Policy and Complex Systems
from 100 % to ~ 67 %, the prey was benefited , increasing their equilibrium population size , as well as their average age . However , now that energy is explicitly accounted for with a movement cost , and individual effectiveness can only be reduced by reducing this movement cost , the benefits of a similar change no longer accrue to the prey population . Figure 5 illustrates this result .
The last row in Figure 5 reproduces the bottom chart in Figure 4 , where the predators ’ individual effectiveness is reduced from 50 % to ~ 25 %. Rather than benefiting , the prey population is reduced in size by a very small amount . Conversely , the predator population increases quite dramatically : their final population size is double in value of what it had at the start of the simulation , and their average age has increased as well . Clearly , they have benefited from the reduction in movement costs , living longer while eating less , and not significantly reducing the overall size of their prey population . Thus , when the trade-off is high , predators will choose to reduce their efforts , both individually and collectively .
A moderate trade-off ( 2.5 %, middle row ) and a low trade-off ( 2 %, top row ) produce less of a change , especially the moderate trade-off . As we can see , the moderate trade-off results in a hunting effectiveness equilibrium that is almost unchanged , still at ~ 50 %, and a movement cost that is nearly the same as well — 0.01 units per turn . As such , the population size and average age for both predators and prey are virtually the same as they were at the start of the simulation . Even though the individual predators could evolve to hunt better ( or worse ), at this trade-off they do not .
The low trade-off condition ( 2 %, top row ) does have negative consequences for both populations . Recall from Figure 4 that the predators increase their hunting effectiveness , from 50 % to very nearly perfect , ~ 97 % on average . In the original model that does not account for energy costs , this would be harmful for the prey population but would not affect the predators at all , in either population size or average age . Here , things are different . The prey population experiences an almost imperceptible decrease in size , while the predators experience a ~ 40 % decline in numbers , and a ~ 30 % decline in average age . The lesson seems to be that if predator success comes too easy , then everyone loses .
IV - Discussion and Future Work
In our previous results , we showed
how increasing the food to the prey population does not truly help the prey ; rather , only the predator population increases in size . Because of this increase in predators , the prey is consumed faster than otherwise : they eat faster and reproduce faster , but since there is no change in the predators ’ hunting ability , the prey must also have a shorter lifespan when there are more predators . The Red Queen hypothesis raises questions , however , about the predators ’ effectiveness : what happens when this is changed ? In particular , can we discover the minimal conditions that put a limit on such change ?
In the first set of experiments , we adjusted this effectiveness directly , by simply dictating how often ( stochastically ) the predators would miss catching a prey . This potentially helps us understand the net effect on population levels that the Red Queen hypothesis can have , but it does not help explain the mechanism that will get us there . Due to the absence of a detailed study , it may be assumed that both the predators and the prey should adapt endlessly , engendering an arms race in their antagonistic abilities . The second set of experiments , however ,
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