/
0 Population Ecology 0 Population Ecology

0 Population Ecology - PowerPoint Presentation

pasty-toler
pasty-toler . @pasty-toler
Follow
502 views
Uploaded On 2016-09-17

0 Population Ecology - PPT Presentation

Population ecologists are primarily interested in understanding how biotic and abiotic factors influence the density distribution size and age structure of populations the overall vitality of a population of organisms ID: 467299

growth population capacity rate population growth rate capacity size carrying organisms type days elephants daphnia day negative predicted rates

Share:

Link:

Embed:

Download Presentation from below link

Download Presentation The PPT/PDF document "0 Population Ecology" is the property of its rightful owner. Permission is granted to download and print the materials on this web site for personal, non-commercial use only, and to display it on your personal computer provided you do not modify the materials and that you retain all copyright notices contained in the materials. By downloading content from our website, you accept the terms of this agreement.


Presentation Transcript

Slide1

0

Population EcologySlide2

Population ecologists are primarily interested in

understanding how biotic and abiotic factors

influence the density, distribution, size, and age structure of populations.

the overall vitality of a population of organisms.

how humans affect the size of wild populations of organisms.

studying interactions among populations of organisms that inhabit the same area.

how populations evolve as natural selection acts on heritable variations among individuals and changes in gene frequency.Slide3

Population ecologists are primarily interested in

understanding how biotic and abiotic factors

influence the density, distribution, size, and age structure of populations.

the overall vitality of a population of organisms.

how humans affect the size of wild populations of organisms.

studying interactions among populations of organisms that inhabit the same area.

how populations evolve as natural selection acts on heritable variations among individuals and changes in gene frequency.Slide4

Dispersion patterns tend to be highly dependent on the spatial scale of the observer. For example, football players lined up on the scrimmage line are clumped at the scale of 100 yards but uniformly dispersed at the scale of a meter. An example of animals that are likely to be clumped at a large scale but uniformly distributed at a small scale is

buffalo grazing on a prairie.

bluegills swimming in a northern lake.

ant nests in an abandoned field.

red-winged blackbirds in a cattail marsh.

all of the above.Slide5

Dispersion patterns tend to be highly dependent on the spatial scale of the observer. For example, football players lined up on the scrimmage line are clumped at the scale of 100 yards but uniformly dispersed at the scale of a meter. An example of animals that are likely to be clumped at a large scale but uniformly distributed at a small scale is

buffalo grazing on a prairie.

bluegills swimming in a northern lake.

ant nests in an abandoned field.

red-winged blackbirds in a cattail marsh.

all of the above.Slide6

Imagine that a species of fish used to be a broadcast spawner (producing many eggs that then get no subsequent parental care) but has evolved to be a mouth brooder (holding the eggs in the

parent’s

mouth

until they hatch and then caring for the young for a while). We would expect the survivorship curve of this species to

shift from Type I to

Type II or III.

shift from Type II to Type I.

shift from Type III to

Type I or II.

shift from Type II to

Type III.

vary unpredictably.Slide7

Imagine that a species of fish used to be a broadcast spawner (producing many eggs that then get no subsequent parental care) but has evolved to be a mouth brooder (holding the eggs in the

parent’s

mouth

until they hatch and then caring for the young for a while). We would expect the survivorship curve of this species to

shift from Type I to

Type II or III.

shift from Type II to Type I.

shift from Type III to

Type I or II.

shift from Type II to

Type III.

vary unpredictably.Slide8

The exponential growth model describes the increase in population size of a population that is not constrained by resources or space. The graph shows the elephant population in Kruger National Park, which appears to have been reproducing exponentially from 1900 to 1963. From this graph, you can tell that

none of the elephants died.

a female elephant living

around 1960 was more likely

to have a baby than a female

elephant living around 1920.

the elephants adapted to

the new park conditions

around 1955.

the vegetation the elephants

eat could support more than 5,000 elephants.

the more elephants there are, the more tourists will visit the park.Slide9

The exponential growth model describes the increase in population size of a population that is not constrained by resources or space. The graph shows the elephant population in Kruger National Park, which appears to have been reproducing exponentially from 1900 to 1963. From this graph, you can tell that

none of the elephants died.

a female elephant living

around 1960 was more likely

to have a baby than a female

elephant living around 1920.

the elephants adapted to

the new park conditions

around 1955.

the vegetation the elephants

eat could support more than 5,000 elephants.

the more elephants there are, the more tourists will visit the park.Slide10

You do a study on elephants and find that there are eight elephants per acre. This is a measurement of

density.

dispersal.

demographics.

survivorship.Slide11

You do a study on elephants and find that there are eight elephants per acre. This is a measurement of

density.

dispersal.

demographics.

survivorship.Slide12

A population of deer grows from 100 to 200 to 600, and when it gets to 600, it levels off. This population must have reached

exponential growth.

carrying capacity.

logistic growth.Slide13

A population of deer grows from 100 to 200 to 600, and when it gets to 600, it levels off. This population must have reached

exponential growth.

carrying capacity.

logistic growth.Slide14

Populations

adjust instantaneously to growth.

Populations

approach carrying capacity smoothly.

An

S-shaped growth curve results when

N

is plotted over time.

The

growth rate increases as

N

approaches K.

Which of the following statements is not an assumption of the logistic model of population growth

?Slide15

Populations

adjust instantaneously to growth.

Populations

approach carrying capacity smoothly.

An

S-shaped growth curve results when

N

is plotted over time.

The

growth rate increases as

N

approaches K.

Which of the following statements is not an assumption of the logistic model of population growth

?Slide16

Semelparous

organisms return to their place of birth to reproduce, but

iteroparous

organisms can reproduce anywhere.

Semelparous

refers only to plants, but

iteroparous

refers to animals.

Semelparous

organisms live after their first reproduction, but iteroparous organisms die. Semelparous organisms die after their first reproduction, but iteroparous organisms are

capable

of repeated reproduction.

What is the difference between

semelparity

and

iteroparity

?Slide17

Semelparous

organisms return to their place of birth to reproduce, but

iteroparous

organisms can reproduce anywhere.

Semelparous

refers only to plants, but

iteroparous

refers to animals.

Semelparous

organisms live after their first reproduction, but iteroparous organisms die. Semelparous organisms die after their first reproduction, but iteroparous organisms are capable of repeated reproduction.

What is the difference between

semelparity

and

iteroparity

?Slide18

10

100

0.5

3

6

Assume

U.S. energy use is 300 GJ per capita and Chinese energy use is 27 GJ per capita. If the U.S. population is 313 million people and the Chinese population is 1.3 billion people, the

total

U.S. energy use is approximately how many times greater than the

total

Chinese energy use

?Slide19

10

100

0.5

3

6

Assume

U.S. energy use is 300 GJ per capita and Chinese energy use is 27 GJ per capita. If the U.S. population is 313 million people and the Chinese population is 1.3 billion people, the

total

U.S. energy use is approximately how many times greater than the

total

Chinese energy use

?Slide20

In the logistic population growth model, the per capita rate of population increase approaches zero as the population size (

N

) approaches the carrying capacity (

K

), as shown in the table. Assume that 

r

max

 = 1.0 and 

K

 = 1,500. You can then calculate the population growth rate for four cases where population size (

N

) is greater than carrying capacity. To do this, use the equation for population growth rate in the table.

Scientific Skills ExerciseSlide21

N

 = 1,510

N

 = 1,600

N

 = 1,750

N

 =

2,000

Which population size has the highest growth rate

?Slide22

N

 = 1,510

N

 = 1,600

N

 = 1,750

N

 =

2,000

Which population size has the highest growth rate

?Slide23

If 

r

max

 is doubled, how would the population growth rates change?

The

population growth rates would be half of what they were.

The

population growth rates would double.

The

population growth rates would be unchanged.

The

population growth rates would be four times what they were.Slide24

If 

r

max

 is doubled, how would the population growth rates change?

The

population growth rates would be half of what they were.

The

population growth rates would double.

The

population growth rates would be unchanged.

The

population growth rates would be four times what they were.Slide25

What does a negative population growth rate tell you about the dynamics of the population?

The

birth rate equals the death rate.

The

population size is increasing instead of decreasing.

The

population size is decreasing instead of increasing.Slide26

What does a negative population growth rate tell you about the dynamics of the population?

The

birth rate equals the death rate.

The

population size is increasing instead of decreasing.

The

population size is decreasing instead of increasing.Slide27

The red line shows the growth 

predicted

 by the logistic model, and the black dots show the 

measured

 growth of the population. Does the measured growth match the predicted growth pattern

?

No

; only a few of the black dots sit on the red line.

Yes

; it matches at the beginning and at the end of the time range.

No

; it is lower than the

predicted

values in

some

parts and higher in

other

parts.

Yes

; it matches over the

whole time

range

.Slide28

The red line shows the growth 

predicted

 by the logistic model, and the black dots show the 

measured

 growth of the population. Does the measured growth match the predicted growth pattern

?

No

; only a few of the black dots sit on the red line.

Yes

; it matches at the beginning and at the end of the time range.

No

; it is lower than the

predicted

values in

some

parts and higher in

other

parts.

Yes

; it matches over the

whole time

range

.Slide29

What is the predicted carrying capacity of the 

Daphnia

 culture?

120

 

Daphnia

/50 mL

135

 

Daphnia

/50 mL

200

 

Daphnia

/50

mLSlide30

What is the predicted carrying capacity of the 

Daphnia

 culture?

120

 

Daphnia

/50 mL

135

 

Daphnia

/50 mL

200

 

Daphnia

/50

mLSlide31

Did the 

Daphnia

 population ever experience a negative growth rate

?

From

about day 70 to day 105, the population decreased in size, indicating a negative growth

rate

.

The

population never experienced a negative growth rate because it stabilized after 140 days and never went to zero.

From

about day 20 to day 50 and from day 100 to day 150, the population fell below the predicted values, indicating a negative growth rate

.Slide32

Did the 

Daphnia

 population ever experience a negative growth rate

?

From

about day 70 to day 105, the population decreased in size, indicating a negative growth rate.

The

population never experienced a negative growth rate because it stabilized after 140 days and never went to zero.

From

about day 20 to day 50 and from day 100 to day 150, the population fell below the predicted values, indicating a negative growth rate

.Slide33

What is the best biological explanation for why the 

Daphnia

population growth rate became negative between days 70 and 105?

The

population’s data defined by the black dots have a slope that is negative during that period.

The

population grew larger than the predicted size during that period.

The

population overshot the carrying capacity

and

started running out of resources during that period.

The

population’s death rate was greater than the birth rate during that period

.Slide34

What is the best biological explanation for why the 

Daphnia

population growth rate became negative between days 70 and 105?

The

population’s data defined by the black dots have a slope that is negative during that period.

The

population grew larger than the predicted size during that period.

The

population overshot the carrying capacity and started running out of resources during that period.

The

population’s death rate was greater than the birth rate during that period

.Slide35

Between days 100 and 160, the 

Daphnia

 population dropped below the predicted carrying capacity before rising back up to it. What is the best biological explanation for why the population stayed below the carrying capacity between days 100 and 160

?

The

predicted carrying capacity is incorrect. It really should be 120 

Daphnia

/50 mL, where the population stabilized during those 60 days.

After

the population overshot the carrying capacity, the debris from dying 

Daphnia

 prevented the population from increasing until the debris decomposed, which took 60 days.

Overcrowding

before day 100 caused the birth rate to

decrease

and the death rate to increase, and it took another

60

days for the relative rates to stabilize.

Daphnia

 decided to limit population growth until they figured out how large a population they could support in the culture, which took 60 days

.Slide36

Between days 100 and 160, the 

Daphnia

 population dropped below the predicted carrying capacity before rising back up to it. What is the best biological explanation for why the population stayed below the carrying capacity between days 100 and 160

?

The

predicted carrying capacity is incorrect. It really should be 120 

Daphnia

/50 mL, where the population stabilized during those 60 days.

After

the population overshot the carrying capacity, the debris from dying 

Daphnia

 prevented the population from increasing until the debris decomposed, which took 60 days.

Overcrowding

before day 100 caused the birth rate to decrease and the death rate to increase, and it took another 60 days for the relative rates to stabilize.

Daphnia

 decided to limit population growth until they figured out how large a population they could support in the culture, which took 60 days

.