Adding a fecundity-survival trade-off to a discrete population model with maturation delay

TL;DR

This paper introduces a new population model incorporating a fecundity-survival trade-off with maturation delay, analyzing how different survival functions and density dependencies affect population stability and extinction thresholds.

Contribution

It develops a class of models that explicitly include trade-offs between maturation delay benefits and survival costs, extending previous models by considering mortality during maturation and different survival functions.

Findings

Optimal maturation delay maximizes population size.

Critical delay threshold leads to extinction.

Oscillatory dynamics observed with Ricker survival function.

Abstract

Although maturation delays are frequently included in population models, researchers rarely account for mortality between birth and maturity. Previous discrete population models have included mortality of immature individuals during the maturation delay finding that increasing the delay decreases the equilibrium population size, eventually leading to extinction. Since maturation delays beyond one breeding cycle are often found in nature, they must also have a benefit leading to a trade-off. We derive a class of models to explore the trade-off between the benefit of a longer maturation delay on fecundity due to larger body sizes at maturity and the down-side on survival. We examine two scenarios: density independent survival and cohort density dependent survival of immature individuals. For the mature and immature individuals, we consider two different, but popular, survival functions: the Beverton--Holt model and the Ricker model. Across all models, we identify a positive maturation delay that maximizes the population size that we refer to as the ``optimal maturation delay'' and a critical delay threshold that results in extinction. We also find oscillatory dynamics with the Ricker survival function for certain ranges of maturation delay. Overall, our delay model sets up a useful phenomenological framework to test multiple combinations of trade-offs in parent survival, offspring survival, and reproductive investment.