Long-Term Monitoring of Population Structure: Alpine Short-Lived Perennials on the Verge of Stability

The local population stage structures of the primrose Androsace albana and the Caucasian forget-me-not Eritrichium caucasicum were observed at permanent sites in the alpine belt of the Northwest Caucasus annually for 14 years (2009–2022), accumulating data of the “identified individuals” type according to known ontogenetic scales. The data allow us to calibrate the corresponding matrix models of population dynamics, from which we can obtain various quantitative characteristics of the monitoring object, in particular, estimate the measure of viability. A well-known approach to predicting the viability of a local population is to estimate its stochastic growth rate (λS) under a certain scenario of random changes in environmental conditions from those observed during the monitoring period. However, only artificial randomness models involved in calculations of λS are proposed in the literature. Our more realistic randomness model (RRM) is associated with variations in the weather and microclimatic conditions of the habitat. It is reconstructed from a sufficiently long (60 years) time series of the weather indicator, which has turned out to be species-specific in the model perennials. The use of RRM in calculations of λS by the Monte Carlo method provides more reliable and accurate estimates of stochastic population growth rates than those using the well-known technique with an artificial randomness model. The obtained estimates of λS are compared between the two species, as well as between those for each of the species obtained from the monitoring data of different durations. The comparison allows us to draw the conclusion given in the title of the paper.