A framework for studying transient dynamics of population projection matrix models

Authors

  • Iain Stott,

    1. Centre for Ecology and Conservation, Biosciences, College of Life and Environmental Sciences, University of Exeter Cornwall Campus, Tremough, Treliever Road, Penryn, Cornwall, TR10 9EZ, UK
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  • Stuart Townley,

    1. College of Engineering, Mathematics and Physical Sciences, University of Exeter, Harrison Building, Streatham Campus, Exeter, Devon, EX4 4QF, UK
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  • David James Hodgson

    Corresponding author
    1. Centre for Ecology and Conservation, Biosciences, College of Life and Environmental Sciences, University of Exeter Cornwall Campus, Tremough, Treliever Road, Penryn, Cornwall, TR10 9EZ, UK
      E-mail: d.j.hodgson@exeter.ac.uk
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E-mail: d.j.hodgson@exeter.ac.uk

Abstract

Ecology Letters (2011) 14: 959–970

Abstract

Empirical models are central to effective conservation and population management, and should be predictive of real-world dynamics. Available modelling methods are diverse, but analysis usually focuses on long-term dynamics that are unable to describe the complicated short-term time series that can arise even from simple models following ecological disturbances or perturbations. Recent interest in such transient dynamics has led to diverse methodologies for their quantification in density-independent, time-invariant population projection matrix (PPM) models, but the fragmented nature of this literature has stifled the widespread analysis of transients. We review the literature on transient analyses of linear PPM models and synthesise a coherent framework. We promote the use of standardised indices, and categorise indices according to their focus on either convergence times or transient population density, and on either transient bounds or case-specific transient dynamics. We use a large database of empirical PPM models to explore relationships between indices of transient dynamics. This analysis promotes the use of population inertia as a simple, versatile and informative predictor of transient population density, but criticises the utility of established indices of convergence times. Our findings should guide further development of analyses of transient population dynamics using PPMs or other empirical modelling techniques.

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