Just like in our daily lives, trade-offs are ever-present in biology. Increased performance in one aspect often leads to reduced performance in others. A common life history trade-off occurs between growth and reproduction: given finite resources, increasing expenditures on reproduction usually leads to decreased ability to grow.
What will happen over the course of evolution in the case where a trade-off between growth and reproduction exists? The outcome often will depend on the circumstances in the environment. In cases where organisms are at high risk of dying early, producing offspring early is at a premium, even if it means not being able to grow large enough to produce many offspring. On the other hand, if the risk of dying young is small, then selection may favor organisms delaying reproduction so that they can grow larger and produce more progeny at a later period.
This simulation examines the growth–reproduction trade-off. In it, two morphs of a fish with different life history strategies exist: the first morph (A) starts reproducing at 15 grams, while the second morph (B) delays reproducing until it reaches 50 grams. The A morph can produce 3 offspring per reproductive per time unit, and the B morph can produce 10 offspring per reproductive per time unit. The A morph has the advantage of earlier reproduction, but the B morph has the advantage of a greater reproductive output.
The carrying capacity of the lake in which these fish live is 100. If the population size is below the carrying capacity, new fish are added to the population from the progeny pool. Whether an A morph or B morph is added to the population depends on the proportion of A and B morph that are progeny. If A morphs have produced 30 offspring and B morphs have produced 60, then the probability that the next fish to be added to the progeny pool will be an A morph is 1/3.
The replacements start at 0 g and grow 5 g per time period. If no offspring are in the progeny pool and the population size is still below the carrying capacity, then the population size remains at its level until there are offspring to replace them.
Adjust the predation rate (p)to 0.1. At p = 0.1, the probability of an adult fish being killed by a predator is 10%. We’ll consider this to be a low predation rate.
Start the simulation. The simulation begins with 10 fish of each morph, with all fish starting at 5 g. The simulation ends if (1) one morph reaches fixation, (2) the fish all die, or (3) 100 time units have elapsed. Run the simulation several times and record the final frequencies of each morph after each run.
What is the general pattern of the results in the low predation condition?
Which morph is usually the most prevalent in the early stages of the simulation? Describe what happens.
Now shift the predation rate (p)to 0.3. At p = 0.3, the probability of an adult fish being killed by a predator is 30%. We’ll consider this to be a high predation rate.
Start the simulation. Record the outcome of the simulation, and repeat for a total of ten trials.
What is the general pattern of the results in the high predation condition?
Comparing the outcomes of the low predation and the high predation conditions, what conclusion can you draw about the effect of predation on the life history strategies?