# Population Dynamics

Lecture 10 & 11 ∙ October 2, 2018

Announcements

Problem sets today and Tuesday

Reading quiz due Tuesday BEFORE class

No time limit

Open book

Feel free to work in groups, but make sure to submit your own

Will ask similar questions on the exam

Grab your exams after class – see me in office hours for questions

Reflections 2 due next Thursday

Exam 2 one week from Tuesday

Review session 10/15, 6-8pm, HH320

today’s objectives

Generate a life table from appropriate data and use it to predict life history tradeoffs and population growth patterns

Interpret survival curves to make inferences about life history and environmental pressures of populations

Interpret age distributions to predict past environmental pressures and future population growth

Previous population size (Nt-1)

Number of births (B)

Number of deaths (D)

Number of immigrants/joiners(I)

Number that emigrate/leave (E)

What processes determine current population size (Nt)?

Population dynamics

Nt = Nt-1 + (B-D) + (I-E)

Previous population size (Nt-1)

Number of births (B)

Number of deaths (D)

Number of immigrants/joiners(I)

Number that emigrate/leave (E)

What processes determine current population size (Nt)?

Population dynamics

Nt = Nt-1 + (B-D) + (I-E)

dispersal

Two levels of consideration

Dispersal affects range expansion and contraction

Dispersal affects local population densities

The distribution and abundance of organisms is dynamic!

The role of dispersal

Dispersal

Dispersal is variable within populations

Large amount of variation in dispersal abilities within populations

Those few individuals that disperse far have the potential to influence the population range

Those individuals that disperse locally influence dispersion patterns within the population

Dispersal

Dispersal is variable among populations

How is dispersal rate likely to influence population response to rapid climate change?

Which species is likely to respond to rapid climate change with shifts in population range?

Africanized honey bees

Eurasian collared doves

White-tailed deer

Dispersal

Dispersal is variable among populations

How is dispersal rate likely to influence population response to rapid climate change?

Which species is likely to respond to rapid climate change with shifts in population range?

Africanized honey bees

Eurasian collared doves

White-tailed deer

Dispersal

Previous population size (Nt-1)

Number of births (B)

Number of deaths (D)

Number of immigrants/joiners(I)

Number that emigrate/leave (E)

What processes determine current population size (Nt)?

Population dynamics

Nt = Nt-1 + (B-D) + (I-E)

Survival patterns, age distribution

Life tables are a useful tool for inferring population processes

Survivorship patterns

Provide a picture of survival and mortality in populations

Used to explore population dynamics in context of

birth

death

survivorship

age distribution

Life tables are a useful tool for inferring population processes

Survivorship patterns

Consist of a series of columns which describe aspects of mortality and reproductive output for members of a population according to age.

Representative of a cohort – a group of individuals born at the same time

If cohorts are similar over time, they can be used to describe a population

If populations are similar over time and space, they can be used to describe a species

Used to:

Analyze probabilities of survival of individuals in a population

Determine ages most vulnerable to mortality

Predict population growth

Make inferences about the environmental factors (biotic and abiotic) and intrinsic factors (life history tradeoffs) that influence population distribution and abundance

Life tables are a useful tool for inferring population processes

Survivorship patterns

Consist of a series of columns which describe aspects of mortality and reproductive output for members of a population according to age.

Representative of a cohort – a group of individuals born at the same time

If cohorts are similar over time, they can be used to describe a population

If populations are similar over time and space, they can be used to describe a species

Used to:

Analyze probabilities of survival of individuals in a population

Determine ages most vulnerable to mortality

Predict population growth

Make inferences about the environmental factors (biotic and abiotic) and intrinsic factors (life history tradeoffs) that influence population distribution and abundance

Life tables are a useful tool for inferring population processes

Survivorship patterns

Consist of a series of columns which describe aspects of mortality and reproductive output for members of a population according to age.

Representative of a cohort – a group of individuals born at the same time

If cohorts are similar over time, they can be used to describe a population

If populations are similar over time and space, they can be used to describe a species

Used to:

Analyze probabilities of survival of individuals in a population

Determine ages most vulnerable to mortality

Predict population growth

Make inferences about the environmental factors (biotic and abiotic) and intrinsic factors (life history tradeoffs) that influence population distribution and abundance

Life tables are a useful tool for inferring population processes

Static life tables

Survivorship patterns

Static life table

Record age at death of individuals within a certain time period

Useful for mobile and long-lived organisms

Age distribution

Calculate difference in proportion of individuals in succeeding age classes

Assumes differences are due to mortality

Two methods

Life tables are a useful tool for inferring population processes

Cohort life tables

Survivorship patterns

Cohort life table

Identify individuals born at same time and keep records from birth to death

Useful for plants and sessile organisms or relatively short-lived species

One method

How to make a life table

Survivorship patterns

Record the number of individuals alive (Nx) in each age class

Age class is determined by census interval

(x to x +1)

Record the number of deaths in each age class

Can infer mortality rate based on proportion surviving

Nx / N0 (N0 is the number of individuals alive at time = 0)

Two kinds of life table are useful

Cohort (dynamic) life table – good for plants and other

sessile organisms

Survivorship patterns

You fill in these, calculate the rest

Two kinds of life table are useful

Cohort (dynamic) life table – good for plants and other

sessile organisms

Survivorship patterns

You fill in these, calculate the rest

Survivorship from one period to the next: 0.625/0.857 = 0.729

Two kinds of life table are useful

Cohort (dynamic) life table – good for plants and other

sessile organisms

Survivorship patterns

You fill in these, calculate the rest

Survivorship from one period to the next: 0.625/0.857 = 0.729

Mortality from one period to the next: 1 – 0.857 = 0.143

Two kinds of life table are useful

2. Static life table – good for mobile and long-lived organisms

Survivorship patterns

Capture individuals in the population and estimate age

Two kinds of life table are useful

2. Static life table – good for mobile and long-lived organisms

Survivorship patterns

Capture individuals in the population and estimate age

Life tables are a useful tool for inferring population processes

Some plants and most mammals have high survivorship of young

Survivorship patterns

Life tables are a useful tool for inferring population processes

Some birds and amphibians have a more constant survivorship or mortality through life

Survivorship patterns

Life tables are a useful tool for inferring population processes

Survivorship patterns

What can you infer about parental care in this cohort?

Parental care is high

Parental care is low

Parental care cannot be determine from this figure

Life tables are a useful tool for inferring population processes

Survivorship patterns

What can you infer about parental care in this cohort?

Parental care is high

Parental care is low

Parental care cannot be determine from this figure

Life tables are a useful tool for inferring population processes

Many plants, invertebrates, amphibians, and fish have very low survivorship as juveniles

Survivorship patterns

We can classify populations based on survivorship patterns

Many populations do not fit these lines exactly, but they provide theoretical limits on population dynamics

This is useful for investigating the source of changing population demographics

Survivorship patterns

We can classify populations based on survivorship patterns

Which survivorship curve do U.S. human populations best fit?

If human populations shifted to a type II pattern, what could we surmise happened to mortality rates?

Mortality may have increased among older people

Mortality may have increased among younger people

Mortality may have increased in both young and old people

There is not enough information to tell

Survivorship patterns

We can classify populations based on survivorship patterns

Which survivorship curve do U.S. human populations best fit?

Type I

If human populations shifted to a type II pattern, what could we surmise happened to mortality rates?

Mortality may have increased among older people

Mortality may have increased among younger people

Mortality may have increased in both young and old people

Survivorship patterns

We can classify populations based on survivorship patterns

Which survivorship curve do U.S. human populations best fit?

Type I

If human populations shifted to a type II pattern, what could we surmise happened to mortality rates?

Mortality may have increased among older people

Mortality may have increased among younger people

Mortality may have increased in both young and old people

Survivorship patterns

We can classify populations based on survivorship patterns

Which survivorship curve is most representative of semelparous species?

Type I

Type II

Type III

Survivorship patterns

We can classify populations based on survivorship patterns

Which survivorship curve is most representative of semelparous species?

Type I

Type II

Type III

Survivorship patterns

We can classify species based on life history traits

 Population attribute r selection K selection Intrinsic rate of increase, rmax High Low Competitive ability Not strongly favored Highly favored Development Rapid Slow Reproduction Early Late Body size Small Large Reproduction Single, semelparity Repeated, iteroparity Offspring Many, small Few, large Survivorship curve type Type III Type I

Classifying life histories

Age Distribution

Age distribution of a population reflects:

History of survival (high and low periods)

Periods of successful reproduction

Growth potential

Are older individuals replacing themselves or not?

Age distributions

age distributions give us qualitative assessments of population growth

Age distribution

Costa Rica is likely to grow faster than Sweden, because it has more young people to replace those that die

age distributions provide evidence of reproductive failures or low survival periods

Age distribution

There may have been a reproductive failure or a major disturbance 60 years ago

Why are there so few young cottonwoods in the Rio Grande population?

Age distribution

This population has not reproduced for over a decade!

Cottonwood seeds germinate in flood plains

Spring floods also reduce competition for cottonwood seedlings

Seasonal flooding has been disrupted by dams

today’s objectives

Generate a life table from appropriate data and use it to predict life history tradeoffs and population growth patterns

Interpret survival curves to make inferences about life history and environmental pressures of populations

Interpret age distributions to predict past environmental pressures and future population growth