principles of ecology (lsu biol 4253, section 3, fall 2014) composite satellite image (“blue...
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Principles of Ecology(LSU BIOL 4253, Section 3, Fall 2014)
Composite satellite image (“Blue Marble 2012”) from Wikimedia Commons
A312 Life Sciences [email protected]
Dr. Kyle E. Harms
http://www.kharms.biology.lsu.edu
K. Harms photo
Complex Causation of Amphibian Deformities & Declines
The Web of Life
Cain, Bowman & Hacker (2014), Fig. 1.13
Ernst HaeckelGerman scientist, philosopher, physician
“oekologie” – combined Greek words for “household” & “knowledge”
What is Ecology?
Photo of Haeckel from Wikimedia Commons
The scientific study of interactions among organisms and their environments
What is Ecology?
K. Harms photo
Ecology is a Component of Environmental Science
Environmental Science – interdisciplinary field that draws concepts, expertise, and tools from natural and social sciences
Map of seasonal Gulf Coast hypoxia – the “dead zone” – from Wikimedia Commons
Environmental Movement – "a political and ethical movement that seeks to improve and protect the quality of the natural environment through changes to
environmentally harmful human activities"
Ecology Can Inform Environmentalism
Quote – Encyclopedia Britannica Online; photos of Carson and her 1962 book – Wikimedia Commons
Rachel Carson
Image from Wikimedia Commons
Levels of Biological Organization
Principal realm of Ecology
Joseph H. Connell
50+ Years of Personal Ecological Research(Rocky inter-tidal, coral reefs, tropical forests, etc.)
Photo of Connell courtesy of Pete Green
Ecological Patterns
Cain, Bowman & Hacker (2014), Fig. 12.9
Observations: Barnacle Inter-tidal Zonation
Semibalanus – Larger barnacle, lower in intertidal
Chthamalus – Smaller barnacle, higher in intertidal
Why?
Barnacle Inter-tidal Zonation
Abiotic influences –
Differential physiological tolerances to desiccation or submersion
Biotic interactions –
Interspecific competition
Predation (e.g., Thais snails preyon Semibalanus)
Alternative Mechanistic HypothesesNatural ecological & evolutionary processes that
could have produced the patterns (i.e., cause-and-effect)
Testable Predictions
Barnacle Inter-tidal Zonation
Abiotic influences –
Move barnacles outside current zones and performance should decline
Biotic interactions –
Remove competition and zones should shift
Remove predators and zones should shift
Selected Experimental Results
Barnacle Inter-tidal Zonation
The absence of competitors & predators produced no change in upper distributions
For Chthamalus, removing Semibalanus increased downslope survivorship & distribution
For Semibalanus, removing Thais increased downslope survivorship & distribution
Barnacle zonation
Mechanistic Explanation / Interpretation
Connell (1961) Ecology, Fig. 5
Observations
Scientific Advancements
Jane Goodall and chimp
Jane Goodall
ObservationsModels (mathematical and computer)
Scientific Advancements
Chaotic population growth
Per capita rate of increase
Pop
ulat
ion
size
(s
cale
d to
max
. si
ze a
tta
inab
le)
ObservationsModels (mathematical and computer)
Controlled Experiments (e.g., laboratory, microcosm, mesocosm)
Scientific Advancements
http://lishaopeng.weebly.com/aquatic-algal-microcosm-experiment.html
ObservationsModels (mathematical and computer)
Controlled Experiments (e.g., laboratory, microcosm, mesocosm)Field Experiments
Scientific Advancements
Replicated fuel-manipulation treatments in Louisiana pine savanna; photo courtesy of Jonathan Myers
Replication (i.e., n>1)
Experiments
Why?
1.0 m
1.5 m
2.0 m
1.0 m
1.5 m
2.0 m
vs.
Avoid spurious influence of uncontrolled variables!
Experiments
Why?
1.0 m
1.5 m
1.0 m
1.5 m
2.0 m2.0 m
Avoid spurious influence of uncontrolled variables!
vs.
Random Assignment of Controls & Treatments
Statistical Analysis
Experiments
Why?
To objectively determine whether results match predictions!
1.0 m
1.5 m
1.0 m
1.5 m
2.0 m2.0 m
vs.
Average male
Average female
E.g., Chi-squared Goodness-of-Fit Test
Statistical Analysis
0
2
4
6
Num
ber
of in
divi
dual
s
p-value – probability of obtaining a test statistic at least as extreme as observed, assuming the null hypothesis is true
6
6
Observed Expected(Null)
6
6
p = 1.0(accept null)
E.g., Chi-squared Goodness-of-Fit Test
Statistical Analysis
p-value – probability of obtaining a test statistic at least as extreme as observed, assuming the null hypothesis is true
0
20
40
60
Num
ber
of in
divi
dual
s
60
40
Observed Expected(Null)
50
50
p < 0.05(reject null;
support alternativehypothesis)
E.g., t-Test
Statistical Analysis
0
40
120
160
Hei
ght (
cm)
180175
172160
p = 0.19(accept null at 5%
level of significance)
165 140155 135148 130130 125
Height (cm)
80
Mean = 158.83 18.50
Mean =143.67 18.40
E.g., Correlation
Statistical Analysis
Correlation coefficient (r) – varies between -1 and 1;0 = no relationship
r = 0.87
120 130 140 150 160 170 180 1900
20
40
60
80
100
120
140
160
180
200
Height (cm)
Leng
th o
f rt
. ha
nd (
mm
)
E.g., Linear Regression
Statistical Analysis
Slope = -0.34; p < 0.05; r2 = 0.78
Examines the relationship between a dependent and an independent variable; p-value tests the slope against null slope = 0; coefficient of determination (r2) expresses how well the data fit the model
120 130 140 150 160 170 180 1900
10
20
30
40
50
60
70
80
90
100
Height (cm)
Num
ber
of r
abbi
ts c
augh
t pe
r m
onth
Photo of Levin from Princeton U.
“It is argued that the problem of pattern and scale is the central problem in ecology, unifying population biology
and ecosystems science, and marrying basic and applied ecology”
S. Levin (1992)
Scale in Ecology
E.g., species-area relationship(s)
Focus
Extent
Hubbell (2001) The Unified Neutral Theory of Biodiversity & Biogeography, Fig. 6.2
Spatial & temporal patterns often change with the scale of measurement
Scale in Ecology
Photos from Wikimedia Commons
E.g., how can we extrapolate from one scale to another (e.g., leaf-level gas exchange and photosynthesis
forest productivity global climate change)?
We seek mechanistic links among patterns and processes across scales
Scale in Ecology