Lecture 17: Human Population Ecology

Slide 2

Human impact is a function of population and consumption (affluence and

technology)

oAffluence the consumption that humans are imposing on natural

systems

oTechnology efficiency with which that affluence is gained

Slide 4

Exponential growth model can’t be sustained forever, it may fit this model for

a while, but not indefinitely

oThis model will hold for any population that has constant birth and death

rates

oIf rates are constant and if (birth rate + immigration) > (death rate +

emigration), population growth is density-dependent and exponential

oExponential growth if r>0

oFor any population that grows and the parameters stay constant, they will

grow faster and faster

dN/dt = rN; solved as Nt = N0ert

Slide 6

The simplest model of density-dependent regulation is the logistic model

oDensity-dependent growth rates are not constant but vary with the

number of individuals in the population

Logistic growth sigmoid growth, asymptotic approach to carrying capacity

(K)

oPopulation starts with exponential growth but flattens out at K

oThe breaking term [(K-N)/K] shows how resources are being exhausted

Slide 7

The data from Allee from before 1949 best fit the sigmoid curve

They reached the conclusion that the carrying capacity would be 2.6 billion

people

Best fit of logistic equation to data suggests levelling at 2.6 billion

Slide 8

So far, human population growth looks more like exponential growth than logistic

The population didn’t fit the logistic model predicted by Allee in the 1940s

About 1000 years ago, there is a breaking point where things seem to grow

faster

About 500 years ago, there was a dip in the European population due to the

bubonic plague

Our population rising so much is a very recent effect

Slide 9

Logistic is just an idea of how density-dependence might work but it’s just way

too simple for reality

Logistic model doesn’t allow overshoot, rather it always has a population

levelling off at K

It assumes that birth and death rates (which is equal to r) and the carrying

capacity (K) to be constant; this is oversimplified

Slide 10

These are 3 different versions of the logistic equation modified to reflect time

delays for when the resource limitation kicks in

Green: normal logistic; Blue: time delay; Red: stronger time delay

Time delays cause populations to overshoot the carrying capacity (K)

Blue and Red graphs both overshoot K

Blue smooths out eventually

Red graph reached carrying capacity so far over that it’s on the brink of

massive collapse

Slide 11

We can’t even model ourselves with the logistic model because reality is far

more complicated

Both r and K have been bumped up by technology and it’s an ongoing process

We can’t use r and K to describe the future because these numbers are both

changing

Slide 12

2% per year growth was the fastest growth rate in history

The time scale on the graph ends at 2100 (end of the century)

Green peaking at 7.5 billion an dropping

Blue levelling at 9 billion

Red 14 billion by 2100 and growing

These projections by the UN are fairly optimistic because they don’t include big

population crashes; they basically include that birth rates will drop more or less

voluntarily as humans change their relationship with the world

Slide 13

Growth rates and their response to changing birth and death schedules depend

on population age structures

Population Momentum even if you get to the point where birth and death

rates are equal, the probability that a person produces offspring is exactly offset

by the probability of a person dying

oA population with a lot of pre-reproductive children in it is still going to

have population growth because those children are still going to reach

reproductive age and have babies

High Momentum this pyramid is typical of any rapidly growing population

oThis is the structure that most of the undeveloped countries are growing

like

oMany populations in the world fit this structure

oIf you reduce growth rate to zero, this population still grows for a

generation or two

Low Momentum might stop growing immediately if you make growth rate

zero

oThis is what European countries are growing like