Current Students
Mr Brian Mandigora (PhD)

Empirical growth models are important forest management and planning tools. However, in light of the more frequent extreme climate events like floods and droughts experienced over the past few decades, it has become more difficult to accurately forecast forest growth and yield. Past rotations no longer accurately explain future rotations in commercial plantations. Furthermore, current models do not explain how wood properties; which are highly commercially significant; respond to daily climatic events like rainfall.

Brian, who is co-supervised by Prof Ben Du Toit, is seeking in his Ph.D. to develop cutting-edge models for growth, yield and wood properties at appropriate spatial and temporal scales in the KwaZulu-Natal region of South Africa. He will make use of data from two collaborating forest companies, Mondi and SAPPI from research plots to build and validate the models.

Brian is originally from Zimbabwe, where he obtained his bachelor’s degree.  He subsequently undertook an M.Sc. degree from Stellenbosch, before beginning his Ph.D. in 2018.  His interests lie in the development and application of models to manage challenges, as well as to exploit opportunities, that climate change and climate variation present in agriculture, particularly forestry.

Mr Gerard Lindner (PhD)

Gerard, who is currently based in the Sabie area, and spends part of his time managing a timber farm, is researching the question of error in models.  He is particularly interested in understanding and quantifying error propagation.  He is exploring the components of error in dominant height models and Site Index prediction, as well as errors in field measurements and how these propagate through to errors in final volume estimation.


Mr Erich Seifert (PhD)

Accurate data on forest structure, stocking volume, biomass, and potential product yield forms the base for efficient forest management. Traditional methods are constrained to only a few tree variables such as tree height and diameter. Information on utilisable stem length, stem taper and sweep, which govern the product yield in a saw mill to a large degree are only estimated by models or not available at all. In consequence stand specific variability is not fully accounted for. The last decades brought about new methods for measuring more tree variables. In particular, high-resolution airborne sensors and new terrestrial sensors such as laser scanning are promising technologies that have undergone successful tests for their application in Forest Mensuration.

Airborne photography is based on the combination of overlapping photographs and provides areal data of a wider spatial range. Modern photogrammetric algorithms such as Structure from Motion (“SfM”) are used to calculate three-dimensional point clouds by combining a large amount of photos. Corresponding points, which identify the same features on different photos are used for this registration process. It has been successfully demonstrated that these methods can be used to determine the crown surface and derive tree heights. Additionally, the usage of multi-spectral imaging allows for identifying tree species. However, airborne photography is not able to provide accurate information on below-canopy structures such as stems and branches.  Certainly, a key challenge is that a successful combination of these methods requires an exact spatial alignment (registration) of terrestrial and airborne derived point clouds.

The objective of Erich’s thesis is to develop novel algorithms for extracting tree and tree parts from remotely sensed data, which can be used for improved combination of dense point clouds from terrestrial laser scanning and high-resolution airborne imagery for forestry applications.  Erich is co-supervised by Prof Jan van Aardt (Rochester Institute of Technology (RIT), USA).

Mr Simon Ackerman (PhD)

Co-supervised by Prof Rasmus Astrup (NIBIO, Norway), Simon is undertaking his Ph.D. project around the following topic: “Industrial forestry compartment characterisation; the effect on end of rotation processes and the forestry supply chain”

Management practices in plantation forestry aim to maximise merchantable timber yield from a compartment. This is primarily achieved by ensuring through intensive site preparation, planting stock management, clone and seedling establishment, post-plant tending, tree uniformity and reduced timber waste at harvesting.  However, in a supply chain context, the relationship between the cost of achieving optimum uniformity against the gains in yield and improved harvesting productivity are not fully understood. The increased cost may not be offset by potential higher yield, improved product quality or production costs. To this end there is a need to establish and quantify this relationship.  Simon’s project aims to to quantify this, involving the use of machine on board computing, tree data recording, terrestrial LiDAR scanning of compartments and photogrammetry.

Mr Justin Erasmus (PhD)

Structural lumber is the single most important product category for local sawmills making up 75% of all sawn softwood products in South Africa. The competitiveness of this product category in local and international lumber markets, and against alternative building materials such as steel, depends to a large extent on the mechanical product performance. Several studies in recent years have displayed an alarming trend of poor stiffness properties of SA pine – lumber from some tree resources have mean modulus of elasticity (MOE) values up to 25% lower than required for the most common structural grade in the country.  The effect of different variables on wood formation will improve the current understanding of wood cell development. The variation and causal relationships between environment and specific cell properties of wood such as MFA is currently not well understood.

Justin’s study will use a semi-process-based modelling approach to explore the effect of a dynamic environment (climate, soil nutrition, competition) on the wood formation of P. patula – the most important commercial softwood in South Africa. This will be a first for this species.  Expanding on existing modelling frameworks for P. patula will contribute to using it commercially in South Africa as a practical decision-support tool and help identify further areas in the wood formation processes which are not well understood. Together with a lumber MOE model, the framework will aid in understanding influencing factors on MOE and assist in forest management decision-making.  Overall, the outcome of this study could be used in integrated growth, wood property, processing, and economic software models which should ultimately provide forest growers and processors with a superior cultivated resource to successfully grade products to higher strength classes and increase the value yields from structural lumber manufacturing.  Dr. Drew co-supervises Justin’s study with Dr. Brand Wessels (Stellenbosch University).

Ms Ayodeji Oyedeji (PhD)

NOTE: Ayodeji’s studies are presently on hold…

Ayodeji is from Ondo state Nigeria. She obtained her Bachelor’s degree in Forestry and Wildlife Management from the University of Agriculture, Abeokuta in Nigeria. Her quest to fill the gap of a specialisation in Forestry (Growth and Yield Modelling) which is mostly dominated by male forest scientists led her to take up the great challenge of undertaking a Master’s degree in Forest modelling also at Federal University of Agriculture Abeokuta. Thereafter, she decided to proceed to Stellenbosch University to have a wider view of what it entails to be a growth and yield scientist. Her PhD Research is on the dynamics of wood formation in Eucalyptus taxa as determined by varying water availability and seasonality.  She is interested in understanding the processes of wood formation and the various accompanying changes growing wood cells and vessels undergo for optimal physiological performance.

Ms Gabi Sibiya (M.Sc.)

Gabi was born and raised in a small town called Amsterdam which is located in the Mpumalanga Province of South Africa.  Her M.Sc. project is using the process based model called CABALA (an acronym for CArbon BAlance), originally developed by Dr. Michael Battaglia (CSIRO, Australia) to provide silvicultural decision support for Eucaluptus globulus plantations. The main objectives for her project are to (1) parameterize CABALA for Eucalyptus grandis x urophylla hybrids in South Africa and (2) test how CABALA will perform in the Southern African environment through comparing the results produced by CABALA with those empirical field data.

Ms Gloria Burengengwa (M.Sc.)

Gloria is from Burundi where she pursued her undergraduate studies in Mathematics. She already has a Master’s degree in Mathematical Sciences at Stellenbosch University, which she did through the African Institute for Mathematical Sciences (AIMS). In her present M.Sc., she is interested in applying mathematics in a climate change context, which brought her to the Forestry Department.  Her research, co-supervised by Dr Drew and Prof Cang Hui,  is focused on a rural area of Zululand at the north of Durban. She is exploring optimal approaches using different mathematical modelling techniques to develop a spatial, daily grid of important daily and or monthly weather variables which will contribute of the improvement of models of agricultural and forest plantation growth.

Recently Completed Students

Mr Ben van Heerden

Mr Johan Stephan

South Africa has agreed to voluntary alignment and compliance with the United Nations Framework Convention on Climate Change, countries Reducing Emissions from Deforestation and Forest Degradation and Intergovernmental Panel on Climate Change initiatives through the South African Department of Environmental Affairs. These initiatives necessitate reduction of greenhouse gas emission, mitigation of the causes and effects of past emissions and adaption to climate changes caused through past emissions. Commercial forest plantations can play a role in mitigating the effects of anthropogenic climate change through capture of atmospheric carbon dioxide (CO2) and storage of carbon (C) in tree biomass, dead organic matter and soil carbon pools.

Understanding the role of South African forest plantations in mitigating climate change starts by accurately quantifying the carbon stored in it’s different carbon pools. Unfortunately, some forest carbon pools have been studied to a lesser extent compared to others such as the carbon captured in decomposing woody roots. Johan aims in his M.Sc study, supervised by Prof Ben Du Toit and Dr David Drew,  to determine the potential of decomposing Eucalyptus grandis x urophylla hybrid woody roots for storing carbon in one of the main pulp wood production areas of South Africa.