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Overgrazing

Overgrazing. Wild Approximations. Use Python Conditional. if condition : statements. if condition : statements else : statements. if condition : statements elif condition : statements else : statements. Overgrazing. How to model population effects?

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Overgrazing

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  1. Overgrazing

  2. Wild Approximations

  3. Use Python Conditional ifcondition: statements ifcondition: statements else: statements ifcondition: statements elif condition: statements else: statements

  4. Overgrazing How to model population effects? If prey population is “too large”, then what?

  5. One Possible Modification Starvation rate Rate 0 Cut-off Prey population

  6. One Simple Modeling Approach prey.append(prey[y] + prey[y] * (growth-predation*pred[y]-starvation(prey[y],starveCutoff,starveRate))/stepsPerYear) defstarvation(prey,cutoff,rate): if prey < cutoff: return 0 else: returnrate

  7. Terminating Wild Approximations Terminate computation when data is too extreme.

  8. Terminating Wild Approximations for y inrange(years*stepsPerYear): times.append(…) prey.append(…) pred.append(…) for y inrange(years*stepsPerYear): newPrey = … newPred = … ifabs(newPrey) > popMaxorabs(newPred) > popMax: break times.append(…) prey.append(newPrey) pred.append(newPred)

  9. Suggested Readings • Carrying capacityand the standard way to adding it to Lotka-Volterra.

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