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Lecture 19

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Department
Biology
Course
BIO220H1
Professor
John Stinchcombe
Semester
Winter

Description
BIO220: Lecture 19 Human Population Ecology  If rates are constant and if (birth+ immigration) > (death + emigration), growth trajectory is density- independent and exponential growth  But the example that we saw: o Density-Dependent (growth of population is sensitive to the density of population) o If density is low, pop grows quickly; if density is high, pop grows slowly o Logistic model (inflection point)  Allee, ‘The Great APPES’ o Tried to project what the human pop was at and where it would be (1940s) Assumed pop growth was logistic, assumed it would reach that upper asymptote (carrying capacity) So they thought ~2.6 billion would be the upper limit of the number of humans that the earth could support But right now, human pop is 7 billion ** Human pop growth looks more exponential than logistic  Extrapolating from the logistic growth graph gave a poor prediction, why? o Extrapolating always inaccurate o Logistic is not a law, just a hypothesis o Logistic assumes r (Rate of pop growth: birth control) and K (Carrying capacity: technological advances, cultural/social components) to be constants o They tried to fit the curve based on their last data point and tried to make an inference well beyond their observed data o Logistic allows no overshoots  doesn’t let us think that we can go above the carrying capacity, it could go back down and up, etc.  We’re not actually changing K, but we’re just in an overshoot No oscillation: no lag time, perfect logistic growth, no growth and constant (Green) Damped: time lag (not instantaneous), effects not felt immediately (Blue) Limit cycles: huge periodic cycles (red)  The growth rate depends on balance of fertility and mortality  Birth rates have been high for much of human history, but death rates dropped radically during 19 -20h th Centuries  Changes in r (rate of pop growth)  first vaccination, hygiene, antibiotics, insecticides  Changes in K (carrying capacity)  genetics, machines, fertilizers, biocides  UN projections; rate is slowing, might level off at 9 billion (rate of growth slow but we’re still growing)  Age structure affects the trajectory: population momentum (fast growing pop have broad based age pyramids, excess of children) o In 1861 majority is young (few old) (High momentum  a lot more individuals who have yet to reach reproductive age) o In 2001 majority is older (pop grow slowly) (Low momentum)  Antoni van Leewenhoek  invented microscope, estimated area of globe that could be inhabitated and thought density for humans was 13.4 billion  Alternative: Brown (focuses on the standard of living) o If we all consumed food like India, we could sustain 10 billion people o If we all consumed like US, we could sustain 2.5 billion people  The Demographic Transition Model 1. Pre-industrial: birth + death rates high, r= 0 2. Death rates drop, birth rates high, pop boom (sanitation, vaccination) 3. Birth rates fall, growth rate slows (contraception, later marriage) 4. Birth and death rates equilibrate, r=0  What causes decline in fertility? o Some cases, government policy (Ex. one chid policy) o Most cases: voluntary decisions by parents motivated by
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