Predv

Predv is a theoretical framework and software package for simulating predator–prey dynamics with explicit predation variability. It was introduced in ecological modeling to examine how individual differences in predation success influence population cycles, stability, and persistence in ecological systems.

The model typically uses two state variables representing prey and predator densities. Prey growth follows a logistic pattern with carrying capacity, while predation is described by a flexible functional response that averages over a distribution of predation efficiencies across predators. The framework accommodates demographic stochasticity and spatial structure, implementing diffusion-like movement on a grid or network. Time can be treated in discrete steps or continuous time, depending on the study design.

Predv has several implementations and variants. Predv-Classic provides a deterministic mean-field version, while Predv-Stochastic introduces birth–death randomness. Predv-Spatial extends the dynamics to a lattice or network to explore spatial patterning, and Predv-ABM offers agent-based simulations. The modular design allows researchers to swap functional responses, variability distributions, and movement rules without altering core equations.

Applications and reception: Predv has been used to investigate how variability in predation efficiency affects stability, bifurcations, and extinction risk. It is employed in theoretical ecology research and graduate teaching, with open-source implementations available in common scientific languages such as Python and R. Limitations include simplified environmental assumptions, sensitivity to parameter choices, and substantial computational requirements for large spatial implementations. The name Predv stems from Predator Variability.