Topic 7 Flashcards
Population
group of potentially interbreeding & interacting individuals of a single species inhabiting a specific area
focused on a group that are all same species and how they interact
Characteristics:
- Distribution size,shape,location of area occupied also called geographic range
- Density: # individuals per unit area or volume
- Structure, e.g., age distribution, sex ratio
- Vital rates: birth, death, immigration & emigration rates —> population growth rates
Why study population ecology?
For things such as
To know how many there of an animal (fish) are so we know how many can be harvested for human use.
Pest infestation > lost wood we can harvest and isn’t useable by other sps so we can see how it effects their pops
Distribution Limits
Physical environment limits geographic distribution
why you find a species in an area can determine its population and distribution
Studying distribution takeaways >
- no species can live in every environment
- understanding a species niche can help us understand where we would find its distribution
Distribution Patterns
definition of ʻsmallʼ & ʻlargeʼ spatial scale depends on organism size
Small scale: little environmental change sig. to organism of study
Large scale: substantial environmental change sig. to organism of study
Spatial extent: area being studied.
keep biology of the species you are working with in mind ex bird versus mussel biology since it determines the spatial scale
Distribution of Individuals on Small Scales
Random:
- An individual has an equal probability of occurring anywhere in an area.
Processes:
- Neutral interactions between individuals, and between individuals and local environment
— Ex: grey squirrels
Regular:
- Individuals are uniformly spaced through the environment.
how individuals interact and how it translates to the space they are living in determines their spread
Processes:
- Antagonistic interactions between individuals or local depletion of resources
—Ex: caused from hating each other red squirrels
Clumped:
- Individuals live in areas of high local abundance, which are separated by areas of low abundance.
Processes:
- Attraction between individuals or to a common resource; limited dispersal.
— Ex: common in species with herds like elk do for protection, species that gather around water
Distributions of Individuals on Large Scales
Significant environmental variation
Can use elevation as a compressed gradient
larger scale but still trying to see behaviors, characteristics or environments that cause the distributions
Plant Abundance Along Moisture Gradients
Santa Catalina Mountains
Southern Arizona
- Arizona madrones are most abundant at midslope.
- On this mountainside, Mexican pinyon pines are most abundant on drier upper slope.
- Douglas-firs are most abundant in moist canyon bottom.
connect dots between what we find and environmental conditions
Animal Size & Population Density
large animals have low density since the ecosystem wouldn’t be able to support them if there was a large population
adaptations can alter the size and populations they can live at
Exs:
- Average pop density of herbivorous mammals decreases with increasing body size
- Many aquatic invertebrates live at higher population densities than other animals of comparable size.
- Mammals tend to live at higher population densities than birds.
Plant Size & Population Density
plants go through such a large differences in size as they age > live in high densities when they are young and some will out grow the others and the little ones will die off leaving the bigger ones.
Ex:
As in animals, plant population density decreases with increasing plant size across a wide range of plant growth forms.
- Duckweed, Lemna, one of the smallest flowering plants, lives at very high population densities.
- The coastal redwood, Sequoia sempervirens, one of the largest trees, lives at one of the lowest population densities.
Commonness & Rarity
Classification based on:
1. Geographic Range (extensive vs. restricted)
2. Habitat Tolerance (broad vs. narrow)
3. Local Population Size (large vs. small)
8 combinations that will tell rarity
be able to recognize which combination is more likely to make a species rare and where they would fall on the spectrum
Rarity III:
Extensive geographic range, broad habitat tolerance, small local populations
more likely to die off from habitat loss
Small local population is what cause the species to be more rare rather than common.
Ex:
- Peregrine falcon
- Tiger
Rarity II:
Extensive range, narrow habitat tolerance, large populations
narrow habitat tolerance is cause to why species is more rare than common.
Rarity VII: Extreme Rarity
Restricted range, narrow habitat tolerance, small populations • California condor, mountain gorilla, giant panda
• Many island species: of 171 bird species known to have become extinct, 155 restricted to islands
Big Concepts
- Physical environment sets limit on geographic distribution of species
- On small scales, individuals with in populations are distributed in patterns that may be random, regular or clumped
- Population density declines with increasing organism size
- Commonness & rarity are influenced by population size, geographic range and habitat tolerance
• Populations have structure, e.g., age, stage, sex that reflect patterns of survival and reproduction and will influence future population growth
• A survivorship curve summarizes the pattern of survival in a population
• The age distribution of a population reflects it’s history of survival, reproduction and potential for future growth
• Populations have structure, e.g., age, stage, sex that reflect patterns of survival and reproduction and will influence future population growth
• A survivorship curve summarizes the pattern of survival in a population
•The age distribution of a population reflects it’s history of survival, reproduction and potential for future growth
Population Abundance (N)
Size of population: # individuals
Density: # individuals per unit area (or volume)
Biomass density: biomass per unit area (or volume) (e.g., tonnes of wood per hectare)
ex selling products acquired from an area like logs or fish
Population Structure
• Patterns of survival & mortality
- tracking the survival of one generation overtime
• Age or stage distribution
- can have individuals that are older or in the middle be more abundant
• Sex ratio
scale of time matters
Rarity Chart
Most common on top, to more rare.
Rarity 0:
- Extensive geographic range
- Broad hahitat tolerance
- Large local population
Species
- Species such as these show no aspects of rarity; they are among the most
common in the biosphere
Ex:
— Dandelion
— House sparrow (Passer domesticas)
Rarity 1:
- Restricted geographic range
- Broad habitat tolerance
- Large local population
Species
- Each of these species show one aspect of rarity, which gives them some vulnerability to extinction.
Ex:
— Monterey pine
— Galápagos medium ground finch
Rarity 2:
- Extensive geographic range
- Narrow habitat tolerance
- Large local population
Species
- Each of these species show one aspect of rarity, which gives them some vulnerability to extinction.
Ex:
— Fremont cottonwood
— California grey whale
Rarity 3:
- Extensive geographic range
- Broad habitat tolerance
- Small local population
Species
- Each of these species show one aspect of rarity, which gives them some vulnerability to extinction.
Ex:
— Forked spleenwort (Asplenium septentrionale)
— Tiger
Rarity 4:
- Restricted geographic range
- Narrow habitat tolerance
- Large local population
Species
- With two aspects of rarity, these three
groups of species are even more vulnerable to extinction
Ex:
— Haleakala silversword
— Fish cow
Rarity 5:
- Restricted geographic range
- Broad habitat tolerance
- Small local population
Species
- With two aspects of rarity, these three
groups of species are even more vulnerable to extinction
Ex:
— Welwitschia
— Tasmanian devil
Rarity 6:
- Extensive geographic range
- Narrow habitat tolerance
- Small local population
Species
- With two aspects of rarity, these three
groups of species are even more vulnerable to extinction
Ex:
— Pacific yew
— Northern spotted owl
Rarity 7:
- Restricted gcographic range
- Narrow habitat tolerance
- Small local population
Species
- Species such as these are the rarest in the biosphere and are the most vulnerable to extinction
Ex:
— Kamalo pritchardia munroi
— mountain gorilla
Patterns of Survival
Life tables:
Age: 0
# alive: 100
Proportion Surviving: 1.00
# dying within cohort: 66
Mortality rate: 0.66
Age: 1
# alive: 34
Proportion Surviving: 0.34
# dying within cohort: 4
Mortality rate: 0.12
Age: 2
# alive: 30
Proportion Surviving: 0.30
# dying within cohort: 17
Mortality rate: 0.57
Age: 3
# alive: 13
Proportion Surviving: 0.13
# dying within cohort: 13
Mortality rate: 1.00
Age: 4
# alive: 0
Proportion Surviving: 0
# dying within cohort: -
Mortality rate: - dying/starting pop
Pop surviving is used since it accounts for any differences in populations
Shows how things are changing between different life classes like how survival rates and mortality rates change which tells us about the biology of the species
Life tables & survivorship curves
Must determine appropriate age intervals
- 10 year, 1 year or 1 month interval
depends on how long the lifespan is
…or stage intervals may be appropriate
-egg, larva,pupa, adult
know what ages would be appropriate to record data at for animals when making a life table and be able to interpret it
Cohort life table
when you follow individuals who are allborn at the same time
Difficulties challenging to follow a cohort with some species it is not possible (ex tortoises that live 200 years)
• Identify individuals born at same time (cohort)
• Follow over time, recording deaths (& sometimes births)
• Easy to interpret
• Difficult (or impossible) to collect these data in nature
- impossible with some species because of keeping track of them
- can’t do feasibly depending on the animal based on their lifespan as it may take too long to gather the data and the animals may outlive you
Static life table
(stationary; time-specific)
Example: Age at death data
• Record age at death of large number of individuals
• Requires accurate estimate of age at death.
Survivorship curve
Another way to describe the life table data
Log scale can also be: % or proportion
logarithmic scale is used so the graph is easy to interpret especially when it is a constant mortality rate.
In a logarithmic scale, a constant rate of mortality is seen as a straight line.
In an arithmetic scale, a constant rate of mortality is seen as a concave curve.
Patterns of Survival: High Survival Among Young
Dall Sheep
- Dall sheep surviving their first year of life have a high probability of surviving to about age nine.
- Sheep ten years old and older are easier prey for wolves and die at a high rate.
Plants
- Despite going through a diverse set of life stages over a short period of time, the annual plant Phlox drummondii shows a pattern of survival similar to Dall sheep.
- P. drummondii lives for less than a single year.
Rotifers
- A similar pattern of survival by the rotifer, Floscularia conifera, is complete within 11 days.
Patterns of Survival: Constant Rates
Sparrows & robins.
- Like many other bird species, white-crowned sparrows and American robins show approximately constant rates of mortality.
Water snakes
- This northern water snake population has slightly higher mortality rates as individuals age.
3 Types of Survivorship Curves
In type I survivorship, juvenile survival is high and most mortality occurs among older individuals.
In contrast, individuals in a population with type Il survivorship die at equal rates, regardless of age.
Individuals showing type IlI survivorship die at a high rate as juveniles and then at much lower rates later in life.
Dall sheep in Denali NP, Alaska
• Is wolf predation threatening population?
• Are highly reproductive ages (2-5 yrs) being preyed on?
- it so the population will be decreased
- can get age of death and what killed them if you know their predators using the static life table to determine what the cause of death was
Age Distribution Rwanda and hungary
can use to understand human populations and how they change overtime to see how it could effect economics, health, etc.
• % of population in each age class
• Death rate in Hungary is age & sex specific
- not a lot in the younger generation which makes it easy to infer that the population will decrease over time if that trend is consistent
- Hungary’s age distribution and negative r indicate a declining population.
• Population increasing faster in
Rwanda
- Rwanda’s age distribution and high r indicate a rapidly growing population
- can see where people are mostly dying in a population which allows you o see where to target your research
- lots of young generations that can grow up to the next category
Age Distribution trees
• Many young trees; regeneration sufficient
•Population stable or increasing
- The age structure of this population of white oaks shows that older trees are being replaced by young trees.
- This population of white oaks is dominated by young individuals.
Age Distribution trees 2nd example
•Population dominated by old trees
• No reproduction for 10+ yrs
- caused by a flood and the trees didn’t have the foundation to not be swept away
• Population declining
The age structure of this population shows that older trees are not being replaced by young trees.
The absence of young trees suggests that this population will not persist.
40- to 50-year-old trees dominate this population.
What causes populations to grow or decline?
Four basic demographic processes
How a population is changing overtme and whats causing it
Add to pop
Birth +
Immigration +
Subtract from pop
Death -
Emigration -
BIDE Dynamics
B, I, D, E: # individuals born, immigrated, died, or emigrated during time t.
Population change described by:
N#+1 = Nt +B+1-D-E
Uppercase = # individuals
Nt = current pop. size of population at time t
Nt +1 = size of population in future (one time unit after t)
t = time: may be yrs, days, hrs
Useful to express equation using per-capita rates Allows comparison among populations.
per-capita rates
like # of births / 100 individuals but it changes depending on the species and population
N#+1 = Nt +B+1-D-E
N#+1 = Nt + Ntb + Nti- Ntd - Nte
Or
N#+1 = Nt + Nt(b + i - d - e)
b, i, d, e are per capita rates (e.g., # births per individual).
Density Dependence & Independence
Density-independent factors: do not vary with population density.
Abundance or population size = # of individuals
Density = # of individuals per area
in some cases it matters if it is a density dependent or density independent
Density-dependent factors: influenced by population density.
- predation, disease, parasitism all decrease pops if it is density dependent and there is a high density.
Rates of Population Change
Age specific schedules
Life tables: survival/mortality
To determine how a population will change in abundance over time, we also need
age specific schedule of births: at a particular age you have a certain number of births happening in your nation.
Age-specific schedule of births (bx) or (mx)
Per capita rate
# offspring per individual (of a specific age) per unit time.
looking at how reproduction and survival with age and are combining them in a calc telling us reproduction rate and how the population is changing.
Rates of Population Change
Net reproductive rate (R0):
average # offspring produced per individual per generation
R0 = Σlxmx
Trying to see if pop stable
R0 = Σlxmx
Increasing R>1
Declining R<1
Unchanged R=1
Generation time
Generation time T = Avg. age at which females reproduce
affects how fast they can react to what causes them a decline.
Dividing Σlxmx by R0 gives an estimate of generation time.
Estimating Rates:
λ = geometric rate of increase
R0=λ for organisms with non-overlapping generations if t = generation time.
The geometric rate of increase, λ is the ratio of numbers at a later time, Nt+1, to numbers at an earlier time, Nt
Earlier time t
Later time Nt+1
especially important for species with overlapping generations > kids being born when previous generation individuals are still alive.
Per Capita Rate of Increase
Given R0 and T we can estimate r (little r)
r= per capita rate of increase for population = intrinsic rate of increase = b-d
r > 0 increasing population
r < 0 declining population
r = 0 stable population
r= lnR0 / T
Two principles of population growth
- Without density-dependent feedback, populations grow exponentially or geometrically.
• Resources are not limiting
• Populations at low densities
• Organism invading new habitat
- Populations eventually show self limitation (density-dependence)
• Resources eventually become limiting
• Growth rates eventually decline
Population Growth Models
- Density-independent growth
Discrete model: geometric growth
Continuous model: exponential growth - Density-dependent growth
Logistic growth
Exponential Growth in Nature
Pollen accumulation rate in lake sediments can be used as an index of population size.
Pollen in lake sediments indicates that Scots pine colonized the Norfolk region of Great Britain about 9,500 years ago.
had population independent growth
invading > no compention so mere is no fight for resources so they grow exponentially
Slowing of Exponential Population Growth
After colonizing, the collared dove population of Great Britain grew exponentially.
However, in less than 20 years population size was less than that predicted by the exponential model, suggesting that population growth had slowed.
Logistic Population Growth
Exponential growth curve modified to include biotic limitations (intraspecific competition)
• Produces S-shaped curve.
• Carrying capacity
k = carrying capacity = population size that can be supported by the
engronment
Carrying capacity (K) represents the theoretical maximum population size in a given location.
If a population starts at a small size it will initially grow rapidly then growth slows and eventually stops; stabilizing at a population size of K, carrying capacity.
More big concepts
• Population size changes as a function of birth, death, emigration & immigration
• Life tables can be used (with age-specific birth rates) to estimate rates of population increase
• In the presence of abundant resources, populations can grow at geometric or exponential rates (density independent)
• If resources are limiting, population growth rates slow and eventually stop (logistic population growth – density dependent).
