EVPP 110 Lecture
Instructor:Dr. Largen Fall 2002
Populations:
Population Ecology
Topics
Population structure and dynamics
Life Histories and their evolution
Populations are defined in several ways
Population
group of individuals of a species living in same area at same time
using common resources
regulated by same natural phenomena
definition is flexible, but allows discourse in similar terms about any population
world human population
population of protozoa in one termite gut
population of deer in a particular forest
Population structure and dynamics
Density and dispersion patterns are important population variables
Population size
an important feature of any population
affects ability of population to survive
small populations tend to become extinct
random events & natural disturbances
likely to endanger small population
inbreeding
lowers population’s "genetic" vigor
reduces genetic variability
Density and dispersion patterns are important population variables
Population density
important to survival of population
if individuals of a population are spaced widely apart they may rarely encounter one another
- can limit reproductive capacities
- even is absolute number of individuals over a wide area is large
Density and dispersion patterns are important population variables
Population density
= # of individuals of a species per unit area or volume
number of oak trees per km2 of forest
number of earthworms per m3 of soil
how is population density measured
impossible or impractical to count all individuals in a population
mosquito larvae in a pond
gypsy moth eggs in a forest
need to use sampling techniques
Density and dispersion patterns are important population variables
sampling technique
method to estimate population density
by direct count of organisms or indicators in a small area or volume
- which is used to project actual density over entire area
examples
- counting number of mosquito in each of 20 0.5L samples of water
- mark-recapture method
Density and dispersion patterns are important population variables
Population dispersion
way in which individuals of a population are spaced within their area
three main patterns of dispersion
clumped
uniform
random
Density and dispersion patterns are important population variables
Population dispersion
clumped
individuals clump into groups or clusters
often in response to uneven distribution of resources
- cottonwoods clumping along a stream bank
most common pattern in nature
Density and dispersion patterns are important population variables
Population dispersion
uniform
individuals are uniformly or evenly spaced
often results from interactions between individuals
- social interactions in case of animals
- competition for sunlight or water in case of plants
relatively common in nature
Density and dispersion patterns are important population variables
Population dispersion
random
individuals spaced in a pattern-less, unpredictable way
- such that they don’t interact strongly with one another or the non-uniform aspects of their environment
not common in nature
Idealized models help us understand population growth
Two types of population growth
exponential
accelerating increase in population size that occurs when growth is unregulated
logistic
population growth that is slowed by population-limiting factors and tends to level off at a carrying capacity
Idealized models help us understand population growth
Exponential growth
rate of expansion of population under ideal conditions
entire population multiplies by a constant factor during constant time intervals
described by the equation G = rN
G = growth rate of the population
N = population size
r = intrinsic rate of increase
graph produces typical J-shaped curve
Idealized models help us understand population growth
Exponential growth
r = intrinsic rate of increase
organism’s inherent capacity to reproduce
- varies by organism
- remains constant for any population expanding without limits
- can be roughly estimated as
- birth rate minus death rate
- r = b - d
Idealized models help us understand population growth
Exponential growth
long periods of exponential growth are not common in real world
consider bacteria example
- one bacterium which undergoes exponential growth (without limits) would produce enough bacteria in 36 hours to cover the entire surface of the earth to a depth of one foot
Figure : Exponential growth of bacteria
Idealized models help us understand population growth
Logistic growth
growth that’s slowed by limiting factors
its equation must account for limiting factors
the exponential equation modified by a term that represents the overall effect of the limiting factors
- (K - N)/K where K = carrying capacity
- number of individuals in a population that the environment can just maintain with no net increase or decrease
Idealized models help us understand population growth
Logistic growth
(K - N)/K
when population is small,
- (K - N)/K has little effect
- logistic curve is very similar to J-shaped exponential curve
Idealized models help us understand population growth
Logistic growth
(K - N)/K
as population gets larger,
- (K - N)/K and the growth rate gets smaller and smaller
- curve becomes S-shaped
- population levels off at the "carrying capacity" when limiting factors causes birth rate and death rate to be equal
Idealized models help us understand population growth
Exponential and logistic growth models
both are mathematical ideals
no natural populations fit either model perfectly
Density-dependent and density-independent factors limit population growth
- Population growth is limited by two general types of factors
- density-dependent factors
- limits to growth related to density of the population
- density-independent factors
- limits to growth not related to density of population
Density-dependent and density-independent factors limit population growth
- density-dependent factors
- affect a greater percentage of individuals in a population as density of the population increases
- as the population grows, individuals compete with increasing intensity for limited resources
- examples
- loss of food
- loss of shelter
Density-dependent and density-independent factors limit population growth
- density-independent factors
- population-limiting effects that are independent of population density
- include abiotic factors
- weather
- physical disruption of habitat
Some populations have "boom-and-bust" cycles
"boom-and-bust" cycle
a rapid increase ("boom") following by a sharp decline ("bust")
often seen in predator-prey interactions
cycling of lynx (predator) and snowshoe hare (prey) populations
may also be tied to food supply, altered hormonal balance from crowding effects, reduced fertility
Figure : Population cycles of the snowshoe hare and lynx
Life Histories and Their Evolution
Life tables track mortality and survivorship in populations
Survivorship
the percentage of an original population that survives to a given age
requires compilation (life table) data
- for each defined age interval
- number living at start of interval
- number dying during interval
- from which can be calculated mortality (death rate) and chance of surviving the interval
Life tables track mortality and survivorship in populations
Survivorship curves
one way to express the age distribution characteristics of a population
varies with species
uses a percentage scale instead of actual life span on horizontal axis
allows comparison of species with different life spans on the same graph
there are three primary types
type I survivorship curve
type II survivorship curve
type III survivorship curve
Life tables track mortality and survivorship in populations
Survivorship curves
there are three primary types
type I survivorship curve
type II survivorship curve
type III survivorship curve
Life tables track mortality and survivorship in populations
type I survivorship curve
exhibited by a population in which mortality rates rise steeply in post-reproductive years
most individuals of the population die in the older age intervals
species with this type curve
produce few offspring & give them intense care to insure their survival
examples
humans, whales, elephants
Life tables track mortality and survivorship in populations
type II survivorship curve
exhibited by a population in which individuals are equally likely to die at any age
mortality more constant over life span
intermediate to types I and III
examples
jellyfish
hydra
some rodents
Life tables track mortality and survivorship in populations
type III survivorship curve
exhibited by a population in which individuals produce vast numbers of offspring
only a few of which survive to reproductive age
- those that do survive become established, reproductive, with low mortality rate
examples
oysters, some plants
Evolution shapes life histories
Life history of an organism
series of events from birth through reproduction to death
life history traits influence growth rte of a population, including
age of first reproduction
number of offspring
amount of parental care given to offspring
energy cost of reproduction
Evolution shapes life histories
life history traits
are shaped by evolution operating through natural selection
every population has a life history adapted to its environment
two main life history categories
opportunistic life history
equilibrial life history
Evolution shapes life histories
opportunistic life history
smaller-bodied organisms
reproduce when young
produce many offspring
populations
tends to grow exponentially
live in unpredictable environments
controlled by density-independent factors
exhibit type III survivorship curve
examples -dandelions, annual plants
Evolution shapes life histories
equilibrial life history
larger-bodied organisms
reproduce later in life
produce fewer offspring but provide care
populations
size tends to be stable
live in predictable environments
controlled by density-dependent factors
exhibit type I survivorship curve
examples -humans, large trees, polar bears
The End.