Population Ecology

14.1 – Characteristics of Populations
 Habitat: the place where an organism or species
normally lives.
 Species: organisms that resemblen one another in
appearance, behaviour, chemistry, and genetic
makeup, and that interbreed, or have the nability to
interbreed, with each other under natural conditions
to produce fertile offspring
Population Size and Density
Population Size: the number of individuals of a
specific species occupying a given area/volume at a
given time
Population Density: the number of individuals of
the same species that occur per unit area or volume
 Crude Density: population density measured in terms
of number of organisms of the same species within the
total area of the entire habitat
 Ecological Density: population density measured in
terms of the number of individuals of the same species
per unit area or volume actually used by the individuals
Practice Problem
Page 651, #1-3
 Population Dispersion: the general pattern in which
individuals are distributed through a specified area
Clumped Dispersion: pattern in which individuals in a
population are more concentrated in certain parts of the
Uniform Dispersion: the pattern in which individuals are
equally spaced throughout a habitat
Random Dispersion: the pattern in which individuals are spread
throughout a habitat in an unpredictable and patternless manner
Measuring Population Characteristics
 Very rare to be able to count total # of individuals in
a population.
Populations are dynamic  numbers and geographic location
changes over time.
Biologists count a sample, and then estimate the total size.
 Indirect Indicators
 Number of fecal droppings
 Number of tracks
 Number of nests
Why is this important?
 Ex// in the forestry industry, population density and
size of valuable tree species  info essential in
determining allowable harvest rates while still
maintaining healthy and viable populations.
Sampling Technique (1)
 Quadrat: a sampling frame used for estimating
population size; frames can be real or virtual
Number of individuals of one or more species can be counted
within each quadrat  population size and density can be
estimated through calculations  population size and density
of entire area estimated.
Most effective for stationary species  can be used for mobile
species as well.
Example Problem
Page 654
Work through the sample problem
Complete #4.
Sampling Technique (2)
 Mark-recapture method: used for mobile
Can estimate population size and density by comparing the
proportion of marked and unmarked animals captured in a
given area
Sometimes called capture-recapture.
Fisheries – restocking programs
Large animals
Ex// polar bears  tranquilized, captured, marked
 Tags, bands, dye.
 Techniques for capturing and marking individual
organisms must be carefully planned  chances of
each individual being caught is equal.
 Marking must not harm, or change behaviour, of
 Marks must not alter the chances of being
Assumptions of mark-recapture
Ideal conditions:
 No new individuals enter the population
 No marked organism dies
 No marked organisms leave the populationjuhb
Mark-Recapture Sampling
 Proportion of marked fish in entire population is
expected to equal the proportion of marked
recaptures in a sample
Sample Problem
Page 655 example problems
Do PP on page 657.
Technological Tracking of Wild Populations
 Mark-recapture not great for migrating/open-ocean
predators (sharks, blue marlin, tuna)
One study: <1% of 20,000 tagged blue marlin recaptured.
 Radio collars, satellite-linked devices, etc.
 Tracking migration/behaviour patterns.
 Cannot restrict or harm animals.
 Microcomputers: attached to dorsal area of fish by
use of a harpoon.
Ethics of Studying Wild Populations
 Possibilities
 Handling of animals during experiments can affect animal’s
behaviour  act differently after release?
 CCAC: Canadian Council on Animal Care
 Three Rs: reduction, refinement, and replacement
Reduction: limit use of animals as much as possible in the study
 Refinement: tweak methods to minimize pain and distress.
 Replacement: replace trapping of animals wherever possible with
computer simulations.
 Page 659, #2 – 6.
14.2 – Measuring and Modelling Population
 Carrying capacity: the maximum number of
organisms that can be sustained by available
resources over a given period of time.
Dynamic: environmental conditions always changing.
Nutrient-poor lake would have smaller carrying capacity per unit
area than a nutrient-rich lake.
 Oligotrophic: lacking in nutrients.
 Eutrophic: nutrient-rich.
 When populations increase in size, amount of
resources available per individual decreases.
Factors that Affect Population Growth
 Populations are always changing
 Experience natural hourly, daily, seasonal, and annual
Births and deaths
 Immigration (in) & emigration (out)
 Population dynamics: changes in population
characteristics determined by natality, mortality,
immigration, emigration.
 Fecundity: potential for a species to produce
offspring in one lifetime.
Ex// starfish: >1 million eggs/year.
Survivorship Curves
 Type I: low mortality rates until beyond reproductive
 Type II: Uniform risk of mortality through life.
 Type III: High mortality rates when young: green sea
turtle (hundreds of eggs, less than 1% reach sexual
 Under natural conditions, fertility is often
significantly less than fecundity.
Calculating Changes in Population Sizes
 Population growth can be calculated by the formula:
 Expressed as a percentage
 Open population
 a population in which change in number and density is
determined by births, deaths, immigration, and emigration
 Closed population
 a population in which change in size and density is
determined by natality (birth rate) and mortality (death
rate) alone
Rare: secluded islands
 “Effectively closed:” short period between mark-recapture:
population is virtually closed.
 Bacterial colonies
Biotic Potential
 Biotic potential: the maximum rate a population can
increase under ideal conditions.
Population Growth Models
 Illustrated by graphing change in population size
over time.
 If birth rates and death rates per individual remains
constant, population grows at a fixed time interval.
Ratio or percent: 1.05 or 5% / year.
 Human population: growth is continuous
 Deaths and births occur at all times.
 Many other species: intermittent
 Births restricted to breeding season
 Geometric growth: a pattern of population growth where
organisms reproduce at fixed intervals at a constant rate
Growth Rate Ratio
 Lambda: fixed growth rate
 N is population size in year (t + 1) and (t) respectively.
We can find population size at any time by rearranging the
Sample/Practice Problems
 Sample problem, Page 663.
 Practice Problem, Page 664 #1
Exponential Growth
 Exponential Growth: a pattern of population growth
where organisms reproduce continuously at a
constant rate
Chosen time interval is not restricted to that of a particular
reproductive cycle.
Can determine instantaneous growth rate of the population
expressed in terms of intrinsic (per capita) growth rate (r).
dN/dt  instantaneous growth rate of population
r  growth rate per capita
N  population size
Doubling Time
 For any population growing exponentially, time
needed for population to double in size, td, is a
For example, if a population has a per capita growth
rate of 0.020 per year (a 2% growth rate), the
approximate time needed for the population to
double would be 0.69/0.020 or 34.5 years.
Sample/Practice Problem
 Sample Problem, page 665.
 Practice Problem #2, page 665.
Geometric vs. Exponential Growth
 Exponential: smooth  continuous reproduction
Increase in numbers rapidly, resulting in a J-shape growth curve.
 Geometric Curve: fluctuates as a result of seasonal or
intermittent reproductive cycles.
Drawn as smooth curves  long-term seasonal fluctuations.
Modelling Logistic Growth
 Geometric & Exponential: assume growth at same
rate indefinitely.
Population has continuous access and unlimited supply of
r is a maximum, rmax.
Not the case in the real world!
 New population: resources plentiful
 As population grows, food, water, light, space in the ecosystem
can limit population growth.
 Growth rate drops below rmax.
 Number of deaths approach number of births  stable
Carrying Capacity
 When births = deaths.
 K: population number at the carrying capacity.
 Logistic growth: represents the effect of carrying
capacity on the growth of a population.
Most common growth pattern seen in nature.
Logistic Growth Equation
Note: if N close to K, then dN/dt = 0
growth virtually ceases.
Sample/Practice Problem
 Sample Problem, page 667.
 Practice Problem #3, 4 page 668.
Logistic Growth Curve
 Three phases to a logistic growth curve
 Shape resembles an S (sigmoidal)
Example of Logistic Growth
 Population of fur seals: St. Paul Island, Alaska.
 Hunting banned in 1911 (seal population low)
 Many unused resources
 Population grew rapidly  carrying capacity reached 
logistic growth curve.
Vague Summary
 Page 667, #1-6
14.3 – Factors Affecting Population Change
 Read/make notes on section 14.3
Practice Problems, page 675, #1-5.