The model has parameters for the prey and for the predator, and you will explore how these parameters influence the dynamics of the populations. In this class you will build and explore a Lotka-Volterra predator-prey model in Excel to gain insight into the ecology of interacting predators and prey.įollow the PDF worksheet ( here), which guides you to build and explore a Lotka-Volterra predator-prey model in Excel. Modifications to the model include the availability of refuges (places where the prey are safe from predators) and carrying capacity (i.e. using logistic growth). In the classic Lotka-Volterra predator-prey model, the predator and prey populations grow exponentially. The Lotka-Volterra predator-prey model offers a foundational framework for understanding the complex dynamics between species interactions and the delicate balance that shapes the stability and persistence of predator-prey relationships in diverse ecological communities. This cyclical pattern continues as predator and prey populations oscillate over time. ![]() ![]() As predator numbers increase, the prey population declines, which, in turn, leads to a decrease in predator numbers due to reduced food availability. The model assumes that the predator’s population growth is directly influenced by the availability of its prey, while the prey’s population growth is affected by predation pressure. The Lotka-Volterra predator-prey model (Rosenzweig and MacArthur 1963) is a fundamental concept in ecological dynamics, widely used to study the dynamics between predator and prey populations in a shared ecosystem. 22.2 Optional: Try these calculations in R.22.1 Animals/plants, not grains of rice.21.2.2 Applying the Exponential Growth Model.21.2 Real-World Application: Breeding Pairs of Merlin (Falco columbarius).21.1.1 Calculating N for any future time point.20.18 Solutions: From population biology to fitness.20.17 Solutions: The legend of Ambalapuzha.20.16 Solutions: Lotka-Volterra predator-prey dynamics.20.15 Solutions: Lotka-Volterra competition.20.13 Solutions: Neutral or adaptive evolution in humans.20.11 Solutions: Hardy-Weinberg equilibrium. ![]() 20.10 Solutions: Trade-offs and the force of selection.20.9 Solutions: How many eggs should a bird lay?.20.8 Solutions: Matrix population modeling.20.7 Solutions: Life tables and survivorship types.20.6.3 You can obtain parameters from graphs.20.6.2 Type of dynamics depends on \(r_m\).20.6.1 Relationship between Logistic and Exponential growth equations.20.6 Solutions: Deeper into logistic growth.20.5 Solutions: Basic logistic population growth.20.4 Solutions: Stochastic population growth.V Animal behaviour, altruism and sexual selection.18 Lotka-Volterra predator-prey dynamics.IV Interactions Between Species and Community Structure.16.2.2 Comparative Analysis (10 minutes).16.2.1 Estimating heritability (15 minutes).16 Heritability from a linear regression.15 Neutral or Adaptive Evolution in Humans: What Drives Evolution of Our Traits?.14.4 Simulation of allele frequency through time.14.3.2 Projecting allele frequency over one time step.13.2 Assumptions of Hardy-Weinberg Equilibrium.12.3 Exploring different life history strategies.12 Trade-offs and the declining force of selection.10.6 Life table response experiment (LTRE). ![]()
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