Roelof Burger

Comparing the Effect of Modeled Climatic Variables on the Distribution of African Horse Sickness in South Africa and Namibia

ABSTRACT: Africa horse sickness (AHS) is a lethal disease of horses with a seasonal occurrence that is influenced by environmental conditions that favor the development of Culicoides midges (Diptera: Ceratopogonidae). This study compared and evaluated the relationship of various modeled climatic variables with the distribution and abundance of AHS in South Africa and Namibia. A comprehensive literature review of the historical AHS reported data collected from the Windhoek archives as well as annual reports from the Directorate of Veterinary services in Namibia were conducted. South African AHS reported data were collected from the South African Department of Agriculture, Forestry, and Fisheries. Daily climatic data were extracted for the time period 1993–2011 from the ERA-interim re-analysis dataset. The principal component analysis of the complete dataset indicated a significant statistical difference between Namibia and South Africa for the various climate variables and the outbreaks of AHS. The most influential parameters in the distribution of AHS included humidity, precipitation, evaporation, and minimum temperature. In South Africa, temperature had the most significant effect on the outbreaks of AHS, whereas in Namibia, humidity and precipitation were the main drivers. The maximum AHS cases in South Africa occurred at temperatures of 20–22° C and relative humidity between 50–70%. Furthermore, anthropogenic effects must be taken into account when trying to understand the distribution of AHS.

Bird species richness and densities in relation to sulphur dioxide gradients and environmental variables

The expansion of coal-fired power stations in South Africa has resulted in growing environmental concerns as they are the largest emitters of sulphur dioxide (SO2). Sulphur dioxide emissions from power plants pose a potential threat to avian populations. However, the effect of SO2 pollution on bird communities is poorly understood. Using point counts we investigated the relationships of bird species richness and species-specific density with SO2 concentrations around Matimba power station. Environmental parameters were derived from remotely sensed data and data reduction was performed using principal component analysis. Generalised linear mixed models were then used to infer the relationships of bird species richness and species-specific densities with SO2 concentrations and the environmental variables. Our results revealed that SO2-polluted air had no influence on bird species richness and densities in our study sites, but SO2 levels were below annual national ambient air quality standards. Vegetation productivity was found to have a greater influence on species densities than SO2 pollution. Monitoring of bird population changes around Matimba power station once neighbouring Medupi power station is fully operational is recommended, as SO2 content of the air will increase significantly, and species may be sensitive to this increase in SO2 levels.