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SUPPLMENTAL MATERIALS
INDEX
A. SUMMARY OF PREDICTOR VARIABLES
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Table 1: National predictors of adaptation
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B. CODEBOOK FOR ADAPTATION INITIATIVES INDEX (AII)
C. ADAPTIVE CAPACITY PREDICTOR VARIABLES — CODEBOOK AND SELECTION
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Table 1: Potential predictors of adaptive capacity and adaptation identified in the literature
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Table 2: Categories or elements of adaptive capacity used to guide variable selection and
analysis
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Table 3: Summary of 22 predictor variables long-listed for analysis.
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D. MAPS OF KEY VARIABLES
Figure 1: Maps showing Adaptation Initiatives Index (AII), and Good governance (CPI)
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E. COLINEARITY OF GDP AND POPULATION SIZE
Figure 2: Scatterplot showing collinearity (or covariation) between GDP (log) and Population
size (log) for countries in the dataset
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SUPPLMENTAL MATERIALS A:
SUMMARY OF PREDICTOR VARIABLES
Exposure
Table 1: National predictors of adaptation. Variables selected for final inclusion in multivariate modeling are highlighted.
A description of the variable selection process is provided in Supplemental Materials C.
Indicator
Description
Global Climate Risk
Index
Index analyzes to what extent countries have been affected by the impacts of losses due to extreme weather events
(mortality and financial losses). Exposure to extreme events has been hypothesized as an important stimulant for
public and political support for climate adaptation. High scores reflect nations most impacted. Data were available
for 111 countries from GermanWatch.
Proportion of the population living within 100 km of the coast was included to investigate the impact of high
biophysical exposure to coastal risks on adaptation. Data were available from the Centre for International Earth
Sciences Information Network for all countries.
Coastal exposure (%
population, within 100
km of the coast)
Information & skills
Technology
Economic
resources
Population
Population density
GDP
GDP per capita
Internet users (per 100
people)
Mobile cellular
subscriptions (per 100
people)
Public perception of
climate change risks
Public awareness of
climate change
Literacy rate
Public expenditure on
education as % GDP
Environmental
Sustainability Index:
Treaty Component (72)
Good governance
(Corruption Perceptions
Index)
Institutions
Civil liberties
Political rights
Government
effectiveness
Voice and
accountability
Political stability
Referenc
e Year
19902008
2000
Population was tested to determine whether a statistically significant relationship is found between country size
and adaptation. This is based on previous research 15,16 on primarily high-income countries indicating that large
countries are more likely to be high adaptors. Data were available for all countries (except the Cook Islands) from
the World Bank World Development Indicators. Density based on people per sq km of land area.
GDP and GDP/capita were selected to measure whether there is a statistically significant relationship between
total country income or per capita income and measured adaptation. Economic growth may affect adaptation
through sensitivity to risk and adaptive capacity, impacting countries abilities to absorb climate stress30, and has
been associated with adaptation in Annex-I nations15. Data were available for all countries (except the Cook
Islands) from the World Bank World Development Indicators.
Selected as a systematically collected proxy of technological capacity and infrastructure within a country. Internet
use reflects the extent of social networks and access to information. Data were available for 114 countries from
the World Bank.
Subscriptions per 100 people. Selected as a systematically collected proxy of technological capacity and
infrastructure within a country. Mobile phone use reflects the extent of social networks and connectivity. Data
were available for 114 countries from the World Bank.
2008
Used as a proxy for public attitudes on climate change to assess whether there is a relationship between perceived
levels of risk from climate change and adaptation action at the national level. Data derived from a global survey
about perceived personal threats from climate change. Individuals who responded positively that they knew a
great deal or something about climate change (awareness) were asked whether they feel there is a very or
somewhat serious personal threat from climate change (perception). Percentages are reported of individuals who
answered positively. Data available for 85 countries, missing India, Small Island States, and some countries in
Eastern Europe and Africa.
HDI national literacy rate estimates (>15yrs). Included as a proxy of national educational attainment and
opportunities. Education is hypothesized to reflect capacity for adaptation because of its relation to human capital.
Data were available from all countries except the Cook Islands.
Greater educational expenditure may imply greater commitment to education and development of human capital,
facilitating adaptive capacity within a population. Data available for 85 countries, missing Small Island States,
India, and some countries in Latin America, Eastern Europe, the Middle East and Africa. Source: UNESCO
The Environmental Sustainability Index creates a participation score ranging from 0 (no participation) to 1 (full
participation), based on the level of participation in the UNFCCC and Kyoto Protocol, Vienna Convention and the
accompanying environmental treaties. Points are allocated based on signature, accession, ratification without
signature, ratification with signature, acceptance, approval, or succession. Previous research on primarily highincome countries15 found the ESI was statistically associated with adaptation outcomes in the health sector. Data
were available for 99 countries. Source: Yale Centre for Environmental Law and Policy
Data were available from the 2008 Corruption Perceptions Index from Transparency International. The CPI
measures perceptions of corruption in the public sector. Used as a proxy measure of the quality of national
institutional governance. Scores were available for all countries except Liechtenstein and range from 0 (highly
corrupt) to 10 (no corruption). Data were available from 110 countries.
An evaluation by Freedom House of the national progress on freedom of expression and belief, associational and
organizational rights, rule of law, and personal autonomy and individual rights. Used as a proxy measure of the
quality of national institutional governance. Scores range from 1 (most free) to 7 (least free). Data were available
from all countries except the Cook Islands.
An evaluation by Freedom House of political rights in a nation, based on electoral process, political pluralism and
participation, and functioning of government. Scores range from 1 (high) to 7 (low). Used as a proxy measure of
the quality of national institutional governance. Data were available from all countries except the Cook Islands.
World bank assessment of government effectiveness based on the quality of public and civil services, the degree
of independence from political pressures, the quality of policy formulation and implementation, and the
credibility of government commitment policy commitments. Used as a proxy measure of the quality of national
institutional governance. Scores range from ~-2.5 to +2.5 based on deviation from the average. Data were
available from 113 countries.
World Bank estimate of perceptions of the extent to which a country's citizens are able to participate in selecting
their government, as well as freedom of expression, freedom of association, and a free media. Used as a proxy
measure of the quality of national institutional governance. Scores range from ~-2.5 to +2.5 based on deviation
from the average. Data were available from all countries except the Cook Islands.
World Bank estimate of political stability based on perceptions of the likelihood that the government will be
destabilized or overthrown by unconstitutional or violent means. Used as a proxy measure of the quality of
2007/200
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2008
2008
2008
19992007
2008
2004
2008
2008
2008
2008
2008
2008
2
Rule of law
Environmental
Performance Index
(EPI)
Equity
Inequality (Gini)
national institutional governance. Scores range from ~-2.5 to +2.5 based on deviation from the average. Data were
available from all countries except the Cook Islands.
World Bank estimate of the extent to which agents have confidence in and abide by the rules of society, including
property rights, police, the courts, and crime. Used as a proxy measure of the quality of national institutional
governance. Scores range from ~-2.5 to +2.5 based on deviation from the average. Data were available from all
countries except the Cook Islands.
The EPI reflects a country’s achievement towards its policy targets, and integrates policy measures using 25
indicators in 10 environmental policy categories. Previous research on primarily high-income countries15 found
the EPI was statistically associated with adaptation outcomes in the health sector. EPI ranges from 1-100; with
higher scores implying that nations have made more progress in meeting predefined targets. Source: Yale Centre
for Environmental Law and Policy. Data available for 2010 for 108 countries, but reflect input data from earlier
years.
Measures the distribution of income among individuals within a country, ranging from 0 (complete equality) to
100 (complete inequality). We hypothesized that countries with higher equity would be better able to adapt to
climate risks. Data were available from the HDI for 85 countries, and exclude a number of large countries in
western and northern Europe (e.g. UK, France, Denmark), Japan, Australia, NZ, Small Island States, Saudi
Arabia, and IAE. Variable excluded from multivariate analyses due to low sample size and no bivariate
association with AII.
2008
2010
2008
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SUPPLMENTAL MATERIALS B:
CODEBOOK FOR ADAPTATION INITIATIVES INDEX (AII)
As per Lesnikowski et al.(In press-b)
DATA SOURCE
The vulnerability, impacts, and adaptation chapter of the National Communications was selected as the data
source for this project because to our knowledge it is the only standardized data source available for a large
number of countries across high, medium, and low income countries. Because national governments self-report
progress on treaty implementation to the FCCC Secretariat, the information presented about vulnerability
response and adaptation is here considered representative of government priorities and commitments. Although
these documents cannot be interpreted as complete inventories of adaptation in each country, they do indicate
the nature and depth of adaptation efforts.
Owing to the principal of common but differentiated responsibility enshrined in the FCCC, reporting
obligations differ between Annex I and non-Annex I parties in terms of timeline and content. The following text
summarizes the reporting guidelines for Annex I parties concerning vulnerability assessment, impacts, and
adaptation:
A national communication shall include information on the expected impacts of climate change and a
outline of the action taken to implement Article 4.1(b) and (e) with regard to adaptation. Parties are
encouraged to use the Intergovernmental Panel on Climate Change (IPCC) Technical Guidelines for
Assessing Climate Change Impacts and Adaptations and the United Nations Environment Programme
(UNEP) Handbook on Methods for Climate Change Impacts Assessment and Adaptation Strategies.
Parties may refer, inter alia, to integrated plans for coastal zone management, water resources and
agriculture. Parties may also report on specific results of scientific research in the field of vulnerability
assessment and adaptation.
Annex I parties submit National Communications at the discretion of the COP every 4-5 years; the most recent
NC was the fifth report, submitted by 1 January 2010. All Annex I reports are then subject to an in-depth review
that assesses the parties progress on implementation of its treaty commitments.
Non-Annex I parties submit their first NC within three years of the entry into force of the convention for that
party, or as financial resources become available. The Global Environmental Facility functions as a financial
support body for non-Annex I parties working toward submitting their National Communications. COP11
(2005) set a timeline for the submission of the second, and in some cases of some countries the third,
communication. The following text summarizes the reporting guidelines for non-Annex I parties:
30. Non-Annex I Parties may use appropriate methodologies and guidelines they consider better able to
reflect their national situation for assessing their vulnerability and adaptation to climate change,
provided that these methodologies and guidelines are consistent, transparent and well documented.
31. Non-Annex I Parties are encouraged to use, for the evaluation of adaptation strategies and measures,
appropriate methodologies they consider better able to reflect their national situation, provided that these
methodologies are consistent, transparent and well documented.
32. Non-Annex I Parties are encouraged to provide information on the scope of their vulnerability and
adaptation assessment, including identification of vulnerable areas that are most critical.
33. Non-Annex I Parties are encouraged to include a description of approaches, methodologies and tools
used, including scenarios for the assessment of impacts of, and vulnerability and adaptation to, climate
change, as well as any uncertainties inherent in these methodologies.
34. Non-Annex I Parties are encouraged to provide information on their vulnerability to the impacts of,
and their adaptation to, climate change in key vulnerable areas. Information should include key findings,
and direct and indirect effects arising from climate change, allowing for an integrated analysis of the
country’s vulnerability to climate change.
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35. Non-Annex I Parties are encouraged to provide information on and, to the extent possible, an
evaluation of, strategies and measures for adapting to climate change, in key areas, including those
which are of the highest priority.
36. Where relevant, Parties may report on the use of policy frameworks, such as national adaptation
programmes, plans and policies for developing and implementing adaptation strategies and measures.
Only countries that submitted National Communications between 2008 and July 1 2012 have been included in
the sample. The most recent Annex I NC (the fifth) was submitted over a period of two years between 2008 and
2009; non-Annex I countries were selected to fit this time frame.
Only the chapter on vulnerability, impacts, and adaptation will be used, unless the reader is specifically directed
to adaptation-relevant information in other chapters.
SAMPLE
The follow 117 countries are included in this analysis:
Albania, Algeria, Angola, Antigua and Barbuda, Argentina, Armenia, *Australia, *Austria, Azerbaijan,
Bahrain, *Belarus, *Belgium, Belize, Benin, Bhutan, Bolivia, Bosnia and Herzegovina, Brazil, *Bulgaria,
Burundi, *Canada, Cape Verde, Chile, Colombia, Congo, Cook Islands, Costa Rica, Cote d’Ivoire, *Croatia,
*Czech Republic, Democratic Republic of the Congo, *Denmark, Dominican Republic, Egypt, *Estonia,
*Finland, *France, Gabon, Georgia, *Germany, Ghana, *Greece, Guinea Bissau, *Hungary, *Iceland, India,
Indonesia, Iran, *Ireland, Israel, *Italy, Jamaica, *Japan, Jordan, Kazakhstan, Kyrgyzstan, *Latvia, *Lebanon,
*Liechtenstein, *Lithuania, *Luxembourg, Macedonia, Madagascar, Malawi, Malaysia, Mali, Malta,
Mauritania, Mauritius, Mexico, Moldova,*Monaco, Mongolia, Montenegro, Morocco, Namibia, *Netherlands,
*New Zealand, Niger, *Norway, Panama, Paraguay, Peru, *Poland , *Portugal, Qatar, *Romania, *Russia,
Rwanda, Saint Lucia, Samoa, San Marino, Saudi Arabia, Senegal, Serbia, Singapore, *Slovakia, *Slovenia,
South Africa, *Spain, Swaziland, *Sweden, *Switzerland, Syria, Tajikistan, Thailand, Togo, Tonga,
Turkmenistan, *Ukraine, United Arab Emirates, *United Kingdom, *United States, Uruguay, Uzbekistan,
Vietnam.
*Annex I group
DATA ORGANIZATION AND ANALYSIS
Data collected from the NC will be contained in a Microsoft Access database. Discrete forms will organize data
by individual action according to: i) country, ii) communication number, iii) reporting year, iv) entry title, v)
vulnerability, vi) level(s) of action, vii) type(s) of action.
The result of this is a database in which a discrete entry (meaning a discrete row) constitutes a discrete action.
In other words, 50 rows indicate 50 actions on climate change. A single action (or row) may thus constitute
more than one type of action, or address more than one kind of vulnerability. In the case of some countries, the
report might discuss at length (for example) the findings of a single assessment. Regardless of how much detail
is provided, however, this would be entered into the database as a single action. The benefit of this approach is
that the range of vulnerabilities and kinds of action being addressed and implemented will be documented. The
drawback is that action entries will not capture how much emphasis is being taken on particular kind of risk; a
single entry may capture three vulnerabilities, but will not be able to identify which vulnerability (or
vulnerabilities) is considered particularly critical.
CODEBOOK: Inclusion criteria
To qualify for inclusion in the dataset, information must meet three criteria.
1. Relevancy: Actions must be concerned with impacts of climatic changes, not impacts of general climate
processes (including carbon sequestration or release) or weather, introductory or background statements,
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methodological descriptions, or sectoral trends. The FCCC defines climate change as “a change of
climate which is attributed directly or indirectly to human activity that alters the composition of the
global atmosphere and which is in addition to natural climate variability observed over comparable time
periods.” This differs from the IPCC definition of climate change, which “refers to any change in
climate over time, whether due to natural variability or as a result of human activity.” For this purposes
of this study, the FCCC definition will be used.
Actions must be concerned with adapting to climate change, not mitigating future climate change (i.e.
emissions reduction). This study uses the IPCC definition of adaptation, “actual adjustments, or changes
in decision environments, which might ultimately enhance resilience or reduce vulnerability observed or
expected changes in climate.”
Actions can be concerned with the effect of climate change on any type of system (human, marine,
terrestrial, or riparian) and any type of vulnerability associated with a changing climate. Both positive
and negative impacts of climate change will be included in the dataset. Where climate change is not
specifically identified as a component of risk, only include the action if it can be reasonably inferred that
climate change is taken into account. Exclude general monitoring of temperature, precipitation, extreme
events, etc unless climate change is a clearly related.
2. Minimum level of information:
Information in the NC must allow the coder to identify the Level of
Action at which the initiative is occurring (groundwork, adaptation), and the Type of Action that the
initiative constitutes (climate change scenario, impact / vulnerability assessment, adaptation research,
stakeholder networking, conceptual tool, policy recommendation, legislation, departmental
development, public awareness / outreach, surveillance / monitoring, infrastructure development /
technology, resource transfer / financial mechanism). All other indicators can be marked indeterminate
or none if the information is unclear or not provided, but the action must be classified according to level
and type to be included in the dataset.
Note: Actions discussed in more than one part of the report should only be entered once. Be careful not
to double enter information on the same actions.
Note: Policy recommendations are frequently embedded within descriptions of other actions,
particularly impaction or vulnerability assessments or adaptation research. Pay close attention to where
recommendations are made and enter them separately.
3. Country involvement: Actions must be conducted either exclusively through the reporting country, or in
cooperation with the reporting country. Include actions that are specific to certain regions (e.g. southern
Africa, central Europe). Exclude descriptions of biomes (e.g. alpine) as they can apply in many regions
around the world. Identification of initiatives carried out by other countries will be excluded. In the case
of initiatives implemented by non-government actors, the action must be conducted within the reporting
country. General discusses about global climate change (e.g. global temperature change) should be
excluded. References to previous National Communications should be excluded.
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Peer reviewed / grey literature should be included in the database only if the content of the document is
specifically about that country. If necessary, check article titles in the NC references. If references are
not clearly related to climate change studies then exclude them. General articles about climate change
impacts or adaptation should be eliminated as background information.
CODEBOOK: Note on titling entries
Entries should be consistently titled so that the name of the initiative is clear. The name of the initiative may
include the name of a program, study, document, regulation, project, conference , tool etc.
In cases where there is no clear initiative title, the type of action and /or vulnerability and / or sector can be
substituted for the name of the program (e.g.: Infrastructure development and technology: Floods; Impact and
vulnerability assessment: Food safety and security).
When entering policy recommendations, use the following format:
Policy recommendation: Type of action recommended
In the case of peer reviewed or grey literature, the name of the document can be used in the name of the entry
(e.g. Climate change impacts on water quality in Egypt); if title is unavailable then the author’s names can be
used instead.
In many cases, the sections concerning impacts and vulnerability discuss risk factors without citing external
sources. Sometimes this is because the only impact and vulnerability assessment reported by a country is an
assessment conducted for the purpose of submitting the National Communication. It may also be difficult to
identify which source information was obtained from if it is discussed multiple times and / or consistent
referencing is not followed. In cases where it is not evident where the information was obtained from, create a
single entry for the National Communicated itself and include all miscellaneous information therein. Select all
relevant options for each indicator. This will ensure that the information is captured in the results analysis. Use
the following format for the entry title:
First / second / third / fourth / fifth National Communication: Country name
CODEBOOK: Indicators
Indicators 1 to 4 are intended to provide basic information on the reporting timeline and Annex I and II
participation. Only on option will be selected per indicator. In cases where a communication was submitted in
one year and updated in another (e.g. submitted 2008, updated or edited 2010), select the most recent (updated)
year (e.g. 2010). A text box will be provided under Indicator 4 (Entry title) where all text from the National
Communication used to code the action should be copied and pasted.
1. Country
Open field
2.
One
Communication
Two
number
Three
Four
Five
3. Reporting year 2008
2009
2010
2011
2012
4. Entry title
Open field (+ text box)
Indicator 5 addresses the question “what are we adapting to.” The options listed under this indicator are
derived from the description of vulnerabilities summarized by the Inter-governmental Panel on Climate Change
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in the Fourth Assessment Report. The vulnerabilities capture six broad categories of impacts: biodiversity,
hydrological systems, agriculture, coastal settlements, health, and economy. They include both human and
natural systems, and each can impact different sectors in varying ways. For example, drought may affect the
agricultural sector in terms of crop productivity, but can also impact human health in terms of public safety and
transmission of water-borne illness. Vulnerabilities can be inter-connected; for example, precipitation alone can
affect agricultural productivity, or it can affect agricultural productivity through changing patterns of flooding,
drought, or run-off. This indicator is not mutually exclusive. In cases where multiple vulnerabilities are
addressed through one groundwork or adaptation action, select all relevant vulnerabilities. This will ensure that
a single row corresponds to a discrete action (e.g. 100 rows indicates 100 actions).
5. Vulnerability
Not mutually
exclusive
Sea level rise
Frozen ground
Rainfall
Runoff
Water quality and
quantity
Floods
Drought
Storms
Wildfires
Erosion / land slides
Desertification
Food quality and
Coastal inundation, saline intrusion. Not
defined as a single, extreme event (e.g.
flooding or storms), but rather a creeping
effect of climate change along coastal areas
Changes in snow cover and / or permafrost,
glacial retreat.
Increase in daily precipitation. Can be linked
to flooding, drought, water safety and security.
NOT precipitation measured in climate change
scenarios.
Level of moisture not absorbed by vegetation.
Can be linked to food safety and security.
Affected by changes in precipitation / drought
/ extreme weather (e.g. floods). Increase of
contamination in drinking and recreational
water supply. Including salt water inundation
of fresh water sources, irrigation for crops, and
water management.
Caused by heavy rains, sea level rise. Public
safety hazard, increases risk of water-borne
contamination and infrastructure damage,
population displacement.
Caused by decrease in precipitation / land-use
changes. Decrease in food security and water
security.
More frequent and violent thunderstorms,
winter storms, tropical storms (hurricanes,
cyclones), high winds, and storm surges.
Public safety hazard, population displacement.
Caused by elevated heat and dry conditions.
Public safety hazard, air quality, population
displacement.
Mudslides, avalanches, rock slides, debris
flows. Public safety hazard, population
displacement.
Land degradation in arid, semi-arid, or dry
areas.
Affected by changes in precipitation /drought.
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quantity
Increase in food-borne contamination,
decrease in food availability. Includes crops,
livestock / animal husbandry, and fisheries.
Infectious disease
Changes in transmission patterns of rodent and
vector-borne diseases.
Air quality
Air pollution, including higher levels of
ground-level ozone, airborne dust, particulates,
increased production of pollens and spores by
plants. Eye, nose, throat irritation; exacerbated
asthma or allergy symptoms; chronic
pulmonary disease or respiratory conditions;
increased risk of certain cancers.
Extreme heat
More frequent and severe heat waves. Heatrelated illness and deaths; respiratory and
cardiovascular disorders.
Extreme cold
More frequent and severe cold conditions.
Hypothermia and cold-related deaths;
respiratory and cardiovascular disorders.
Mental health
Psychological impacts resulting from climate
change stress.
Human health (general) Physical health and well-being affected by
climatic changes. Includes respiratory disease.
Marine ecosystem health Loss of species, migration, spread of pests and
wildlife disease in salt water bodies. Including
coral bleaching and ocean acidification, sea
surface temperatures, sea-ice biomes, and
changes in oceanic currents.
Freshwater ecosystem
Loss of species, migration, spread of pests and
health
disease, hydrological systems, and river
shifting.
Terrestrial ecosystem
Loss of species, migration, spread of pests and
health
disease. Including forest system health,
wetlands, bogs, peatlands, NPP (not carbon
sequestration), and general terms like
biodiversity.
Economic
Loss of profitability or viability, or increased
costs in private sectors due to climatic change.
Includes insurance, tourism, agriculture,
forestry, etc.
Electricity /
Loss of power and / or communication due to
telecommunications
extreme weather.
Displacement / conflict
Mass population displacement, violence
resulting from resource scarcity or population
movement
Traditional lifestyles
Loss of cultural traditions, methods of
acquiring and using natural resources
Other (Description field) Vulnerabilities not captured among the options
above. Includes general references to “extreme
weather events” and “climate change” in cases
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Indeterminate
where vulnerabilities are not specified.
Includes UV radiation.
Program described, vulnerability(ies)
addressed not specified.
Variable 6 address the question “how are we adapting.” It distinguishes actions by two levels: groundwork and
adaptation. These levels were developed for this systematic analysis to define a difference between scoping and
preparatory actions, and full adaptation responses. The adaptation category draws on the IPCC definition of
adaptation as “actual adjustments, or changes in decision environments, which might ultimately enhance
resilience or reduce vulnerability observed or expected changes in climate.” This analysis goes beyond this
definition, however to separate actions that have a tangible impact on government services and community
functioning (adaptation), and actions that establish the knowledge base and decision-making structures to design
and implement adaptation (groundwork).
The categories are not mutually exclusive in the sense that a single action can constitute both groundwork and
adaptation (e.g. a government program has an adaptation research department as well as a public awareness
department). This will ensure that a single row corresponds to a discrete action (e.g. 100 rows indicates 100
actions).
Example: National Climate Change Program, country Z
 Research program on developing heat response systems, information campaigns through TV
advertising
o Level of Action: Groundwork; Adaptation
6. Level(s) of
Action
Not mutually
exclusive
Groundwork
Steps taken to prepare for and inform
adaptation responses. Includes climate / impact
and vulnerability / adaptation research,
stakeholder organization and decision-making,
determination of goals and priorities, and
recommendations for action.
Adaptation
Steps taken to increase resilience of
communities to vulnerabilities associated with
climate change. Tangibly alters the delivery of
government services. Includes legislation
action, departmental organization, awareness
programs, monitoring systems, public and
private infrastructure, financial or technical
support, and performance reviews assessing
adaptation effectiveness.
Variable 7 addresses the question “how are we adapting.” It lists types of groundwork and adaptation actions
that constitute responses to vulnerability. The separation between groundwork and adaptation action is similar
to the distinction made in Tompkins et al 2010 between “building adaptive capacity” and “implementation
actions,” but to our knowledge previous adaptation analyses have not created specific categories of steps
necessary to prepare for and inform adaptation and the tangible initiatives that actually increase human
resilience. The typology of groundwork action (climate change scenarios, impact / vulnerability assessments,
adaptation research, stakeholder networking, conceptual tools, and policy recommendations) was developed
based on the type of actions reported in the National Communications. The range of preparatory actions
discussed in the NC have been organized into these six categories and tested against three NC (Jordan, Bhutan,
and Australia) to ensure that the options capture all kinds of actions discussed.
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The adaptation component of this indicator encompasses categories of adaptation types identified in the IPCC
AR4 (physical, technological, investment, regulatory, market- market actions are excluded given that the focus
of this analysis is on public-driven adaptation) and is based on the typology of possible adaptation measures to
manage health risks summarized in the Canadian Assessment of Vulnerabilities and Adaptive Capacity. This
typology was amended to fit adaptations outside the health sector as well. The category “medical interventions”
has been replaced with financial support and resource /information transfers, and department development has
been added to reflect the kinds of responses reported in the NC.
Categories are not mutually exclusive; select as many types of action as describes a single response described in
the report. This will ensure that a single row corresponds to a discrete action (e.g. 100 rows indicates 100
actions).
Example: National Climate Change Program, country
 Research program on developing heat response systems, information campaigns through TV
advertising
o Level of Action: Groundwork; Adaptation
o Type of Action: Adaptation research; Public awareness / outreach
Because policy recommendations can vary considerably in terms of specificity and frequently are repeated
several times with slight modifications or overlap with other sectors, only one entry per type of action
recommended should be entered for each country. For example, Germany may recommend various
infrastructure developments throughout the NC to deal with flood management or extreme storms. Only one
entry for infrastructure should be made however, with all relevant vulnerabilities and sectors selected. This will
avoid the repeated addition of identical or similar entries for policy recommendations. Germany’s list of policy
recommendations would appear like this in the database:
 Groundwork: Policy Recommendation: Infrastructure development / technology
o Vulnerabilities: floods, storms
o Sectors: emergency management, spatial planning
 Groundwork: Policy Recommendation: Regulation
o Vulnerabilities: heat, floods, disease, fires, water
o Sectors: health, spatial planning, forestry, water
 Groundwork: Policy Recommendation: Conceptual tool
o Vulnerabilities: Sea-level rise, heat, drought, terrestrial ecosystems
o Sectors: Spatial planning, environment, health, agriculture
This approach is not intended to provide a detailed list of individual policy recommendations; this would be
impossible since often they are reiterated throughout reports with varying levels of detail. Instead it will allow
us to look at gaps in adaptation action and see if countries have at least progressed on recommending action to
close those gaps.
7. Type(s) of
Groundwork Climate Change
Predictions based on global or regional
level action Scenario
climate models and emissions scenarios on
Action
Not mutually
global or regional climatic change.
exclusive
Typically expressed as change in air
temperature and precipitation.
Impact /
Study of vulnerabilities and / or response
Vulnerability
capacity within national or local context.
Assessment
May also include adaptation research.
Includes scenarios or modeling programs
created to inform adaptation. May include
research about climate change indicators.
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Adaptation
Research
Adaptation
level action
Study of response options based on
vulnerability context. May include impact
/vulnerability assessments. Includes R&D
for adaptation.
Conceptual Tool
Modeling programs or tools (including
data sets, tools created for other purposes
but applied to adaptation studies),
databases of information, strategic
guidelines, plans, frameworks, policy
documents that guide adaptation policy.
Not legally binding- sets goals, objectives,
and priorities. Including vague statements
and concepts (e.g. flood risk management,
drought strategy).
Stakeholder
Networking, information sharing, idea
Networking
sharing among decision-makers,
researchers, civil society, and / or the
public. Includes meetings, workshops, and
conferences.
Policy
Actions described by report authors as
Recommendations something that “should be done.”
(from the NC)
Recommendations are not connected with
a policy document and no indication is
given that these recommendations have
been implemented. Note the type of action
that the recommendation is addressing in
the title of the entry. E.g.: Groundwork:
Policy Recommendation: Infrastructure
development and technology.
Organizational
Creation of government agencies,
Development
departments, working groups, or ministries
with mandates that address climate change
issues. Includes increasing capacity of
existing groups to address climate change.
Implies allocation of government funding.
Regulation
Binding regulations, rules, guidelines,
laws, or statutes. Passed through legislative
bodies or executive powers. Includes
regulations on operating procedures for
agriculture, public utilities, health care, etc.
Includes modification of existing
regulations.
Public Awareness General information campaigns to educate
/ Outreach
communities about the impacts of climate
change and sources of particular
community vulnerability. Also includes
early warning systems that inform
communities of extreme events and
provide information on proper individual
12
Surveillance /
Monitoring
Infrastructure /
Technology /
Innovation
Resource Transfer
/ Financial
Mechanisms
Review
or household response. E.g. heat wave
warning systems, storm warning systems.
These warning systems may (and probably
will) include surveillance and monitoring
systems that inform authorities about when
the public should be notified about
elevated risk (e.g. weather stations that
monitor and predict temperatures, used in
heat warning systems).
Systems for registering vulnerable
populations and tracking weather patterns.
Monitoring systems may be used in
conjunction with public awareness and
outreach programs to notify the public
when elevated risks are detected (e.g. heat
watch warning systems).
Building and construction, infrastructure
projects (e.g. roads, airports, railways),
public works maintenance (e.g. sewage
systems, water treatment), crop technology
(e.g. seed varieties, irrigation projects), and
conservation.
Funding for autonomous adaptation and
research, actions at other jurisdiction levels
(e.g. local initiatives), technology /
information transfers (including support
for domestic autonomous adaptation and
international development / aid). Not just a
description of how much money the
government spends.
Evaluation of how well integrated climate
change perspectives are in existing
programs, measure, etc. Makes
recommendations for how climate change
can be better mainstreamed.
Other (Description field)
N/A
Further Description of Variable 5
The categories available in variable 5 were developed based on the findings of Working Group 2 of the Fourth
Assessment Report of the IPCC. The IPCC organizes its discussion of impacts and vulnerabilities by sector and
by region. The summary tables provided below reflect this approach. The tables present information provided in
two boxes within the Technical Summary, individually identifying future impacts and vulnerabilities. The first
box identifies impacts and vulnerabilities by sector, and the second box identifies impacts and vulnerabilities by
region. The grey column in each table indicates how the impacts and vulnerabilities identified by the IPCC are
coded in variable 5.
13
Note: Mental health is not distinguished from general human health in the IPCC vulnerability summary, but is
specifically addressed frequently enough in the National Communications to warrant its own category.
Box TS.5 Main projected impacts for systems and sectors. Taken from Fourth Assessment Report, Technical
Summary.
Grey indicates vulnerability categories used in the database.
IPCC:
System,
sector
Freshwater
resources
and their
management
Ecosystems
IPCC: Description of vulnerability
Decrease in water volumes in glaciers and
snow cover, reduced water availability
Increase in runoff and water availability in
higher latitudes, decrease in mid-latitudes and
dry tropics
Increase in drought areas, increase in
precipitation and flood risks
Categories of
vulnerabilities
Frozen ground
Water quality / quantity
Runoff
Water quality / quantity
Drought
Rainfall
Floods
Increased flood hazards in river basins
Floods
Decrease in water resources in semi-arid areas Water quality / quantity
Increase in people living in water stressed river Water quality / quantity
basins
Sea level rise increasing salinisation of
Sea level rise
groundwater and estuaries, decrease in fresh
Water quality / quantity
water availability
Decreased groundwater recharge in water
Water quality / quantity
stressed areas
Higher water temperatures, increased
Water quality / quantity
precipitation, and longer periods of low flows
Rainfall
will increase water pollution
Uncertain quantity projections of precipitation, Water quality / quantity
river flows, and water levels
Rainfall
Compromised functioning of water
Water quality / quantity
infrastructure / water management
Negative impacts on freshwater systems
Water quality / quantity
outweigh benefits
Changing runoff patterns, affected by increase Runoff
precipitation variability and shifting water
Rainfall
supply / quality and flood risks
Water quality / quantity
Ecological impacts, species extinction, and
Terrestrial ecosystem
major biome changes in: tundra, boreal forest, health
mountain and Mediterranean-type ecosystems, Marine ecosystem health
mangroves, salt marshes, coral reefs, sea-ice
Freshwater ecosystem
biomes.
health
Initial positive impacts in NPP in savannas and Fire
species-poor deserts, contingent on sustained
Extreme events (Other)
CO2 fertilization and only moderate change in Drought
fire and extreme events (drought)
CO2 excluded (as
component of climate
14
NPP increases in high latitudes (migration of
woody plants), NPP decline in lower latitudes
(ocean, land)
Carbon sequestration by taiga expansion may
be offset by albedo changes, wildfire, forest
loss, methane losses
Tropical sequestration dependant on land-use
change, likely dominated by cc by 2100 in
drier regions
Amazon forests, China’s taiga,
Siberian/Canadian tundra changing, tropical
forests may experience severe biodiversity loss
Low-productivity zones in sub-tropical oceans
like to expand, productive polar sea-ice biomes
likely to contract
Polar species dependent on sea-ice biome
likely to experience habitat degradation and
losses
Loss of coral to bleaching
Accelerated release of carbon from carbon
stocks (peatlands, tundra, permafrost, soil)
Food, fibre
and forest
products
Intensification / expansion of wildfires
Greater rainfall variability likely to affect
inland / coastal wetland species
Surface ocean pH likely to decrease, impairing
shell/exoskeleton formation
Increase cereal crop / pasture yields in mid and
high-latitudes, decreased yields in seasonally
dry and tropical regions
Increased in people at risk of hunger
marginally
Increased frequency / severity of extreme
climate events, increased risk of fire, pests,
disease outbreak
Smallholder and subsistence farmers,
pastoralists, artisanal fisherfolk at risk of
localized impacts
Global food production likely to increase to
3C, then likely to decrease
Forestry production only likely to change
moderately, production will shift to highlatitude regions
Local extinction of particular fish species
Food and forestry trade projected to increase,
system, not an impact)
Terrestrial ecosystem
health
Marine ecosystem health
Excluded (as components
of climate system, not
impacts)
Excluded (as components
of climate system, not
impacts)
Terrestrial ecosystem
health
Marine ecosystem health
Marine ecosystem health
Marine ecosystem health
Excluded (as components
of climate system, not
impacts)
Fires
Freshwater ecosystem
health
Marine ecosystem health
Food quality / quantity
Food quality / quantity
Food quality / quantity
Fires
Food quality / quantity
Food quality / quantity
Food quality / quantity
Food quality / quantity
Marine ecosystem health
Freshwater ecosystem
health
Food quality / quantity
15
greater dependence on food-import in
developing countries
Lower response rate of forests to elevated CO2
Coastal
systems and
low-lying
areas
Industry,
settlement
and society
Health
Increased coastal exposure to cc and sea level
rise
Increased coral bleaching and mortality, harm
to mangroves and salt marshes due to sea level
rise
Increase sea surface temperatures (SST)
resulting in more coral bleaching and mortality
Loss of coastal wetlands, salt marshes, and
mangroves to sea level rise
Increased ocean acidification
Greater risks of coastal flooding due to sea
level rise and increased storm activity
Potential impact can be reduced by adaptation
Key human vulnerabilities in low-lying coastal
systems (deltas, coastal urban areas, small
islands)
Greatest increase in vulnerability likely to be
in the South, South-East, East-Asia, urbanized
coastal locations, small-island regions
Committed to some degree of sea level rise
beyond 2100 because of inertia in the system
Benefits / costs vary widely by location and
scale
Vulnerability greater in coastal / riverine areas,
and areas with economies closely linked to
climate-sensitive resources
Economic impacts will rise with increased
extreme weather activity
Poor communities and households particularly
vulnerable due to limited resource access
Economic costs of extreme weather require
effective economic and financial risk
management
Likely to increase equity concerns and
pressure on government capacity
Urban water systems vulnerability to sea level
rise and reduced water availability
Increased food insecurity leading to
malnutrition, hunger
Coastal flooding resulting in larger mortality
Increase in heat-related mortality
Changing risks patterns of malaria
Excluded (as component of
climate system, not
impacts)
Sea level rise
Marine ecosystem health
Sea level rise
Marine ecosystem health
Sea level rise
Marine ecosystem health
Marine ecosystem health
Floods
Sea level rise
Storms
No impact
No impact
No impact
Sea level rise
No impact
No impact (sector
description)
Economic
Extreme weather events
(Other)
No impact (vulnerable
groups description)
Economic
No impact
Sea level rise
Water quality / quantity
Food quality / quantity
Floods
Extreme heat
Infectious disease
16
Northward expansion of certain vector-borne
disease (e.g lyme disease, tick-borne
encephalitis)
Increase in burden of diarrhoeal disease
Increase in ozone-related mortality /
cardiovascular disease mortality with increases
in air pollution concentrations
Increased risk of dengue
Reduction in cold-related deaths greater than
increase in heat-related deaths
Infectious disease
Food quality / quantity
Water quality / quantity
Air quality
Infectious disease
Extreme cold
Extreme heat
Box TS.6 The main projected impacts for regions. Taken from Fourth Assessment Report, Technical Summary.
Grey indicates vulnerability categories used in the database.
IPCC:
IPCC: Description of vulnerability
Categories of vulnerabilities
Region
Africa
Stresses likely to be greatest where they coFood quality / quantity
occur with multiple stresses (e.g. poor access to
(Health a sector in this case)
resources, food insecurity, poor health systems)
Increase in arid and semi-arid land
Desertification
Declining agricultural yields due to drought and Food quality / quantity
land degradation, especially in marginal areas
Drought
(mixed rain-fed, semi-arid systems)
Desertification
Water stress, runoff increase in East Africa
Water quality / quantity
(possibly floods), decrease in runoff and drought Runoff
in other areas
Floods
Drought
Changes in freshwater NPP affecting food
Food quality / quantity
supplies, possible reduction in fish yields
Species migration, range changes, extinction
Terrestrial ecosystem health
Degradation of mangroves and coral reefs
Marine ecosystem health
Sea level rise affecting coastal communities
Sea level rise
Asia
Loss of mangroves to sea level rise, loss of
Sea level rise
cultivated land to salt marshes
Increased risk of flooding in coastal and
Floods
megadelta regions
Tibetan Plateau glacier disappearance
Frozen ground
Decay of Himalayan glaciers
Frozen ground
Loss of Asian coral reefs
Marine ecosystem health
Increase in population affected by water stress
Water quality / quantity
Availability of freshwater in India will drop,
Water quality / quantity
increased rain and flash floods resulting in
greater proportion of runoff and reduced
proportion of groundwater access
Risk of hunger high as crop yields increase in
Food quality / quantity
East and South-East Asia but decrease in Central
and South Asia
Increased demand for agricultural irrigation in
Food quality / quantity (water
17
Australia,
New
Zealand
Europe
arid and semi-arid regions
Increased frequency of forest fires in northern
Asia
Most vulnerable sectors are natural ecosystems,
water security, coastal communities
Altered ecosystems (invasive species, habitat
loss, ecosystem damage): Great Barrier Reef,
rain forests, alpine areas
Increase water security problems, decline in
runoff and river flows in Murray Darling Basin
Coastal development at risk from sea level rise
and storms
Increased wildfires risk
Risks to infrastructure from extreme weather
events (frequently exceeded design criteria)
Increased energy demand in summer, risk of
black-outs due to increased temperature
Decline in agricultural and forestry production
due to drought and fire; initial benefits in New
Zealand due to increased precipitation
Growth rates of economically important
plantation crops expected to increase
Increase in heat-related mortality for elderly
individuals
Increased risk of extreme winter precipitation in
UK / northern Europe
Increase in annual runoff in northern Europe,
decrease in southern Europe
Increase in river-basin area categorized as
severely water-stressed
Increase in people living in water-stressed
watersheds
Increase in number of people affected by coastal
flooding
Decline in hydropower potential, strong regional
variability
Vulnerability of European flora to extinction
Increased crop production in northern Europe,
decreased production in southern Europe
Increase in forested areas in northern Europe,
decrease in southern Europe, changes in
distribution of tree species increase in forest fire
risk in southern Europe
Amphibian and reptile species likely to expand
range if dispersal range is unlimited
Disappearance of small Alpine glaciers, reduced
volume in large glaciers
Changing summer tourism trends in the
for agricultural production)
Fires
No impact
Marine ecosystem health
Terrestrial ecosystem health
Water quality / quantity
Runoff
Sea level rise
Storms
Fires
Extreme weather events
(Other)
Electricity
Extreme heat
Food quality / quantity
Drought
Fire
Rainfall
Economic
Extreme heat
Storms
Runoff
Water quality / quantity
Water quality / quantity
Floods
Electricity
Terrestrial ecosystem health
Food quality / quantity
Terrestrial ecosystem health
Fires
Terrestrial ecosystem health
Frozen ground
Economic
18
Mediterranean and north
Unlikely shutdown of Meridional Overturning
Circulation but would have huge impact on
crops, cold-related death, winter transport,
economic centers, population migration
Latin
America
North
America
Disappearance of inter-tropical glaciers, reduced
water availability and hydropower generation
Reductions in rainfall leading to severe water
shortages
Increase in people suffering from inadequate
water supplies
Sea level rise and weather extremes like to affect
low-lying areas, buildings and tourism, coastal
morphology, mangroves, availability of drinking
water
Sea surface temperature increases harming coral
reefs and fish stocks
Decrease in soil water leading to replacement of
tropical forest with savannas and semi-arid with
arid vegetation
Increased frequency and intensity of hurricanes
in Caribbean Basin
Rice yields expected to decline, soybean yields
likely to increase
Number of additional people at risk of hunger
likely to increase
Cattle productivity likely to decline
Adaptation initiatives being implemented in
fisheries and agricultural sectors, early warning
flood systems being set up
New institute to mitigate / prevent impacts from
natural hazards
Increased destructiveness of coastal storms and
storm surges will increases losses associated
with sea level rise
Sea level rise and tidal surges / flooding will
affect of coastal infrastructure and transportation
Severe heatwaves will increase in magnitude in
cities where they already occur
Daily average ozone levels projected to increase
in eastern US, especially in most polluted cities
Decreases in snow pack in western mountains,
increase in snow melt, winter rain events,
flooding
Increased demand for water, decrease in water
supplies
Marine ecosystem health
Food quality / quantity
Extreme cold
Economic
Migration / conflict
Frozen ground
Water quality / quantity
Electricity
Rainfall
Water quality / quantity
Water quality / quantity
Sea level rise
Marine ecosystem health
Water quality / quantity
Marine ecosystem health
Desertification
Storms
Food quality / quantity
Food quality / quantity
Food quality / quantity
Food quality / quantity
Floods
Extreme weather events
(Other)
Storms
Sea level rise
Sea level rise
Storms
Floods
Extreme heat
Air quality
Frozen ground
Rainfall
Floods
Water quality / quantity
19
Increased forest production, but greater
sensitivity to drought, storms, insects
Polar
Regions
Increased aggregate crop yields, but big regional
variation
Impacts on forest through pests, diseases, and
fire
Increased coastal wetlands loss due to sea level
rise, decrease in salt-marsh biodiversity
Impacts of climate change likely to be worst for
specific groups / regions like indigenous, the
poor, elderly in cities, those dependent on
narrow resource bases
Need to invest in adaptation based on projected
future conditions, not past experience
Reductions in sea-ice extent, near complete loss
of summer sea ice
Reduced thickness / extent of Arctic glaciers and
ice caps, Greenland ice sheet, Antarctica
Peninsula glaciers and ice sheet
Decrease in northern permafrost
Increase in coastal erosion, changes to
groundwater drainage systems and ecosystem
disruption due to permafrost melting
Spread of forest and tundra, loss of tundra and
polar desert
Decrease in habitat for migratory birds and
mammals (seals, polar bears), changes in species
abundance and distribution
Encroachment of alien species
Reductions in lake and river ice cover, affecting
under-ice habitations, ice-jamming / flooding
Freshwater warming leading to reductions in fish
stocks, productivity / distribution of aquatic
species
Impacts on infrastructure and traditional
indigenous ways of life
Increase in agricultural and forestry productivity,
some benefits and disadvantages to traditional
ways of life
Increase in large-scale forest fires and insect
outbreaks
Reduced winter mortality, cardiovascular /
respiratory deaths
Increased wildlife vulnerability to pests and
diseases like tick-borne encephalitis
Increase in frequency / severity of Arctic
flooding, erosion, drought, permafrost
destruction, public health, water supply,
Terrestrial ecosystem health
Drought
Storms
Food quality / quantity
Terrestrial ecosystem health
Fire
Sea level rise
Marine ecosystem health
No impact
No impact
Frozen ground
Terrestrial ecosystems
Frozen ground
Frozen ground
Terrestrial ecosystem health
Erosion
Frozen ground
Terrestrial ecosystem health
Terrestrial ecosystem health
Marine ecosystem health
Terrestrial ecosystem health
Terrestrial ecosystem health
Freshwater ecosystem health
Traditional lifestyles
Traditional lifestyles
Fires
Terrestrial ecosystem health
Extreme cold
Infectious disease
Floods
Erosion
Drought
20
infrastructure
Small
Islands
Changes in frequency /type/timing of
precipitation increasing contaminant loading in
freshwater systems
Adaptation already occurring through resource
and wildlife management schemes / behavior
Sea level rise and increase sea surface
temperature will accelerate erosion and harm
mangroves and coral reef. Will also have an
effect on desirability as tourist destinations
Port facilities likely to face damage and flooding
due to sea level rise and cyclone intensity
Coastal airports likely to be at risk of inundation,
flooding, and damage from erosion
Arctic islands face accelerated erosion due to
permafrost warming and loss of ground ice
Reduction in rainfall likely to reduce size of
freshwater lens
Increase agricultural economic costs
Invasion of alien species likely to occur in mid
and high latitude islands causing losses to
biodiversity
Increase in disease outbreaks due to vectors and
increasing temperature / decreasing water
availability, as economically harmful
Negative effect on tourism sector, need for
desalinization treatments to offset water
shortages
Adaptation options likely to be limited and very
costly
Adaptation can also be achieved with co-benefits
for sustainable development
Health
Water quality / quantity
Rainfall
Freshwater ecosystem health
No impact
Sea level rise
Marine ecosystem health
Erosion
Economic
Sea level rise
Floods
Storms
Sea level rise
Floods
Erosion
Erosion
Frozen ground
Water quality / quantity
Economic
Terrestrial ecosystem health
Marine ecosystem health
Infectious disease
Water quality / quantity
Economic
Economic
Water quality / quantity
No impact
No impact
21
SUPPLIMENTAL MATERIALS C:
ADAPTIVE CAPACITY PREDICTOR VARIABLES — CODEBOOK AND SELECTION
Methods
We identify variables theorized as predictors of adaptive capacity or adaptation. Variables were selected based on
canvassing the literature on adaptive capacity and vulnerability. While our project examines adaptation actions, it is
appropriate to examine literature on adaptive capacity and vulnerability. First, adaptive capacity is closely related to
adaptation, as adaptive capacity represents potential adaptation (Adger et al., 2004). Second, vulnerability as defined by
the IPCC includes exposure to climate threats, sensitivity to climate impacts, and adaptive capacity. The exposure and
sensitivity components capture whether a country will have to actually adapt to climate change, and therefore influences
adaptation outcomes. Finally, predictors of adaptive capacity and vulnerability are linked. The IPCC definition of
vulnerability includes adaptive capacity; Brooks et al. (2005) subsumed the two categories in their analysis. We also
briefly examined literature on barriers to translating adaptive capacity into adaptation outcomes (Burton et al., 2004a),
which documents similar predictor variables. Variables were relatively saturated. A list of preliminary variables identified
from the literature is summarized in Table 1.
Table 1: Potential predictors of adaptive capacity and adaptation identified in the literature
Variable
Selected references
(Burton et al., 2004b)
 Location/urbanisation
o Rural population density
(Gbetibouo et al., 2010)
o Growth in urban pop’s
(Adger and Vincent, 2005)
o Pop migration
(Burton et al., 2004b)
o Rural population
(Adger et al., 2004)
(Lesnikowski et al., In press-a,
 Population size
Yohe and Tol, 2002, Burton et
al., 2004b)
(Downing et al., 2001, Brooks et
 Resource pressure - population density
al., 2005, Burton et al., 2004b)
(Burton et al., 2004b)
 Age structure
(Adger and Vincent, 2005),
 Dependency ratio
(Downing et al., 2001)
(Downing et al., 2001)
 Completed fertility1
(Burton et al., 2004b)
 Monetary policies
o Market participation – free trade agreements
(Burton et al., 2004b)
o Access to markets
(Bowen et al., 2012)
o Market participation – extent of participation in domestic and
(Burton et al., 2004b)
international markets
o Global interconnectivity – trade balance
(Adger and Vincent, 2005)
o Savings and investment, public and private investment
(Burton et al., 2004b)
o Savings and investment, household savings
(Williamson et al., 2012, Burton
et al., 2004b)
o Savings and investment, genuine savings
(van den Bergh, 2009)
o Economic autonomy – debt repayments % GNI averaged over
(Brooks et al., 2005)
decade
o Macroeconomic stability, access to capital, competitive markets,
(Bowen et al., 2012)
firm performance
o
o Risk spreading through insurance, trade, safety nets, and economic
(Goklany, 2007)
diversification
(Lesnikowski et al., In press-a,
 State support for health and education
1
The number of children born per woman to a cohort of women by the end of their childbearing years.
22
o
o






% budget for social infrastructure (schools and hospitals))
Health expenditure per capita USD PPP
o Public health expenditure % GDP
o Education expenditure % GNP, % gov’t expenditure
Marginalization
o Rate of poverty and extreme poverty
o Human Poverty Index
Collective responsibility, underlying social welfare function – Inequality –
Gini
National wealth
o GDP per capita – USD PPP
o
o
o
Size of economy – total GDP
GNI total PPP
Index of Sustainable Economic Welfare (ISEW)
o
AKA Genuine Progress Indicator (GPI)
o Sustainable Net Benefit Index (SNBI)
Other composites
o Human Development Index (HDI)
o Borda rankings
Agriculture
o Share of agric GDP (Gbetibouo)
o Dependence on agriculture – agricultural employees % total pop,
rural pop % total, agricultural employees % male pop, agricultural
employees % female pop (Brooks)
o Agricultural self-sufficiency – agricultural production index
o Cereal yield (Goklany) / cereal production per capita
o Animal protein consumption per capita
Environmental quality (UNDP, Engle and Lemos2)
o
o Extent of natural resources
o
o
o
o
Expansion/abandonment of agricultural lands, soil degradation or
desertification
Land degradation index
Protected land area %
Forest change rate %/year
o
% forest cover
o
o
Unpopulated land area
Land managed %, fertilizer consumption, SO2 emissions per land
area
Brooks et al., 2005, Burton et al.,
2004b)
(Burton et al., 2004b)
(Brooks et al., 2005) (Goklany,
2007)
(Adger and Vincent, 2005)
(Brooks et al., 2005)
(Adger and Vincent, 2005, Kelly
and Adger, 2000, Burton et al.,
2004b)
(van den Bergh, 2009)
(Yohe and Tol, 2002, Kelly and
Adger, 2000)
(Yohe and Tol, 2002, Goklany,
2007, Burton et al., 2004b)
(Lesnikowski et al., In press-a)
(Brooks et al., 2005)
(Adger et al., 2004, van den
Bergh, 2009)
(Adger et al., 2004, van den
Bergh, 2009)
(van den Bergh, 2009)
(Adger et al., 2004, van den
Bergh, 2009)
(van den Bergh, 2009)
(Brooks et al., 2005)
(Brooks et al., 2005)
(Downing et al., 2001)
(Downing et al., 2001)
(Burton et al., 2004b, Bowen et
al., 2012)
(Burton et al., 2004b)
(Gbetibouo et al., 2010)
(Brooks et al., 2005)
(Brooks et al., 2005, Burton et al.,
2004b)
(Burton et al., 2004b, Brooks et
al., 2005)
(Brooks et al., 2005)
(Downing et al., 2001)
23




Water quality and quantity (UNDP)
o Sustainability of water resources – groundwater recharge per capita,
water resources per capita
o Dependence on natural resources sensitive to water stress and water
availability – % rural pop
o Water Poverty Index (WPI)
Other composites
o Index of Human Insecurity, Environmental Vulnerability Index,
Environmental Sustainability Index, Environmental Performance
Index
 Institutions of global governance – environmental treaty
participation
 Domestic envr governance – World Economic Forum
Survey
Commitment to GHG mitigation – Carbon emission reductions
Governance
o Political / civil liberties
 Influence on political process - Civil liberties, political rights
 Political freedom - Human Freedom Index & Political
Freedom Index
 Freedom of expression
 Protection for minorities and minority viewpoints
o Effectiveness
 Ability to deliver services – Government effectiveness
 Effectiveness of policies – control of corruption
 Global corruption index
 Perception of corruption
 Honest governments
o Stability
 Conflict – internal refugees (1000s) scale by pop
 Willingness to invest in adaptation – political stability
 Willingness to invest in adaptation – rule of law
(Brooks et al., 2005)
(Adger and Vincent, 2005)
(Adger et al., 2004)
(Adger et al., 2004)
(Lesnikowski et al., In press-a)
(Lesnikowski et al., In press-a)
(Lesnikowski et al., In press-a)
(Yohe and Tol, 2002)
(van den Bergh, 2009)
(Engle and Lemos, 2010)
(Goklany, 2007)
(Brooks et al., 2005)
(Brooks et al., 2005)
(Adger and Vincent, 2005)
(Lesnikowski et al., In press-a)
(Goklany, 2007)
(Brooks et al., 2005)
(Brooks et al., 2005)
(Brooks et al., 2005, Goklany,
2007)
o

Decision-making processes
 Participatory decision making – Voice and accountability
Institutions

Institutions to fairly enforce rules of trade

Education – entitlement to information
o Literacy rate

o Proficiency levels on envr sci performance scale
Access to information and knowledge
o Familiarity with existing data on climate change, available data on
climate change, climate change expertise
o Communication and public awareness
o Knowledge development, technical assistance, local research
Social capital

o Share of farmers in farm org’s – proxy for social networks
o State-CSO relations
Cognitive barriers (AR4): attitudes to risk

(Brooks et al., 2005)
(Tompkins and Adger, 2005,
Gupta et al., 2010)
(Goklany, 2007)
(Burton et al., 2004b, Gbetibouo
et al., 2010, Brooks et al., 2005)
(Yohe and Tol, 2002)
(Goklany, 2007)
(Amundsen et al., 2010)
(Burton et al., 2004b)
(Burton et al., 2004b)
(Gbetibouo et al., 2010,
Williamson et al., 2012, Engle
and Lemos, 2010)
(Gbetibouo et al., 2010)
(Engle and Lemos, 2010)
(Tompkins and Adger, 2005)
24


o Individual risk perception
o Public perception of cc risk
Public values
Health
o
General health – Life expectancy at birth
o
o
Burden of ill health – disability adjusted life expectancy
Infant mortality
o
o
Removal of economically active pop – HIV prevalence % adults
Population with access to sanitation
o
o
Healthcare availability – Maternal mortality per 100,000
Access to safe water



Commitment to rural comm’s – rural pop w/o access to safe
water %
o Food security
 General food availability– food production index (annual
change averaged over certain years)
 Nutritional status – Calorific intake
 Access to nutrition – food price index (annual change
averaged over certain years)
 Hunger – food supplies per capita
 Malnutrition
Social networks and access to information –Internet users
Technology
o Fuel used by households (e.g., firewood)
o Housing with electricity
o Presence of modern farming methods
 Irrigation rate

Telephones per 1000 pop  Mobile cellular subscriptions (per 100
people)
o Early warning systems
Infrastructure
o Roads
 Isolation of rural communities – roads (km, scaled by land
area with 99% of pop)
o Rail and air transport, electricity generation, communication, dams,
buildings
o Infrastructure index
R&D
o Commitment and resources for research – R&D investment % GNP
o R&D expenditures
o Capacity to undertake research and understand issues – scientists and
engineers in R&D per million pop
o Endogenous technological development
Technology transfer

Frequency of past events
o


(Engle and Lemos, 2010)
(Lesnikowski et al., In press-a)
(Burch, 2010)
(Burton et al., 2004b, Gbetibouo
et al., 2010)
(Yohe and Tol, 2002, Goklany,
2007)
(Brooks et al., 2005)
(Burton et al., 2004b, Goklany,
2007)
(Brooks et al., 2005)
(Downing et al., 2001, Brooks et
al., 2005, Goklany, 2007, Engle
and Lemos, 2010)
(Brooks et al., 2005)
(Downing et al., 2001, Goklany,
2007, Engle and Lemos, 2010)
(Brooks et al., 2005)
(Burton et al., 2004b)
(Burton et al., 2004b, Brooks et
al., 2005)
(Brooks et al., 2005)
(Brooks et al., 2005)
(Goklany, 2007)
(Goklany, 2007)
(Burton et al., 2004b)
(Burton et al., 2004b)
(Burton et al., 2004b)
(Burton et al., 2004b, Gbetibouo
et al., 2010)
(Adger and Vincent, 2005)
(Engle and Lemos, 2010)
(Burton et al., 2004b)
(Burton et al., 2004b)
(Brooks et al., 2005)
(Burton et al., 2004b, Engle and
Lemos, 2010)
(Gbetibouo et al., 2010)
(Brooks et al., 2005)
(Goklany, 2007)
(Brooks et al., 2005)
(Burton et al., 2004b)
(Engle and Lemos, 2010)
(Gbetibouo et al., 2010)
25





Coastal risk – km coastline (scale by land area with 99% of pop)
Coastal risk – pop w/i 100km of coastline %
o Flood prone pop
Climate mortality risk - # people killed by climate-related disasters per
decade as % of national pop
Vulnerability to natural hazards
o Number people killed by nat disasters 1990-2000 in each country,
normalized with size of pop in 1995 (middle of decade)
o Number people affected (not killed), normalized with pop
o Material damage in USD, normalized with GDP
Disasters Risk Index
(Brooks et al., 2005)
(Brooks et al., 2005)
(Downing et al., 2001)
(Brooks et al., 2005)
(Yohe and Tol, 2002)
(Yohe and Tol, 2002)
(Yohe and Tol, 2002)
(Yohe and Tol, 2002)
(Adger et al., 2004)
A long-list of 22 predictor variables was selected based on 1) depth of support in the literature, with emphasis on
empirically analyzed variables, 2) appropriateness to national-level inference, and 3) availability of data. In selection, we
were guided by the goal of comparing broad theoretical components of adaptive capacity based on Smit and
Pilifosova (2003): Economic resources, Technology, Information & Skills, Social Infrastructure, Institutions, and
Equity, summarized in Table 2. We also include a category for Exposure to reflect predominantly geographic and
biophysical attributes affecting risk exposure. We thus aimed to identify variables reflecting these adaptation components
that would be measurable and comparable at the national level. As such, we excluded composite vulnerability or
development variables such as the Human Development Index (HDI) or the GAIN climate vulnerability index
since these measures aggregate several conceptual processes and preclude comparison and consideration of the
different determinants of adaptive capacity. Mitigation was excluded as related but not relevant to processes of
adaptation. For multiple variables proxying similar processes, we selected the variables with the strongest
theoretical or empirical plausible impact on adaptation. We were unable to identify plausible predictor variables
reflecting social infrastructure that were appropriately measured at the national level. Social infrastructure
processes are likely to occur at scales below the national-level or through mechanisms that are not well tracked
using systematically standardized quantitative measures. The final long-list of 22 variables selected for
preliminary analysis is listed in Table 3.
Table 2: Categories or elements of adaptive capacity used to guide variable selection and analysis
Description from Smit and Pilifosova (2003)
Elements of
adaptive
capacity
Economic
It is widely accepted that wealthy nations are better prepared to bear the costs of adaptation
resources
to climate change impacts and risks than poorer nations, through economic assets, capital
resources, and financial wealth. It is also recognized that poverty is directly related to
vulnerability. Although poverty should not be considered synonymous with vulnerability, it
is an indicator of the ability to cope.
Technology
Lack of technology has the potential to seriously impede a nation's ability to implement
adaptation options by limiting the range of possible responses. Many of the adaptive
strategies identified as possible in the management of climate change directly or indirectly
involve technology (e.g., warning systems, protective structures, crop breeding and
irrigation, settlement and relocation or redesign, flood control measures).
Information & Lack of trained and skilled personnel can limit a nation's ability to implement adaptation
Skills
options. In general, countries with higher levels of stores of human knowledge are considered
to have greater adaptive capacity than developing nations and those in transition. Illiteracy as
well as poverty may be key determinants of low adaptive capacity, implying that it is
important to ensure that systems are in place for the dissemination of climate change and
adaptation information nationally and regionally and that there are forums for discussion and
innovation of adaptation strategies at various levels.
Social
Some researchers regard the adaptive capacity of a system as a function of availability of and
26
infrastructure
Institutions
Equity
access to resources by decision makers, as well as vulnerable subsectors of a population. For
example, the Philippine island of Mindanao uses hydroelectric power to generate more than
90% of its electricity, which in turn supports local development and industry. During El
Niño, drought conditions resulted in suspension of production by the hydroelectric plant and
severely increased the economic vulnerability of the region. In the coastal area of Hong
Kong, the capacity to adapt to the risk of typhoons differs for existing urban areas and for
new coastal land reclamation. For existing urban areas, there is no possibility of retreat or
accommodation, although during urban renewal the formation level of the ground could be
raised, thereby decreasing the vulnerability of settlements.
In general, countries with well-developed social institutions are considered to have greater
adaptive capacity than those with less effective institutional arrangements—commonly,
developing nations and those in transition. The role of inadequate institutional support is
frequently cited in the literature as a hindrance to adaptation. It is generally held that
established institutions in developed countries not only facilitate management of
contemporary climate-related risks but also provide an institutional capacity to help deal with
risks associated with future climate change.
It is frequently argued that adaptive capacity will be greater if social institutions and
arrangements governing the allocation of power and access to resources within a community,
nation, or the globe assure that access to resources is equitably distributed. The extent to
which nations or communities are "entitled" to draw on resources greatly influences their
adaptive capacity and their ability to cope. Some people regard the adaptive capacity of a
system as a function not only of the availability of resources but of access to those resources
by decision makers and vulnerable subsectors of a population.
Table 3: Summary of 22 predictor variables long-listed for analysis, including results of bivariate analyses with our
Adaptation Initiatives Index (AII). Variables highlighted in grey were selected for final inclusion in multivariate
modeling. Justifications for variable inclusion/exclusion are provided.
N.
countries
Mean
(Std Dev)
Correlation with
Adaptation Score
(probability)
Retained?
Comments
-0.20 (0.03)
Log likelihood in
univariate glm
model (outcome:
Adaptation Score)
-318.67
Global Climate Risk
Index
111
88.6 (36.8)
Y
Significant negative correlation
Coastal exposure (%
population, within 100
km of the coast)
116
49.7 (39.3)
0.24 (0.01)
-336.67
Y
Significant positive correlation
Population (log)
Population density (log)
115
115
15.8 (1.9)
4.2 (1.5)
0.22 (0.02)
-0.02 (0.81)
-334.30
-337.13
Y
N
No correlation; absolute population retained
GDP (log)
GDP per capita (log)
115
115
24.7 (2.2)
8.9 (1.6)
0.31 (<0.01)
0.18 (0.06)
-331.23
-335.32
Y
N
Internet users (per 100
people)
Mobile cellular
subscriptions (per 100
people)
Public perception of
climate change risks
114
36 (28)
0.29 (<0.01)
-326.55
Y
Significant positive correlation
114
86 (38)
0.19 (0.04)
-329.52
N
Significant positive correlation, but highly
collinear with internet users (0.73, p<0.01);
internet users retained
85
50 (18)
0.31 (<0.01)
-245.46
Y
Significant positive correlation
In
fo
r
m
ati
on
&
ski
lls
Technol
ogy
Economic
resources
Exposure
Indicator
Significant positive correlation
Significant positive correlation
Marginal correlation; collinear with GDP
(0.52, p<0.01); absolute GDP retained
27
Institutions
Equity
Public awareness of
climate change
85
68 (23)
0.25 (0.02)
-246.98
N
Significant positive correlation, but highly
collinear with perceptions of climate change
risks (0.72, p<0.01); public perception of
risks retained
Literacy rate
115
89 (16)
0.18 (0.06)
-335.36
Y
Public expenditure on
education as % GDP
85
4.75 (1.39)
0.17 (0.13)
-247.52
N
Significant positive correlation; transformed
into binary variable to account for negative
skewing.
No significant correlation or association
Environmental
Sustainability Index:
Treaty Component (72)
Good governance
(Corruption Perceptions
Index)
99
0.71 (0.18)
0.42 (<0.01)
-276.26
Y
Significant positive correlation; correlations
with other institutional variables below 0.70
110
4.6 (2.2)
0.44 (<0.01)
-307.40
Y
Civil liberties
115
2.8
-0.33 (<0.01)
-330.57
N
Political rights
115
3.0
-0.41 (<0.01)
-326.78
N
Government
effectiveness
113
0.25 (0.98)
0.44 (<0.01)
-317.18
N
Voice and
accountability
115
0.15 (1.0)
0.37 (<0.01)
-328.48
N
Significant positive correlation; highly
collinear with all institutional variables;
retained as the institutional variable with
the lowest GLM log likelihood association
with Adaptation Score and high &
consistent collinearity across institutional
variables
Significant positive correlation, but highly
collinear with all institutional variables;
Corruption Perceptions Index retained
Significant positive correlation, but highly
collinear with all institutional variables;
Corruption Perceptions Index retained
Significant positive correlation, but highly
collinear with all institutional variables;
collinearity with Corruption Perceptions
Index 0.95.
Significant positive correlation, but highly
collinear with all institutional variables;
Corruption Perceptions Index retained
Political stability
115
0.14 (0.84)
0.20 (0.03)
-334.74
N
Rule of law
115
0.21 (1.00)
0.39 (<0.01)
-327.75
N
Environmental
Performance Index
(EPI)
Inequality (Gini)
108
61.5 (12.4)
0.20 (0.04)
-311.47
Y
85
39.7 (8.3)
0.08 (0.43)
-247.32
N
Significant positive correlation, but highly
collinear with all institutional variables;
Corruption Perceptions Index retained
Significant positive correlation, but highly
collinear with all institutional variables;
Corruption Perceptions Index retained
Significant positive correlation; correlations
with other institutional variables below 0.70
No significant correlation or association;
Many countries missing from data
Many of our potential predictor variables were collinear, essentially reflecting similar proxies of national
development or wealth. We thus identified a reduced set of variables (shaded grey in Table 3, above) for use in
multivariate regression using bivariate analyses comparing all predictor variables with AII. Variables
significantly correlated with adaptation at p<0.10 were considered for retention. Pairs of variables within
adaptive capacity categories that were strongly correlated with each other (Pearson correlation: p>0.7) were
considered for elimination where the more significant variable (lowest log likelihood) was retained. All
variables were checked for linear relationships with the outcome (AII) and transformed where appropriate.
Variables retained for multivariate regression are highlighted in Table 1. A summary of metrics and
justifications for variable selection is provided in the Supplemental Materials.
References
Adger, WN, Brooks, N, Bentham, G, Agnew, M and Eriksen, S (2004) New indicators of vulnerability and
adaptive capacity. East Anglia, UK: Tyndall Centre for Climate Change Research
Adger, WN and Vincent, K (2005) Uncertainty in adaptive capacity. Comptes Rendus Geoscience 337: 399-410
Amundsen, H, Berglund, F and Westskog, H (2010) Overcoming barriers to climate change adaptation a
question of multilevel governance? Environment and Planning C-Government and Policy 28: 276-289
Bowen, A, Cochrane, S and Fankhauser, S (2012) Climate change, adaptation and economic growth. Climatic
Change 113: 95-106
Brooks, N, Adger, WN and Kelly, PM (2005) The determinants of vulnerability and adaptive capacity at the
national level and the implications for adaptation. Global Environmental Change-Human and Policy
Dimensions 15: 151-163
28
Burch, S (2010) Transforming barriers into enablers of action on climate change: Insights from three municipal
case studies in British Columbia, Canada. Global Environmental Change-Human and Policy
Dimensions 20: 287-297
Burton, I, Malone, E, Huq, S, Lim, B and Spanger-Siegfried, E (2004a) Adaptation policy frameworks for
climate change: developing strategies, policies and measures. In Programme, UND (ed). Cambridge, UK
Burton, I, Malone, E, Huq, S, Lim, Be and Spanger-Siegfried, Ee (2004b) Adaptation policy frameworks for
climate change: developing strategies, policies and measures. In programme, UND (ed). Cambridge, UK
Downing, TE, Butterfield, R, Cohen, S, Huq, S, Moss, R, Rahman, A, Sokona, Y and Stephen, L (2001)
Vulnerability Indices: Climate Change Impacts and Adaptation. UNEP Policy Series. Nairobi, Kenya:
UNEP
Engle, NL and Lemos, MC (2010) Unpacking governance: Building adaptive capacity to climate change of
river basins in Brazil. Global Environmental Change-Human and Policy Dimensions 20: 4-13
Gbetibouo, GA, Ringler, C and Hassan, R (2010) Vulnerability of the South African farming sector to climate
change and variability: An indicator approach. Natural Resources Forum 34: 175-187
Goklany, IM (2007) Integrated strategies to reduce vulnerability and advance adaptation, mitigation, and
sustainable development. Mitigation and Adaptation Strategies for Global Change 12: 775-786
Gupta, J, Termeer, C, Klostermann, J, Meijerink, S, van den Brink, M, Jong, P, Nooteboom, S and Bergsma, E
(2010) The Adaptive Capacity Wheel: a method to assess the inherent characteristics of institutions to
enable the adaptive capacity of society. Environmental Science & Policy 13: 459-471
Kelly, PM and Adger, WN (2000) Theory and practice in assessing vulnerability to climate change and
facilitating adaptation. Climatic Change 47: 325-352
Lesnikowski, A, Ford, J, Berrang-Ford, L, Barrera, M, Berry, P, Henderson, J and Heymann, S (In press-a)
National-level factors affecting likelihood to adapt to the health effects of climate change. Global
Environmental Change
Lesnikowski, A, Ford, JD, Berrang-Ford, L, Barrera, M and Heymann, SJ (In press-b) How are we adapting to
climate change? A global assessment of the state of adaptation. Mitigation and Adaptation Strategies for
Global Change
Smit, B and Pilifosova, O (2003) From adaptation to adaptive capacity and vulnerability reduction. In Smith, J,
Klein, RJT and Huq, S (eds) Climate change, adaptive capacity, and development. (pp 356). London:
Imperial College Press
Tompkins, EL and Adger, WN (2005) Defining response capacity to enhance climate change policy.
Environmental Science & Policy 8: 562-571
van den Bergh, J (2009) The GDP paradox. Journal of Economic Psychology 30: 117-135
Williamson, T, Hesseln, H and Johnston, M (2012) Adaptive capacity deficits and adaptive capacity of
economic systems in climate change vulnerability assessment. Forest Policy and Economics 15: 160166
Yohe, G and Tol, RSJ (2002) Indicators for social and economic coping capacity - moving toward a working
definition of adaptive capacity. Global Environmental Change-Human and Policy Dimensions 12: 25-40
29
SUPPLMENTAL MATERIALS D:
MAPS OF KEY VARIABLES
A)
B)
Figure 1: Maps showing a) Adaptation Initiatives Index (AII), and b) Good governance (CPI), for nations
included in dataset. AII scores range zero to a maximum of 19. CPI values range from a minimum of zero (high
corruption) to a maximum of 10 (low corruption).
30
SUPPLMENTAL MATERIALS E:
COLINEARITY OF GDP AND POPULATION SIZE
26
24
22
Monaco
Liechtenstein
Japan
Germany
FranceKingdom
United
Italy
Russia
Brazil
Spain
Canada
Mexico
Australia
Korea, South (Rep)
Netherlands
Poland
Indonesia
BelgiumSaudi
Switzerland
Sweden
Arabia
Norway
Austria
Denmark
Greece
Iran
Argentina
United
Arab
Emirates
Finland
South
Thailand
Africa
Ireland
Portugal
Colombia
Czech
Republic
Malaysia
Israel
Romania
Chile
Ukraine
Algeria Egypt
Singapore
Hungary
Kazakhstan
New Zealand
Peru
Qatar
Slovakia Angola
MoroccoVietnam
CroatiaBelarus
LuxembourgSlovenia Bulgaria
Syria Republic
LithuaniaAzerbaijan
Dominican
Latvia
Uruguay
Lebanon
Costa &Rica
Ghana
Uzbekistan
Serbia
Montenegro
Estonia Panama
Cote
dÍIvoire
Jordan
Bahrain
Turkmenistan
Bosnia
and
Herzegovina
Iceland
Paraguay
Bolivia
Gabon
Jamaica
Senegal
Albania
Georgia
Congo
(Republic)
Armenia
Congo (Dem Republic)
Macedonia
Mauritius
Madagascar
Namibia
Mali
Malta
Benin
Moldova
Mongolia
Niger
Kyrgyzstan
Tajikistan
Rwanda
Malawi
Mauritania
Togo
Swaziland
India
San Marino
Burundi
Cape Verde
Antigua andBelize
Barbuda
Saint Lucia Bhutan
Guinea Bissau
Samoa
Tonga
20
logGDP
28
30
United States
10
12
14
16
logpop
18
20
Figure 2: Scatterplot showing collinearity (or covariation) between GDP (log) and Population size (log) for
countries in the dataset. GDP and population size are highly collinear (Pearson’s Correlation Co-efficient =
0.73, p<0.01).
31