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  <last_published>2011-11-28T14:47:20</last_published>
  <indexXML>&lt;mdoxml version=&quot;1.0&quot;&gt;&lt;h3&gt;Discrete Modelling&lt;/h3&gt;
&lt;p&gt;We often use &lt;em&gt;discrete&lt;/em&gt; mathematics to model a population when time is modelled in discrete steps. This fits well with annual censuses of wildlife populations. &lt;/p&gt;
&lt;p&gt; &lt;/p&gt;
&lt;p&gt;Sometimes populations are themselves discrete, such as:&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;Species with non-overlapping generations (eg. annual plants)&lt;/li&gt;
&lt;li&gt;Species with pulsed reproductions (eg. many wildlife species in seasonal environments)&lt;/li&gt;
&lt;/ul&gt;
&lt;h3 style=&quot;text-align: center;&quot;&gt;&lt;mdo:image alt=&quot;&quot; src=&quot;winter%20cress.jpg&quot; style=&quot;width: 213px; height: 181px;&quot;&gt;&lt;/mdo:image&gt;&lt;/h3&gt;
&lt;p style=&quot;text-align: center;&quot;&gt;Winter cress is a winter annual plant.&lt;/p&gt;
&lt;h3&gt;Geometric Growth&lt;/h3&gt;
&lt;p&gt;The population equation, $N_{t+1}=\lambda N_t$ , from &lt;a href=&quot;http://nrich.maths.org/7730?part=index&quot;&gt;before&lt;/a&gt; means that over discrete intervals of time,$t_0, t_1, t_2, ...$, the rate of change in population size is proportional to the size of the population.&lt;/p&gt;
&lt;p&gt;We first solve this equation: $$\begin{align*} N_{t+1}&amp;amp;=\lambda N_t \\ &amp;amp;=\lambda \lambda N_{t-1} \\&amp;amp; =...\\ &amp;amp;= \lambda^{t+1} N_0 \\ \Rightarrow N_t &amp;amp;=\lambda^t N_0 \end{align*}$$ The population size will depend on the value of $\lambda$&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;If $\lambda&amp;gt; 1$ then exponential increase&lt;/li&gt;
&lt;li&gt;If $\lambda=1$ then stationary population&lt;/li&gt;
&lt;li&gt;If $\lambda&amp;lt; 1$ then exponential decrease&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;&lt;strong&gt;Question:&lt;/strong&gt;  If a population of owls increases by 40% in a year, what is the value of &lt;em&gt;r&lt;/em&gt; and $\lambda$ ?&lt;/p&gt;
&lt;p style=&quot;text-align: center;&quot;&gt;&lt;mdo:image alt=&quot;&quot; src=&quot;owls.jpg&quot; style=&quot;width: 307px; height: 168px;&quot;&gt;&lt;/mdo:image&gt;&lt;/p&gt;
&lt;p&gt;Given there were initially 10 owls, what will the population size be in 75 days?  Can you plot this population growth?&lt;/p&gt;
&lt;p&gt; &lt;/p&gt;
&lt;h3&gt;Exponential Growth&lt;/h3&gt;
&lt;p&gt;Some populations may grow continuously, without pulsed births and deaths (eg. humans). In these cases, time is a continuous smooth curve, so we use differential equations to represent this continuous model.&lt;/p&gt;
&lt;p&gt;Using our discrete model from above: $$\begin{align*} N_{t+\Delta t}&amp;amp;=\lambda^{\Delta t} N_t =(1+r)^{\Delta t}N(t)\approx (1+r\Delta t) N(t)\\  \Rightarrow \Delta N_t&amp;amp;\approx r \Delta t N_t \\  \\\Rightarrow \lim_{\Delta t \to 0} \frac{\Delta N(t)}{\Delta t} &amp;amp;=\frac {\mathrm{d}N(t)}{\mathrm{d}t}=rN(t) \end{align*}$$ &lt;strong&gt;Question: &lt;/strong&gt; Solve the equation,
$\frac {\mathrm{d}N(t)}{\mathrm{d}t}=rN(t)$ , using standard integrals, showing that the solution is $N(t)=N_0e^{rt}$.&lt;/p&gt;
&lt;p&gt; &lt;/p&gt;
&lt;p&gt;Different values of &lt;em&gt;r&lt;/em&gt; determine the change in population size, as shown below.&lt;/p&gt;
&lt;h4 style=&quot;text-align: center;&quot;&gt;&lt;mdo:image alt=&quot;&quot; src=&quot;Exponential%20Num%201.JPG&quot; style=&quot;width: 505px; height: 347px;&quot;&gt;&lt;/mdo:image&gt;&lt;/h4&gt;
&lt;p&gt;Also note the connection between the discrete and continous solutions:  $$\begin{align*} N_t =\lambda^t N_0  &amp;amp;\text{  and  }  N(t)=N_0 e^{rt} \\ \Rightarrow \lambda^t&amp;amp;=e^{rt} \\ \lambda&amp;amp;=e^r \\ \ln(\lambda)&amp;amp;=r \end{align*}$$ &lt;strong&gt;Question:&lt;/strong&gt;  Using the discrete model above, how long does it take for this population to double in size? What
about the continous case?&lt;/p&gt;
&lt;p&gt; &lt;/p&gt;
&lt;h3&gt;Limitations of the Models&lt;/h3&gt;
&lt;p&gt; &lt;/p&gt;
&lt;p&gt;Consider a population of insects which suddenly dies out right before the start of every time period, and whose children hatch right after. A discrete model would lead us to believe that there are no insects during the entire period, so instead we should use a continuous model.&lt;/p&gt;
&lt;p&gt;On the other hand, it is often impossible to continually monitor the population size, so we approximate using the discrete case.&lt;/p&gt;
&lt;p&gt; &lt;/p&gt;
&lt;p&gt;Choosing which of discrete or continuous to use is an important decision in modelling populations.&lt;/p&gt;
&lt;p&gt;Can you also think of any assumptions we have made with these models, and why they could be a problem? Consider the environment the population inhabits and differences between members of the population.&lt;/p&gt;
&lt;p&gt;Click &lt;a href=&quot;http://nrich.maths.org/7048?part=index&quot;&gt;here&lt;/a&gt; to see the geometric model adapted to include environmental resistance.&lt;/p&gt;
&lt;p&gt; &lt;/p&gt;
&lt;p&gt;&lt;strong&gt;Question: &lt;/strong&gt; If $\lambda = 1.25$, by how much does a population of blue footed boobies increase per year?&lt;/p&gt;
&lt;p style=&quot;text-align: center;&quot;&gt;&lt;mdo:image alt=&quot;&quot; src=&quot;100529-46%20Blue%20Foot%20Boobies%20at%20Los%20Tuneles.jpg&quot; style=&quot;width: 266px; height: 199px;&quot;&gt;&lt;/mdo:image&gt;&lt;/p&gt;
&lt;p&gt;The population N(t) of blue footed boobies is assumed to satisfy the logistic growth equation $\frac {\mathrm{d}N}{\mathrm{d}t}=\frac{1}{500} N(t) \big( 1-N(t)\big)$ . Given $N_0=200$, solve for N(t). Repeat for $N_0=2000$. Discuss the long-term behaviour of the population in both cases.&lt;/p&gt;
&lt;p&gt; &lt;/p&gt;&lt;/mdoxml&gt;</indexXML>
  <solutionXML>&lt;mdoxml version=&quot;1.0&quot;&gt;
&lt;p&gt;We then solve this equation: $$\begin{align*} \frac {\mathrm{d}N}{\mathrm{d}t}&amp;amp;=rN(t) \\ \frac {\mathrm{d}N}{N(t)}&amp;amp;=r\mathrm{d}t \\ ln\big(N(t)\big)&amp;amp;=rt+c \\ N(t)&amp;amp;=e^{rt}e^{c} \\ \therefore N(t)&amp;amp;=N_0e^{rt} \end{align*}$$&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;The birth and death rates remain constant and unvaried for different individuals&lt;/li&gt;
&lt;li&gt;No random changes over time (eg. due to fire, drought)&lt;/li&gt;
&lt;li&gt;The population is closed&lt;/li&gt;
&lt;li&gt;No time lag in the continuous model&lt;/li&gt;
&lt;/ul&gt;

&lt;/mdoxml&gt;</solutionXML>
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  <end_user_role>2</end_user_role>
  <difficulty>4</difficulty>
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  <title>Population Dynamics - part 2</title>
  <description>Second in our series of problems on population dynamics for advanced students.</description>
  <spec_group>Applications
    <specifier>biology</specifier>
  </spec_group>
  <spec_group>Pre-Calculus and Calculus
    <specifier>Calculus generally</specifier>
  </spec_group>
  <spec_group>Using, Applying and Reasoning about Mathematics
    <specifier>Mathematical modelling</specifier>
  </spec_group>
  <spec_group>Collections
    <specifier>Population Dynamics</specifier>
  </spec_group>
</resource>