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UNI101Y1 (52)

# Ch11 Population Growth and Regulation3.pdf

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School
University of Toronto St. George
Department
University College Courses
Course
UNI101Y1
Professor
Spencer Barrett
Semester
Winter

Description
 there is another reason to express pop. growth as an exponential function  whereas the change in absolute # of indiv. depends on the pop. size, the change in the logarithm of pop. size is linear over time  if we plot the natural logarithm (ln) of N as a function of time, we obtain a straight line whose slope is the value of r  we can see this by taking the logarithm of the expression for the exponential growth, N(t) = N(0)e , which is ln[N(t)] = ln[N(0)] + rt o this is the eqn for the straight line w/ an intercept at t = 0 of ln[N(0)] and a slope of r  the growth rates of diff pop., or of a single pop. over time, can be compared readily by plotting the logarithm of pop. size over time Calculating Population Growth Rates from Birth and Death Rates  exponential growth: the indiv. contribution to pop. growth (r) is the diff. b/w birth rate (b) and death rate (d) calculated on a per capita basis, thus r = b – d  geometric growth: the per capita growth rate per unit of time (R) is the diff. b/w the per capita rates of birth (B) and death (D) per unit of time, thus R = B – D & λ = 1 + R  in the case of individuals moving b/w subpopulations: r = b – d + i – e  immigration (i), emigration (e)  birth and death rates pertain to populations not to indiv.  ex. an indiv. groundhog dies only once, it can’t have a personal death rate  when birth and deaths are averaged over a pop., they take on meaning as rates of d
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