POPULATIONS

1
POPULATIONS

• Review for Lecture 481

2
most important concept

•      
• Most populations grow exponentially unless
  some limiting factor changes the rate of birth or
  death or migration
• So you need to know about
  the DNA tools

3
Chapter 48
4
This chapter and Lab 9 emphasize two problems

• The exponential explosion problem, when
  populations grow too fast.
• The extinction problem, just the opposite.

5
lab

• Work in groups on computers population
  simulations etc.
• (optional) Bring your own laptop and install our
  CD
• some explanations at beginning so be on time.

6
Figure 48.1a
7
The extinction problem. 1 November 2002
Science Mag.

• almost half of all plant species could be facing
  extinction.
• Since animals are nearly always dependent on
  specific plants, directly or indirectly, for food
  and nesting sites, the outlook is horrible.

8
The extinction problem. keep notes on how
your experiences in Labs 9, 10, and 8 (field
trip) relate to these components of the
extinction problem

• habitat destruction (or partial destruction
  affecting a limiting factor)
• habitat fragmentation
• edge effects (note speciation seems to increase
  at habitat edges but speciation is too slow to
  make up for the losses of other species when
  patches become too small)
• gene pool bottlenecks (inbreeding problems)
• Random accident effects becoming worse in smaller
  populations (LAB 9)
• demographic stochasticity
• loss of genetic variability (genetic
  stochasticity)
• corridors connecting patches and fragments

9
most important concept revised

•      
• Most populations grow exponentially unless
  some limiting factor changes the rate of birth or
  death or migration
• Other populations decline exponentially unless
  something replenishes their habitats limiting
  factors.

10
Extinctions and
Explosions Both problems are exponential
growth or decay, nearly always caused by damage
to a habitat or by moving a population out of its
natural habitat.
11
exponential explosion problem, when populations
grow too fast.

• Nearly all populations are capable of
  exponential growth.
• How fast the exponential growth (or decline) will
  be depends on
• the energy available to the population
• demographic factors (like potential mothers)

12
demographic factors

• b fecundity (birth rate, especially age-specific
  rates)
• d death (mortality rates vs. survivorship)
• i e immigration and emigration rates.
• age structure of the population (age pyramids
  ignored at beginning of chapter)

13
Figure 48.9b
Less-developed countries
100
95
1998 data
90
85
2050 projections
80
75
70
65
60
55
50
45
40
35
30
25
20
15
10
5
0
0
100
100
200
200
300
300
(in millions)
Females
Males
14
US http//www.census.gov/cgi-bin/ipc/idbpyrs.pl?c
tyUSoutdymax250 India http//www.census.go
v/cgi-bin/ipc/idbpyrs.pl?ctyINoutdymax250
Italy http//www.census.gov/cgi-bin/ipc/idbpyrs
.pl?ctyIToutdymax250
15
demographic factors (b, d, i, e, and age
structure) are affected by

• interactions with other species (competitors for
  limiting factors, predators, prey, pollinators,
  parasitic diseases, etc.)
• stochasticity chance (weather, fires, tidal
  waves, volcanoes, asteroids, stochasticity in
  other species, etc.)
• the population's genetic composition, its
  adaptations for its specific niche the relative
  frequency of alleles which contribute to
  migration and survival and reproduction under the
  specific conditions in its habitat.

16
Exponential vs Density-dependent

• J- shape growth S-shape growth

17
The math

• N (density)
• t
• N0
• Nt
• per capita rates of birth, death, and net
  migration (b, d, i)
• K or Nmax or carrying capacity

18
The math

• lambda ? like interest rate compounded
  periodically. 3 per t 1.03
• Nt N0?t
• FV PV(?)t

19
The math

• Nt N0?t
• r
• e
• Nt N0ert
• continuous (instant) compound interest (like APR)

20
Figure 48.2a
800
? 1.6
Discrete Growth (Nt N0?t)
600
400
200
Population size (N)
0
2
4
0
1
3
800
r 0.47
600
400
Continuous Growth (Nt N0ert)
200
0
2
3
0
1
4
Time (t)
21
r

• Nt N0ert
• r includes b, d, I
• r is what biologists think about as the maximum
  potential for population growth for each
  population

22
Figure 48.2b
Exponential growth
High r
500
Moderate r
400
300
Population size (N)
200
Low r
100
Very low r
0
1
5
0
2
3
4
6
7
8
9
10
Generations
23
Figure 48.3
Carrying capacity
Population size
Time
24
(No Transcript)
25
MORE ABOUT density-dependence

• Population growth rates depend on the rates of
  birth, death, and net migration. In nature, these
  rates are sometimes controlled by limiting
  factors which are density-dependent, factors
  which change because the population size (its
  density) has changed.

26
Density-dependent limiting factors

• Density-dependent limiting factors include energy
  and material sources which decrease as density
  increases and other factors which may increase as
  population size increases waste products,
  predators, and parasites

27
Density-dependent growth

• For a population to be truly density-dependent,
  something must keep it from maximizing its
  genetic potential to reproduce or survive or
  immigrate. Also, that something must be sensitive
  to the population's density so that the something
  has a stronger impact when the population gets
  larger.

28
Examples of Density-dependent Growth

• a larger population will attract more parasites
  (diseases), which will increase the mortality
  rate
• larger populations run out of nesting sites so
  that fewer individuals reproduce or so that more
  individuals emigrate to other habitats
• larger populations produce higher concentrations
  of wastes which may poison some individuals or
  their mutualists or maybe attract more predators
  or diseases
• when food becomes scarce, some individuals may
  not have enough energy left to produce eggs or
  some individuals may forage for food at more
  dangerous times and in riskier places so that
  survivorship.....

29
most important concept revised

•      
• Most populations grow exponentially unless
  some limiting factor changes the rate of birth or
  death or migration
• Other population decline exponentially unless
  something replenishes their habitats limiting
  factors.

30

• www.bio.brandeis.edu/biomath/top.html.

31
Figure 48.1b
Changes in Wood Buffalo Park population
200
160
Number of cranes
120
80
40
0
1940
1970
1980
1990
1950
2000
1960
Year
32
Population Growth

• Exponential growth (Fig. 48.2b)
• Growth continues indefinitely and is
  density-independent.
• Can occur for short intervals, but cannot be
  sustained.

33
Figure 48.2b
Exponential growth
High r
500
Moderate r
400
300
Population size (N)
200
Low r
100
Very low r
0
1
5
0
2
3
4
6
7
8
9
10
Generations
34
Figure 48.3
Carrying capacity
Population size
Time
35
Figure 48.4a
Bridled goby
36
Figure 48.4b
Survival and recruitment at different population
densities
0.7
0.6
0.5
0.4
Proportion surviving
0.3
0.2
0.1
0.0
2
6
0
4
8
10
12
Initial density N/m2
37
Figure 48.4c
Survival and recruitment at different population
densities
4
3
2
Immigrant density (N/m2)
1
0
0
2
12
4
8
10
6
Initial density (N/m2)
38
Figure 48.5a
Historical growth
6
1999 6 billion
1900 1.5 billion
5
1700 600 million
4
1500 400 million
Human population (billions)
3
1 A.D. 150200 million
2
45 million
1
0
10,000 B.C.
8000
6000
4000
2000
0
2000 A.D.
Year
39
Figure 48.5b
Recent growth
12
11
10
High
1998 Projections
9
Medium
8
Low
7
Human population size (billions)
6
5
4
3
2
1950
1970
1990
2010
2030
2050
Year
40
Figure 48.5c
1992 Projections
Projected population in 2050
Fertility rate
12.5 billion
High
Medium
10.15 billion
Low
7.8 billion
The 1992 projections for 2050 are higher than
those from 1998 primarily because the earlier
projections did not account for the impact of
AIDS.
41
Figure 48.6a
Red grouse
42
Figure 48.6b
10,000
Two control populations (no drug treatment)
1000
100
10
Strong four-year cycle
Population size (N)
1
1987
1989
1991
1993
1995
10,000
Two experimental populations (anti-parasite drug
treatments)
1000
100
Treatment 2
Treatment 1
10
Population cycle eliminated
1
1991
1993
1989
1995
1987
Year
43
Figure 48.7
44
Figure 48.8a
Persistent oil in mussel beds
45
Figure 48.8b
led to slow recovery in other species.
46
Figure 48.8c
led to slow recovery in other species.
47
Population Structure

• Age structure
• Developed nations have an age distribution that
  tends to be even. (Fig. 48.9a)
• Developing nations have an age distribution that
  is bottom-heavy (mostly young individuals).
  (Fig. 48.9b)

48
Figure 48.9a
More-developed countries
100
1998 data
95
90
85
2050 projections
80
75
70
65
60
55
50
45
40
35
30
25
20
15
10
5
0
0
20
20
40
40
60
60
(In millions)
Females
Males
49
Figure 48.9b
Less-developed countries
100
95
1998 data
90
85
2050 projections
80
75
70
65
60
55
50
45
40
35
30
25
20
15
10
5
0
0
100
100
200
200
300
300
(in millions)
Females
Males
50
Population Structure

• Geographic structure
• Many species exist as a metapopulation.
• Small, isolated populations, even those on nature
  reserves, are unlikely to survive over the long
  term. (Fig. 48.10a-c)

51
Figure 48.10a
A metapopulation is made up of small, isolated
populations.
Individuals
Habitat patches
52
Figure 48.10b
Although some subpopulations go extinct over
time...
53
Figure 48.10c
migration can restore or establish
subpopulations.
54
Figure 48.11
55
Demography and Conservation

• Demography the study of factors that determine
  the size and structure of populations through
  time.

56
Figure 48.12
57
Demography and Conservation

• Life tables
• Summarize the probability that an individual will
  survive and reproduce in any given year over the
  course of its lifetime. (Fig. 48.13a)

58
Figure 48.13a
Three general types of survivorship curves
1000
Type l
High survivorship
100
Type ll
Low survivorship
Number of survivors (Nx)
Low survivorship
Steady survivorship
10
1
Type lll
High survivorship
0.1
Age
59
Figure 48.13b
Exercise Survivorship curve for Lacerta vivipara
1000
100
10
Number of survivors (Nx)
1
0.1
7
0
1
2
3
5
6
8
4
Age (years)
60
Demography and Conservation

• Life tables
• Contain useful pieces of information, such as
  survivorship, fecundity, and net reproductive
  rate.

61
Figure 48.14a
Life table
Age (x)
Survivorship (lx)
Fecundity (mx)
0 (birth)
0.0
3.0
0.33
1
2
4.0
0.2
0.2
5.0
3
62
Figure 48.14b
Fate of first-generation females
0 (newborns)
Total population size (N)
1-year-olds
2-year-olds
3-year-olds
Year
4000 ( 3000 1000)
3000 ( 1000 x 3.0)
1000 (just introduced)
1000 (just introduced)
1st
800 ( 200 x 4.0)
200 ( 1000 x 0.2)
2nd
200 ( 40 x 5.0)
40 ( 200 x 0.2)
3rd
4th
5th
63
Figure 48.14c
Fate of first- and second-generation females
Total population size (sum across all rows)
Year
0 (newborns)
1-year-olds
2-year-olds
3-year-olds
4000 ( 3000 1000)
1st
1000
3000
5000 ( 3800 1000 200)
800 3000 (3000 1000 x 3.0)
1000 ( 3000 x 0.33)
2nd
200
800 ( 3000 x 0.2)
200 3200 (3200 800 x 4.0)
3rd
40
600 (600 120 x 5.0)
120 ( 3000 x 0.04)
4th
5th
64
Demography and Conservation

• Population viability analysis (PVA)
• Populations are considered viable if they have a
  95 probability of surviving for at least 100
  years.

65
Figure 48.15a
Leadbeaters possum
66
Figure 48.15b
Population viability analysis
80
High migration
60
40
Population size
Low migration
20
No migration
0
10
20
50
30
40
60
90
100
0
80
70
Years
67
Box 48.1, Figure 1