1. A framework for risk assessment. 1.1. A probabilistic framework. 1.2. Causes of extinction -- 2. White rhinoceros on Ndumu Reserve. 2.1. Formulating a birth-and-death model. 2.2. Parameters and initial conditions. 2.3. The deterministic prediction. 2.4. Adding demographic stochasticity. 2.5. Introducing a population ceiling. 2.6. Removing constant numbers. 2.7. Environmental variation. 2.8. Risk assessment -- 3. Useful methods when data are scarce. 3.1. The exponential model for population growth. 3.2. Density dependence, the logistic equation and magpie geese. 3.3. Other forms of density dependence. 3.4. A model for suburban shrews. 3.5. More about unstructured models -- 4. Structured populations. 4.1. Age structure. 4.2. The Leslie matrix. 4.3. Stage structure. 4.4. Simulating variability. 4.5. Correlation and autocorrelation. 4.6. Migration and dispersal. 4.7. Density dependence -- 5. Spatial structure and metapopulation dynamics. 5.1. Components of spatial structure
5.2. Occupancy models. 5.3. A population dynamic model -- 6. Conservation genetics. 6.1. Consequences of the loss of genetic diversity. 6.2. Drift, risk and genetic diversity. 6.3. The effects of inbreeding on population dynamics. 6.4. A stochastic model for Banksia cuneata. 6.5. The genetics of metapopulations -- 7. Extensions of risk assessment. 7.1. The scarcity of data. 7.2. Species viability analysis. 7.3. Implementation -- App. A.1 Random number generators -- App. A.2 Algorithms for random numbers -- App. A.3 Random events and correlated random numbers -- App. A.4 More about sensitivity analysis
Analysis
Organisms Population Dynamics
Organisms Population Dynamics
Notes
Includes index
Bibliography
Includes bibliographical references (pages [285]-308) and index
