## Estimating Animal Abundance: Closed PopulationsWe hope this book will make the bewildering variety of methods for estimat ing the abundance of animal populations more accessible to the uninitiated and more coherent to the cogniscenti. We have tried to emphasize the fun damental similarity of many methods and to draw out the common threads that underlie them. With the exception of Chapter 13, we restrict ourselves to closed populations (those that do not change in composition over the period(s) being considered). Open population methods are in many ways simply extensions of closed population methods, and we have tried to pro vide the reader with a foundation on which understanding of both closed and open population methods can develop. We would like to thank Miguel Bernal for providing the St Andrews example dataset used frequently in the book; Miguel Bernal and Jeff Laake for commenting on drafts of the book; Jeff Laake for providing Figure 10.1; NRC Research Press for allowing us to use Figures 10.2, 10.3, 10.4, 10.5, 10.6 and 10.7; the International Whaling Commission for allowing us to use Figure 12.1; Sharon Hedley for providing Figures 12.1 and 12.2. D.L.B. is eternally indebted to Carol, Alice and Aidan for their support through writing the book, and for the many evenings and weekends that it has taken from them. |

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### Contents

3 | |

Using likelihood for estimation | 12 |

Building blocks 37 | 35 |

Plot sampling | 55 |

Removal catcheffort and changeinratio | 72 |

Simple markrecapture | 104 |

Distance sampling | 131 |

Nearest neighbour and pointtonearestobject | 165 |

Dealing with heterogeneity | 199 |

Integrated models | 227 |

Dynamic and open population models | 245 |

Which method? 269 | 267 |

A Notation and Glossary | 278 |

B Statistical formulation for observation models | 284 |

State models for markrecapture and removal methods | 294 |

299 | |

### Other editions - View all

Estimating Animal Abundance: Closed Populations D.L. Borchers,Stephen Stephens,W. Zucchini No preview available - 2010 |

### Common terms and phrases

abundance estimates animal abundance animal-level variables animals detected assumed assumption bias binomial binomial distribution capture history capture occasion capture probability catch-effort catchability Chapter conditional likelihood confidence interval covered region depends design-based detected animals detection function detection probability estimate abundance estimation of abundance Exercise females full likelihood given groups heterogeneity independently inference interval estimation involve likelihood Equation likelihood function line transect sampling line transect survey log-likelihood males mark-recapture mark-recapture methods marked animals matrix maximum likelihood estimator migration counts model-based nonparametric bootstrap normally distributed number of animals observation model open populations parametric bootstrap perpendicular distance plot sampling plot survey point transect sampling point transect survey probability density probability density function profile likelihood proportion random variable recapture resamples shown in Figure simple random sample simple removal method spatial state model St Andrews example survey design survey occasion survey region survey-level variables Technical section tion two-sample unmarked animals vector watch periods zero