Buffalo genetics: Why should we assess?©

Following on an introductory article in the three-part series, DR BEN GREYLING, programme manager of the ARC Animal Production Institute of Beef Cattle Improvement highlights important factors that may affect the genetic status of Cape buffalo.


The Cape buffalo Syncerus caffer caffer is one of four genetically and phenotypically recognised subspecies of African buffalo that once roamed the continent in numbers exceeding a few million. Historically, the species inhabited nearly the whole of sub-Saharan Africa, constituting up to 35% of the large herbivore biomass, making them a very important component within the ecosystem. The population dynamics of Cape buffalo, or black gold as they are often referred to, have been impacted upon over centuries by climatic fluctuations, habitat fragmentation, over hunting, droughts and disease. The latter, of course, is central to the fact that strict movement-control regulations are imposed on buffalo.

Today, an estimated 112 000 Cape buffalo occur in southern Africa, and although a few free-ranging populations still exist, most populations, especially the larger ones, are confined to designated conservancies. In South Africa, a significant number of buffalo is also found on wildlife ranches.

If one considers the factors that affect the genetic status of these different populations, it is clear that scientifically based management and conservation strategies are needed to ensure sustainability. Fragmented and small populations, for instance, are prone to genetic drift, resulting in a decreased level of genetic variation and potential loss of fitness.

The advent of molecular genetic tools enabled us to gain insight into many of the processes that affect the dynamics of buffalo populations, and most studies focused on large populations in east and southern Africa, including the KNP and Hluhluwe-iMfolozi populations (HiP) in SA. A few of the most important factors that may affect the genetic status of both large and small populations will be highlighted, with specific relevance to genetic variation, the degree to which populations are genetically differentiated, the effective population size (an indication of a population’s ability to sustain genetic variation), levels of gene flow within and among populations and levels of inbreeding.

Genetic characterisation of large populations
Differentiation and variation
Over the last more than ten years research has indicated historically significant migration and subsequent gene flow among Cape buffalo populations across the continent, resulting in populations from southern and east Africa being only marginally different genetically. Buffalo from central and south-western Africa, however, (which excludes the Cape buffalo), form distinctly different lineages (subspecies), thus necessitating the preservation of these subspecies separately. The migration was predominantly north to south, probably in response to vegetation changes in the distant past (Pleistocene period). In SA, the fact that genotypes (or genetic lines) from the Kruger National Park (KNP) and other eastern African populations also share very high levels of similarity, further supports the migration theory.

The levels of population differentiation (or being genetically different) have implications for management and conservation. In the event that little population differentiation exists between populations, as is the case with many Cape buffalo populations from both east and southern Africa, a regional scale management approach is proposed. The very small genetic differences between the two populations thus invalidate the misconception that Cape buffalo populations from east Africa is genetically ‘very different’ from buffalo in SA. It has also been shown that with regard to genetic variation, KNP has a higher level of variation than many of the east African populations, based on mitochondrial DNA marker studies. There are, of course, recognised phenotypic differences among the populations, which is the product of interaction between genetics and the environment over time.

It is quite remarkable that most large Cape buffalo populations exhibit high levels of genetic variation, considering the fact that the rinderpest outbreak during the late 1800s dramatically reduced their numbers. In SA alone it is estimated that more than 90% of the buffalo succumbed to the disease, together with more than 2,5 million head of cattle. This raised concerns that the rinderpest might have created a bottleneck effect, potentially severely reducing genetic variation. However, the moderate to high levels of genetic variation we see today can be attributed to, amongst others, the rapid recolonisation of the populations following the outbreak of the disease. Buffalo, especially the males, are known to be highly dispersive, ensuring gene flow over vast distances. Of course, it may be that the bottleneck effect may have been over estimated and that significantly more animals, having themselves high levels of genetic variation, survived than what was believed to be the case.

Genetic drift is another important factor to consider since it affects dynamics, especially when dealing with smaller populations. It can result in a reduction of genetic variation, potential inbreeding and eventual loss of fitness (inbreeding depression). A few populations in SA have been shown to have experienced drift, and unless they are augmented with ‘new’ genetic material (e.g. through translocations), current levels of variation will not be sustainable. In fact, variation will systematically erode. HiP has been shown to have experienced drift, probably due to the rinderpest bottleneck, and exhibits significantly lower levels of genetic variation compared to KNP. A contributing factor to the low level of genetic variation for HiP may be that the founder population, following the bottleneck, could have been genetically impoverished. Despite the fact that the genotypes of KNP and HiP share high levels of similarity, drift in HiP has resulted in the two populations being significantly differentiated from each other (Figure 1). The latter, however, does not suggest that the two populations require separate genetic management strategies.  

Another very important genetic parameter to understand is the effective population size, one of the most important indicators of a population’s ability to maintain genetic diversity. Relating normal census sizes to sustainability may be misleading; the ratio between census size and effective population size is a more accurate method of assessment. A number of studies have shown that several populations in southern and eastern Africa (e.g. HiP, St Lucia and Addo) have low effective population sizes, and unless augmented with ‘fresh’ genetics (e.g. through translocations), will experience genetic erosion in the long term.

Dynamics within ranched populations and herds
Managing genetics on buffalo ranches is of particular importance in view of the implications of fragmented small populations on genetic variation, and also bearing in mind the extent to which human intervention plays a role on ranches. Selection of breeding individuals and gene flow, for instance, is often facilitated through management. Inbreeding is one of the most prominent threats encountered in small populations, and recordkeeping, especially with regard to pedigree data, has become an essential tool to prevent close relatives from mating with each other.
Paternity tests, using DNA technology, is a valuable tool to be used not only to verify parentage, but also to maintain pedigree records. The technology can also be used to assess the level of genetic variation within entire herds / small populations.

Male dominance have been shown to be very strong among herds in large conservancies, implying that the effective male population size can be very low as a result of a very small percentage of reproducing males. This phenomenon may result in what is called the “male inbreeding effect”, which causes a reduction in genetic variation and which may be particularly prominent in small herds. Monitoring of male dominance through genetic testing can be very useful to detect ‘over representation’ of genes from dominant males. Interestingly, the environment has been shown to play a role in male dominance. In KNP, for instance, particular ‘bull lines’ (bulls with specific genetic profiles or genetic make-up) dominate depending on the availability of good vegetation. Even more fascinating is that their dominance is also related to a biased sex-ratio of calves produced. This phenomenon is attributed to genes on the Y-chromosome being switched on and off in reaction to environmental changes. It is likely that this phenomenon will prevail within small populations / herds, ultimately affecting their dynamics and composition.
To conclude
In order to devise interventions aimed at conserving biodiversity, it is vital to understand and uncover the driving forces behind population dynamics. By studying large populations, we have gained insight into these forces, and furnished baseline information regarding genetic parameters of Cape buffalo populations throughout Africa. The availability of this information can also be used as a valuable tool to benchmark genetic parameters of small populations, complementing existing management and conservation practices in the process. Although molecular genetic technologies will undoubtedly play an ever-increasing role in the characterisation of large populations, it will also add value to the currently flourishing buffalo-ranching industry in South Africa.

Figure 1. Genetic differentiation between KNP and HiP. An example of how genetic drift can result in significant differentiation between two large Cape buffalo populations. The genetic distance between them is high enough to enable the assignment of individuals to their population of origin with very high accuracies: 99,4 % of all individuals could be assigned correctly to their respective populations of origin. The results are based on data from a large sample size that was genotyped using DNA markers.

© Game & Hunt. Published Volume 18/12 pp 53,55

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