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∈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-2⁡for⁡n∈ℕ

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+r⁡Pn=(1+r)Pn,P0=1.
Pn+1=Pn+r⁡Pn=(1+r)Pn,P0=1.
Pn+1=Pn+(M-Pn-1)r⁡Pn-1
Fn=Fn-1+Fn-2⁡for⁡n∈ℕ
∴ 
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