- Title
- The application value and most appropriate mapping scales for site classification and evaluation in the South African forest industry
- Creator
- Sibhakabhaka, Thembisa
- Subject
- Forests and forestry -- South Africa
- Subject
- Forest products industry -- South Africa Geographic information systems
- Date Issued
- 2020
- Date
- 2020
- Type
- Thesis
- Type
- Masters
- Type
- MSc
- Identifier
- http://hdl.handle.net/10948/49281
- Identifier
- vital:41617
- Description
- The South African forest industry is challenged with aspects related to socio-political developments, conflicts with biodiversity values, uncertainties related to climate change, several biotic and abiotic risks, and a limited potential for expansion. For this reason, efficient and optimal land-use is essential, which requires sustainable forest management practices and accurate information and decision support systems. Tree growth patterns, productivity and risks vary according to changes in geology, topography, climate and soil conditions. It is therefore required that forest managers, planners and researchers have a conceptual understanding of the concept of forest site classification and evaluation. This is essential not only for improved levels resilience, but also to maintain a competitive industry in terms of socio-economic and environmental performance. The first chapter of the study aimed to investigate the perceptions and interpretations of a range of representative stakeholders from the forestry industry regarding the value, shortcomings, requirements and design of forest site classification and evaluation systems in use in the local industry. A questionnaire with 16 questions was used for this purpose, and data was analysed using quantitative and qualitative techniques. Results indicated variable levels of understanding amongst respondents of terminology and the nature of systems used in industry. Trends in responses were influenced by the background of stakeholders, the role of individuals in the value chain of forestry as well as past experiences. The perceived importance and value of potential site evaluation applications varied substantially amongst different stakeholders. Results point towards a narrow-focus application for site classification and evaluation systems for site-specific forestry, with a lesser regard with aspects of risk management and environmental performance. Several technical aspects related to site variables, data resolution and scale of presentation were also questioned by participants. Listed priorities for research and development include the integration of site classification and evaluation systems into corporate information systems, modernizing technology, more appropriate site evaluation models, advanced climatic modelling and the development of indices of water and nutrient availability related to forest productivity. There is general agreement for the development of a national forest site classification system. The value of this part of the study lies in the contribution it makes towards our knowledge of stakeholder perceptions regarding site classification and evaluation, as well as the valuable comments made by participants for the refinement of such systems that can serve as indicators for entities involved in education, governance and strategic forest management. The second data chapter of the study involved the development of high-resolution site classification systems in the form of Site Types for two selected study areas in South Africa, one located in Mpumalanga, and the other in the southern Cape. This enabled a comparative analysis with existing low-resolution Land Type classifications that were developed by different authors for the same two study areas, in terms of its reliability, accuracy and general usefulness for applications in the plantation forestry value chain. The comparison of the two types of classification systems revealed that the climate data forming part of the database were of equal accuracy and resolution. However, an obvious difference was detected in the information pertaining to soil in terms of descriptive and spatial data. In the case of both study areas, the Site Type classification systems revealed many soil and geological features that were not indicated by the lower-resolution Land Type systems. Variation in characteristics related to parent material, soil classification, soil depth, intensity of subsoil wetness and soil organic matter were not adequately reflected in these systems. This can potentially have important implications for applications such as species choice, predictions of yield, nutrient optimization, ratings of soil resilience, biodiversity management and evaluations for carbon sequestration potential. The data forming part of this study indicate that although Land Type classification systems can provide valuable support at strategic levels of planning and management, there are several limitations for use at finer scales of resolution. The final chapter of the study includes an investigation and qualitative comparison of the usefulness of Site Type vs. Land Type classification systems, based on existing knowledge in the industry. The two systems are compared in terms of its input towards the following applications: site-species matching, timber yield prediction, site amelioration / site preparation requirements, nutrient management requirements, vegetation management / weed control, management of pests and diseases, determination of risk for soil compaction, soil erosion and nutrient loss, decision making regarding forest engineering operations, prediction of wood / fibre properties, biodiversity management and lastly planning of research activities / priorities. This analysis indicated that applications that require data on only climate and general soil patterns can be supported with equal success by both types of site classification systems. On the other hand, in cases where high-resolution data on site factors are required, Land Type classification systems had numerous shortcomings and received a much lower rating of suitability. The outcome of the study can provide guidance on the development and design of future site classification and evaluation systems for the South African forest industry. High-resolution databases of key site factors should receive priority, together with the development of decision support systems based on causal relationships. This will contribute to the resilience and sustainability of an industry that is increasingly confronted with questions related to the placement, design and management of forest plantations.
- Format
- xii,131 leaves
- Format
- Publisher
- Nelson Mandela University
- Publisher
- Faculty of Science
- Language
- English
- Rights
- Nelson Mandela University
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NMU School of Natural Resource Management
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