It is believed that the process-based model 3-PG (Physiological Principles Predicting Growth; Landsberg and Waring, 1997) can potentially play a useful role within South African forestry, both as an operational and a strategic tool. Strategic applications may include the prediction of potential productivity on a site-by-site basis; broadscale productivity estimates based on remote sensing and the spatial application of 3-PG; identification of production constraints; and estimation of carbon fluxes to help address sustainability issues. Operationally, 3-PG could complement empiricallybased models or be used in conjunction with them as a hybridised product. The challenges of this study were therefore to see whether it is possible to adapt 3-PG to predict the growth and yield of E. grandis under South African conditions, test that model predictions are consistent with observed growth data and are biologically reasonable, and to assess the practicality of using 3-PG as either a strategic or operational tool. The main emphasis of this study was to understand the internal logic of 3-PG and how physiological processes are represented, and to develop methods to objectively parameterise and initialise the model. Thereafter a detailed model validation study was performed, ending off with selected potential applications of 3-PG within the South African context. The sensitivity of predicted stand volume (SV) and leaf area index (LAI) to the values of the species-specific parameters in 3-PG was examined. These analyses enabled the development of three distinct parameter sensitivity classes: insensitive parameters (i.e. those that can be varied widely without affecting the outputs studied), sensitive parameters (i.e. those whose value strongly affects the outputs, and non-linear parameters (i.e. those for which the outputs depend in a non-linear manner on the parameter value). Minimum data requirements for the parameterisation and initialisation of 3-PG are considered in detail. Conventional methods used for the parameterisation of models, specifically 3-PG, are reflected upon. An automated parameter estimation technique was examined and used for the estimation of selected parameters. Species-specific parameters were categorised according to data source estimation and sensitivity classes. Parameters describing allometric and age-dependent relationships were assigned values using observed data from biomass harvests. Critical parameters that could not be directly assigned using observed data were the ratio of foliage to stem allocation (i.e. P2 and p2o), allocation of net primary production (NPP) to roots (TJRX and T]Rn), optimum temperature for growth (7^,) and maximum canopy quantum efficiency (acx)- These were estimated using Parameter ESTimation, by fitting model output to corresponding observed growth data. As well as species-specific parameter values, mandatory inputs required by 3-PG include weather data, site-specific factors such as site fertility (FR) and physical properties of the soils, and stand initialisation data. Objective techniques to determine these site-specific factors and the initial values for the biomass pools were proposed. Most of these data are readily available for sites where experimental trials exist, or where monitoring networks are in place. However, this is the exception rather than the rule, so alternative data and information sources are required. These, together with the need for accurate weather inputs (especially monthly rainfall) and physical properties (especially soil texture, maximum available soil water and FR) of the sites being modelled were explored. 3-PG was validated using four simple tests by comparing predicted versus observed SV. Results showed that 3-PG predictions are relatively consistent with observed stand data. Analyses performed using time-series data showed model predictions accurately tracked observed growth in response to erratic and fluctuating weather conditions. Results from the initial model validation showed production on high and low productivity sites was under- and over-predicted, respectively. Further results presented here show a similar, but less marked trend (i.e. over- and under-predictions are not as extreme), and individual biases are less than those from predictions made using another locally developed parameter set. The application of 3-PG showed that the model is able to make estimates of tree growth that are consistent with those used within the forestry site classification. This showed the considerable potential 3-PG has for strategic planning by the forest industry (i.e. projected wood supplies etc) and in research planning (refining existing site classifications). The model could be useful in predicting growth in various areas where E. grandis is not grown, assisting in future decision making. 3-PG was able to identify growth constraints on a site-by-site basis and distinguish among them, and was able to identify environmental and site limitations to plantation growth, and how they vary in space and time. These results together with predictions of site productivity demonstrate the potential for 3-PG to be used to improve existing forest site classifications. The model comparison study between empirically-based models and 3-PG showed that although the empirical models made accurate predictions of volume under static climatic conditions, under fluctuating weather conditions empirical estimates of volume were less accurate than those made with 3-PG. 3-PG can therefore be used operationally with minimum input data to predict growth using enumeration data. This is useful in saving time and cutting costs. The use of process-based models (PBMs) in general, and 3-PG in particular, needs to be "championed'' to the South African forest industry. This is necessary for two reasons. Firstly, the model and the manner with which it describes physiological processes of growth need to be explained in layman's terms. This will demonstrate how and why a process-based model can work better in a fluctuating environment than empirically based models. Secondly the comparison between 3-PG and the local empirical models needs to be presented as an example of how 3-PG can be applied on an operational basis. It is accepted that much convincing is still required. / Thesis (Ph.D.)-University of KwaZulu-Natal, Durban, 2005.

The use of remotely sensed data to estimate forest attributes involves the acquisition of ground forest data. Recently the acquisition of ground data (field based) to estimate leaf area index (LAI) and biomass are becoming expensive and time consuming. Thus there is a need for an easy but yet effective means of predicting the LAI, which serves as an input to the forest growth prediction models and the quantification of water use by forests. The ability to predict LAI, biomass and eventually water use over a large area remotely using remotely sensed data is sought after by the forestry companies. Remotely sensed LAI values provide the opportunity to gain spatial information on plant biophysical attributes that can be used in spatial growth indices and process based growth models. In this study remotely sensed images were transformed into LAI value estimates, through the use of four vegetation indices (Normalized Difference Vegetation Index (NDVI), Corrected Normalized Difference Vegetation Index (NDVlc), Ratio Vegetation Index (RVI) and Normalized Ratio Vegetation Index (NRVI). Ground based measurements (Destructive Sampling and Leaf Canopy Analyzer) relating to LAI were obtained in order to evaluate the vegetation indices value estimates. All four vegetation indices values correlated significantly with the ground-based measurements, with the NDVI correlating the highest. These results suggested that NDVI is the best in estimating the LAI in Eucalyptus grandis x camaldulensis in the Zululand region with correlation coefficients of 0.78 for destructive sampling and 0.75 for leaf canopy analyzer. Visual inspection of scatter plots suggested that the relations between NDVI and ground based measurements were variable, with R2 values of 0.61 for destructive sampling and 0.55 for Leaf Canopy analyzer. These LAI estimates obtained through remotely sense data showed a great promise in South African estimation of LAI values of Eucalyptus grandis x camaldulensis. Thus water use and biomass can be quantified at a less expensive and time-consuming rate but yet efficiently and effectively. / Thesis (M.Sc.)-University of Natal, Pietermaritzburg, 2001.

Thesis (MScFor (Forest and Wood Science))--University of Stellenbosch, 2007. / The study was undertaken to determine the potential physiological benefits to plants provided by the double colonisation of host plant roots by endomycorrhizal (AM) and ectomycorrhizal (ECM) fungi, when growing under normal and under salt stress conditions. Plants of the Eucalyptus grandis x E. camaldulensis clone were grown in a sterile soil with 0 and 75 mM NaCl and with or without infection with the fungi Glomus etunicatum (an AM fungus) and Pisolithus tinctorius (an ECM fungus). The Eucalyptus clone formed both ECM and AM in single and double inoculation. The mycorrhizal symbiosis did not provide any nutritional benefits to the hosts. The double colonisation had no effect on plant growth under normal growth conditions while single colonisations of AM and ECM reduced growth. Double colonisation reduced host plant specific leaf mass by 12% and increased total leaf area by 43% compared with the control under these growth conditions. This colonisation also reduced photosynthesis per leaf area by 29% compared with the control. The reduced photosynthesis of the double colonisation did not result in reduced plant growth because these plants may have had a high total plant photosynthesis because of their large total leaf area. The double symbiosis however did not reduce salt stress when host plants were exposed to 75 mM NaCl, while the AM fungus increased plant dry weight by 13% compared to the control. AM and ECM colonisation in the double colonised roots under salt stress was decreased by 18 and 43% compared to that in plants under normal growth. The reduced colonisation may have reduced the fungi’s abilities to be beneficial to the host plant. The double symbiosis is recommended based on the documented positive effects of this symbiosis to plant growth and the considered possible long-term benefits to host plants growing in saline soils.

South Africa depends largely on afforestation programs for its timber supplies due to the great demands for fiber and wood products. This has brought discomfort to other water users who have advocated that the effects of afforestation on water resources are detrimental to the country as a whole since South Africa is known as a water scarce country. This study has undertaken to integrate a process-based model and remote sensing data to estimate water use and productivity of Eucalyptus grandis in the Zululand areas of South Africa. The remote sensing techniques and recently developed "process based model" that is 3PG-S were used to estimate water use and productivity of Eucalyptus grandis, an economically important plantation species grown in the summer rainfall areas of South Africa. The study utilized monthly Landsat Thematic Mapper datasets and climatic data as inputs into the 3PG-S model, determined the Leaf Area Index (LAI) and Specific Leaf Area (SLA) through direct (destructive sampling) and indirect measurements (LiCor- 2000) and assessed the relationships between various vegetation indices (VI's) using correlation and regression analyses. The results suggest that all the indices, except the ratio VI, correlated significantly with LiCor-determined and destructively measured LAI values with both normalized difference vegetation index (NDVI) and Ratio Vegetation Index (RVI) (r=0.86, p / Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritburg, 2007.