The African savanna elephant (Loxodonta africana) is a keystone species in southern Kenya, and due to poaching and crop raiding the future of this megaherbivore is uncertain. The Maasai community is working towards sustaining Kenya’s elephant populations by opening up a corridor between the Maasai Mara Game Reserve and the Amboseli Game Reserve in Kenya’s Rift Valley. Elephants from both parks will have the ability to migrate into this new area. Since creation of the corridor, a new population of elephants has colonized the central area; however, we know little about their herd structure, including, where they came from or the sex ratio. In this study we used genetic markers to determine the sex ratio of the elephant populations serving as sources for elephants moving into the corridor, as well as the sex ratio of the elephants that have moved into the corridor since its inception. To determine the sex of individual elephants we collected dung samples from the three areas of interest. We extracted DNA from the samples, and used microsatellite genotyping with 8 different loci to identify unique individuals within the sample pool. Individuals were sexed by first amplifying genetic makers on the X and Y chromosomes (ZFX/ZFY), and then cutting the PCR product using a restriction enzyme that recognized a Y specific restriction site.
Initial samples of 13-18 individuals per population indicate that sex ratios of the two source populations are highly and significantly (by Sign test, P<0.05) female-biased, with females comprising 84-89% of individuals in each sample. Based on a preliminary sample of five individuals, elephants in the corridor appear to have a more even sex ratio (60% female). We believed the population in the corridor may contain more males, because males are the sex to disperse within elephant species. Knowing the sex ratio of elephant populations within this area will give us a better understanding of herd composition, migration patterns, and the movement of genes between populations. This information will enable park and wildlife managers to design more effective conservation plans.