2. Overview of Vulnerability
Physical
Changes
Stressors
New system/
environment
Response
System
Social
(Cutter 2003)
3. Vulnerability in Coastal Systems
• Affected by environmental and social
systems that bring various hazards
• Consisted of vulnerable communities
that are at risk from hazard effects
• Vulnerability varies according to
factors inherent to communities
• Exposure to hazards
• Limited mitigation capacity
(USAID 2007)
Knowledge about “factors influencing vulnerability” will support systems
for community adaptation and mitigation
4. In the Philippines, 822 of
the 1502 municipalities are
in coastal zones (55%)
• 60% of 87,000,000 population is in
the coastal areas (in 2005)
• Provides 43% of per capita protein 24 disasters
needs in 2010
(CRED 2010 )
• Employs 1,000,000 people in the
coastal rural areas Potential
threats
• 5% contribution to GDP (2,500,000
metric tons/year )
• Warmer temperature (i.e. 1998 El Nino)
• Economic benefits valued at Study Objective
• Stronger typhoons
US$3,500,000,000 annually
• Overexploitationfactors that affectof
Determine the and poor regulation
Current Situation
coastal communities’ vulnerability
resources (brought by population
increase and competition)
5. Case Study
•5 coastal villages in Baler, Aurora
•Rich in terrestrial and marine
•Threatened by natural hazards
•Poor social conditions
(Manila Observatory 2005)
6. Conceptual and Methodological Framework
Two (2) Composite Index
Frameworks were constructed:
• coastal community
vulnerability index (CCVI);
and
• IPCC- CCVI (based on
IPCC vulnerability
elements)
Composite Index (UNEP 2002)
• a single measure that combines
measures of different situations
(modified from Buckle et al. 2001) • establishes ranking for comparative
analysis useful for vulnerability
assessments
7. The CCVI and IPCC-CCVI Framework
Sub-factor Sub-factor Vulnerability 1. CCVI 2. IPCC-CCVI
Variables Indicators Factors
Frequency and Intensity of
Social Hazards
Occurrence and Effects of V
Social Hazards (2)
Frequency and Intensity of
2. Establish scales for and Effects of
Occurrence Geographical Factors Exposure u
Natural Hazards
Natural Hazards (2)
measuring variablesDependency on
Fish Produced for Food
l
Level of
by the respondent’s for Food (2)
Other Food Production Fisheries
Food Security Factors n
scores
Fish Produced for Income Level of Dependency on Economic and Livelihood
e
Other Income Sources Fisheries for Income (2) Factors r
3. Aggregate scores and
Age, Tenure, Occupation and Demographic Factors a
Social Information (4) Sensitivity
compute for the indices
Household Size
Indices’ values are computed b
Access to Services Importance of Services from
based on scored responses of
Importance of Services Coastal Ecosystems (2)
Environmental Factors i
Institutions with Resourcein a social survey
individuals Policy and Institutional l
Institutions for Natural
Management Initiatives Resource Management (2) Factors i
Participation of Communities Adaptive Capacity
Capital Goods Factors t
y
Natural Capital Financial Capital Physical Capital Human Capital Social Capital
Availability and Access to Credit
1. Assign indicators and
Communication, Work Disruptions Membership and Benefits from
Utilization of Land Facilities variablescaused each of
Transportation and for by Sickness Social Networks
Availability of Livelihood Implements Availability and Access to
Liquefiable Assets
the seven factors Important Information
8. Steps in Data Collection and Analysis
Field Data Collection
The Questionnaire Survey: (August to September 2010)
-Secondary Major Sections Drafting the
Four (4) Data Planning with
Pre-testing of
village leaders
- Sourcing Questionnaire
Household Characteristics and Tenure Questionnaire
and local
-(2months) Use and Access (1month)
Resource Survey Survey (2 days)
academe
- Social and Environmental Trends
No hard data Site Manpower
- Livelihood and Economic Activities
available Selection Limitation
- Composed of component variables that are
scaled from minimum to maximum values
Training of 20
- Example: of
Validation Assessing the frequency of social
Data Analysis Conducting the
local
Information and Presentation actual 182
hazard, Social discrimination enumerators (2
(GIS, SPSS)
(March 2011) Never; 2= Seldom; surveys (4 days)
- Scales: 1= days)
3= Occasional; 4= Often; 5= Very often Time Skill
- Get the Minimum=1; Maximum=5; Limitation Limitation
- Collect all responses to get Average
9. Process for Computing Indices of Variables, Sub-
factors and Factors of Vulnerability
• Sample Computation: Social
Standardization of 82 discrimination in Sabang
Component variable component indices Variable
Scales
n
5= Very Often
Index 4= Often
3= Occasional 47 1.32 1 5 0.08
Computation of the 23 sub- 2=Seldom
factor variable indices 1= Never
Variables Frequency of All Types
of Social Hazards
Human environmental
Computation of the 21 sub- destruction
0.42
factor indices Social conflict 0.34 0.25 0.25
Sub- Social discrimination 0.08
factors Social security 0.16
Computation of the 7 major Sub-factors of Geographical
factors indices Factors
Frequency of Natural Hazards 0.54
Factors Intensity of Natural Hazards 0.90
0.58
Frequency of Social Hazards 0.25
Intensity of Social Hazards 0.62
10. Process for Computing for Vulnerability using CCVI
• Sample Computation: CCVISub-
Sabang
Coastal Community Vulnerability Major Factors
Index (CCVI) is computed based on Major Factors Σ
factors
Σ
the weighted average of all the factors Geographical Factors
Geographical 4
0.58 4 2.32
Factors (GF)
Environmental 2 1.08
Environmental
0.54
Factors 2
Factors (EF)
Food Security Factors
Food Security
0.74 2 1.48
2
Factors (FF)
Economic and Livelihood
Economic and
2
Factors 0.62 2 1.24 11.21
Livelihood
21 0.53
Factors (ELF)
Policy and and Institutional
Policy
Institutional 0.60 2 1.2 2
Factors
Factors (PIF)
Demographic
Demographic Factors
Factors (DF)
0.51 4 2.04 4
Capital Good
Factors (CGF)Good Factors
Capital 0.37 5 1.85 5
12. Correlation of Indices of Major Factors with CCVI
0.70
0.60
Major Factors
Y'= 0.43+0.16x
0.50
Y'=0.03+0.95x
0.40
Y'=0.93-1.11x
0.30
0.20
0.45 0.47 0.49 0.51 0.53 0.55
CCVI
R R2
Geographical Factors 0.96 0.93
Environmental Factors 0.3 0.09
Food Security Factors -0.36 0.13
Economic and Livelihood Factors -0.42 0.18
Policy and Institutional Factors 0.52 0.27
Demographic Factors 0.91 0.83
Capital Good Factors -0.85 0.73
13. Normalized Maps of Factors and CCVI
Geographical Demographic Environmental Food Security
Legend
BalerMunicipalMap
rnnccvi
Value
Max
High : 1
Economic and Livelihood Policy and Institutional Capital Good CCVI
Mapping Software: ArcGIS 9.3.1 Tool: Spatial Analyst Geo-reference coordinate system: WGS 1984
Low : 0
Min Map source: GADM Version 0.8 from http://biogeo.berkeley.edu/gadm/
14. Conclusion
• There were little difference in resulting CCVI among the five (5) coastal communities
(Sabang, with the highest CCVI, is the most vulnerable )
• Food, policy and economic factors have high values that deem to influence vulnerability
of coastal communities the most
• Variation of indices at factor level assume areas of vulnerability for a coastal
community, the factor contributions vary accordingly on the values at the other index
levels
• When there is no hard data source, the method may be effective but only for rapid
appraisal and its strength depends on quality of surveyed data within a specific time
• Focus of future study:
• improve identifying suitable and objective variables and indicators
• create a hybrid method for indexing vulnerability that combines social survey data
with hard information sources
• analysis of relevant of indicators by statistical tools (i.e. principal component
analysis, factor analysis, regression analysis)
• modeling using multi criteria decision analysis of factors (AHP, ANP, game theory)
• Communicate results to local government to encourage robust data collection and
information management system (i.e. fish catch monitoring, satellite data)
