Transcript Slide 1
Vulnerability Assessment
by
Nazim Ali
Senior Research Fellow
Global Change Impact Studies Centre
Islamabad, Pakistan
Vulnerability
“Vulnerability defines the extent to which climate change
may damage or harm a system. It depends not only on a
system’s sensitivity but also on its ability to adapt to new
climatic conditions’ (Watson et al., 1996).”
Vulnerability can not be attributed to only climatic factors
as social and economic factors also play important role
in determine the status of nutrition security of individual
Types of Vulnerability
Social Vulnerability
Economic Vulnerability
Population Growth, Poor Health, Gender Discrimination
Economic Stability, Trade, Investment, Prices, Income
Environmental Vulnerability
Loss of Land, water, production potential
Probability of Being Food Insecure at Different
Income Levels
Probability of being Insecure
0.80
0.70
0.60
0.50
0.40
0.30
0.20
0.10
0.00
2 6 10 14 18 22 26 30 34 38 42 46 50 54 58 62 66 70 74 78 82 86 90 94 98
Income (000)
Probability Function for Household with Different No.
of Members
0.80
Probability of Insecurity
0.70
0.60
0.50
HH4
0.40
HH7
0.30
HH14
0.20
0.10
0.00
2
6
10
14
18
22
26
30
34
Income (000)
38
42
46
50
54
58
Cropped Area with Source of Irrigation
Variables
Tubewell
C+T
Rain
Wheat
72.8
73.5
72.9
Rabi fodder
23.3
20.6
23.5
Rice
41.0
60.2
0.0
4.0
2.7
0.0
23.2
19.9
44.5
187.7
183.6
150.0
3169.5
3109.7
2340.7
Sugarcane
Kharif fodder
Cropping Intensity
Average Yield
Wellbeing
Hypothetical Wellbeing Function
Stressor
Vulnerability Assessment
Vulnerability:
V = f (Sensitivity/ State Relative to Threshhold
V = f ( |dW/dX| / W/Wo)
Exposure:
V . Px . dX
Adaptation:
A = V existing – V modified
Yield (Kg/ha)
Impact of Change in Temperature at
Different Water Stress Levels
5000
4500
4000
3500
3000
2500
2000
1500
1000
500
0
-5.0
-4.0
-3.0
-2.0
-1.0
0.0
1.0
2.0
3.0
4.0
Temprature Change ('C)
Sialkot 2 375
Sialkot 2 550
Sialkot 3 375
Sialkot 3 550
5.0
6.0
Spatial Impact of Change in Temperature at
Different Water Stress Levels
6000
Yield (kg/ha)
5000
4000
3000
2000
1000
0
-6.0
-5.0
-4.0
-3.0
-2.0
-1.0
0.0
1.0
2.0
3.0
4.0
5.0
Temprature Change ('c)
Sheikhup 3 375
Sialkot 2 375
Sialkot 3 375
Sheikhup 2 375
6.0
7.0
Comparative Contribution of Climatic Factors
in Wheat Production
Unstandardized Coefficients
Model
(Constant)
B
Std. Error
-3.496
0.356
LNCO2
0.546
0.036
LNIRRI
0.393
LNGSL
Standardized
Coefficients
t
Sig.
Beta
-9.809
0.000
0.341
15.072
0.000
0.034
0.260
11.483
0.000
1.628
0.056
0.484
28.947
0.000
SDLNGSL-slk
-0.112
0.051
-1.119
-2.188
0.029
SDLIRRI-slk
-0.099
0.048
-0.152
-2.049
0.041
0.628
0.316
1.025
1.985
0.047
LOCAT-slk
Dependent Variable: LNYIELD
Yield skp = 0.0303 × CO20.546 × IRRI0.393 × GSL1.628
Elasticity of Production = 2.566
Yield slk = 0.0568 × CO20.546 × IRRI0.294 × GSL1.516
Elasticity of Production = 2.355
Macro Level Vulnerability Assessment
Sensitivities Category:
Sensitivity
Proxy variables
Proxy for:
Functional Relationship
Food
Sensitivity
>Cereals production/
area
>Protein
consumption /capita.
-Degree of modernization ,access of farmers
to inputs to buffer against climate variability
and change.
-Access of a population to markets and other
mechanisms (e.g consumption shift) for
compensating for shortfalls in production.
-Sensitivity low as production
high
-Sensitivity high as
consumption low
Ecosystem
s Sensitivity
%land Managed
Fertilizer use/
cropland area
Degree of human intrusion in to the natural
landscape and land fragmentation
Nitrogen/ phosphorus loading of ecosystems
and stresses from pollution.
Sensitivity high as % land
managed high 60-100 kg/ha is
optional. X<60 kg/ha,
sensitivity high due to nutrient
deficits and potential cultivation
of adjacent ecosystems.
X>100 kg/ha (caped at 500
kg/ha), sensitivity high due to
increasing runoff.
Water
resources
sensitivity
Renewable supply
and inflow
Water Use
Supply of water from internal renewable
resources and inflow from rivers
Withdrawals to meet current or projected
needs
Sensitivity calculated using
ratio of available water used:
Sensitivity high as water used
high
Human
population
health
sensitivity
Completed fertility
Life expectancy
Composite of conditions that affect human
health including nutrition, exposure to disease
risks, and access to health services
Sensitivity low as fertility low
and life expectancy high
Macro Level Coping Capacity
Coping Capacity Category:
Economic
Capacity
GDP (market)/
Capita Gini Index
Distribution of access to markets,
technology, and other resources useful
for adaptation
Coping capacity high
as GDP/cap high; at
Present GINI held
constant
Human and
Civic
resources
Dependency ratio
Literacy
Social and economic resources available
for adaptation after meeting other present
needs Human capital and adaptability of
labor force
Coping capacity low
as dependency high
Coping capacity high
as literacy high
Renewable
natural
capital
Population
density SO2/
Area %land
unmanaged
Population pressure and stresses on
ecosystems Air quality and other stresses
On ecosystems Landscape fragmentation
and ease of ecosystems migration
Coping capacity low
as density high
Coping capacity low
as SO2high Coping
capacity high as %
unmanaged land high
Basic Linkage System
•Vulnerability is more of less subjective that can not be measured by taking
individual stressor this creates the need for BSL.
•Basic Linkage System (BSL) : A tool for analyzing agricultural policies and
food system prospects in broader setting.
•It should consider
•Broader Food System (National, Regional, International)
•Population
•Land Cover Change
•Agricultural Production
•Demand and Trade
•etc
•Than it would be possible to view this vulnerability in holistic way.
So…..What’s Next?
BSL Model for South Asia?
or
Improvement in Institutional response to
GEC?