Drummond:PopGen: Difference between revisions

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==Notes on population genetics==
==Per-generation and instantaneous growth rates==
<p>
<p>
Let <math>n_i(t)</math> be the number of organisms of type <math>i</math> at time <math>t</math>, and let <math>R</math> be the ''per-capita reproductive rate'' per generation.  If <math>t</math> counts generations, then
Let <math>n_i(t)</math> be the number of organisms of type <math>i</math> at time <math>t</math>, and let <math>R</math> be the ''per-capita reproductive rate'' per generation.  If <math>t</math> counts generations, then
:<math>n_i(t+1) = n_i(t)R</math>
:<math>n_i(t+1) = n_i(t)R\!</math>
and
and
:<math>n_i(t) = n_i(0)R^t</math>.
:<math>n_i(t) = n_i(0)R^t.\!</math>
</p>
</p>
<p>
<p>
Now we wish to move to the case where <math>t</math> is continuous and real-valued.
Now we wish to move to the case where <math>t</math> is continuous and real-valued.
As before,<br/>
As before,<br/>
:<math>n_i(t+1) = n_i(t)R</math><br/>
:<math>n_i(t+1) = n_i(t)R\!</math>
but now<br/>
but now<br/>
:<math>\begin{matrix}
:{|
n_i(t+\Delta t) &=& n_i(t)R^{\Delta t}\\
|align="right" |<math>n_i(t+\Delta t)\!</math>
n_i(t+\Delta t) &=& n_i(t)R^{\Delta t} + n_i(t) - n_i(t)\\
|<math>=n_i(t)R^{\Delta t}\!</math>
n_i(t+\Delta t) - n_i(t) &=& n_i(t)R^{\Delta t} - n_i(t)\\
|-
\frac{n_i(t+\Delta t) - n_i(t)}{\Delta t} &=& \frac{n_i(t)R^{\Delta t} - n_i(t)}{\Delta t}\\
|align="right" |<math>n_i(t+\Delta t) - n_i(t)\!</math>
\frac{n_i(t+\Delta t) - n_i(t)}{\Delta t} &=& n_i(t) \frac{R^{\Delta t} - 1}{\Delta t}\\
|<math>= n_i(t)R^{\Delta t} - n_i(t)\!</math>
\lim_{\Delta t \to 0} \left[\frac{n_i(t+\Delta t) - n_i(t)}{\Delta t}\right] &=& \lim_{\Delta t \to 0} n_i(t) \frac{R^{\Delta t} - 1}{\Delta t}\\
|-
\frac{d n_i(t)}{dt} &=& n_i(t) \lim_{\Delta t \to 0} \frac{R^{\Delta t} - 1}{\Delta t}\\
|align="right" |<math>\frac{n_i(t+\Delta t) - n_i(t)}{\Delta t}</math>
\frac{d n_i(t)}{dt} &=& n_i(t) \ln R\\
|<math>=\frac{n_i(t)R^{\Delta t} - n_i(t)}{\Delta t}</math>
\end{matrix}</math>
|-
where the last simplification follows from [http://en.wikipedia.org/wiki/L%27Hopital%27s_rule L'Hopital's rule].  Explicitly, let <math>\epsilon=\Delta t</math>.  Then<br/>
|align="right" |<math>\frac{n_i(t+\Delta t) - n_i(t)}{\Delta t}</math>
:<math>
|<math>=n_i(t) \frac{R^{\Delta t} - 1}{\Delta t}</math>
\begin{matrix}
|-
\lim_{\Delta t \to 0} \frac{R^{\Delta t} - 1}{\Delta t} &=& \lim_{\epsilon \to 0} \frac{R^{\epsilon} - 1}{\epsilon}\\
|align="right" |<math>\lim_{\Delta t \to 0} \left[{n_i(t+\Delta t) - n_i(t) \over \Delta t}\right]</math>
&=& \lim_{\epsilon \to 0} \frac{\frac{d}{d\epsilon}\left(R^{\epsilon} - 1\right)}{\frac{d}{d\epsilon}\epsilon}\\
|<math>=\lim_{\Delta t \to 0} \left[ n_i(t) \frac{R^{\Delta t} - 1}{\Delta t}\right]</math>
&=& \lim_{\epsilon \to 0} \frac{R^{\epsilon}\ln R}{1}\\
|-
&=& \ln R \lim_{\epsilon \to 0} \frac{R^{\epsilon}}{1}\\
|align="right" |<math>\frac{d n_i(t)}{dt}</math>
&=& \ln R.
|<math>=n_i(t) \lim_{\Delta t \to 0} \left[\frac{R^{\Delta t} - 1}{\Delta t}\right]</math>
\end{matrix}
|-
</math>
|align="right" |<math>\frac{d n_i(t)}{dt}</math>
|<math>=n_i(t) \ln R\!</math>
|}
where the last simplification follows from [http://en.wikipedia.org/wiki/L%27H%C3%B4pital%27s_rule L'Hôpital's rule].  Explicitly, let <math>\epsilon=\Delta t</math>.  Then<br/>
:{|
|-
|<math>\lim_{\Delta t \to 0} \left[{R^{\Delta t} - 1 \over \Delta t}\right]</math>
|<math>= \lim_{\epsilon \to 0} \left[\frac{R^{\epsilon} - 1}{\epsilon}\right]</math>
|-
|
|<math>=\lim_{\epsilon \to 0} \left[\frac{\frac{d}{d\epsilon}\left(R^{\epsilon} - 1\right)}{\frac{d}{d\epsilon}\epsilon}\right]</math>
|-
|
|<math>=\lim_{\epsilon \to 0} \left[\frac{R^{\epsilon}\ln R}{1}\right]</math>
|-
|
|<math>=\ln R \lim_{\epsilon \to 0} \left[R^{\epsilon}\right]</math>
|-
|
|<math>=\ln R\!</math>
|}
</p>
</p>


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:<math>\frac{d n_i(t)}{dt} = n_i(t) \ln R</math>
:<math>\frac{d n_i(t)}{dt} = n_i(t) \ln R</math>
is
is
:<math>n_i(t) = n_i(0) e^{t\ln R} = n_i(0) R^{t}</math>
:<math>n_i(t) = n_i(0) e^{t\ln R} = n_i(0) R^{t}.\!</math>
Note that the continuous case and the original discrete-generation case agree for all values of <math>t</math>.  We can define the ''instantaneous rate of increase'' <math>r = \ln R</math> for convenience.
Note that the continuous case and the original discrete-generation case agree for all values of <math>t</math>.  We can define the ''instantaneous rate of increase'' <math>r = \ln R</math> for convenience.
</p>
</p>
</div>
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Per-generation and instantaneous growth rates

Let [math]\displaystyle{ n_i(t) }[/math] be the number of organisms of type [math]\displaystyle{ i }[/math] at time [math]\displaystyle{ t }[/math], and let [math]\displaystyle{ R }[/math] be the per-capita reproductive rate per generation. If [math]\displaystyle{ t }[/math] counts generations, then

[math]\displaystyle{ n_i(t+1) = n_i(t)R\! }[/math]
and
[math]\displaystyle{ n_i(t) = n_i(0)R^t.\! }[/math]

Now we wish to move to the case where [math]\displaystyle{ t }[/math] is continuous and real-valued. As before,

[math]\displaystyle{ n_i(t+1) = n_i(t)R\! }[/math]
but now
[math]\displaystyle{ n_i(t+\Delta t)\! }[/math] [math]\displaystyle{ =n_i(t)R^{\Delta t}\! }[/math]
[math]\displaystyle{ n_i(t+\Delta t) - n_i(t)\! }[/math] [math]\displaystyle{ = n_i(t)R^{\Delta t} - n_i(t)\! }[/math]
[math]\displaystyle{ \frac{n_i(t+\Delta t) - n_i(t)}{\Delta t} }[/math] [math]\displaystyle{ =\frac{n_i(t)R^{\Delta t} - n_i(t)}{\Delta t} }[/math]
[math]\displaystyle{ \frac{n_i(t+\Delta t) - n_i(t)}{\Delta t} }[/math] [math]\displaystyle{ =n_i(t) \frac{R^{\Delta t} - 1}{\Delta t} }[/math]
[math]\displaystyle{ \lim_{\Delta t \to 0} \left[{n_i(t+\Delta t) - n_i(t) \over \Delta t}\right] }[/math] [math]\displaystyle{ =\lim_{\Delta t \to 0} \left[ n_i(t) \frac{R^{\Delta t} - 1}{\Delta t}\right] }[/math]
[math]\displaystyle{ \frac{d n_i(t)}{dt} }[/math] [math]\displaystyle{ =n_i(t) \lim_{\Delta t \to 0} \left[\frac{R^{\Delta t} - 1}{\Delta t}\right] }[/math]
[math]\displaystyle{ \frac{d n_i(t)}{dt} }[/math] [math]\displaystyle{ =n_i(t) \ln R\! }[/math]

where the last simplification follows from L'Hôpital's rule. Explicitly, let [math]\displaystyle{ \epsilon=\Delta t }[/math]. Then

[math]\displaystyle{ \lim_{\Delta t \to 0} \left[{R^{\Delta t} - 1 \over \Delta t}\right] }[/math] [math]\displaystyle{ = \lim_{\epsilon \to 0} \left[\frac{R^{\epsilon} - 1}{\epsilon}\right] }[/math]
[math]\displaystyle{ =\lim_{\epsilon \to 0} \left[\frac{\frac{d}{d\epsilon}\left(R^{\epsilon} - 1\right)}{\frac{d}{d\epsilon}\epsilon}\right] }[/math]
[math]\displaystyle{ =\lim_{\epsilon \to 0} \left[\frac{R^{\epsilon}\ln R}{1}\right] }[/math]
[math]\displaystyle{ =\ln R \lim_{\epsilon \to 0} \left[R^{\epsilon}\right] }[/math]
[math]\displaystyle{ =\ln R\! }[/math]

The solution to the equation

[math]\displaystyle{ \frac{d n_i(t)}{dt} = n_i(t) \ln R }[/math]
is
[math]\displaystyle{ n_i(t) = n_i(0) e^{t\ln R} = n_i(0) R^{t}.\! }[/math]
Note that the continuous case and the original discrete-generation case agree for all values of [math]\displaystyle{ t }[/math]. We can define the instantaneous rate of increase [math]\displaystyle{ r = \ln R }[/math] for convenience.