Evaluating the protection of wildlife in parks: the case of African buffalo in Serengeti
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Human population growth rates on the borders of protected areas in Africa are nearly double the average rural growth, suggesting that protected areas attract human settlement. Increasing human populations could be a threat to biodiversity through increases in illegal hunting. In the Serengeti ecosystem, Tanzania, there have been marked declines in black rhino (Diceros bicornis), elephant (Loxodonta africana) and African buffalo (Syncerus caffer) inside the protected area during a period when there was a reduction of protection through anti-poaching effort (1976–1996). Subsequently, protection effort has increased and has remained stable. During both periods there were major differences in population decline and recovery in different areas. The purpose of this paper is to analyse the possible causes of the spatial differences. We used a spatially structured population model to analyze the impacts of three factors—(i) hunting, (ii) food shortage and (iii) natural predation. Population changes were best explained by illegal hunting but model fit improved with the addition of predation mortality and the effect of food supply in areas where hunting was least. We used a GIS analysis to determine variation in human settlement rates and related those rates to intrinsic population changes in buffalo. Buffalo populations in close proximity to areas with higher rates of human settlement had low or negative rates of increase and were slowest to recover or failed to recover at all. The increase in human populations along the western boundary of the Serengeti ecosystem has led to negative consequences for wildlife populations, pointing to the need for enforcement of wildlife laws to mitigate these effects.
KeywordsAfrican buffalo Animal monitoring data Enforcement Illegal hunting Instantaneous rate of population change Serengeti National Park
Conservation has traditionally responded to potential loses of biota by establishing legally protected areas (Pressey 1994; Rodrigues et al. 2004). Wittemyer et al. (2008) have shown that average human population growth rates on the borders of protected areas in Africa and Latin America were nearly double the average rural growth, suggesting that protected areas attracted human settlement. People perceive or obtain benefit from their proximity to such areas (de Sherbinin and Freudenberger 1998; Scholte 2003) but, there could be a concomitant threat to biodiversity within them. Many species are continuing to decrease within protected areas (Brashares et al. 2001; Newmark 2008) often due to the illegal wildlife harvesting for meat and trophies (Milner-Gulland et al. 2003). This is particularly true for African nature reserves where local species extinctions are directly linked to human population proximity, high reserve perimeter to area ratios, and bushmeat hunting (Brashares et al. 2001; Ogutu et al. 2009).
In the Serengeti ecosystem, Tanzania, there have been marked declines in black rhino (Diceros bicornis), elephant (Loxodonta africana) and African buffalo (Syncerus caffer) inside the protected area (Dublin et al. 1990b; Metzger et al. 2007; Sinclair et al. 2007). Declines in the numbers of large herbivores were attributed to cessation of anti-poaching activities during a period of economic decline. Analysis of the trends in the buffalo population over the whole area has suggested that population change was primarily due to illegal hunting, and that enforcement of wildlife laws reduced the illegal offtake (Hilborn et al. 2006) a conclusion also reached for other areas (Hilborn et al. 2006; Jachmann and Billiouw 1997; Keane et al. 2008; Leader-Williams and Milner-Gulland 1993). Using 50 years of buffalo census data, Hilborn et al. (2006) established that illegal hunting and enforcement activities could account for the overall trends in buffalo population yet examination of the buffalo total counts indicated variation in the buffalo population recovery; some areas have almost completely recovered from the population low of 1994 and other areas have failed to recover. Therefore, the main purpose of this paper is to analyse the possible causes of these spatial differences.
Buffalo are known to be targeted by illegal hunters (Sinclair 1977). Park rangers who actively search for snares and signs of illegal hunting have identified buffalo carcasses in the field (Hilborn personal observation) and buffalo meat appears in villagers bushmeat diets (Ndibalema and Songorwa 2007). Illegal hunting remains a large threat to conservation efforts in the Serengeti (Holmern et al. 2007; Kaltenborn et al. 2005; Loibooki et al. 2002) and, therefore, we determined whether illegal hunting was a contributing factor to the spatial differences in buffalo recovery.
Materials and methods
The Serengeti-Mara ecosystem is located east of Lake Victoria and northwest of the Ngorongoro highlands and the Rift Valley (Fig. 1) and is described elsewhere (Sinclair and Arcese 1995b; Sinclair et al. 2007; Sinclair and Norton-Griffiths 1979). Serengeti National Park is designated IUCN land category II and is managed for ecosystem protection and recreation. A network of game reserves and conservation areas are located to the west and east of Serengeti National Park (Fig. 1). This whole area is known as the Greater Serengeti Ecosystem. The east of the national park boundary is settled by Maasai pastoralists who rarely hunt for wild meat and their lifestyles tend to be consistent with conservation of wildlife (Polansky et al. 2008). In contrast, human settlements to the west of the park boundary do consume game meat regularly (Holmern et al. 2006; Loibooki et al. 2002; Nyahongo et al. 2005).
Buffalo total counts
Beginning in the early 1960s, buffalo populations were censused by aerial survey every few years. A detailed description of methods is given in Sinclair (1977). In 1970 all observations of buffalo (individuals and herds) in the Greater Serengeti Ecosystem were plotted on a map of the ecosystem. These observations were later incorporated into a GIS using the Universal Transverse Mercator (UTM) coordinates. From the 1992, 1998, 2000, 2003, and 2008 censuses similar data were obtained using global positioning system (GPS) technology. The buffalo population was close to its maximum in 1970 and this census was therefore used as the baseline with which we compared the following years. We determined the instantaneous rate of change in the buffalo population from 1970 to 2008 by zone. Zones within the park (Fig. 1) represent distinct geographical and ecological areas. Buffalo herds are relatively sedentary, confine themselves to a home range of less than 20 km in diameter, and so rarely cross over zone boundaries (Sinclair 1977). These zones were the north, far east, far west, center, south and short grass plains. Because buffalo do not use the short grass plains we did not include this area in our analysis. We summed buffalo numbers within each zone for each year that we had census data and compared these numbers with those in 1970 to show the relative change. A major drought in 1993 affected all zones and caused a 40% mortality (Sinclair et al. 2007, 2008).
Spatial population dynamics model
where r is an intrinsic rate of growth assumed to be the same in all zones. Carrying capacity for zone a is ka and Sy is survival from drought in year y, assumed to be 1.0 for all years except 1993, the year of the drought. The exploitation rate from hunting in zone a and year y is ua,Py is the relative hunting effort in year y, va is the relative hunting effort for zone a, and q is a scalar relating hunting effort and area specific vulnerability to the exploitation rate. Eay is the number of buffalo in zone a killed by lions in year y, Ly is an index of the number of lions in buffalo habitat in year y, and z scales the lion abundance index to lion mortality rate.
The relative hunting effort (P) is poachers arrested per number of patrols day−1 (see Hilborn et al. 2006. Figure 1b). The zone specific vulnerability parameters (va) were estimated relative to that in the north which was fixed at 1.0. The parameter q is the harvest rate per unit of hunting effort (P) in a zone with v = 1.
Food supply and rainfall
While rainfall was the primary determinant of the food supply in most of Serengeti (Fig. 1), the far east differed by lacking riverine grassland. In this zone rainfall was less suitable as a predictor of resources (Sinclair 1977). Hence, thirdly we estimated the carrying capacity for each zone independent of its size and rainfall.
Intrinsic rate of increase and lion predation
Fine scale buffalo population rate of increase (1970–1998 and 2000–2008)
Relation between buffalo numbers and human densities
We calculated the distance of each buffalo observation to the nearest edge of the park where there was human settlement in 1970, 1992, 1998, 2000, 2003 and 2008. Using Pearson’s correlation coefficient we determined the spatial correlation between buffalo counts and distance to humans (see below).
Hunter population estimates
We used two years of human census data, 1978 and 2002 (Bureau of Statistics, Dar es Salaam) for the area west of the Serengeti National Park boundary to Lake Victoria. Census data were organized by local areas called wards (similar to US counties). The area (km2) of each ward was known and we converted the ward population to density (humans km−2). From the human density we calculated the hunter density. Hunter density is a proportion of human density, which changes with the distance from the protected area boundary. The equation is that given in Campbell and Hofer (1995). For each ward, we determined the instantaneous rate of change of hunter density between 1978 and 2002.
Total population numbers of buffalo in the protected area
Buffalo population trends by region
Spatial population dynamics model
Candidate models of buffalo population changes over the last 50 years in the five regions of the Serengeti
Equal k in all zones, no hunting, lions or drought
Equal k, equal hunting in all zones, no lions or drought
Equal k, lion predation, no hunting or drought
Equal k, hunting different by zone (va estimated), no lions or drought
Equal k, hunting different by zone (va estimated), drought included (S1993 estimated), no lions
K different for far east, hunting different by zone (va estimated), drought included (S1993 estimated), no lions
K different for far east, hunting different by zone (va estimated), drought included (S1993 estimated), lion predation included
Final model parameter estimates
Final ‘best’ model parameter estimates that predict population changes for the five different regions (L was 10% for the final model). Hunting was greatest in the North zone
Hunting mortality in 1978
Average lion mortality rate (%)
Fine-scale analysis of buffalo and human population changes
This pattern of buffalo population growth is the converse of the human population growth adjacent to the protected area (Fig. 7b). Hunters living within 40 km of the protected area were estimated as 20,000 in 1973 and 36,000 in 2002. The instantaneous rate of increase was 0.03 per year, similar to the national average. Numbers within 10 km of the protected area increased from 13,000 to 24,000, a similar rate of change (3% per year). However, the population adjacent to the northwest border of the park has increased at a faster rate (4.4% per year) mostly through immigration (Campbell and Hofer 1995). In 1978 human population densities varied ranging from 0.1–954 people km−2 and in 2002 the range in densities spanned 15–2,840 people km−2.
Buffalo increase and distance to reserve boundary
In 1970, prior to the decrease phase there was no spatial relationship between buffalo occupancy and distance to the reserve boundary. During the hunting phase there was a positive relationship between distance and buffalo numbers (1992, r = 0.15, P-value < 0.001, and 1998 r = 0.23, P-value = 0.03). When enforcement was increased (2000–2008) there was no relationship between distance and buffalo.
Our results explain the spatial variation in buffalo population recovery across the protected area and elaborate on the work of Hilborn et al. (2006), which confined itself to the time trends of the whole buffalo population. Buffalo population changes are best explained largely by hunting but model fit was improved with the addition of predation mortality. Food supply was only a factor in areas where hunting was least, namely the east and south. In addition, our spatial results are consistent with the trends in the elephant population (Sinclair et al. 2007, 2008). Elephants behave more as one cohesive population, which moves away from disturbed areas and finds sanctuary in more peaceful areas, so that densities are a reflection of movements.
Buffalo on the other hand are extremely philopatric and remain within their home range irrespective of the disturbance (Sinclair 1977). Therefore, buffalo numbers reflect the local dynamics of an area. The buffalo populations in close proximity to areas with higher rates of human settlement had low or negative intrinsic rates of population increases and, therefore, were either slowest to recover or failing to recover at all. Areas of slow buffalo recovery are consistent with the previous analysis by Campbell and Hofer (1995), which identified similar areas of high human exploitation on a different suite of species, namely the resident antelopes. Hunter populations reside along the western and north-western boundaries of the protected area, and incursions are made into the park from the west. Human populations have increased considerably in the past 30 years (Fig. 7b) and buffalo numbers in the north and the far west reflect these changes in human populations along the boundaries. In contrast, the strong gradient in food supply, which is determined by the rainfall gradient (Fig. 1), is opposite to the trends in population recovery, i.e. areas of high food supply are those with the least recovery.
In conclusion, the increase in human populations along the western boundaries of the Serengeti ecosystem has led to negative consequences within the protected area on wildlife populations, as indicated by trends in the buffalo population. This result is consistent with the predicted impacts from increases of human settlement around protected areas elsewhere in Africa (Harcourt et al. 2001; Wittemyer et al. 2008). Hilborn et al. (2006) suggested that these negative consequences are mitigated by increases in enforcement of wildlife laws by protected area authorities.
This work was made possible by the contribution of data from many sources; International Livestock Research Institute provided the Kenya human population data, M. Loibooki provided the Tanzanian human population census data, the Tanzania Wildlife Research Institute and the Frankfurt Zoological Society permitted us to use the current animal census data. We are grateful to Tanzania National Parks and Tanzania Wildlife Research Institute for their continued support of the Serengeti Biodiversity Program. This work has been funded by the Natural Sciences & Engineering Research Council of Canada and the Frankfurt Zoological Society.
This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.
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