Fundamentals of Predator-Prey Relationships: Lecture Notes
Lotka-Volterra Model
- Developed independently by:
- Volterra: Italian mathematician, based model on shark catches in Fiume.
- Lotka: Austrian demographer, ecologist, chemist, and mathematician (moved to America), developed model from a theoretical standpoint.
- The models were very similar and developed at the same time, thus the Lotka-Volterra model was born.
- Famously applied to Lynx and Snowshoe Hare dynamics.
- Data from Hudson Bay Trading Company fur records (1847-1903).
Prey in the Lotka-Volterra Model
- Prey grow exponentially in the absence of predators (r*N), without density dependence.
- Predators control prey density.
- Factors affecting this control:
- Prey density.
- Predator density.
- Predator hunting efficiency.
Predators in the Lotka-Volterra Model
- Growth rate of the predator population is dependent on the prey.
- Factors affecting this:
- Prey density.
- Predator density.
- Predator hunting efficiency.
- Prey conversion efficiency (not every calorie consumed is absorbed).
Predator-Prey Model: Population Growth Rate
- Prey population growth rate loss due to predator consumption rate.
- Predator population growth rate is directly related to prey capture.
- Includes:
- Prey.
- Predator.
- Conversion rate of prey.
- Hunting efficiency.
- Predator death rate.
Predator-Prey Model: Mass Action
- The relationship between variables is called "mass action."
- Mass action = homogeneous mixing.
- A very common function in many types of models.
Predator-Prey Model: Dynamics
- Higher prey conversion leads to less prey and more predators.
- Timing of the cycles is also changed.
- Lotka-Volterra style equations lead to cycles.
Dynamics of Snowshoe Hare and Lynx
- Data taken from the Hudson Bay Trading Company Records.
- Show cycles of hare and lynx populations over time.
Host-Parasitoid Dynamics
- Illustrates oscillations in host and parasitoid populations over generations.
Lotka-Volterra Models: What Can They Tell Us?
- Effects of:
- Increasing prey density.
- Increasing predator density.
- Long/short-lived predators.
- Efficient/inefficient predators.
- High nutritive value (high conversion) of prey to new predators.
- BUT IS IT REALISTIC?
Is the Lynx-Hare Interaction a Lotka-Volterra Relationship?
- We can make the model fit the data.
- Lynx populations peak a little after the hares.
- BUT snowshoe hares cycle on islands without lynx present.
- What else could influence prey populations?
- Density dependence (general).
- Food availability.
- Pathogens.
Examining the Real Impact of Predation (and Food) in the Snowshoe Hares
- Krebs et al (1995) Impact of Food and predation on the snowshoe hare cycle. Science 269 (5227): 1112-1115
- What they did:
- Added food to sites.
- Excluded predators.
- Excluded predator & added food.
- Added fertilizer.
- Left things alone (control).
Snowshoe Hare Investigation: Findings
- Krebs et al. (1995) Science 269 (5227): 1112-1115
- Giving food increased hares x 3.
- Excluding predators increased hares X 2.
- Excluding predator and increasing food increased hares x 11.
- Effects are more than additive (multiplicative?).
- Complex interaction between predation and food.
Ground Squirrel - Food / Predation Study
- Karels et al. (2000) J of Anim Ecol 59 (2): 235-47
- Demonstrates the impact of predator exclosure and food supplementation on ground squirrel population density.
How Good Is the Lotka-Volterra Model?
- Lotka-Volterra does give one explanation for predator-prey cycles.
- Matches the snowshoe hare – lynx data BUT there are obviously other things going on.
- Not all predator-prey relationships show cycles.
- Some show more stable dynamics.
- The model doesn’t take into account influences on the prey other than predation
- Prey density dependence
- Pathogen influences
- Prey competition with other species
- Doesn’t (in simplest form) consider predator handling efficiency of the prey.
Adding Prey Density Dependence to the Lotka-Volterra Model
\frac{dN}{dt} = r \cdot N (1 - \frac{N}{K}) - a \cdot N \cdot P
- Leads to damped oscillations reaching a steady state.
- Incorporates carrying capacity (K) for the prey.
Predator – Handling Efficiency (Holling Type I)
- Work carried out by Rigler (1961).
- Linear increase in feeding with prey density until a maximum.
- Maximum is a limit e.g. daphnia can only swallow at a certain rate.
Predator – Handling Efficiency (Holling Type II)
- An asymptotic relationship.
- Increased consumption as density increase.
- BUT the rate of consumption slows as prey increases.
- Predators take a certain amount of time to HANDLE prey.
- At first, the availability of prey is the over-riding time constraint – got to catch them to eat them.
- BUT when they’re easy to catch, then the time to process them becomes the more important constraint.
Predator – Handling Efficiency (Holling Type III)
- Sigmoidal relationship between host/prey density and consumption or attack rate.
- At low prey density, the host has to increase its search effort.
- This means that section A of the curve approximates exponential increase.
- As prey/host density increases, the Holling type II response results.
Holling Feeding Responses
- Illustrates the three types of functional responses: Type I (linear), Type II (asymptotic), and Type III (sigmoidal).
Holling’s Functional Responses Type II
- Number attacked vs. Host Density.
- % Mortality: Inverse density-dependent.
- Th low, Th high (T_h = handling time).
Holling’s Functional Responses Type III
- Number attacked vs. Host Density.
- % Mortality: Density-dependent at low density, inverse density-dependent at high density.
Incorporating Holling Type II
- Wilkinson M.H.F. (2006) Mathematical Modelling of Predatory Prokaryotes. In: Jurkevitch E. (eds) Predatory Prokaryotes. Microbiology Monographs, vol 4. Springer, Berlin, Heidelberg. https://doi.org/10.1007/7171_054
- h = handling time.
- Damped oscillations reaching an equilibrium.
- LIMIT cycles.
Summary
- Predators and prey often shown linked cycles.
- These linked cycles can be modeled using Lotka-Volterra predator-prey models.
- Many natural systems do fit the model (or its extensions).
- But other influences, such as food supply, can interact with and alter the relationship between the species.
- The model can describe non-cycling populations if density-dependence is included in the prey.
- Further modifications to alter the prey handling times allows both cyclic and stable dynamics under different conditions.
- Prey handling efficiency and form varies across species.