The viability of populations can be quantified with several measures, such as the probability of extinction, the mean time to extinction, or the population size. While conservation management decisions can be based on these measures, it has not yet been explored systematically if different viability measures rank species and scenarios similarly and if one viability measure can be converted into another to compare studies. To address this challenge, we conducted a quantitative comparison of eight viability measures based on the simulated population dynamics of more than 4500 virtual species. We compared (a) the ranking of scenarios based on different viability measures, (b) assessed direct correlations between the measures, and (c) explored if parameters in the simulation models can alter the relationship between pairs of viability measures. We found that viability measures ranked species similarly. Despite this, direct correlations between the different measures were often weak and could not be generalized. This can be explained by the loss of information due to the aggregation of raw data into a single number, the effect of model parameters on the relationship between viability measures, and because distributions, such as the probability of extinction over time, cannot be ranked objectively. Similar scenario rankings by different viability measures show that the choice of the viability metric does in many cases not alter which population is regarded more viable or which management option is the best. However, the more two scenarios or populations differ, the more likely it becomes that different measures produce different rankings. We thus recommend that PVA studies publish raw simulation data, which not only describes all risks and opportunities to the reader but also facilitates meta-analyses of PVA studies.
Keywords: PVA; extinction; population dynamics; population‐viability analysis; survival.
© 2023 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.