F- Oliver Gathmann a Thesis Submitted in Conformity with the Requirements

INSECT COMMUNITY PATTERNS M SPACE: STATISTICAL TOOLS, SIMULATIONS, AND EMPIRICAL DATA FROM SOUTHERNONTARIO COLDWATER SPIUNGS F-Oliver Gathmann A thesis submitted in conformity with the requirements for the degree of Ph.D. Graduate Department of Zoology University of Toronto Copyright @ 2000 by F. Oliver Gathmann National Library Bibliothèque nationale du Canada Acquisitions and Acquisitions et Bibliographie Services services bibliographiques 395 Wellington Street 395, rue Wellington OttawaON K1AON4 Ottawa ON K1A ON4 Canada Canada The author has granted a non- L'auteur a accorde une licence non exclusive licence allowing the exclusive permettant à la National Library of Canada to Bibliothèque nationale du Canada de reproduce, loan, distribute or sell reproduire, prêter, distribuer ou copies of this thesis in microform, vendre des copies de cette thèse sous paper or electronic formats. la forme de microfiche/nlm, de reproduction sur papier ou sur format électronique. 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Contents Prolog 1 Bibliography .................................................. 6 1 Empirical Data 1 Insect emergence in Southern Ontario coldwater springs: patterns of species diversity and species- environment relationships 9 1.1 introduction ................................................ 9 1.2 StudyArea ................................................ 11 1.3 Material and Methods ........................................... 12 1.4 Results ................................................... 13 1.4.1 Abioticdata ............................................ 13 1.4.2 Taxonlist ............................................. 18 1.4.3 Species frequency ........................................ 18 1.4.4 Species abundance ........................................ 19 1.4.5 Species richness ......................................... 19 1.4.6 Species-environment relationships ................................ 21 1.5 Discussion ................................................. 24 Aclaowledgements ............................................... 26 Bibliography .................................................. 26 II Simulation Tools 2 Inter-site: a new tool for the simulation of spatially reaiistic population dynamics 31 2.1 introduction ................................................ 31 2.2 Implementation of the inter-site simulator ................................ 33 2.2.1 Programming paradigm ..................................... 33 2.2.2 Progs-amn~inglanguage and environment ............................ 34 2.2.3 Simulation technique ....................................... 35 2.2.4 Architecture and basic usage ................................... 35 2.3 A sample application: Adler and Nuernberger revisited ......................... 39 2.3.1 The original model ........................................ 39 2.3.2 The reconstnrction ........................................ 40 2.3.3 Running the reconstruction .................................... 42 2.4 Discussion ................................................. 42 Acknowledgements ............................................... 46 Bibliography .................................................. 46 3 Python as a Discrete Event Simuiation environment 51 3.1 Background ................................................ 51 3.2 ElementsofDES ............................................. 52 3.3 Mapping real-world objects into Python objects for DES ........................ 53 3.4 Simulation object code assembly ..................................... 54 3.5 Monitoring ................................................ 59 3.6 Realtime multivariate analysis of results ................................. 60 3 -7 Experiences and availability ....................................... 60 3.8 Conclusion ................................................ 61 Acknowledgements ............................................... 61 Bibliography .................................................. 61 III Statistical Tools 4 Neighborhood-based permutation and ordination methods for analyzing multivariate spatial data: theory and application on data from ecoIogica1 communities 64 4.1 Introduction ................................................ 64 4.2 Theory: Methods for detecting similarity patterns in multivariate spatial data .............. 65 4.2.1 Defining neighborhood relationships on objects ......................... 66 4.2.2 Permutation methods ....................................... 67 4.2.3 Ordination methods ........................................ 71 4.3 Application: Tests on artificial data .................................... 74 4.3.1 Tools for data generation and analysis .............................. 74 4.3.2 Artificial landscapes ....................................... 75 4.3.3 Mantel Comelogram analyses .................................. 76 4.3.4 Ordination analyses ........................................ 79 4-4 Application: ecological data from Southern Ontario coldwater springs ................. 80 4.4.1 Mantel Comelogram ....................................... 83 4.4.2 Spatial Ordinations ........................................ 84 4.5 Discussion ................................................. 86 4.6 Conclusions ................................................ 88 Acknowledgements ............................................... 88 Appendix .................................................... 88 Bibliography .................................................. 90 Epilog 94 Bibliography .................................................. 102 Appendix A PyDAS: The Python Data Analysis Servant. User Manual. 106 A.1 Introduction ................................................ 106 A.2 Architectural Remarks .......................................... 107 A.2.1 Main Notebook .......................................... 107 A.2.2 Dialog Widgets .......................................... 107 A.2.3 DataTypes ............................................ 108 A.3 Data Operations .............................................. 109 A.3. L Entering or Importing Data .................................... 109 A.3.2 ManagingTables ......................................... 112 A.3.3 Browsing and Editing Data Tables ................................ 115 A.3.4 Exporting Data .......................................... 116 A.4 Analysis .................................................. 117 A.4.1 Ordination Procedures ...................................... 117 A.4.2 Permutation Procedures ..................................... 124 Bibliography .................................................. 129 B Access to the Southern Ontario spring data set on the web 131 List of Figures 1.1 Studyarea ................................................. 11 1.2 Summary of abiotic data ......................................... 14 1.2 Summary of abiotic data, contd. ..................................... 15 1.3 Histogram of species frequencies ..................................... 18 1.4 Rank-abundance plots ........................................... 20 1.5 Species per site per group ......................................... 21 1.6 CCA plot of emergence data ....................................... 22 2.1 Blockdiagram of the simuIator architecture ............................... 36 2.2 Entity and Event Template structure ................................... 37 2.3 Template Set of the sample application .................................. 40 2.4 Results fiom the regular landscape .................................... 43 2.5 Results from the clumped landscape ................................... 44 3.1 DESdiagram ............................................... 53 3.2 Mapping real-world into Python objects ................................. 54 Factor maps ................................................ 75 Mantel Correlograms ........................................... 77 Mantel Comelograms ........................................... 78 SCA ordinations for the clumped Iandscape ............................... 81 SPCA ordinations for the dumped 1~3cape.............................. 82 Moving Widow Mantel Correlogram for the spring data set ...................... 83 Ordinations for the Southern Ontario springs data set .......................... 85 Python code for a Moving Window algorithm .............................. 89 Effect of range restrictions on spatial community similarity patterns .................. 97 Effect of metacommunity dynamics on spatial community similarity patterns ............. 98 A.l The main notebook ..................................... - ......108 A.2 The create data table fiom input dialog window ...................... - ......110 A.3 The data table browser window ............................... - ......112 A.4 The data table select dialog window ............................ - ...... 113 AS ïhe data table convert dialog window ...........................- ...... 114 A.6 The data sheet window .......................................... 115 A.7 The CA dialog window .......................................... 118 A.8 The PCA dialog window ......................................... 120 A.9 The CCA dialog window .......................................... 121 A.10 The RDA dialog window ........................................

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