Identifying links between vital rates and environment: a toolbox for the applied ecologist

In a rapidly changing world, understanding and predicting population change is a central aim of applied ecologists, and this involves studying the links between environmental variation and vital rates (survival, fecundity, etc.). Demographic analysis and modelling can be daunting for practicing ecologists, and here we provide an overview of some of the most important issues and methods. Collection of demographic data should follow standardized protocols and the statistical power to detect links with environment is critically dependent on long time-series. Candidate environmental covariates should be carefully selected with a view to reducing the risk of spurious correlations. The relevant sample size for environment-demography links is typically the number of years and mixed models with random year effects offer a powerful framework to enforce this. Data on individually marked animals are the best source of information on demography. These data can be analysed and demographic parameters estimated using a wide variety of capture-mark-recapture models, available in standard software packages. Population models integrate all demographic variables and provide estimates of population growth rate. Two common classes of models are matrix models and integrated population models, where the latter combine parameter estimation and dynamic modelling.Synthesis and applications. Careful demographic analysis and modelling has provided solutions for many real-world problems in population management, as well as assisting the development of general principles. The tools currently available are flexible and powerful, and the main limitations to their more general use are data availability and training. Careful demographic analysis and modelling has provided solutions for many real-world problems in population management, as well as assisting the development of general principles. The tools currently available are flexible and powerful, and the main limitations to their more general use are data availability and training.