| Foreword | p. xi |
| Preface | p. xiii |
| Acknowledgments | p. xvii |
| Introduction | |
| Ecology: The Study of Distribution and Abundance and of the Mechanisms Driving Their Change | p. 1 |
| Genesis of Ecological Observations | p. 6 |
| The Binomial Distribution as a Canonical Description of the Observation Process | p. 9 |
| Structure and Overview of the Contents of this Book | p. 13 |
| Benefits of Analyzing Simulated Data Sets: An Example of Bias and Precision | p. 16 |
| Summary and Outlook | p. 20 |
| Exercises | p. 21 |
| Brief Introduction to Bayesian Statistical Modeling | |
| Introduction | p. 23 |
| Role of Models in Science | p. 24 |
| Statistical Models | p. 27 |
| Frequentist and Bayesian Analysis of Statistical Models | p. 28 |
| Bayesian Computation | p. 38 |
| WinBUGS | p. 38 |
| Advantages and Disadvantages of Bayesian Analyses by Posterior Sampling | p. 41 |
| Hierarchical Models | p. 43 |
| Summary and Outlook | p. 44 |
| Introduction to the Generalized Linear Model: The Simplest Model for Count Data | |
| Introduction | p. 48 |
| Statistical Models: Response = Signal + Noise | p. 48 |
| Poisson GLM in R and WinBUGS for Modeling Time Series of Counts | p. 55 |
| Poisson GLM for Modeling Fecundity | p. 66 |
| Binomial GLM for Modeling Bounded Counts or Proportions | p. 67 |
| Summary and Outlook | p. 71 |
| Exercises | p. 72 |
| Introduction to Random Effects: Conventional Poisson GLMM for Count Data | |
| Introduction | p. 73 |
| Accounting for Overdispersion by Random Effects-Modeling in R and WinBUGS | p. 82 |
| Mixed Models with Random Effects for Variability among Groups (Site and Year Effects) | p. 90 |
| Summary and Outlook | p. 110 |
| Exercises | p. 112 |
| State-Space Models for Population Counts | |
| Introduction | p. 115 |
| A Simple Model | p. 118 |
| Systematic Bias in the Observation Process | p. 121 |
| Real Example: House Martin Population Counts in the Village of Magden | p. 126 |
| Summary and Outlook | p. 131 |
| Exercises | p. 131 |
| Estimation of the Size of a Closed Population from Capture-Recapture Data | |
| Introduction | p. 134 |
| Generation and Analysis of Simulated Data with Data Augmentation | p. 139 |
| Analysis of a Real Data Set: Model Mtbh for Species Richness Estimation | p. 157 |
| Capture-Recapture Models with Individual Covariates: Model Mt+X | p. 162 |
| Summary and Outlook | p. 169 |
| Exercises | p. 170 |
| Estimation of Survival from Capture-Recapture Data Using the Cormack-Jolly-Seber Model | |
| Introduction | p. 172 |
| The CJS Model as a State-Space Model | p. 175 |
| Models with Constant Parameters | p. 177 |
| Models with Time-Variation | p. 183 |
| Models with Individual Variation | p. 192 |
| Models with Time and Group Effects | p. 199 |
| Models with Age Effects | p. 208 |
| Immediate Trap Response in Recapture Probability | p. 212 |
| Parameter Identifiability | p. 216 |
| Fitting the CJS to Data in the M-Array Format: The Multinomial Likelihood | p. 220 |
| Analysis of a Real Data Set: Survival of Female Leisler's Bats | p. 231 |
| Summary and Outlook | p. 237 |
| Exercises | p. 238 |
| Estimation of Survival Using Mark-Recovery Data | |
| Introduction | p. 241 |
| The Mark-Recovery Model as a State-Space Model | p. 243 |
| The Mark-Recovery Model Fitted with the Multinomial Likelihood | p. 248 |
| Real-Data Example: Age-Dependent Survival in Swiss Red Kites | p. 255 |
| Summary and Outlook | p. 261 |
| Exercises | p. 261 |
| Estimation of Survival and Movement from Capture-Recapture Data Using Multistate Models | |
| Introduction | p. 264 |
| Estimation of Movement between Two Sites | p. 268 |
| Accounting for Temporary Emigration | p. 281 |
| Estimation of Age-Specific Probability of First Breeding | p. 288 |
| Joint Analysis of Capture-Recapture and Mark-Recovery Data | p. 295 |
| Estimation of Movement among Three Sites | p. 300 |
| Real-Data Example: The Showy Lady's Slipper | p. 307 |
| Summary and Outlook | p. 311 |
| Exercises | p. 312 |
| Estimation of Survival, Recruitment, and Population Size from Capture-Recapture Data Using the Jolly-Seber Model | |
| Introduction | p. 316 |
| The JS Model as a State-Space Model | p. 317 |
| Fitting the JS Model with Data Augmentation | p. 319 |
| Models with Constant Survival and Time-Dependent Entry | p. 328 |
| Models with Individual Capture Heterogeneity | p. 335 |
| Connections between Parameters, Further Quantities and Some Remarks on Identifiability | p. 339 |
| Analysis of a Real Data Set: Survival, Recruitment and Population Size of Leisler's Bats | p. 341 |
| Summary and Outlook | p. 345 |
| Exercises | p. 346 |
| Estimation of Demographic Rates, Population Size, and Projection Matrices from Multiple Data Types Using Integrated Population Models | |
| Introduction | p. 348 |
| Developing an Integrated Population Model (IPM) | p. 350 |
| Example of a Simple IPM (Counts, Capture-Recapture, Reproduction) | p. 357 |
| Another Example of an IPM: Estimating Productivity without Explicit Productivity Data | p. 363 |
| IPMs for Population Viability Analysis | p. 366 |
| Real Data Example: Hoopoe Population Dynamics | p. 371 |
| Summary and Outlook | p. 379 |
| Exercises | p. 380 |
| Estimation of Abundance from Counts in Metapopulation Designs Using the Binomial Mixture Model | |
| Introduction | p. 383 |
| Generation and Analysis of Simulated Data | p. 388 |
| Analysis of Real Data: Open-Population Binomial Mixture Models | p. 396 |
| Summary and Outlook | p. 409 |
| Exercises | p. 411 |
| Estimation of Occupancy and Species Distributions from Detection/Nondetection Data in Metapopulation Designs Using Site-Occupancy Models | |
| Introduction | p. 414 |
| What Happens When p 1 and Constant and p is Not Accounted for in a Species Distribution Model? | p. 419 |
| Generation and Analysis of Simulated Data for Single-Season Occupancy | p. 420 |
| Analysis of Real Data Set: Single-Season Occupancy Model | p. 427 |
| Dynamic (Multiseason) Site-Occupancy Models | p. 436 |
| Multistate Occupancy Models | p. 450 |
| Summary and Outlook | p. 459 |
| Exercises | p. 460 |
| Concluding Remarks | |
| The Power and Beauty of Hierarchical Models | p. 464 |
| The Importance of the Observation Process | p. 472 |
| Where Will We Go? | p. 474 |
| The Importance of Population Analysis for Conservation and Management | p. 476 |
| A List of WinBUGS Tricks | p. 479 |
| Two Further Useful Multistate Capture-Recapture Models | p. 487 |
| References | p. 497 |
| Index | p. 515 |
| Table of Contents provided by Ingram. All Rights Reserved. |
