Manly / McDonald / Thomas Resource Selection by Animals

Statistical design and analysis for field studies
1993
ISBN: 978-94-011-1558-2
Verlag: Springer Netherland
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 177 Seiten, eBook

We have written this book as a guide to the design and analysis of field studies of resource selection, concentrating primarily on statistical aspects of the comparison of the use and availability of resources of different types. Our in tended audience is field ecologists in general and wildlife biologists in particular who are attempting to measure the extent to which real animal populations are selective in their choice of food and habitat. As such, we have made no attempt to address those aspects of theoretical ecology that are concerned with how animals might choose their resources if they acted in an optimal manner. The book is based on the concept of a resource selection function, where this is a function of characteristics measured on resource units such that its value for a unit is proportional to the probability of that unit being used. We argue that this concept leads to a unified theory for the analysis and interpretation of data on resource selection and can replace many ad hoc statistical methods that have been used in the past.

Zielgruppe

Research

Autoren/Hrsg.

Manly, B.B.

McDonald, L.

Thomas, D.L.

Inhaltsverzeichnis

Introduction to resource selection studies. Examples of the use of resource selectory studies. Examples of the use of resource selection functions. Statistical modelling procedures. Studies with resources defined by several categories. Estimating a resource selection probability function from a census of resource units using logistic regression. Estimating a resource selection probability function from a census of resource units at several points in time using the proportional hazards model. Estimating a resource selection function from samples of resource units using proportional hazards and log-linear models. Estimating a resource selection function from two samples of resource units using logistic regression and discriminant function methods. General log-linear modelling. Analysis of the amount of use. The comparison of selection for different types of resource unit. References. Index.