Posted by: oikosasa | June 28, 2013

Exploitation-interference link

How interference competition affect population dynamics is explored in the new Early View paper in Oikos “Linked exploitation and interference competition drives the variable behavior of a classic predator–prey system” by John P. DeLong and David Vasseur. Here’s John’s background story and summary:

We had a hunch. While trying to understand how interference competition works, we began to suspect that traits that influenced the rate at which consumers encountered their resources would also influence the rate at which consumers encountered each other. Maybe some measure of exploitation competition would therefore be related to a measure of interference competition.

Figure 1. Traits that influence the rate of consumer-resource encounters might also influence the rate of consumer-consumer encounters, generating a link between exploitation and interference competition.

Figure 1. Traits that influence the rate of consumer-resource encounters might also influence the rate of consumer-consumer encounters, generating a link between exploitation and interference competition.

 

To find out, we measured foraging rates in the classic Didinium nasutum – Paramecium aurelia predator-prey system. By measuring foraging rates at different levels of both the predator and the prey, we could fit a functional response to the data and retrieve estimates of parameters that reflect the magnitude of these forms of competition. If there was any variation in those parameters, we would expect it to be correlated.

Delong2

Figure 2. Here a Didinium nasutum is consuming a Paramecium bursaria.

We created 16 different populations and nudged them in different directions – they received varying amounts of nutrients, varying amounts of prey and predators, and were allowed to grow for different amounts of time. Then we pulled individuals from the populations and conducted the foraging experiments, once for each population separately. Our functional response included the power-law form of interference – mutual interference – and the standard ‘a’ parameter that characterizes exploitation. Across the populations, exploitation was strongly correlated with interference.

Figure 3. Interference competition (which gets more intense as it gets more negative) is strongly and positively related to exploitation competition (a).

Figure 3. Interference competition (which gets more intense as it gets more negative) is strongly and positively related to exploitation competition (a).

 

Turns out we weren’t the first ones to suspect this. In 1954, Park suggested that the two forms of competition might be linked, but since that time research into competition has largely investigated interference separately from exploitation. Keeping them separate is likely to obscure how competition influences ecological and evolutionary dynamics, especially given that interference can have a rather strong impact on foraging rates.

For example, the Didinium – Paramecium is famous for having highly variable dynamics. Usually, dropping a few Didinium into a plate full of Paramecium leads to one cycle of growth followed rapidly by the extinction of both populations. However, slowing everything down can lead to more oscillatory behavior. These variable dynamics are easily explained by the link between exploitation and interference, with low interference and low exploitation leading to oscillatory dynamics, intermediate competition values leading to stabilized dynamics, and higher values of both leading to deterministic extinction.

Figure 4. Predator-prey dynamics, here simulated for Didinium – Paramecium, vary from oscillatory to deterministic extinction due to the correlated nature of the interference and exploitation parameters.

Figure 4. Predator-prey dynamics, here simulated for Didinium – Paramecium, vary from oscillatory to deterministic extinction due to the correlated nature of the interference and exploitation parameters.

 

We also found a way to modify the mathematical formulation for the ‘a’ parameter that generates the kind of exploitation-interference relationship we observed. This model suggests that the rate of travel of the predator is an important driver of both forms of competition, bringing a measurable trait to bear on this problem.

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