Review of Estimation of Parameters for Animal Populations: A Primer for the Rest of Us by Larkin A. Powell and George A. Gale

Authors

Max Post van der Burg, United States Geological Survey, Northern Prairie Wildlife Research CenterFollow

Date of this Version

12-2016

Document Type

Book Review

Citation

The Prairie Naturalist 48: 111. December 2016

Comments

Published by the Great Plains Natural Science Society, 2016. United States government work. Public domain material.

Abstract

“Me? A modeler? Never!” This is the opening challenge of the book, Estimation of Parameters for Animal Populations: A Primer for the Rest of Us, by Larkin Powell and George Gale. I say “challenge” because I think this book attempts to challenge the misconception that quantitative methods are out of reach for most biologists and wildlife scientists. When many of us attend college or graduate school to study wildlife science there’s a sense that, at some point, there will be math. But it appears that the attitude of many students toward this reality is to simply suffer through the math, quickly forget it, and then move on. That is, until they encounter it again on the job. As a person who started out their professional life in a non-quantitative way, but later learned how to think quantitatively, I assure you that it is possible to learn this stuff. You just need the right resources. For students, this might mean seeking out the right teachers, whereas practicing wildlife professionals may have to rely more on books. The problem is that there aren’t many easily accessible books available on this topic for those who want to learn, but really cannot devote their time to a Ph.D. in statistics. Powell and Gale’s book sets out to remedy this. The first part of the book is dedicated to understanding many of the basic quantitative estimation concepts that a wildlife professional might encounter. These include concepts such as maximum likelihood and variance estimation. While these may seem like esoteric topics to those who do not think of themselves as modelers, many of these concepts underlay the process of estimating fundamental population parameters, like abundance or survival.