MATH089 Project 1 - Population models

Posted: 08/24/21

Due: 09/03/21, 11:55PM

1Difference equations

1.1Mathematics of difference equations

1.2Fibonacci population model

In 1202 Fibonacci introduced a model of population growth based on discrete time reproduction with death or infertility.

1.2.1Hypotheses

The formal assumptions within the Fibonacci popoulation model are:

  1. Count rabbit pairs, denote by F one male and one female;

  2. Assume rabbit pairs do not die;

  3. Assume each pair reproduces in a constant time interval of one month;

  4. Assume one unit of time from birth to fertility;

  5. Assume each rabbit pair reproduces exactly one new rabbit pair;

  6. Assume all rabits pairs are fertile.

Denote time by n, and let Fn denote the number of pairs at time n.

1.2.2Mathematical formulation

The Fibonacci model leads to the relation

Fn=Fn-1+Fn-2forn

with initial conditions F0=0, F1=1. The model exhibits exponential growth as shown in Fig. 1

function F(n)
  if ((typeof(n)==Int64) && (n>=0))
    if (n<2) 
       return n
    end
    return F(n-1)+F(n-2)
  else
    print("Invalid argument\n")
  end
end

F

Julia]

Figure 1. Logarithmic representation of Fibonacci rabbit pair growth.

N=30; n=0:N; Fn=F.(n); clf(); plot(n,log.(Fn),"o");
xlabel("n (months)"); ylabel("F(n) (rabbit pairs)");
title("Fibonacci population model"); grid("on");
savefig(homedir() * "/courses/MATH089/images/Fibonacci.eps")

1.3Malthus population model

A different population model is given

Pn+1=Pn+rPn=(1+r)Pn,P0=1.
Pn+1=Pn+rPn=(1+r)Pn,P0=1.
Pn+1=Pn+(M-Pn-1)rPn-1
Fn=Fn-1+Fn-2forn
function P(n,r)
  if ((typeof(n)==Int64) && (n>=0) && (r>-1))
    if (n==0) 
       return 1
    end
    return (1+r)*P(n-1,r)
  else
    print("Invalid argument\n")
  end
end

P

P(2,0.1)

1.2100000000000002

Figure 2.

N=30; n=0:N; r=1; Pn=P.(n,r); plot(n,log.(Pn),"o");
xlabel("n (months)"); ylabel("P(n)");
title("Malthus population model"); grid("on");
savefig(homedir() * "/courses/MATH089/images/Malthus.eps")

1.4Logistic population model

2Systems of difference equations

2.1Predator-prey models

2.2Resource-Gatherer-Prey models

2.3Susceptible-Infectious-Recovered disease propagation models

3Differential equations

3.1Limits of difference equations

3.2Correspondence principle