5. Estimating survival and movement
James D. Nichols, William L. Kendall, and Michael C. Runge
5.1 Introduction
Goals of bird conservation programs typically are expressed in terms of either
abundance or quantities such as extinction probability that are strongly influenced
by abundance. Abundance is accordingly the state variable used in most models
of bird populations, and its estimation is therefore important (Chapters 1, 2).
Changes in abundance over time are functions of four fundamental demographic
parameters: reproduction, survival, emigration, and immigration. Conservation
programs that seek to bring about changes in abundance must do so via manage-
ment actions that influence one or more of these four parameters (see Chapters 12,
13, 14). Estimation of these quantities and, more importantly, the relationship
between these quantities and environmental variables, bird density and conserva-
tion actions, forms a central methodological topic in bird conservation. Methods
for studying reproduction have been presented in Chapter 3, and this chapter deals
with methods for estimating survival and movement in and out of populations.
More detailed treatment of the material presented here can be found in Seber
(1982) and Williams et al. (2002), and for birds, in particular, in Clobert and
Lebreton (1991).
Sometimes it is possible to draw inferences about survival and movement based
on counts of birds. For example, estimation of survival is sometimes based on
counts of birds in different age classes. Although appropriate methods exist for
such estimation (e.g. Udevitz and Ballachey 1998; Williams et al. 2002), they
require restrictive assumptions about time- and age-specific sampling probabilit-
ies and population growth that are often difficult to meet. We thus tend to agree
with Clobert and Lebreton (1991) that such methods have not been generally
useful for birds. However, a recent Bayesian analysis successfully used counts of
first-year and older Whooping Cranes (Grus americana) to estimate age-specific
survival and recruitment rates (Link et al. 2003), and this approach holds promise