1) Unstructured population models. Continuous and discrete-time population models. Sensitivity analysis. Estimation of parameters for ecological models
2) Age and class-structured population models.Construction of the population matrix. Projection of the population. Perturbation analysis. Density dependence in structured models.
3) Stochastic models. The effect of variability in population parameters. Quantification of the effect of the variability. Implementing variability in simple models: Environmental and demographic stochasticity. Perodicity in structured models. Stochasticity in structured models.
4) Individual based models (IBMs). Variability among individuals. Description of IBMs.
5) Statistical inference. Life Table Response Experiments (LTRE). Confidence intervals for vital rates. Comparison of populations. Loglinear analysis.
6) Spatially structured models. Modelling dispersal. Stage structured populations. Metapopulations. Synchronicity
7) Population Viability Analysis. Conservation paradigms. Final and practical recommendations
9) Case studies.
Graduate level of General Ecology, elemental Calculus and Algebra
After the course the student should be able to:
1) Identify problems and more relevant features of the populations;
2) Choose adequate models;
3) Extract basic information to feed the models;
4) Estimate basic population parameters;
5) Make a projection of the population and assess viability;
6) Evaluate the sensitivity of the model and;
7) Propose action plans.