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The University of Melbourne

EVSC30003 Environmental Risk Assessment
Exam 2014

Reading Time: 15 minutes
Writing Time: 3 hours


This paper has 5 pages (including this one)



Instructions to Students

This is a take-home, open-book examination. You should attempt to answer all questions, and all
parts of all questions.

The number of marks allotted is shown for each question. Marks total 100. Sub-questions are of
equal value unless stated otherwise.

Each question has a strict word limit. Markers will cease to interpret answers beyond the word limit
of each question.

It is forbidden to discuss any part of this exam with current and/or past students, or to seek
help from or use any other person for support. The work must be solely the product of the
individual student. If collusion is detected, all those involved will be given a grade of 0 for
the exam.

Exams should be submitted as hard copy (either hand written or printed) to the School of Botany
reception desk on or before 4:30 pm on Tuesday, June 10th, 2014.

Terry Walshe (twalshe@unimelb.edu.au) is available to answers questions about the exam by
email.

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Question 1. (twelve marks, 250 words)

‘Scientific knowledge (i.e. prevailing understanding of risk management) is not a transcendent mirror of
reality. It both embeds and is embedded in social practices, identities, norms, discourses, instruments and
institutions.’ - Jasanoff (2004)

Discuss in the context of stakeholder engagement in risk-based decision making.


Question 2. (eight marks, 200 words)

The figure below shows a cognitive map capturing understanding of the drivers of algal blooms in an inland
river. The system could also be described using a Bayesian Belief Network (BBN).



What are the strengths and weaknesses of cognitive maps and BBNs in this context?


Question 3. (fourteen marks)

(a) How does the ‘law of small numbers’ affect the interpretation of data? (four marks, 100 words)

(b) Two alternatives to buffer against psychological frailties in the interpretation of data are
 use of a specified p-value for the Type I error rate (typically 0.05), or
 routine use of confidence intervals.

Which of these two alternatives is better in your opinion? Why? (ten marks, 200 words)


Question 4. (ten marks)

Public health managers are concerned about the risks posed by a novel disease to an isolated community
of indigenous people. If exposure occurs, high contagion or widespread genetic vulnerability will result in an
epidemic. These three variables are uncertain. Upper and lower bounds for the likelihood of exposure (E),
high contagion (C) and genetic vulnerability (GV) are E0.2, 0.6, C0.3, 0.5, and GV0.6, 1.0.

Draw a logic tree that captures this narrative of cause-and-effect, and calculate upper and lower bounds for
the risk of an epidemic (eight marks).

What assumptions about dependencies do these calculations make? (2 marks)
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Question 5. (eight marks, 150 words)

An ecotoxicologist uses Monte Carlo simulation to explore variation in the dose of a contaminant to which a
population of crustaceans is exposed. Results of the simulation are shown below.



The regulatory agency specifies that no more than 1% of the population can exceed a dose of 4 mg/kg/yr.

Do the model results suggest that the tolerable dose has been exceeded? (2 marks)
Do the results look reasonable? (3 marks)
How could assumptions of the analysis compromise its reasonableness? (3 marks)


Question 6. (ten marks, 200 words)

The manager of Wilson’s Promontory National Park identified three alternatives for improving the condition
of coastal-grassy woodlands: burning (blue line), shooting exotic herbivors (brown line) and shooting all
herbivores (green line). The decision to implement any one alternative depends, in part, on trade-offs
between conservation outcomes, public outrage and monetary cost. These trade-offs were captured as
weights in a multi-citeria decision analaysis. The graph below shows the weight assigned to conservation
outcomes (the vertical red line) and the merit of the three alternatives as that weight varies.


How sensitive is the outcome of the analysis to the weight assigned to conservation?
Imagine burning is no longer available as an alternative. How sensitive is the outcome now?
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Question 7. (twelve marks)
A forestry company has three strategic options in the face of uncertainty posed by a fungal disease that may
or may not be harmful to timber. The options are to do nothing, improve genetic resistance of the host trees,
or expand the business by increasing the forest estate. The subjective beliefs of senior managers is that
there is a 75% chance the disease will be benign and a 25% chance it will be harmful. The table below
summarises the judgments of senior managers regarding the profit anticipated under each option and state.
disease
Action benign (0.75) harmful (0.25)
Do nothing $150,000 $50,000
Improve host resistance $120,000 $80,000
Increase estate $180,000 $60,000

(a) Calculate subjective expected utility (SEU) for each of the three options (four marks)
(b) What is the best option according to the SEU decision criterion? (two mark)
(c) What attitude to risk underpins the maximin decision criterion? What is the best option using
maximin? (three marks)
(d) What attitude to risk underpins the maximax decision criterion? What is the best option using
maximax? (three marks)


Question 8. (eight marks)
Biological surveys for rare and threatened species are usually required prior to development of a site
containing native vegetation. The chance of failing to detect a rare or threatened species depends on how
hard we look.

Let’s say a site looks like good habitat for the threatened Corroboree Frog. Ecologists believe that
Corroboree frogs occur at 25% of sites with good habitat. The frog is difficult to detect. If it is in fact present,
there is a 50% chance of detecting it in any one survey. Three surveys fail to detect the species.

(a) What is the probability that all three surveys will fail to detect the species, if in fact it is present? (three
marks)

The frog is distinctive and cannot be confused with other species. It’s reasonable to assume that the frog is
never recorded as present when in fact it is absent (the false positive rate is zero).

Bayes' rule is given as:


∑ )H(P)H|D(P
)H(P)H|D(P
)D|HPr(
jj
11
1 =

(b) If the frog is recorded as absent in each of three surveys, use Bayes' rule to calculate the posterior
probability that it is in fact present at the site (five marks).
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Question 9. (eight marks)

A cohort study was initiated to examine the effect of exposure to oxalic acid in chocolate on osteoporosis.
There were 5368 people in the cohort exposed to oxalic acid (they regularly ate chocolate). There were
8264 people in the cohort not exposed to chocolate.

The number of cases of osteoporosis in the two cohorts was compared. There were 310 cases in the
exposed cohort and 403 cases in the unexposed cohort.

(a) What is the rate of disease in these two groups? (two marks)
(b) What is the correct measure of effect between exposure and outcome for this study? (two marks)
(c) What is the numerical value of this measure? (two mark)
(d) Interpret this result in one plain language sentence. (two marks)


Question 10. (ten marks)

Demographic stochasticity poses a substantial risk to the viability of a small population of a critically
endangered snail. Define ‘demographic stochasticity’. (2 marks)

The per annum fecundity (f) of each individual in the population is estimated to be 0.4. The per annum
survivorship (s) of each individual is estimated to be 0.7. The current population size (Nt) is 10 individuals.

(a) Using the formula below, calculate the mean expectation for the population size next year. (3 marks).

N t+1 = (f+s)Nt.

(b) A computer simulates demographic stochasticity by drawing random numbers from a uniform
distribution bounded by zero and one. A single iteration of the simulation draws the random numbers
shown in the table below. Assuming again that Nt = 10, calculate the population size next year.
(5 marks).

Individual Fecundity Survivorship
1 0.20 0.76
2 0.56 0.37
3 0.36 0.91
4 0.57 0.46
5 0.15 0.59
6 0.19 0.07
7 0.21 0.26
8 0.33 0.52
9 0.66 1.00
10 0.74 0.94



END OF EXAMINATION



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