The simplistic predator-prey model dictates the only effect on prey numbers (by predation) is the direct level of predation which occurs i.e. the number of prey a predator consumes. However, prey can respond to the presence of predators in their vicinity by altering their morphological responses or their behaviour. This normally occurs as an attempt to reduce the probability of predation (i.e. the changes in behaviour/ morphology are anti-predator responses) but this can sometimes cause more harm than good, especially when in reality predation rates in the majority of systems are actually quite low. For example, 75% of Wildebeest mortality is due to starvation, therefore predation makes up less than 25%.

Typically predators are inefficient too; this makes sense because if a prey animal is unable to escape a predator – it loses its life, whereas if the predator fails to catch the prey animal it is normally able to simply catch another. Efficient predators will cause extinction of their prey which shows nearly all known predators are inefficient in catching their prey.

Predators normally target individuals who are less able to escape, such as the old or sick. However, as individuals such as these are unlikely to reproduce again, the population suffers limited reduction in overall fitness i.e. the cost of predation on a population is lower than expected.

Changes in Prey Behaviour

The presence of a predator causes the initiation of anti-predator responses in prey; these responses are typically behavioural and are an attempt to reduce the risk of predation. In doing so, the prey often expose themselves to increased amounts of lethal indirect effects (e.g. starvation). Lethal indirect effects are simply a result of the behavioural changes caused by the presence of the predator.

The lethality of risk effects (the changes of prey behaviour) can be just as large as the risk of predation, if not greater. This is due to the behavioural responses of the prey to the risk effects impacting on growth rates, reproduction or survivability. Behavioural responses to risk effects include:

• Change in habitat or use of habitat
• Increased time used for vigilance (i.e. less foraging etc.)
• Altered foraging (This could be reduced foraging, a change in diet, etc.)
• Altered movement patterns
• Change in sensitivity to environmental conditions

Examples

An example of this is the response of Zooplankton species to predatory water fleas. The response of Zooplankton to predators in one experiment showed them descend to much deeper depths during the day and only feed at night. The negative effect this had on the growth rate of the zooplankton was 7x as large as typical circumstances.

Another example is the habitat transition of Elk from grassland to forest when there is a threat of predation. Wolves are the natural predator of Elk, and find it more difficult to hunt them when they are located in the forest. Male Elk are sometimes unable to make the transition to the forest habitat because they have engaged in rutting behaviour with other males; this leaves them requiring large amounts of energy to recover. Such energy would not be available to the Elk from the forest so they remain in the high energy density grassland. As a result they are up to 6x as vulnerable to predation (Creel et al. 2005).

Bluegill Sunfish are predated by the Largemouth Bass. The presence of Largemouth Bass forces the Sunfish to forage in the less nutritious weedy areas. As a result their growth is impaired, reduced by around 27% (Werner, Hall 1988).

Signalling To Predators

The presence of a predator can cause some species of prey animals to begin exhibiting signals. These signals are an honest measure of fitness which the predator can use to judge whether the prey is worth hunting.

Stotting is an unusual jumping behaviour exhibited by some quadrupeds (such as gazelle). It involves the animal leaping high into the air, raising all four legs from the ground. Stotting is used as a signal by predators to determine the fitness of an animal and as such, stotting is now performed by prey in the presence of a predator.

Stotting is energetically costly to the individual, so only the fittest individuals are able to maintain frequent, high quality stotting behaviour. As a result, stotting competitions occurs between the fleeing population – the individual with the weakest and least frequent jumps is the most likely to be selected by the predator for consumption (FitzGibbon, Fanshawe 1988).

Reproductive Costs of Predation Risk

Risk effects don’t just increase the likelihood of mortality of prey, they can also affect reproduction. This was shown in an experiment which used aphids as the prey and Damsel bugs as the predators.

In this experiment (Nelson, Matthews & Rosenheim 2004), there were 3 conditions:

• Normal – Predator and prey contained together, untreated
• No predator – Prey were kept alone to monitor the control rate of reproduction
• Mutilated predators – The proboscis of the predator was removed so that the predator could not consume the prey but their presence could still affect the prey

The results were; under no-predator conditions, the reproduction rate was high and with the introduction of a normal predator – reproduction decreased. Interestingly, under normal densities, when the mutilated predator was introduced, the amount of reproductive loss was equivalent to that when a normal predator was introduced – despite the fact they could not predate. This showed that the prey were suffering as a result of the predator presence and not because of the predation.

Reproductive Loss due to Predation Risk

As the above experiment showed, the risk of predation doesn’t just affect survivability – it can also affect reproduction. The risk of predation alone (i.e. where the predator had be mutilated to prevent actual consumption of prey) is enough to reduce reproductive capabilities.

Another example of this has been observed in deer, preyed upon by wolves. In this experiment (Creel, Christianson 2008). The reproductive rate of the deer was measured in the absence of predators. The survival of the calves was also measured half a year later.

In the control situation, reproductive rate was high and there was a relatively small loss of calves over the winter period. When predators were introduced, again the reproductive rate of the deer and half-year survival of the calves was measured. A 40% drop in reproductive rate was observed and the half-year survivability of the calves also decreased greatly – around 2x as many calves not surviving the winter.

The decrease in both reproductive rate and survivability was owed to the risk effect of the predator. In the presence of the wolf predators, the prey responded by altering their habitat – their new habitat providing much less nutrition. This experiment showed again that, the risk effect can be just as large as the actual predation risk.

Decreased Growth Rate and Increased Mortality Due to Predation Risk

An example of how the risk effect can cause a decrease in growth rate was shown by Havel & Dodson in Daphnia pulex. This tiny marine species is preyed upon by the larvae Chaoborus midge. In response to the presence of their predators, Daphnia grow defensive spines around their body. Whilst this increases their chances of surviving predation 2-fold, it comes at a great cost to growth. Their development time increases by anything from 10-100%. This is due to their source of nutrition being low in protein; therefore the extra effort put into growing defensive spines reduces available protein for general growth (Havel, Dodson 1987).

Inevitably, reduction in growth rate, reproductive rate, grazing rate etc. due to the risk effect will likely increase mortality rate. To show this, Schmitz et al. used grasshoppers, predated by spiders. Their experiment contained 3 conditions, similar to the Nelson experiment; no-predators, maimed predators and normal predators.

Taking the no-predator condition as control, the introduction of unchanged predators reduced grasshopper density (i.e. increased mortality) by around 20-30%. Interestingly, the introduction of maimed predators (spiders whose mouthparts had been sealed shut to prevent actual consumption of prey) also saw a drop in grasshopper density only slightly less than that observed when normal predators were introduced. Even though the spiders were unable to kill their prey, they still managed to reduce their numbers – completely by altered prey behaviour due to their presence (Rothley, Schmitz & Cohon 1997).

Ecological Costs vs. Fitness Costs

How is it that responses which can reduce available energy, reduce resource availability, decrease the reproductive rate and increase mortality more so than the direct effect of predation, evolve in the first place? All these costs are measured as ecological costs; these costs affect the whole population or species. This differs from fitness costs which are based solely upon the individual. Antipredator responses which have an impact on ecological costs may not impact the fitness of individuals as much. An antipredator response can evolve if it has relatively large ecological costs – but not if it lowers the fitness of an individual.

Whilst it may be possible for an antipredator response which does lower individual fitness to evolve, such behaviour will not be selected for by natural selection and thus not exhibited by future generations.

Generally, all antipredator responses have at some point increased the fitness of an individual (even if they do impact on ecological costs).

References

Creel, S. & Christianson, D. 2008, “Relationships between direct predation and risk effects”, Trends in Ecology and Evolution, vol. 23, no. 4, pp. 194-201.

Creel, S., Winnie Jr., J., Maxwell, B., Hamlin, K. & Creel, M. 2005, “Elk alter habitat selection as an antipredator response to wolves”, Ecology, vol. 86, no. 12, pp. 3387-3397.

FitzGibbon, C.D. & Fanshawe, J.H. 1988, “Stotting in Thomson’s gazelles: an honest signal of condition”, Behavioral Ecology and Sociobiology, vol. 23, no. 2, pp. 69-74.

Havel, J.E. & Dodson, S.I. 1987, “Reproductive costs of Chaoborus-induced polymorphism in Daphnia pulex”, Hydrobiologia, vol. 150, no. 3, pp. 273-281.

Nelson, E.H., Matthews, C.E. & Rosenheim, J.A. 2004, “Predators reduce prey population growth by inducing changes in prey behavior”, Ecology, vol. 85, no. 7, pp. 1853-1858.

Rothley, K.D., Schmitz, O.J. & Cohon, J.L. 1997, “Foraging to balance conflicting demands: Novel insights from grasshoppers under predation risk”, Behavioral Ecology, vol. 8, no. 5, pp. 551-559.

Werner, E.E. & Hall, D.J. 1988, “Ontogenetic Habitat Shifts in Bluegill: The Foraging Rate-Predation Risk Trade-off”, Ecology, vol. 69, no. 5, pp. pp. 1352-1366.