OECOLOGY OF PLANTS: AN INTRODUCTION TO THE STUDY OF PLANT-COMMUNITIES
CONTENTS 1 INTRODUCTION 2 PATTERNS IN VEGETATION ECOLOGY PATTERN RECOGNITION INTERPRETATION OF PATTERNS SAMPLING FOR PATTERN RECOGNITION GETTING A SAMPLE ORGANIZING THE DATA PATTERN RECOGNITION IN R 3 TRANSFORMATION DATA TYPES SCALAR TRANSFORMATION AND THE SPECIES ENIGMA VECTOR TRANSFORMATION EXAMPLE: TRANSFORMATION OF PLANT COVER DATA 4 MULTIVARIATE COMPARISON RESEMBLANCE IN MULTIVARIATE SPACE GEOMETRIC APPROACH CONTINGENCY MEASURES PRODUCT MOMENTS THE RESEMBLANCE MATRIX ASSESSING THE QUALITY OF CLASSI?CATIONS 5 CLASSI?CATION GROUP STRUCTURES LINKAGE CLUSTERING AVERAGE LINKAGE CLUSTERING MINIMUM-VARIANCE CLUSTERING FORMING GROUPS SILHOUETTE PLOT AND FUZZY REPRESENTATION 6 ORDINATION WHY ORDINATION? PRINCIPAL COMPONENT ANALYSIS PRINCIPAL COORDINATES ANALYSIS CORRESPONDENCE ANALYSIS HEURISTIC ORDINATION THE HORSESHOE OR ARCH EFFECT FLEXIBLE SHORTEST PATH ADJUSTMENT NONMETRIC MULTIDIMENSIONAL SCALING DETRENDED CORRESPONDENCE ANALYSIS HOW TO INTERPRET ORDINATIONS RANKING BY ORTHOGONAL COMPONENTS RANK METHOD A SAMPLING DESIGN BASED ON RANK (EXAMPLE) 7 ECOLOGICAL PATTERNS PATTERN AND ECOLOGICAL RESPONSE EVALUATING GROUPS VARIANCE TESTING VARIANCE RANKING RANKING BY INDICATOR VALUES CONTINGENCY TABLES CORRELATING SPACES THE MANTEL TEST CORRELOGRAMS MORE TRENDS: ‘SCHLAENGGLI’ DATA REVISITED MULTIVARIATE LINEAR MODELS CONSTRAINED ORDINATION NONPARAMETRIC MULTIPLE ANALYSIS OF VARIANCE SYNOPTIC VEGETATION TABLES THE AIM OF ORDERING TABLES STEPS INVOLVED IN SORTING TABLES EXAMPLE: ORDERING ELLENBERG’S DATA 8 STATIC PREDICTIVE MODELLING PREDICTIVE OR EXPLANATORY? EVALUATING ENVIRONMENTAL PREDICTORS GENERALIZED LINEAR MODELS GENERALIZED ADDITIVE MODELS CLASSI?CATION AND REGRESSION TREES BUILDING SCENARIOS MODELLING VEGETATION TYPES EXPECTED WETLAND VEGETATION (EXAMPLE) 9 VEGETATION CHANGE IN TIME COPING WITH TIME TEMPORAL AUTOCORRELATION RATE OF CHANGE AND TREND MARKOV MODELS SPACE-FOR-TIME SUBSTITUTION PRINCIPLE AND METHOD THE SWISS NATIONAL PARK SUCCESSION (EXAMPLE) DYNAMICS IN POLLEN DIAGRAMS (EXAMPLE) 10 DYNAMIC MODELLING 10 1 SIMULATING TIME PROCESSES 10 2 SIMULATING SPACE PROCESSES 10 3 PROCESSES IN THE SWISS NATIONAL PARK 10 3 1 THE TEMPORAL MODEL 10 3 2 THE SPATIAL MODEL 11 LARGE DATA SETS: WETLAND PATTERNS 11 1 LARGE DATA SETS DIFFER 11 2 PHYTOSOCIOLOGY REVISITED 11 3 SUPPRESSING OUTLIERS 11 4 REPLACING SPECIES WITH NEW ATTRIBUTES 11 5 LARGE SYNOPTIC TABLES? 12 SWISS FORESTS: A CASE STUDY 12 1 AIM OF THE STUDY 12 2 STRUCTURE OF THE DATA SET 12 3 SELECTED QUESTIONS 12 3 1 IS THE SIMILARITY PATTERN DISCRETE OR CONTINUOUS? 12 3 2 IS THERE A SCALE EFFECT FROM PLOT SIZE? 12 3 3 DOES THE VEGETATION PATTERN RE?ECT ENVIRONMENTAL CONDITIONS? 12 3 4 IS TREE SPECIES DISTRIBUTION MAN-MADE? 12 3 5 IS THE TREE SPECIES PATTERN EXPECTED TO CHANGE? 12 4 CONCLUSIONS BIBLIOGRAPHY