Distance sampling : estimating abundance of biological populations
著者
書誌事項
Distance sampling : estimating abundance of biological populations
Chapman & Hall, 1993
- : hard
- : pbk
大学図書館所蔵 件 / 全21件
-
該当する所蔵館はありません
- すべての絞り込み条件を解除する
注記
Bibliography: p. 421-440
Includes index
内容説明・目次
- 巻冊次
-
: hard ISBN 9780412426605
内容説明
This study concerns the use of distance sampling to estimate the density or abundance of biological populations. Line and point transect sampling are the primary distance methods. Here, lines or points are surveyed in the field and the observer records a distance to those objects of interest that are detected. The sample data are the set of distances of detected objects and any relevant covariates; however, many objects may remain undetected during the course of the survey. Distance sampling provides a way to obtain reliable estimates of density of objects under fairly mild assumptions. Distance sampling is an extension of plot sampling methods where it is assumed that all objects within sample plots are counted. The objective of this book is to provide a comprehensive treatment of distance sampling theory and application. It covers the theory and application of distance sampling with emphasis on line and point transects. Specialized applications are noted briefly, such as trapping webs and cue counts. General considerations are given to the design of distance sampling surveys.
目次
- Introductory concepts
- conceptual background
- statistical theory
- line transects
- point transects
- extensions and related work
- study design and field methods
- illustrative examples.
- 巻冊次
-
: pbk ISBN 9780412426704
内容説明
one can choose a point instead and measure the radial distances of the animals detected. It is very appropriate that the leading exponents in this field have come together to produce an authoritative description on 'how to do it'. They bring with them many years of experience in this research area. This book is a must for all those involved in estimating animal abundance as the methods can be used for such a wide variety of animal species including birds and marine mammals. The methods also apply to clusters of animals such as schools of dolphins and to animal signs. The beauty of such methods lies in the fact that not every animal has to be seen when a population is investigated. At the heart of the methodology is a 'detectability' function which is estimated in some robust fashion from the distances to the animals actually seen. Many species are not always visible and may be detected by the sounds they make or by being flushed out into the open. Clearly animals can have widely different behaviour patterns so that different models will be needed for different situations. This book provides a tool box of such methods with a computer package which helps the researcher to select the right tool for each occasion. The authors have a reputation for being very thorough and, typically, they endeavour to cover every conceivable situation that might be encountered in the field.
目次
1 Introductory concepts.- 1.1 Introduction.- 1.2 Range of applications.- 1.3 Types of data.- 1.4 Known constants and parameters.- 1.5 Assumptions.- 1.6 Fundamental concept.- 1.7 Detection.- 1.8 History of methods.- 1.9 Program DISTANCE.- 2 Assumptions and modelling philosophy.- 2.1 Assumptions.- 2.2 Fundamental models.- 2.3 Philosophy and strategy.- 2.4 Robust models.- 2.5 Some analysis guidelines.- 3 Statistical theory.- 3.1 General formula.- 3.2 Hazard-rate modelling of the detection process.- 3.3 The key function formulation for distance data.- 3.4 Maximum likelihood methods.- 3.5 Choice of model.- 3.6 Estimation for clustered populations.- 3.7 Density, variance and interval estimation.- 3.8 Stratification and covariates.- 4 Line transects.- 4.1 Introduction.- 4.2 Example data.- 4.3 Truncation.- 4.4 Estimating the variance in sample size.- 4.5 Analysis of grouped or ungrouped data.- 4.6 Model selection.- 4.7 Estimation of density and measures of precision.- 4.8 Estimation when the objects are in clusters.- 4.9 Assumptions.- 4.10 Summary.- 5 Point transects.- 5.1 Introduction.- 5.2 Example data.- 5.3 Truncation.- 5.4 Estimating the variance in sample size.- 5.5 Analysis of grouped or ungrouped data.- 5.6 Model selection.- 5.7 Estimation of density and measures of precision.- 5.8 Estimation when the objects are in clusters.- 5.9 Assumptions.- 5.10 Summary.- 6 Extensions and related work.- 6.1 Introduction.- 6.2 Other models.- 6.3 Modelling variation in encounter rate and cluster size.- 6.4 Estimation of the probability of detection on the line or point.- 6.5 On the concept of detection search effort.- 6.6 Fixed versus random sample size.- 6.7 Efficient simulation of distance data.- 6.8 Thoughts about a full likelihood approach.- 6.9 Distance sampling in three dimensions.- 6.10 Cue counting.- 6.11 Trapping webs.- 6.12 Migration counts.- 6.13 Point-to-object and nearest neighbour methods.- 7 Study design and field methods.- 7.1 Introduction.- 7.2 Survey design.- 7.3 Searching behaviour.- 7.4 Measurements.- 7.5 Training observers.- 7.6 Field methods for mobile objects.- 7.7 Field methods when detection on the centerline is not certain.- 7.8 Field comparisons between line transects, point transects and mapping censuses.- 7.9 Summary.- 8 Illustrative examples.- 8.1 Introduction.- 8.2 Lake Huron brick data.- 8.3 Wooden stake data.- 8.4 Studies of nest density.- 8.5 Fin whale abundance in the North Atlantic.- 8.6 Use of tuna vessel observer data to assess trends in abundance of dolphins.- 8.7 House wren densities in South Platte River bottomland.- 8.8 Songbird surveys in Arapaho National Wildlife Refuge.- 8.9 Assessing the effects of habitat on density.- Appendix A List of common and scientific names cited.- Appendix B Notation and abbreviations, and their definitions.
「Nielsen BookData」 より
