Quantitative Conservation Biology: Theory and Practice of Population Viability Analysis

ISBN : 9780878935468

William F. Morris; Daniel F. Doak
480 Pages
176 x 231 mm
Pub date
Jun 2002
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This text provides practical, intelligible, and intuitive explanations of population modelling to empirical ecologists and conservation biologists. Modelling methods that do not require large amounts of data (typically unavailable for endangered species) are emphasized. As such, the book is appropriate for undergraduate and graduate students interested in quantitative conservation biology, managers charged with preserving endangered species, and, in short, for any conservation biologist or ecologist seeking to better understand the analysis and modelling of population data.


1. What Is Population Viability Analysis, and How Can It Be Used in Conservation Decision-Making?
2. The Causes and Quantification of Population Vulnerability
3. Count-based PVA: Density-independent Models
4. Count-based PVA: Incorporating Density Dependence, Demographic Stochasticity, Correlated Environments, Catastrophes and Bonanzas
5. Accounting for Observation Error in Count-based PVAs
6. Demographic PVAs: Using Demographic Data to Build Stochastic Projection Matrix Models
7. Demographic PVAs: Using Projection Matrices to Assess Population Growth and Viability
8. Demographic PVAs Based on Vital Rates: Removing Sampling Variation and Incorporating Large Variance, Correlated Environments, Demographic Stochasticity, and Density Dependence into Matrix Models
9. Using Demographic PVA Models in Management: Sensitivity Analysis
10. Population Dynamics across Multiple Sites: the Interaction of Dispersal and Environmental Correlation
11. Methods of Viability Analysis for Spatially Structured Populations
12. Critiques and Cautions: When to Perform (and When Not to Perform) a Population Viability Analysis

About the author: 

William F. Morris is a Professor in the Biology Department at Duke University.; Daniel F. Doak is a Professor in the Environmental Studies Program at the University of Colorado at Boulder.

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