Age and sex composition counts of wildlife Ogutu et al. (2006), in collaboration with the World Wide Fund for Nature (WWF), carried out two further vehicle ground sample counts of impala, warthog, topi, hartebeest, zebra, and giraffe including their age and sex. These counts were conducted in the MMNR, Koyiaki and a small section of Siana ranch in November 2003 and April 2004. The November 2003 survey was also conducted during the dry season. In contrast, the April 2004 survey was conducted

in the late-wet season. They used a strip-transect sampling technique assuming complete census of all animals within a fixed strip width of 100 m either side of the transect centerline (Ogutu selleck compound et al. 2006). The transects were distributed over the MMNR and pastoral ranches in proportion to their areas,

with 22 transects established in the reserve and 13 in Koyiaki. Each transect was 10 km long. After every 1 km along each transect, the vehicle was stopped and the numbers, age class relative to adult size, sex and GPS locations of wildlife were recorded within 200 m on either side of the transect centerline. These species were classified, whenever possible, into three age classes: newborns (<1 month), juveniles (1–18 months), adults (>18 months). A combination of horn shape and length and body size were used to assign the herbivores to sex and age categories, PFKL however, ages were not assigned to adults (Sinclair BIBF 1120 cell line 1995; Ogutu et al. 2008). Only the number of individuals sighted per age class in each transect, summed over all transects in the reserve and the ranches, from this dataset were used in analyses. Comparing wildlife and livestock densities between landscapes To account for clustering, non-normality and non-homogenous variances of animal counts, and varying frequency of counts we used negative binomial regression model

for overdispersed count data to compare the mean density for each herbivore species in each 5 × 5 km2 grid cell between the MMNR and Koyiaki pastoral ranch using the aod package in R (Lesnoff and Lancelot 2010; R Development Core Team 2010). More specifically, we used the log link click here function and specified the variance function for the negative binomial model as φu(1 + (u/k)), where u is the mean, φ is the overdispersion parameter and k is the ‘aggregation parameter’. Differences in the expected herbivore counts between landscapes were tested for significance using the Wald Chi-squared test (Draper and Smith 1998). A similar analysis was performed to compare the mean densities from the ground mapping censuses per 1 × 1 km2 grid cells between the MMNR and Koyiaki pastoral ranch (Reid et al. 2003).