Title: Impact Assessment
1Impact Assessment
2Impact assessment
- What is the impact of one or more management
techniques on an environmental variable of
interest? - Effects of grazing on biodiversity in California
grasslands - Establishment of marine protected areas in
Channel Islands how do they affect lobster
abundance? - Has some event caused a change in the
environment? - Power plant goes on line
- Hurricane
- Challenge is to establish causation
- This is a conceptual issue, not a statistical
issue!
3San Onofre Nuclear Power Plant
- Units 2 3 came online in May 1983
- Cooling water discharge creates turbidity due to
volume of flow - This has potential negative effects on giant
kelp - Reduced light at sea floor reduces growth and
survival of baby kelp - Sediments bury hard substrate
- Data collected on total area of kelp forest,
using sidescan sonar - Question did the power plants negatively impact
the kelp bed adjacent to the cooling water
discharge site?
4Before-After (BA)
- Suppose we have data from power plant outflow
site before and after operation began - Is kelp area lower after the power plant went
online?
5Two-sample t-test
- If two samples, X and Y, are from populations
with the same mean -
- Then the quantity
- follows a t distribution with
nx ny 2 degrees of freedom
6Assumptions of 2-sample t-test
- Populations from which x and y are sampled are
normally distributed - Test is pretty robust as long as sample sizes are
similar and 2-tailed tests are being considered - The more samples, the better
- If non-normality is strong, dont put confidence
in alpha levels below 0.01 - Populations from which x and y are sampled have
same variances - Violations mean that P values will be somewhat
too small - Use Welchs approximate t test instead
7Welchs approximate t-test
- If two samples, X and Y, are from populations
with the same mean but different variances - Then the quantity
- follows a t distribution with
- degrees of freedom
8BA (continued)
9BA (conclusion)
- The assumptions of the t-test are moderately
violated - However, P value is extremely small we can be
confident that the true P is less than a
reasonable alpha (0.05 or even 0.01) - Thus, with high confidence we can reject the null
hypothesis that the kelp area was the same before
and after the power plant went online - Does this mean the power plant has caused this
difference?
10Control-Impact (CI)
- Suppose we have data from power plant outflow
site and a control site nearby, but only after
operation began - Is kelp area lower in impact site than control
site?
11Again, do a 2-sample t-test
12CI
- Conclusion Fail to reject the null hypothesis
that Control and Impact sites have same amount of
kelp! - Does this mean that power plant has no effect on
kelp?
13Before-After Control-Impact (BACI)
- If we have data from both sites (Control and
Impact) at both periods (Before and After) then
we can - Use the Control site to control for temporal
changes in kelp that are unrelated to the power
plant coming on line - Also called a counterfactual
- Use the Before period to determine the relative
quality of the two sites before the power plant - We want to focus on the difference of
differences
14Estimate the effect size
15Combining all the information simple BACI using
ANOVA
- Use Site, Period and Site x Period interaction in
ANOVA - The model
S site (C1, I-1) P period (B-1, A1)
Overall mean kelp density
Deviation from overall mean associated with being
in a given Period (After b2, Before -b2),
averaged over both sites
Deviation from site mean associated with being in
a given Period (After b3, Before -b3),
OR Deviation from period mean associated with
being in a given Site (Control b3, Impact -b3)
Deviation from overall mean associated with being
in a given site (Control b1, Impact -b1),
averaged over both periods
16- Overall mean
- Site means
- Period means
- Interactions
17BACI with ANOVA
18We can do even better!
19Before-After Control-Impact Paired Series (BACIPS)
- Calculate deltas for each sample time by
subtracting value at control site from value at
impact site - controls for temporal variability in environment
- Do a two-sample t-test to see if mean delta
changes from before to after
20BACIPS continued
21BACI BACIPS conclusions
- Reject null hypothesis that true effect size is
zero - BACIPS gives more power
- Could have drawn conclusion sooner
- Gives more confidence under violation of
assumptions - Does this mean the power plant has caused this
effect?
22Impact assessment general considerations
- We need some way to control for variability that
might confound our conclusions - Temporal changes unrelated to event in question
- Differences in underlying quality between sites
- Can also control by including measurements of
additional variables that might affect response - SST, amount of rocky reef, etc.
- What if monitoring only starts after event occurs?
23Environmental challenge
- The problem There is a great deal of controversy
about how to manage California grasslands for
biodiversity values. In particular, there is
debate about whether grazing by cattle is
promotes or is deleterious to plant diversity - Data on plant diversity and relative abundance
have been collected from plots at Sedgwick
Reserve where grazing has been either allowed or
excluded. - Your job Using these data, determine whether
grazing increases or decreases plant diversity.
24Diversity in Sedgwick grassland plots
252-sample t-test of H
26Paired t-test
- If observations naturally come in pairs
- Control treatment plots next to each other
- Calculate differences, di xi - yi
- Use one-sample t-test to test H0 md 0
27Paired t-test
282-sample vs paired t-test
- TWO SAMPLE t-TEST
- Difference of means
- Use when observations are independent between
groups - Assumes each population is normally distributed
- PAIRED t-TEST
- Mean of differences
- Use when observations are naturally paired
- Assumes population of differences is normally
distributed
- Both will estimate same mean difference
- If there is variation among pairs (e.g., due to
location, soil type, habitat), then paired test
will have more power to reject null hypothesis
29Independence and randomness
30Further Reading
- Schmitt, R.J., and C.W. Osenberg, eds. 1996.
Detecting Ecological Impacts. Academic Press, San
Diego. - Stewart-Oaten, A., W.W. Murdoch, and K.R. Parker.
1986. Environmental impact assessment
pseudoreplication in time? Ecology 67 929-940. - Zar, Chapters 8.1-8.4, 9.1-9.3 (t-tests), 10.l,
12.1-12.2 (ANOVA)