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  • https://doi.org/10.1111/2041-210x.12543Copy DOI Icon

Perturbation analysis of transient population dynamics using matrix projection models

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Abstract

Summary Non‐stable populations exhibit short‐term transient dynamics: size, growth and structure that are unlike predicted long‐term asymptotic stable, stationary or equilibrium dynamics. Understanding transient dynamics of non‐stable populations is important for designing effective population management strategies, predicting the responses of populations to environmental change or disturbance, and understanding population processes and life‐history evolution in variable environments. Transient perturbation analyses are vital tools for achieving these aims. They assess how transient dynamics are affected by changes to vital rates, population structure, or underlying variables that affect these. These changes could be imposed deliberately by population managers, or driven by environmental variables. Methodological approaches to transient perturbation analysis are diverse, and different methods are suited to different applications: choosing a method to use may be challenging. Here, I review existing methods for prospective transient perturbation analysis, and identify a number of key considerations for ecologists when choosing a method. These include the approach taken in calculating the perturbation, the type of model being analysed, the perturbation structure, the population response of interest, nonlinear response to perturbation, standardization for asymptotic dynamics, the initial population structure, and the time frame of interest. I discuss these with reference to the application of transient perturbation analyses in both population management and comparative analysis. The diversity of transient perturbation analyses available means that existing approaches are applicable to a wide range of population management and comparative analysis scenarios. It is important, however, for ecologists using these methods to know exactly what is being measured. Despite a wealth of existing methods, I identify some areas that would benefit from further development.

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