“Assessing the influence of temporal autocorrelations on the population dynamics of a disturbance specialist plant population in a random environment”
Eric Alan Eager, Diana Pilson, Helen M. Alexander, and Brigitte Tenhumberg
The effects of autocorrelated disturbances on disturbance specialist plants and their seed banks
Stringing together disturbances
It has been known for a long time that soil disturbances influence the population dynamics of many plant species. For disturbance specialist plant populations like wild sunflower (Helianthus annuus), these disturbances are essential for the germination of seeds, and subsequent population growth. Such natural disturbances occur in a relatively random, unpredictable fashion than disturbances in an agricultural setting, and thus traditional approaches to modeling population dynamics generally do not work. Additionally, data suggests that these disturbances do not happen independently, that the presence or absence of a disturbance during one time period affects disturbance profiles during later time periods.
One way to incorporate all of these ideas into a study of disturbance specialist plants is to use mathematical models, which are an efficient and useful way of determining how various disturbance regimes affect the size, composition and eventual fate of plant-seed bank systems.
Eric Eager and colleagues created a mathematical model and used extensive simulations to find that increasingly-positive autocorrelations in the presence of disturbance had different effects on plant-seed bank populations depending on population viability. More-viable populations responded negatively to increasingly positive autocorrelations due to an increased chance for a string of “bad” years to derail population sizes, while less-viable populations responded positively to such autocorrelations, with an increased chance of a string of “good” years providing an opportunity for populations to increase when small. Read the Article