SYSTEMS THINKING
–
AN
ESSENTIAL SKILL FOR
UNDERSTANDING AND
MANAGING COMPLEXITY
Carl Smith
School of Agriculture and Food Science, University of Queensland (UQ)
Macquarie Island
• Situated about 1500 km south-south-east of Tasmania,
about half way between Tasmania and Antarctica
• The main island is approximately 34 km long and 5.5
km wide at its broadest point
• Around 3.5 million seabirds arrive on Macquarie Island
each year to breed and moult
Macquarie Island
Macquarie Island
• Many types of feral animals were introduced to
Macquarie Island in the 19th century, including cats, rabbits, rats and mice.
• Feral cats had a devastating effect on the native
Macquarie Island
• So what do you think happened when the feral cats
were removed? The seabirds were saved, right?
With Cats
Without Cats
Macquarie Island
• What the management plan of Macquarie Island failed
to realise is that cats don’t just eat seabirds, they also eat rabbits, rats and mice
• The eradication of cats caused an explosion in the
rabbit, rat and mice populations on Macquarie Island, the impact of which was just as bad for seabirds as having cats on the island
• This is a classic example of policy resistance (a fix that
failed), which resulted from the failure of managers to understand the system
Rabbit Population Rabbit Births
+
+ Rabbit Birth Rate
+
Rabbit Deaths
-+
Rabbit Death Rate
+
Cat Population Cat Births
+
+ Cat Birth Rate
+
Cat Deaths
-+ Cat Death Rate
+ +
-Cat Cull + Seabird Habitat
Eaten +
R1 B1
R2 B2
B3
Fixes that Fail
–
Macquarie
Island
Seabirds Lost Remove Cats
Rabbit Population Habitat
Destruction
+
-+
+ +
B
R
Delay
The Moral to this Story
(Sterman, 2000, Chapter 1)• “When you are confronted with any complex system that has things about it that you want to fix, you cannot just step in and set about fixing them. You cannot meddle with one part of a complex system without the almost certain risk of setting off disastrous events that you hadn’t counted on in other parts. If you want to fix something, you are first obliged to understand the whole system” (biologist Lewis Thomas, 1974)
The Moral to this Story
• To understand the whole system you have to:
1. Integrate knowledge from different disciplines, i.e. be multidisciplinary
2. Understand how the interactions among system components (system structure) influence system behaviour
3. By understanding the relationship between system structure and behaviour, identify points where you can intervene to influence system behaviour whilst minimising unintended consequences
• Complex system dynamics is determined by
interactions and feedbacks among system components, not by the number of components
• The dynamics of all systems arises from the
interaction of just 2 feedback loops –positive (or
reinforcing) and negative (or balancing)
• Positive feedback loops reinforce or amplify change
while negative feedback loops balance or counteract change
The Relationship between
System Structure and Behaviour
Positive or reinforcing feedback loops Negative or balancing feedback loops
Dynamics of Multiple-Loop Systems
B R Chickens
Eggs CrossingsRoad +
+
+
Out of these common modes of behaviour, which one would best represent the number of people with the flu over the flu season?
Infected Population
Susceptible Population
-Recovered or Dead Population
+ Infection Rate
+
Basic Overshoot and Collapse CLD for
the Flu
Susceptible Population with
Symptoms
Recovered/Dead Population Susceptible people
becoming infected
- +
Infected people starting to show symptoms
- +
Infected people recovering or dying
- +
Disease transfer probability
+
Number of contacts between infected and susceptible people +
Probability of meeting a susceptible person +
Total Population
-+ B1
Total contacts between infected and other people
per day
Total infected population
+ +
Contacts an infected person has with other people per
day Delay time for symptoms to develop
-B2
+ Delay time for symptomatic people to
recover or die
-Population with
Symptoms
Recovered/Dead Population Susceptible people
becoming infected
- +
Infected people starting to show symptoms
- +
Infected people recovering or dying
- +
Disease transfer probability
+
Number of contacts between infected and susceptible people +
Probability of meeting a susceptible person +
Total Population
-+ B1
Total contacts between infected and other people
per day
Total infected population
+ +
Contacts an infected person has with other people per
day Delay time for symptoms to develop
-B2
+ Delay time for symptomatic people to
recover or die
-B3
R2
-B4
Stock and Flow Structure derived
from the CLD
Simulated Behaviour of the System
(Infected population peaks at 17,500 at day 12)Reduce contacts per infected person from
2 to 1 other person per day
(Infected population peaks at 14,500 at day 22)
Reduce chance of disease transfer due to
contact from 50% to 25%
Reduce contacts to 1 person per day and
chance of disease transfer to 25%
(Infected population peaks at 9,500 at day 43)
• Lots!
• The livestock production system contains many
feedback loops that control its dynamics
• We are currently building a simple livestock production
model for Selayar as part of a World Bank and UQ funded project called Capturing Coral Reef and Related Ecosystem Services (CCRES)
What has Systems Thinking got
to do with Livestock Production?
• The system models we are building for CCRES aim to
simulate the interactions between society and coastal ecosystems to understand problems such as fish catch decline, mangrove loss, water pollution and food security
• Some of these interactions are caused by land use
change and land use change is influenced by crop and livestock production, as well as population growth
• The next slide represents some of the feedback loops
within the livestock production system that we are trying to model in Selayar
What has Systems Thinking got
to do with Livestock Production?
Livestock Production Demand for meat and
livestock products
+
Price of meat and livestock products
+
Population growth
+ +
Supply of meat and livestock products
+
-Household income
+
Consumption of land and water for livestock
production
+
Land and water resource available for livestock production
-+
Land and water degradation +
-+ +
-Competition with substitutes and imports
-Consumption of land and
water by population
+
-B5
+
Land and water resources available for population
-Livestock Production Model
Livestock Demand Model
• They essentially model balancing loops within the livestock production system that seek a dynamic equilibrium between consumption, production and price
• They also obey limits to growth, that is, livestock
production cannot exceed the carrying capacity of land and water
• Lets look at a scenario
What do these Models do?
Population grows and reaches
limits to growth
There is no change in the desired
household demand for meat
12:30 PM Wed, 16 Nov 2016
Untitled Page 1
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Weeks
1: Population 2: Houses 3: Urban land area
1
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1 1 1 1
Population growth Total demand for meat
Total livestock production Meat price
2:31 PM Wed, 16 Nov 2016 Untitled
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1
1 1 1
2:31 PM Wed, 16 Nov 2016
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Weeks
1: total desired liv estoc…y by liv estock ty pe[Cattle]2: total f attening liv estock by liv estock ty pe[Cattle]
1
1 1 1
2
2 2 2
Population grows and reaches
limits to growth
12:30 PM Wed, 16 Nov 2016 Untitled
Page 1
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Weeks
1: Population 2: Houses 3: Urban land area
1
Population growth Total demand for meat
Total livestock production Meat price
2:42 PM Wed, 16 Nov 2016 Untitled
Page 1
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Weeks 1: total demand f or meat by liv estock ty pe[Cattle]
1
0.00 250.00 500.00 750.00 1000.00
Weeks
1: total desired liv estoc…y by liv estock ty pe[Cattle]2: total f attening liv estock by liv estock ty pe[Cattle]
1
0.00 250.00 500.00 750.00 1000.00 Weeks 1: actual meat price[Cattle]
1 1 1
1
• When managing any system, understand the
relationship between system structure and system behaviour
• Use multiple sources of knowledge to develop your
understanding, i.e. be multidisciplinary
• Use your understanding of system structure to
carefully target your interventions, otherwise your cure may end up being worse than the disease
• When managing systems there is rarely a silver bullet
solution to problems, therefore multiple interventions may be needed
