Population dynamics of sea ducks: using models to understand the causes, consequences, evolution, and management of variation in life history characteristics

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Abstract

In this chapter, I explore population dynamics of sea ducks by developing population models. In determining which life history characteristics had the greatest influence on future population dynamics, adult female survival consistently had the highest sensitivity and elasticity and this result was robust across a wide range of life history parameter values. Conversely, retrospective models consistently found that the majority of annual variation in lambda was associate with variation in productivity. Stochastic models that are base on process variation and incorporate correlations among life history parameters are the most useful for visualizing the probability of achieving a desired management outcome. Effective management targets both the mean and the variance parameters and takes advantage of correlations among life history parameters. Example models demonstrate that sea duck species can achieve equal fitness using a variety of survival and productivity combinations. Sea duck populations will tend to have long time largest in terms of responding to management actions. Understanding the role of density-dependent population regulation is critical for effective sea duck management and conservation.

Additional publication details

Publication type Book chapter
Publication Subtype Book Chapter
Title Population dynamics of sea ducks: using models to understand the causes, consequences, evolution, and management of variation in life history characteristics
Chapter 3
ISBN 978-1-4822-4897-5
Volume 46
Year Published 2015
Language English
Publisher CRC Press
Publisher location Boca Raton, FL
Contributing office(s) Alaska Science Center Biology WTEB
Description 34 p.
Larger Work Type Book
Larger Work Subtype Monograph
Larger Work Title Ecology and conservation of North American sea ducks: Studies in Avian Biology v. 46
First page 63
Last page 96
Online Only (Y/N) N
Additional Online Files (Y/N) N