demres: An R package to study time-varying demographic resilience

Quantifying the resilience of populations to disturbances is essential to assess how threatened populations are. Demographic resilience has been defined as the ability of populations to resist and recover from alterations in their demographic structures. Resilience metrics are typically obtained by applying transient analyses to matrix population models. Until now, the questions of how demographic resilience can change over time, how to quantify such temporal variation and when it is important to account for it have not yet been studied. However, since demographic rates fluctuate over time, it is essential to evaluate whether and under what conditions the assumption of time-constant demographic resilience remains appropriate.

In this study we introduce demres - an R package that offers functions to quantify time- varying and time-constant demographic resilience metrics, including time to convergence, damping ratio, inertia, maximum amplification, maximum attenuation and reactivity. The package also allows the comparison of these two approaches, both visually and by means of distance metrics.

We use a case study to illustrate the versatility of demres and demonstrate how this tool can be readily used by conservation biologists, managers and others to assess the time- varying resilience of wildlife populations using long-term demographic data. Our framework facilitates standardised comparisons of demographic resilience metrics, for example by means of comparative studies across populations and species.