Risk Assessment in Conservation Biology

A cohesive guide to the available mathematical modelling methods that can be used in population viability analysis. It is therefore extremely valuable to both the practitioner of conservation biology and theoretical population biologists. The models used are stochastic models for demographic risk assessment, particularly those dealing with unstructured population models, area-based models and structured, projection-matrix models.

Part 1 A framework for risk assessment: probabilistic framework; causes of extinction. Part 2 White rhinoceros on Ndumu Reserve: formulating a birth and death model; parameters and initial conditions; the deterministic prediction; adding demographic stochasticity; introducing a population ceiling; removing constant numbers; environmental variation; risk assessment. Part 3 Useful methods when data are scarce: the exponential model for population growth; density dependence, the logistic equation and magpie geese; other forms of density dependence; model for suburban shrews; more about unstructured models. Part 4 Structured populations: age structure; the Leslie matrix; stage structure; simulating variability; correlation and autocorrelation; migration and dispersal; density dependence. Part 5 Spatial structure and metapopulation dynamics: components of spatial structure; occupancy models; a population dynamic model. Part 6 Conservation genetics: consequences of the loss of genetic diversity; drift, risk and genetic diversity; the effects of inbreeding on population dynamics; a stochastic model for "Banksia Cuneata"; the genetics of metapopulations. Part 7 Extensions of risk assessment: the scarcity of data; species viability analysis; implementation. Appendices: random number generators; algorithms for random numbers; random events; more about sensitivity analysis.