Digital soil mapping as a tool for improved road and game drive management within Phinda Private Game Reserve, Kwa-Zulu Natal

With the development of digital technology during the last decade and the improvement of Geographic Information Systems (GIS), it has become easier for various scientific fields to predict and extrapolate data. Various organisations and institutions continuously develop algorithms and software to assist with specific challenges in multiple fields of science. These technologies and principles have also been effectively applied in the soil science field of pedology. Traditional soil mapping, although effective, is time consuming, arduous and expensive. It is thus important to develop methods whereby the soil forms of an area can be identified faster while providing accurate information to the reader/ user. Conservation areas, such as Phinda Private Game Reserve (Phinda), which covers a large area (greater than 28 000 ha) can benefit from a soil map. The importance of a proper soil map has a great many uses in conservation, but not every organisation or individual can afford it. This is where digital soil mapping (DSM) or Predictive Soil Mapping (PSM) comes into its own. Substantial research and development have been done in the form of methodology and software systems for DSM although it has not been effectively applied to conservation management. By applying these techniques, accurate and interactive soil maps were developed without the burdensome expenses or dangers associated with traditional soil observations in a conservation area. The application of DSM and the use of the soil land inference model (SoLIM) at Phinda resulted in maps based on the Fey soil-form classification as well as a soil sensitivity index (SSI). The SSI was developed based on the various soil forms present at Phinda and the factors that determine its sensitivity to various types of degradation. These digital maps indicated accuracies of 71% (Fey classification) and 72% for the SSI. The kappa values indicated a substantial agreement (0.63) for the Fey classification map and a moderate agreement (0.57) for the SSI map. The SSI was then combined with the predator sightings and the location of infrastructure and commercial lodges to derive the agreement of activities, game drives, which includes off-road driving (ORD) on sensitive soils. As erosion is a concerning problem, predominantly caused by human activities within Phinda, it was necessary to use the SSI map as a base of comparison. This digitally produced soil map will be presented to the conservation management at Phinda whereby planning can be conducted, literally, from the ground up. Proper planning will thus prevent a loss of soil and consequently a loss of biodiversity. All the information was then combined to developed recommendations for Phinda as to improve the overall road network by upgrading, removing and rehabilitating certain roads and provide advice concerning ORD. These decisions, in turn, prevent long-term soil and biodiversity loss while still providing clients with a true African bush experience.

College of Agriculture and Environmental Sciences