Data from: Assessing the influence of temporal autocorrelations on the population dynamics of a disturbance specialist plant population in a random environment
Eager, Eric Alan
Alexander, Helen M.
Published Apr 21, 2017 on Dryad.
Cite this dataset
Eager, Eric Alan; Pilson, Diana; Alexander, Helen M.; Tenhumberg, Brigitte (2017). Data from: Assessing the influence of temporal autocorrelations on the population dynamics of a disturbance specialist plant population in a random environment [Dataset]. Dryad. https://doi.org/10.5061/dryad.bq340
Biological populations are strongly influenced by random variations in their environment, which are often autocorrelated in time. For disturbance specialist plant populations, the frequency and intensity of environmental stochasticity (via disturbances) can drive the qualitative nature of their population dynamics. In this article, we extended our earlier model to explore the effect of temporally autocorrelated disturbances on population persistence. In our earlier work, we only assumed disturbances were independent and identically distributed in time. We proved that the plant seed bank population converges in distribution, and we showed that the mean and variance in seed bank population size were both increasing functions of the autocorrelation coefficient for all parameter values considered, but the interplay between increasing population size and increasing variability caused interesting relationships between quasi-extinction probability and autocorrelation. For example, for populations with low seed survival, fecundity, and disturbance frequency, increasingly positive autocorrelated disturbances decreased quasi-extinction probability. Higher disturbance frequency coupled with low seed survival and fecundity caused a nonmontone relationship between autocorrelation and quasi-extinction, where increasingly positive autocorrelations eventually caused an increase in quasi-extinction probability. For higher seed survival, fecundity, and/or disturbance frequency, quasi-extinction probability was generally a monotonically increasing function of the autocorrelation coefficient.