Method development for emergent properties in stage-structured population models with stochastic resource growth.

• Modelling population dynamics in ecological systems reveals properties that are difficult to find by empirical means, such as the probability that a population will go extinct when it is exposed to harvesting. In this article, we use an aquatic ecological system containing one fish species and an underlying resource as our model. In particular, we study a class of stage-structured population systems, in both the deterministic and the stochastic settings, including stochasticity in such a way such that we allow the underlying resource to have a random growth rate. In these models, we study how properties connected to the fish species depend on different harvesting rates. To investigate models in the stochastic setting, we use Monte Carlo simulations to capture several of the emergent properties of the population. These properties have previously been studied in the deterministic case. In the stochastic setting, we get estimates for the expected outcome of population properties in our model, but we also get measures of dispersion. There are properties that emerge when introducing randomness in the model that cannot be studied in the deterministic cases, such as the probability of extinction. In this paper, we develop a method to derive this property. We also construct a method to determine the recovery potential of a species by introducing it in a virgin environment.

Nyckelord

Logistic; Method development; Population dynamics; Probability of extinction; Semi-chemostat; Semi-logistic; Stage-structured; Stochastic

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