CUMULATIVE textbook and lecture notes for the class BIOLOGY281: General Ecology at the University of Michigan. Notes were taken WN2024 under Prof. Christopher Dick.
Chapter
1:
What
is
Ecology
in
Action?
1.1
Ecological
Questions
●
2
basic
questions
asked
by
population
ecologists:
○
What
is
the
abundance
of
a
population?
○
What
is
the
distribution
of
the
population?
1.2
Testing
Hypotheses
●
To
be
study-worthy,
hypotheses
must
be
plausible
and
generate
testable
predictions
●
Consider
all
hypotheses
when
attempting
to
understand
a
biological
process
●
Hypotheses
for
buffalo/wildebeest
population
increase
in
the
1960s/1970s:
○
Food
Availability
Hypothesis:
food
was
better
in
quality
or
more
abundant
■
Rainfall
influences
grass
production
■
To
test:
established
exclosures
(experimental
fenced
areas
that
reduces
unwanted
factors)
●
Harvested
vegetation
within
exclosures
regularly
and
measured
the
amt
of
grass
that
grew
compared
to
the
amt
of
rainfall
●
Predicted
positive
correlation
between
rainfall
and
grass
production
■
As
rainfall
increased,
grass
production
also
increased
–
significant
positive
effect
on
grass
availability
■
Rainfall
records
were
the
same
as
historical
averages
→
likely
not
the
reason
for
population
increase
○
Predator
Release
Hypothesis:
reduction
(release)
from
high
levels
of
predation
■
To
test:
compared
previous
surveys
of
predator
levels
■
Found
that
predator
populations
also
increased
during
this
time
○
Rinderpest
Release
Hypothesis:
rinderpest
is
a
virus
that
attacks
cattle
and
other
ruminants
(mammals
who
digest
plant-based
food
by
softening
it
within
the
rumen
where
it
ferments)
■
Great
Rinderpest
Plague
of
1890
killed
95%
of
cattle
in
southern/eastern
Africa
■
Hypothesized
that
rinderpest
was
keeping
wildebeest
and
cattle
populations
unnaturally
low
in
the
50s,
and
that
they
were
recovering
in
the
60s
●
When
both
variables
are
numeric
or
continuous,
use
correlation
analysis
to
eval
relationship
b/n
them
●
Statisticians
use
the
correlation
coefficient
(r)
to
describe
correlation
strength
○
1.0
=
strong
positive,
-1.0
=
strong
negative,
0
=
no
correlation 1.3
Observation,
Modeling,
and
Experimentation
●
Ecology
happens
in
the
real
world
○
Controlling
variables
is
difficult
○
Replication
of
experiments
may
be
impossible
●
Must
be
able
to
observe
and
pick
up
on
small
nuances
●
3
types
of
observations
○
Observe
actual
processes
with
their
senses
○
Learn
from
published
literature
○
Observe
what
other
people
are
doing
or
saying
■
Local
communities,
other
scientists/experts
from
other
fields,
bouncing
ideas
off
of
other
ecologists
●
Scientific
models
seek
to
describe
a
system
or
predict
what
it
will
do
in
the
future
●
Ecologists
differ
from
other
biology
fields
because
their
research
spans
and
integrates
many
levels
of
the
biological
hierarchy
1.4
Linking
the
Biological
Hierarchy
●
Ecologists
study
interactions,
so
must
understand
all
levels
of
the
biological
hierarchy
but
usually
focus
on
the
level
of
the
organism
and
above,
up
to
the
biosphere
●
Can
use
the
Serengeti
to
represent
the
different
levels
of
the
biological
hierarchy
●
Organism:
individual
life
form
○
At
this
level,
can
ask
how
individual
buffalo
forages
in
a
manner
that
meets
its
daily
energy
and
nutritional
needs
●
Can
explore
distribution
and
abundance
of
populations
at
a
location
○
Wildebeest,
zebra,
and
Thompson
gazelle
migrations
●
Populations
interact
to
form
communities
○
Wildebeest
grazing
stimulates
regrowth
of
grasses/plants
→
gazelles
and
other
populations
can
eat
them
○
Communities
of
wildebeest,
gazelles,
grasses,
and
plants
all
interact
●
The
ecosystem
includes
all
communities
and
abiotic
features
that
interact
with
each
other
●
Landscapes
are
interacting
and
spatially
connected
ecosystems
○
West
of
the
Serengeti,
ecosystem
is
dominated
by
agriculture
○
Humans
hunt
elephants,
wildebeests,
etc
●
Landscapes
are
parts
of
larger
regions
with
common
set
of
environmental/evolutionary
influences
○
On
this
level,
look
at
abundance
and
species
richness
●
The
biosphere
is
the
highest
level;
the
part
of
the
world
that
supports
life
●
3
primary
abiotic
factors
studied
in
the
Serengeti:
○
Nutrients
■
Highest
levels
in
the
southeastern
plain
■
Lowest
in
the
northwest
○
Fire ■
Almost
all
started
by
humans
●
Improve
grazing
pastures,
park
management,
honey
hunters
smoking
out
bees
■
Only
occur
in
dry
season
but
in
typically
wetter
areas
●
Wetter
area
→
more
grass
growth
→
more
dry
grass
for
fuel
in
the
dry
season
○
Rain
■
Lowest
levels
in
the
southeastern
plain
■
Highest
in
the
northwest
●
Due
to
rain/nutrient
levels,
migrating
animals
spend
the
wet
months
in
the
southeast,
then
move
to
the
northwest
in
the
dry
season
○
Distribution
of
abiotic
factors
influences
distribution
of
organisms
●
Much
of
the
western/northern
portion
of
the
Serengeti
is
open
woodland
with
canopy
cover
b/n
2%
and
30%
○
Grass
grows
easily
between
the
trees
●
El
Nino
Southern
Oscillation
(ENSO)
:
a
large-scale
atmospheric
system
that
affects
the
global
climate
○
Associated
with
high
temperature
and
low
pressure
in
the
Pacific
region
○
Affects
Serengeti
climate
○
Fluctuates
~5
years
Lecture
–
1/16
●
Scientific
Method
○
Make
observations,
ask
questions
○
Previous
knowledge/intuition
→
form
hypotheses
○
Evaluate
hypotheses
by
experiment,
observation,
or
modeling
○
Use
results
to
modify
hypothesis,
pose
new
questions,
or
draw
conclusions
●
Scientific
method
is
iterative
and
self-modifying
●
Serengeti:
79
large
mammal
species
○
Southeast
and
northwest
corners
=
wet
areas
■
In
between
is
very
dry
■
Breeding
season
spent
in
southeast,
migrate
to
northwest
during
dry
season
●
60s-70s:
wildebeest
population
growing
rapidly…
why?
●
Tony
Sinclair’s
hypotheses:
○
Food
availability:
more
rain
=
more
food/higher
quality
food
available
■
Prediction:
food
quality
and
abundance
increased
in
early
60s
and
remained
high
throughout
the
decade
■
Test:
●
Use
exclosures
to
test
productivity
of
grasslands
in
areas
with
increased
rainfall
●
Determine
if
rainfall
had
increased
significantly
over
the
period
of
population
increase ■
Was
not
found
to
be
true
○
Predator
release:
less
predators
=
more
survival
■
Prediction:
large
predators
declined
in
the
60s
■
Test:
look
at
records
of
predator
populations
■
Not
found
to
be
true
○
Rinderpest
release:
rinderpest
was
a
disease
that
affected
cattle
and
other
ruminants,
rinderpest
eradicated
so
wildebeest
populations
rebounded
■
Predictions:
●
Negative
correlation
between
rinderpest
infection
and
ruminant
abundance
●
No
correlation
between
rinderpest
infection
and
non-ruminant
abundance
●
Increased
survival
rate
in
juvenile
ruminants
●
Kinds
of
experiments
○
Lab:
control
everything,
possibly
reductionistic
○
Field:
can
manipulate
things
but
maybe
not
“natural”
○
Natural:
may
have
confounding
factors
●
Rules
of
experimental
design
○
Replication
○
Randomization
○
Avoid
pseudoreplication
●
False
positive
→
type
I
error
○
Incorrectly
reject
the
null
●
False
negative
→
type
II
error
○
Incorrectly
accept
the
null
●
Types
of
data
○
Categorical:
finite
number
of
categories/groups
○
Discrete:
numeric
variables
that
have
countable
number
of
values,
no
decimals
○
Continuous:
numeric
variables
w/
infinite
number
of
values
between
any
two
values
●
What
kind
of
test?
○
Independent:
Quantitative;
Dependent:
quantitative
→
correlation
or
regression
○
Ind:
Categorical;
Dependent:
quantitative
→
T-test,
ANOVA
○
Ind:
categorical;
dependent:
categorical:
chi-squared
Chapter
2:
The
Physical
Environment
Intro
●
Biome:
large
geographical
area
w
characteristic
groups
of
organisms
adapted
to
that
particular
environment
○
Terrestrial
biomes
influenced
by
temp,
moisture,
and
soil
○
Aquatic
biomes
influenced
by
temp,
chemical
composition
of
water,
and
currents
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