Tuning the strength of predation: effects of an abiotic factor on predator-prey dynamics

Background/Question/Methods

Predator-prey cycling is a classical ecological interaction that can be described by mathematical models. Abiotic factors can influence the interactions between predator and prey, and can disproportionately affect one over the other. We refined an existing predator-prey model and ran experiments to determine how predator-prey dynamics are altered when the strength of predation is influenced by an abiotic factor specifically, salinity.

Chemostats are ideal for these studies since they can be modeled by mathematical equations and provide a laboratory means of observing population dynamics over time. We used the alga Chlorella autotrophica as prey, and the rotifer Brachionus plilcatilis as its predator. Both organisms are euryhaline, however studies have shown that C. autotrophica is more tolerant of salinity than B. plicatilis suggesting the strength of predation could be tuned with salinity.

First, we conducted 24 hour growth rate experiments on our algae and rotifers across a range of salinities and choose four salinities (3, 16, 35, 45 g/L) to conduct our chemostat experiments. Second, we conducted the predator-prey chemostat experiments. Lastly, we did rotifer egg development time, egg viability experiments. These experiments allowed us to modify and calibrate an existing predator-prey model to let us see how salinity influenced our predator-prey system.

Results/Conclusions

Our growth rate experiments showed that our algae were more tolerant of salinity than our rotifers. There were two salinities (3 and 45 g/L) where rotifers had similar growth rates, and at those same salinities, our alga species’ growth rates were also similar. However, the chemostat dynamics at these two salinities were different suggesting growth rate was not the only significant parameter.

Egg development time tripled and egg viability was halved at higher salinities, partially explaining the difference in dynamics between chemostats. In addition, simulations from our model suggested that feeding behavior of rotifers at low algal densities contributed to the differences between the 3 and 45 g/L chemostats. Specifically, the degree and type of functional response had a significant impact on dynamics (i.e. differences between type II and type III).

Our results suggest that abiotic factors can influence the temporal dynamics of interacting organisms and that we cannot exclusively look at their immediate responses to stress, since consequences manifest themselves at through time. Here we have demonstrated that an environmental abiotic factor can influence the strength of predation, which in turn can effect predator-prey dynamics with consequences that can propagate through a simple food chain.