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The Characterisation of the Yellowwoods' Leaf Area Index The characterisation of the Yellowwoods’ leaf area index, within a southern African mistbelt forest, using Geographic Information Systems and Remote Sensing Nokwanda Gumede 214514482 A thesis submitted in fulfilment for the degree of Master in Environmental Sciences, in the School of Agricultural, Earth and Environmental Sciences, University of KwaZulu-Natal, Pietermaritzburg, South Africa Supervisor: Professor Onisimo Mutanga Co supervisor: Doctor Mbulisi Sibanda May 2020 I. Abstract Forests hold a plethora of ecological functions, that are critical in the maintenance of biodiversity. For instance, the mistbelt forests are small and fragmented forest ecosystems, which are dominated by South Africa’s national tree - Podocarpus latifolius or the ‘real’ Yellowwood. The Yellowwood trees are regarded as a priority species, because they support large communities of plants, birds and mammals, attributing to the maintenance of biodiversity. They also store carbon and provide habitat as well as resources for pollinators. Meanwhile, they produce durable, high quality timber which is harvested for cultural, medicinal and commercial use. Subsequently, the podocarps have been listed as endangered species owing to extensive logging. Current forest species productivity information is urgently required in the characterisation of forest condition, especially that of disturbed habitats which support a variety of indigenous species and contribute immensely to ecosystem resilience. Leaf area index (LAI) is a widely applied measure of photosynthetic capacity and productivity, that may reveal this information. Meanwhile, local level floral biodiversity and productivity is driven by topographic heterogeneity. Micro landscape level processes associated with topography are important in the determination of leaf area index, that may be applied as proxy measures of productivity. However, this is not well understood, especially for unique forest types such as the Afromontane mistbelt forest. Recently, Geographic Information Systems and Remote Sensing, have progressed to assume a pivotal role in the monitoring of vegetation, offering increased spatial coverage and modern, automated processing techniques. The applicability of digital elevation models such as the Shuttle Radar Topographic Mission, facilitates the retrieval of objective topographic measurements, that can be used in the explanation of leaf area. Meanwhile, the onset of “new generation” sensors, such as Sentinel 2 Multispectral Instrument has provided opportunity for investigating leaf area index, which cannot be achieved using traditional field surveys. This progression is supplemented by the application of machine learning algorithms, in the modelling of ecological relationships. Applying these algorithms in this regard, has demonstrated strength in managing data of high dimensionality, with speed and accurate results. The study therefore set out to characterise the leaf area index of the Yellowwood within a southern African mistbelt forest, using Geographic Information Systems and Remote Sensing techniques. Specifically, the study evaluated the role of Shuttle Radar Topographic Mission digital elevation model derived topographic variables, in the explanation of LAI, using Principal Component Analysis (PCA) and regression analysis. It also assessed the utility of Sentinel 2 imagery, in the estimation LAI, using the Random Forest (RF) regression ensemble. The stepwise linear regression analysis showed that topographic indices accounted for approximately 85 % of leaf area index variance (SEE = 35m2/m2; R2 = 0.85). Optimal topographic variables included the mass balance index and sky view factor. These can explain the micro landscape properties relating to ecosystem budgets and visible sky. Results also indicated that the backward elimination method optimally predicted the leaf area index of Yellowwood trees (RMSE = 0.48; R2 = 0.59). Further, predictors derived from the Red Edge bands were the most influential variables in predicting leaf area index. The study demonstrated the applicability of remotely sensed data and Geographic Information Systems in the retrieval of forest productivity proxies, such as leaf area index. II. Preface The study was undertaken in the School of Agricultural, Earth and Environmental Sciences, University of KwaZulu- Natal, Pietermaritzburg, South Africa, from March 2018 to May 2020, under the supervision of Professor Onisimo Mutanga and Doctor Mbulisi Sibanda, to fulfil the requirements of a Master’s of Science in Environmental Science. I, Nokwanda Gumede, declare that the current work represents my own ideas and has never been submitted to any other academic institutions. Acknowledgement has been duly made for statements originating from other authors. Nokwanda Gumede (Candidate) Signed: ________________________________________ Date: ___________________________________5 May 2020 As the candidate’s supervisors, we certify the aforementioned statement and have approved this thesis for submission. Professor Onisimo Mutanga (Supervisor) Signed: _____________________________________ Date: _____5 May_______________________________ 2020 Doctor Mbulisi Sibanda (Co-supervisor) Signed: _______________________________________ Date: ____________________________________5 May 2020 III. Declaration I, Nokwanda Gumede, declare that: 1. The research reported in this thesis, except where otherwise indicated is my original research. 2. This thesis has not been submitted for any degree or examination at any other institution. 3. This thesis does not contain other person’s data, pictures, graphs or other information, unless specifically acknowledged as being sourced from other persons. 4. This thesis does not contain other persons writing, unless specifically acknowledged as being sourced from other researchers. Where other written sources have been quoted: a. Their words have been re-written, and the general information attributed to them has been referenced. b. Where their exact words have been used, their writing has been placed in italics inside quotation marks and referenced. 5. This thesis does not contain text, graphics or tables copied and pasted from the internet, unless specifically acknowledged, and the source being detailed in the thesis and in the references section. Signed: ________________________________________Type text here Date: _______________________________5 May 2020 __ IV. Dedication “To all those who let monotonous lives, in the hope that they may experience at second hand the delights and dangers of adventure.” – Agatha Christie. V. Acknowledgements I would like to thank God for His grace and mercy: Qhubeka Nkosi usiphumelelise! Many thanks to Prof. Mutanga and Dr. Sibanda, for their continued support and encouragement, invaluable suggestions, and guidance, from the beginning to the final submission of this work. A big thank you to the Geography Department, everyone who helped me, especially Phindile, Nonjabulo and Dr. Sibanda for the assistance with the fieldwork. A special note for my parents, family, and friends for being nice to me when I was not! Thank you for the love, support, and kindness during this time. This work is based on the research supported wholly by the DST/ National Research Foundation of South Africa (Grant Numbers: 84157). VI. Table of Contents Abstract ........................................................................................................................................................................ II Preface ......................................................................................................................................................................... III Declaration ................................................................................................................................................................. IV Dedication .................................................................................................................................................................... V Acknowledgements ................................................................................................................................................... VI List of Tables .............................................................................................................................................................. IX List of Figures ............................................................................................................................................................ IX Chapter One ................................................................................................................................................................. 1 General introduction .................................................................................................................................................... 1 1.1. Introduction ................................................................................................................................................. 1 1.2. Aim and Objectives .................................................................................................................................... 3 1.3. Research Questions ................................................................................................................................... 4 1.4. Structure of the Thesis .............................................................................................................................. 4
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