BIOB50H3 Chapter Notes - Chapter 9: Exponential Growth, Escherichia Coli, Survivorship Curve

23 views6 pages
5 Feb 2013
School
Course
Professor

For unlimited access to Textbook Notes, a Class+ subscription is required.

CHAPTER 9: POPULATION GROWTH AND REGULATION
Human Population Growth: A Case Study
Human population was over 6.8 billion in 2010 and 3 billion in 1960
From 1860-1991, while the human population has quadrupled in size, our energy
consumption has increased 93-fold
Previously, our population increased relatively slow.
We reached 1 billion in 1825, after 200,000 years, for the first time as a result of
Industrial Revolution.
No one knows for sure when we switched from a relatively slow to explosive
increases in population size
According to best info, there were 500 million people in 1550 and population was
doubling every 275 years.
Population started growing at a very rapid rate once it hit 1 billion
First it doubled from 1 to 2 billion by 1930, in 105 years, and then to 4 billion by
1975, in 45 years.
By 1975, it was growing at an annual rate of 2% which means it doubled after
every 35 years
With that rate, our population would increase to more than 27 billion by 2080,
which is quite unlikely, however
Over the last 50 years, the annual rate has slowed considerably, from 2.2% in
early 1960s to a present rate of 1.18%
Currently, our population increases by about 80 million per year (more than 9100
per hour)
5 countries account for about half of the annual increase: India (21%), China
(11%), Pakistan (5%), Nigeria (4%), and United States (4%)
If this current rate sustains, there will be 15 billion people by 2080
Introduction
Earth is finite and can't support ever-increasing population, thus restricting our
capacity for rapid population growth
Fungi, known as giant puffballs, can produce about 7 trillion offspring per
individual but not all of them reach adulthood.
In the case of loggerhead sea turtles, even if you protect these endangered
species by increasing their newborn survival to 100%, their population would
continue to decline.
An ecologist must understand what factors promote and limit population growth
Life Tables
To obtain life table data for a plant, you mark a large number of seeds as they
germinate and then follow their fate over growing seasons
Life table provides a summary of how survival and reproductive rate vary with
age for organisms. It can be based on age, size, or life cycle stage
In a life table,
x is a variable such as age
Nx is the number of individuals alive at age x
Sx = Nx+1 / Nx. It is the age-specific survival rate, which is the chance that an
individual of age x will survive to be x + 1.S2.
Unlock document

This preview shows pages 1-2 of the document.
Unlock all 6 pages and 3 million more documents.

Already have an account? Log in
Ix = Nx / No. It represents survivorship, which is the proportion of individuals
that survive from birth to age x
Fx represents fecundity, which is the average number of offspring produced by a
female of age x
A cohort life table is where the fate of a group of individuals born during the
same time period (a cohort) is followed from birth to death. These are often for
plants or other sessile organisms because they can be marked and followed
easily
A static life table is often used for highly mobile organisms or ones with long life
spans. It is a table where the survival and reproduction of individuals of different
ages during a single time period are recorded.
You construct a static life table by first estimating the organisms' ages,
determining age-specific birth rates by counting # of offspring by individuals
produced, and then determining age-specific survival rate (only if we assume the
survival rate has remained constant during organisms' lifetimes)
When birth and death rate are hard to find or correlate poorly with age, life tables
are based on sizes or life cycle stages
For some, reproduction rate is closely related to size than age
We can also predict change in size and composition over time by using birth and
death rates
Many economic, sociological, and medical applications rely on human life table
data such as life insurance companies
2009 report by U.S. Centres for Disease Control and Prevention provided
information on Ix , Fx , and life expectancy (expected # of years remaining) of
females
In U.S., Ix doesn't drop greatly until age 70, while in Gambia, many people die at
young age especially those born in the annual "hungry season" (July-Oct)
E.g., 47%-62% of Gambian reached age 45, compared to >96% of U.S. females
Ix can be graphed as a survivorship curve where the data is plotted from
hypothetical cohort (typically of 1000 individuals) that will reach different ages
Ix curves can be classifies into 3 types
Type I survivorship curve is where newborns, juveniles, and young adults have
high survival rates and most survive until old age. E.g. US females and Dall mountain
sheep
Type II survivorship curve is where individuals have a constant chance of dying
throughout their lives. E.g. mud turtles (after second year) and some fish, plants, and
birds
Type III survivorship is where most individuals die young. It's the most common
one in nature since many species produce a lot of offspring. E.g. giant puffballs, oysters,
marine corals, most known insects, and plants like desert shrub
Age Structure
Age class - individuals whose ages fall within a specified range
Age structure - describes proportions of the population in each age class
Age structure influences how rapidly population grows or shrinks
In general, population with more individuals of reproductive age will grow
more rapidly
Unlock document

This preview shows pages 1-2 of the document.
Unlock all 6 pages and 3 million more documents.

Already have an account? Log in

Get access

Grade+
$10 USD/m
Billed $120 USD annually
Homework Help
Class Notes
Textbook Notes
40 Verified Answers
Study Guides
1 Booster Class
Class+
$8 USD/m
Billed $96 USD annually
Homework Help
Class Notes
Textbook Notes
30 Verified Answers
Study Guides
1 Booster Class