Distance Sampling: Methods and Applications

Distance Sampling: Methods and Applications
Author :
Publisher : Springer
Total Pages : 285
Release :
ISBN-10 : 9783319192192
ISBN-13 : 3319192191
Rating : 4/5 (191 Downloads)

Book Synopsis Distance Sampling: Methods and Applications by : S. T. Buckland

Download or read book Distance Sampling: Methods and Applications written by S. T. Buckland and published by Springer. This book was released on 2015-08-08 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, the authors cover the basic methods and advances within distance sampling that are most valuable to practitioners and in ecology more broadly. This is the fourth book dedicated to distance sampling. In the decade since the last book published, there have been a number of new developments. The intervening years have also shown which advances are of most use. This self-contained book covers topics from the previous publications, while also including recent developments in method, software and application. Distance sampling refers to a suite of methods, including line and point transect sampling, in which animal density or abundance is estimated from a sample of distances to detected individuals. The book illustrates these methods through case studies; data sets and computer code are supplied to readers through the book’s accompanying website. Some of the case studies use the software Distance, while others use R code. The book is in three parts. The first part addresses basic methods, the design of surveys, distance sampling experiments, field methods and data issues. The second part develops a range of modelling approaches for distance sampling data. The third part describes variations in the basic method; discusses special issues that arise when sampling different taxa (songbirds, seabirds, cetaceans, primates, ungulates, butterflies, and plants); considers advances to deal with failures of the key assumptions; and provides a check-list for those conducting surveys.


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Introductory concepts. Introduction. Range of applications. Types of data. Known constants and parameters. Assumptions. Fundamental concept. Detection. History