Victorian Wetlands
Total Page：16
File Type：pdf, Size：1020Kb
Frontispiece: Kangeroo Swamp, site number 48. Air oblique photograph by Neville Rosengren, March 1981. NUMERICAL ANALYSES OF MACROPHYTE VEGETATION IN VICTORIAN WETLANDS IN RELATION TO E~VIRONMENTAL FACTORS by Michele Mary Barson B.A.(Hons),M.Sc. 1984 A thesis submitted for the degree of Doctor of Philosophy at the University of Melbourne CONTENTS Page Declaration i Acknowledgements ii Abstract iv List of Figures vii List of Tables x Chapter 1 Introduction 1. The value of wetlands 1 2. Types of wetland classifications 5 3. Aims of the study 8 4. Same definitions 9 5. Description of the study area 9 Chapter 2 Classification of wetlands vegetation l. Data collection 13 Selection of wetland sites 13 Sampling considerations 14 Sample size 16 Choice of attributes 17 2. Classification of floristic data 19 Choice of unit to be classified 19 Scale of measuranent 20 Choice of strategy 20 3. Validation of groups produced by numerical classifications 21 4. Methods of analysis 5. Results 23 Stopping rules 24 Floristic groups 25 6. Discussion 32 Criteria for the assessment of a classification 32 Adequacy of a class representation 33 Evidence for relevance of the model and adequacy of fit 34 7. Conclusions 38 Chapter 3 The effects of data reduction on classification 1. Introduction 40 2. Application of data reduction techniques 43 3. Results 47 A. Data set after reduction by EIDENT 47 B. Results of classification of aquatic and semi-aquatic species 53 4. Discussion 56 5. Conc:lusions 60 c.'1apter 4 ordination of wetland sites 1. Introduction 61 2. Choice of strategy 64 Data transfonnations and sbnilarity measures 65 3. Results 68 Principal Coordinates Analyses 68 Detrended Correspondence Analysis 71 4. Discussion 72 5. Conclusions 77 6. Summary of results of floristic analyses 78 Chapter 5 Physical and chemical characteristics of aquatic macrophyte habitats in Victoria 1. Introduction 79 2. Methods 81 A. Sample collection and analyses 81 B. Numerical analyses of data 83 3. Results A. Laboratory analyses 84 B. Numerical analyses 87 4. Discussion 93 5. Conclusions 98 Chapter 6 Vegetation-environment relationships 1. Introduction 100 2. Choice of strategy 101 A. canonical Correlation Analysis 101 B. Analysis of variance 103 C. Discrlininant analysis 104 3. Results 108 A. canonical Correlation Analysis 108 B. Analysis of variance 110 c. Discrbninant Analyses III 4. Discussion 113 A. canonical Correlation Analysis 113 B. Analysis of Variance 113 c. Discrbninant Analyses 114 5. conclusions 117 Chapter 7 Conclusions 119 1. Summary of results 119 A. Floristic analyses 119 B. water chemistry analyses 120 c. vegetation-environment relationships 121 2. Evaluation of method.s am results of the study 122 A. Variability of wetlands vegetation 123 B. Assessment of ~~e classification of wetlands vegetation 124 c. Vegetation-environment relationships 129 D. Relationships with other Australian wetlands 132 3. Recommendations for conservation 134 Bibliography 137 Appendix I 155 Species recorded fram the Victorian ~~tlands sampled DECLARATION I hereby dec~e that this thesis is my own work~ except where specifically stated to the contrary~ and that it is not substantially the same as any other thesis which has already been submitted to any other university. MICHELE BARSON ii ACKNOWLEJX;EMEt-.."TS It is a pleasure to acknowledge the assistance of the following people: Dr. P. Y. Ladiges, my supervisor, for her patience and encouragement and Dr. M.B. Dale of the CSIRO Division of Computing Research for the guidance provided through the maze of nunerical methods. Dr. D. Ratcliff, CSIRO Division of Mathematics and Statistics, who carried out the analyses for Chapter Six. Andrew Corrick of the Victorian Fisheries and Wildlife Division and Lex Thompson of the Department of Forestry, University of Melbourne provided information about many of the wetlands wnich were sampled. Ian Clarke, Mark Ellaway , Ros Gleadow, Steve Gloury, Laur ie Koster, Sigrid Kraemers, Phil Ladd, Vuong Nuygen, Neville Rosengren and Dick Williams braved snakes, uncertain substrates and turbid waters to provide assistance and company in the field. Equipment and advice regarding L,e analysis of water samples was provided by Dr. M. McCormick of the E.P.A. Laboratory, Latrobe University and Dr. J.D. Smith of the Department of Marine Chemistry, University of Melbourne. I am grateful to Lyn McKinley for assistance in the preparation of samples. Irene Folie, Colin Summerbell and John Myers of the Botany School are thanked for their patience and advice. Thanks are also due to the Chairmen of the Departments which supported this work, Dr. D.M. Calder and professor T.C. Chambers (Botany School) ard Dr. J.R.V. Prescott iii and Dr. T.M. perry (Geography Department) • Special thanks are due to Lois Davey for the inter library loan service, Rob Bartlett who drew the diagrams and to Shirley Fricke, Ruth Terrell-Phillips, Jenny Gilbert and Robyn Cotter for typing. Jenny Ziviani and David wadley provided friendship and hospitality in Brisbane. Dr. Eric Bird, Professor Eddy van der Maarel and Mr. LeO Devin are thanked for their constant encouragement. This work was supported by a Commonwealth pOstgraduate Research Award. iv ABSTRACT This study was undertaken to investigate the variability of vegetated victorian wetlands and to establish the relationships between this variation and major environmental factors. Criteria for the selection of the 55 wetlands sampled included the presence of aquatic macrophyte or helophyte vegetation, the presence of at least an intermittent water body and, comparative lack of disturbance of the si te. Si tes were also chosen to reflect the considerable lithological and climatic variation found across lowland victoria. At each site, species presence/absence data, water depth and water transparency were recorded within 1m square quadrats positioned at Sm intervals along transects located to ~est sample the vegetation. At each transect, water samples were collected for the analysis of major ions, and substrate samples were taken for the estimation of texture and measurenent of pH and percentage salts. The maximtm depth of t..'1e basin when flooded and its water regime were estimated and the geology and rainfall of the catchment were recorded. An information statistic strategy was used to classify the large, relatively sparse floristic set of data. The classification recognised five distinctive, relatively homogenous and ecologically interpretable groups of wetlands, which were characterised as having saline, very saline, turbid, acidic or calcareous waters, and a further three freshwater groups which were closely related to one another. v The application of data reduction techniques suggested that the infonnation statistic model was unable to adequately define some of the freshwater groups of sites primarily because of the highly heterogenous nature of the data set. TWO more data sets were produced by deleting species with low "eident" values (Dale and Williams 1978) and by deleting species regarded as terrestrial. However, classification of these reduced data sets did not provide markedly better results. The relationships between the groups (and their members) generated by classification was examined through indirect ordination of the floristic data. Inspection of the results indicated that six of the eight groups identified by classification of the floristic data could be recognised. However, two groups of sal ine si tes could not be separated, largely because they were both species-poor. Six sites were identified as the probable cause of overlap of some of the freshwater groups. Laboratory determination of the major ionic constituents of the waters of the 55 wetlands indicated that the orders of anion dominance were Cl>HC03+C03>S04 (freshwater sites) or Cl>S04>HC03+C03 (saline and coastal freshwater si tes) and those for cations were Na>Mg>Ca>K or Na>Ca>Mg>K (freshwater) and Na>Mg>Ca)K (saline sites). The dominance of chloride and sodiun ions in the waters sampled suggested that salinity was a major factor affecting the distribution of aquatic macrophytes in Victoria. Numerical classification of the wetlands on the basis of their vi water chemistry was undertaken to provide a comparison with the eight group floristic classification. However, two of the intuitively recognised groups, the turbid and calcareous waters, were not identified by classification of the water chemistry data, and me:nbership of the two independently generated sets of groups was not identical. The nature of the hypothesized joint pattern between the floristic and the water chemistry data was further investigated by canonical correlation analysis, analysis of variance and discrlininant analyses. These analyses ccnfirmed that overall, the variance observed in the vegetation of the wetlands sampled was significantly influenced by water chemistry. However, the level of vegetational variation identified as a result of classification of the floristic data (eight groups) did not correspond well with the measured differences in the water chemistry variables. Vegetation differences which could be attributed to water chemistry differences were those between the saline groups, the turbid water group, the acidic water group, the freshwater complex of three groups, and possibly the calcareous group. The salinity variable largely separated the saline groups from t.."1e rest, whilst pH separated the acidic water and calcareous water groups from each other and the freshwater complex. The turbid water group was separated