in many cases, as losses are not equally distributed. Thus even where actual livestock losses are below perceived losses the impact on individual households can still be devastating (Oli et al., Reference Oli, Taylor and Rogers1994; Cozza et al., Reference Cozza, Fico, Battistini and Rogers1996; Thirgood et al., Reference Thirgood, Woodroffe, Rabinowitz, Woodroffe, Thirgood and Rabinowitz2005). In many cases the emerging commercial farmers may not be in as strong an economic position as formerly advantaged farmers to withstand the impacts of predation. Smaller herd sizes, relatively low calving percentages, reliance on small stock both as a source of cash income and sustenance, and a lack of diversity in farming production are all factors that exert pressure on emerging commercial farmers.
Whether the extent of a carnivore problem is real or perceived, removal of carnivores will continue if the underlying attitude of a broad spectrum of farmers is negative and the perceived level of conflict is high. Our work indicates the need for an interdisciplinary approach to combine conservation education with agricultural training. The challenge lies in moving the focus of farmers away from the removal of carnivores and towards pro-active livestock management techniques to reduce losses. This will require integrated interdisciplinary training in carnivore ecology and kill identification, to replace perceptions of loss with accurate verification, and training in livestock management to reduce losses to carnivores and other causes.
A sense of ownership over human–carnivore conflict and understanding the role of carnivores help build positive attitudes. By shaping perceptions, positive attitudes can be cultivated before the human–carnivore conflict escalates to a point where farmers become resentful and unwilling to work with the conservation sector. Some NGOs are taking an integrated approach to carnivore conservation training. Further research is needed to quantify the outcomes of this approach to determine if perceptions are being positively influenced and if the conflict is escalating, or not.
Acknowledgements
We would like to thank the Cheetah Conservation Fund (CCF) under the directorship of Dr Laurie Marker for making this study possible, the CCF staff, particularly Lorraine Bowden, Josephine Henghali and Gebhardt Nikanor for help with the surveys, Matti Nghikembua for his help with the map, and the emerging commercial farmers for their patience in sharing information.
Biographical sketches
Bonnie Schumann is interested in carnivore conservation, with a particular focus on resolution of human–carnivore conflicts occurring outside protected areas. Judith Walls is interested in the human aspects of conservation and looks at the role of individuals and businesses in environmental management. Victor Harley is an environmental consultant with diverse interests ranging from wildlife monitoring and census to sustainable agriculture and best practice.
