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INVASIVE ALIEN PLANTS OF SOUTH AFRICA'S FRESHWATER SYSTEMS: ACCELERATING IDENTIFICATION OF SPECIES AND CLIMATICALLY SUITABLE AREAS FOR SPECIES INVASION by Lerato Nakedi Hoveka Dissertation submitted in fulfilment of the requirements for the degree MAGISTER SCIENTIAE in Botany in the Faculty of Science at the University of Johannesburg Supervisor: Prof Michelle van der Bank Co-supervisor: Dr J. Stephen Boatwright Co-supervisor: Dr Kowiyou Yessoufou January 2014 DECLARATION I declare that this dissertation hereby submitted to the University of Johannesburg for the degree MAGISTER SCIENTIAE (Botany), is my own work and has not been previously submitted by me for a degree at another institution. Lerato Nakedi Hoveka January 2014 i DEDICATION I dedicate my thesis to my beloved nephew and niece, Lethabo and Toriso Hoveka. “A good head and good heart are always a formidable combination. But when you add to that a literate tongue or pen, then you have something very special” - Nelson Mandela ii TABLE OF CONTENTS Index to figures vii Index to tables ix List of abbreviations x Acknowledgements xi Abstract xiii 1. Chapter one: General introduction and objectives 1 1.1. A brief summary of plant diversity and threats in South Africa 2 1.2. Species invasion: processes and impacts 3 1.2.1 Conceptual clarification 3 1.2.2. Processes of species invasion 3 1.2.2.1. Introduction of alien invasive species to new 4 environments 1.2.2.2. Colonization 7 1.2.2.3. Naturalization 7 1.2.2.3.1. The enemy release and Darwin 8 naturalization hypotheses 1.2.2.3.2. The allelopathy hypothesis 9 1.2.2.3.3. The border tolerance hypothesis 10 1.2.2.3.4. The hybrid vigour hypothesis 11 1.2.3. Impacts of invasive alien plants 11 1.2.3.1. Ecological impacts of invasive alien plants 12 1.2.3.2. Economic impacts f invasive alien plants in 14 South Africa 1.3. Management of invasive aquatic plants in South Africa 16 iii 1.3.1. Classification of invasive aquatic plants 16 1.3.1.1. Emergents plants 17 1.3.1.2. Floating plants 17 1.3.1.3. Submerged plants 17 1.3.2. Management action 21 1.3.2.1. Preventive actions 21 1.3.2.1.1. Environmental education approach 21 1.3.2.1.2. Environmental legislative approach 22 1.3.2.2. Early detection and rapid response (EDRR) 24 1.3.2.2.1. Early detection 24 1.3.2.2.2. Identification and verification with 25 emphasis on DNA barcoding 1.3.2.3. Risk assessment 27 1.3.2.4. Rapid response planning and implementation 30 1.3.2.5. Control and eradication 30 1.4. Aim and objectives of the study 33 2. Chapter two: DNA barcoding of invasive aquatic plants of 34 South Africa’s freshwater systems 2.1. Introduction 35 2.2. Material and methods 38 2.2.1. Taxon sampling and taxa templates 38 2.2.2. DNA extraction, amplification, sequencing and alignment 53 2.2.3. Satistical data analyses, species monophyly and BLAST 56 analysis 2.3. Results 60 2.3.1. Barcoding gap analysis 60 iv 2.3.2. Discriminatory power 62 2.3.3. PCR success 66 2.3.4. Species monophyly 66 2.3.5. BLAST results 69 2.4 Discussion 70 2.5 Conclusions 73 3. Chapter three: Potential effects of the changing climate on the 74 five worst invaders of South Africa’s freshwater systems 3.1. Introduction 75 3.2. Material and methods 78 3.2.1. Occurrence data 78 3.2.2. Predictor variables 79 3.2.3. Ecological niche modelling 81 3.2.4. Model performance evaluation 81 3.2.5. Model output 82 3.3 Results 83 3.3.1. Best climatic predictors for species distribution of the bad 83 five 3.3.2. Model performance 86 3.3.3. Model output 89 3.4. Discussion 100 3.5 Conclusion 103 4. Chapter four: General conclusions 104 v 5. Chapter five: References 110 Appendices 135 vi INDEX TO FIGURES Chapter one Figure 1.1 9 An illustration of the Enemy Release Hypothesis. Figure 1.2 18 Emergent aquatic plants. Figure 1.3 19 Floating aquatic plants. Figure 1.4 20 Submerged aquatic plants. Figure 1.5 32 Mechanical control of water hyacinth by Working for Water employees. Figure 1.6 32 Eichhornia crassipes under biological control by Neochetina eichhorniae Chapter two Figure 2.1 61 Evaluation of the barcode gap in the core barcode. Figure 2.2 64 Barplot showing the false positive and false negative rate of identification of invasive aquatic species as pre-set thresholds change. Figure 2.3 66 PCR efficiency for the three DNA regions tested vii Figure 2.4 67 One of the most parsimonious trees from the combined plastid genes. Chapter three Figure 3.1 86 Jack-knife analysis indicating the predictor variable based on the AUC values. Figure 3.2 89 ROC curve statistics results. Figure 3.3 92 Assessment of the effects of climate change on the distribution of Azolla filiculoides. Figure 3.4 93 Assessment of the effects of climate change on the distribution of Eichhornia crasspies. Figure 3.5 94 Assessment of the effects of climate change on the distribution of Myriophyllum aquaticum. Figure 3.6 95 Assessment of the effects of climate change on the distribution of Pistia stratiotes. Figure 3.7 96 Assessment of the effects of climate change on the distribution of Salvinia molesta. viii INDEX TO TABLE Chapter two Table 2.1 40 List of taxa with voucher information and GenBank accession number for each DNA. region. Table 2.2 54 Primers used for DNA amplification and sequencing. Table 2.3 56 Summary of statistics for the datasets generated. Table 2.4 65 Identification efficacy of DNA barcode regions using distance-based methods. Table 2.5 69 BLAST analysis of the aquarium plants. Chapter three Table 3.1 80 List of global bioclimatic variables from the WorldClim database used for predicting ecological niches. Table 3.2 83 Conversion of pixel cover area in arc minutes to Kilometres. Table 3.3 97 Dams occurring in climatically suitable areas for invasion by the ‘bad five’ currently and in the future. Table 3.4 99 Summary of the area for potential suitable area currently and in the future in km2 ix LIST OF ABBREVIATIONS °C = Degree Celsius ABI = Applied Biosystems, Inc. BOLD = Barcode of Life Database CBOL = Consortium Barcode of Life CTAB = Hexadecyltrimethylammonium bromide DMSO = Dimethyl Sulfoxide DNA = Deoxyribonucleic acid F = Forward primer g = gram GenBank (NCBI) = National Centre for Biotechnology Information IAPs = Invasive Alien Plant species matK = Maturase K min = minutes No = Number PAUP = Phylogenetic Analysis Using Parsimony software program PCR = Polymerase Chain Reaction PVP = Polyvinyl pyrolidone R = Reverse primer rbcL = ribulose-bisphosphate carboxylase gene sec = second trnH-psbA = spacer between trnH and psbA genes Verdc. = Verdcourt, Bernard Warner = Warner, Rose Ella x ACKNOWLEDMENTS I thank God almighty for this guidance, mercy and protection throughout my academic career. I wish to thank my parents, grandparents, and siblings for the love, encouragement and support that they have given me throughout my studies. To Malome Mathome, Ausi Dodi, Mamokgolo Fenny and Malome Masilo, kea leboga Bakone. I am grateful for my supervisors Prof Michelle Van der Bank, Dr Stephen Boatwright and Dr Kowiyou Yessoufou for their patience, guidance and the valuable contribution that they have made towards this study. I am indebted to Kennedy Leso and Thabang Phago for their support, advice and assisting me with the field work and the identification of plants. I express my gratitude to Anthony King, Julie Coetzee, Angela Bowens, Matt Parkison and Grant Martin for providing me with plant material to use for the DNA barcoding. I value the contribution that Jephris Gere and Bezeng Bezeng have made to this study. I appreciate the training, skill and advice that you have given me. xi To the members of the African Centre for DNA Barcoding, especially Barnabas Daru and Ledile Mankga, thank you for your love and support, and for sharing valuable knowledge with me throughout the study. To Ronny Kabongo, thank you very much for helping me with the spider analyses. I am grateful to Les Powrie for providing the occurrence data used in this study. Finally, I thank my sponsors - the South African National Biodiversity Institute, Department of Environmental Affairs, the Expanded Public Works Programme, the Working for Water Programme and the University of Johannesburg - for the financial support that they have provided. xii ABSTRACT In South Africa, controlling and eradicating Azolla filiculoides and Eichhornia crassipes cost annually approximately US$ 60 million to the national budget. However, the success of these operations is mixed because invasive aquatic plants often spread very rapidly either before they are spotted or before decisions are taken to implement control actions. This limitation is further exacerbated by difficulties in determining the invasion potential of newly introduced or unknown aquatic plants, as well as difficulties inherent to species identification.