controls and additive series
DESCRIPTION
Controls and additive series. Group exercise: Read your stream control example, and decide on: (1) What is wrong with the design? (2) How you might fix it. C. C. A. A. B. B. Scenario 1. Before. After. Scenario 2. B. C. A. + pollutant. E. F. D. - pollutant. - PowerPoint PPT PresentationTRANSCRIPT
Controls and additive series
Group exercise:
Read your stream control example, and decide on:
(1) What is wrong with the design?
(2) How you might fix it.
Scenario 1
A B C A B C
Before After
Scenario 2
A B C
D E F
+ pollutant
- pollutant
What is the probability that the 3 “worst” streams are randomly assigned to the pollutant treatment?
3/6 * 2/5 * 1/4 = 2/40 or 5%
Scenario 3
A B C A B CBefore After
D E F D E F
Before After
+ chemical in alkaline solution
control
Scenario 4
A B C A B CBefore After
D E F D E F
Before After
+ pollutant
control
0
5
10
15
20
25
30
35
40
45
control + pollutant
Det
rita
l los
s (m
g / w
eek)
with insectsno insects
Scenario 5
?
Insect abundance =
m1 * width +
m2 * dioxin +
m3 * width*dioxin +
Y-intercept
(and error)
Summary of control types
Which scenarios lacked:
• Control for initial conditions?
• Unmanipulated, contemporaneous control?
• Control for side effect of manipulation?
• Control for covariates?
• Control for non-target response?
BACI design
• Unmanipulated, contemporaneous control
• Initial conditions
Eg. Scenario 3
Before After
Before After
+ pollutant
control
Before After Control Impact
BACI design
• Unmanipulated, contemporaneous control
• Initial conditions
Before After
+ pollutant
control
Before After Control Impact
Study SiteRoadsHiking trail
WaterContour 100m ((10m)
Major Roads
Study Site
Legend
Camp
Sky
line
SICAMOUS
N
EW
S
Kamloops
Sicamous Sicamous
Kamloops
Example of BACI design:Ernest Leupin’s study
on forest fragments and birds
Forest residue
Roads Openings Selection cut
N
C a m p M t . M a r a
H i k i n g
T r a i l
S k y l i n e
0 1 2 K i l o m e t e r s
Sicamous Creek Research Forest
How can we analyze BACI designs?
Randomized block?
What is n?
What is k?
How many independent experimental units in total?
A treatment x date ANOVA?
Before After
Before After
+ pollutant
control
A B C A B C
D E F D E F
How can we analyze BACI designs?
Randomized block?
A treatment x date ANOVA?
Before After
Before After
+ pollutant
control
A B C G H I
What is n?
What is k?
How many independent experimental units in total?D E F J K L
How can we analyze BACI designs?
Two separate ANOVAs / t-tests?
Before After
Before After
+ pollutant
control
Different? Different?
How can we analyze BACI designs?
Two separate ANOVAs / t-tests?
A B Cbefore after before after before after
Y variable
before after
Impact sites
How can we analyze BACI designs?
• Need to have match the number of datapoints with the number of experimental units
• Need to take advantage of built-in control for stream identity
How can we analyze BACI designs?
One solution:
Use difference between before and after as the data!
Before After
Before After
+ pollutant
control
A B C A B C
D E F D E F
Difference
Difference
A B C
D E F
Example: Additive series design for container mosquito larvae
1985
1996
Aedes albopictus invades N America from SE Asia in 1985, via used tire trade at Houston
Breeds in containers habitats (old tires, treeholes), like native species, Aedes aegypti
Aedes albopictus
Ranges overlap, potential for interspecific competition
Experimental design (“Additive series”)
Juliano, S. 1998. Species introduction and replacement amongst mosquitoes: interspecific resource competition or apparent competition? Ecology 79: 255-268.
Aedes aegypti
Aed
es a
lbop
ictu
s
Substitutive or
replacement series
Experimental design (Additive series)
Juliano, S. 1998. Species introduction and replacement amongst mosquitoes: interspecific resource competition or apparent competition? Ecology 79: 255-268.
Aedes aegypti
Aed
es a
lbop
ictu
s
Addition design
Experimental design
Juliano, S. 1998. Species introduction and replacement amongst mosquitoes: interspecific resource competition or apparent competition? Ecology 79: 255-268.
Aedes aegypti
Aed
es a
lbop
ictu
s Can asses Aedes aegypti performance in these treatments
Hypotheses:
Aedes aegypti
Aed
es
alb
op
ictu
s
aeg 20 20 40 60albo 0 40 20 0
Aed
es
aeg
ypti
re
spo
nse
Albo has an effect on Aeg, and effect of 1 Albo = 1Aeg
aeg 20 20 40 60albo 0 40 20 0
Aed
es
aeg
ypti
re
spo
nse Albo has no effect
on Aeg, so effect of 1 Albo = 0 Aeg
aeg 20 20 40 60albo 0 40 20 0
Aed
es
aeg
ypti
re
spo
nse
Albo has an effect on Aeg, but effect of 1 Albo < 1Aeg
Hypotheses:
Aedes aegypti
Aed
es
alb
op
ictu
s
aeg 20 20 40 60albo 0 40 20 0
Aed
es
aeg
ypti
re
spo
nse
Albo has an effect on Aeg, and effect of 1 Albo = 1Aeg
aeg 20 20 40 60albo 0 40 20 0
Aed
es
aeg
ypti
re
spo
nse Albo has no effect
on Aeg, so effect of 1 Albo = 0 Aeg
aeg 20 20 40 60albo 0 40 20 0
Aed
es
aeg
ypti
re
spo
nse
Albo has an effect on Aeg, but effect of 1 Albo < 1Aeg
Results
aeg 20 20 40 60albo 0 40 20 0
Aed
es
aeg
ypti
su
rviv
ors
hip
ANOVA: treatment x food x tire(=block)
Followed by t-tests (posthoc)