ecology reflection
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
More information is required
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
More information is required
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