locating climate insecurity in africa

8/2/2019 Locating Climate Insecurity in Africa

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This paper is produced as part othe Strauss Centers program onClimate Change and Arican PoliticalStability (CCAPS). The programconducts research in three coreareas, seeking to investigate whereand how climate change posesthreats to stability in Arica, identiystrategies to support accountableand eective governance in Arica,and evaluate the eectiveness ointernational aid to help Aricansocieties adapt to climate change.

Executive Summary

Arica is among the continents most vulnerable to climate change

partly because o geography, and partly because o the low adaptivecapacity o many Arican countries.

Much o the current discussion on Arica, climate change, andsecurity is o limited practical use to policymakers, or multiplereasons: a lack o reliable data, a narrow ocus on conict as the onlysecurity outcome o interest, and insufcient attention to variationsin vulnerability at the sub-national level.

To address those shortcomings, the CCAPS program sought toidentiy which areas in Arica are most vulnerable to climate changeand whyat the most detailed scale possible.

When it comes to prioritizing limited resources, policymakers shouldocus frst on the regions and countries where the eects o climatechange, i poorly managed, could lead to a large number o deathsthat is, areas characterized by not only high physical vulnerabilityto climate hazards, but also dense populations, low household andcommunity resilience, and weak governance.

Parts o the continentsuch as the Democratic Republic o theCongo (DRC), Sudan, and Somaliamay be less physically exposedto climate-related hazards, but more vulnerable due to other actors,such as weak governance and low household and community

resilience. In these regions, support or basic governance capacityand conict resolution is as important as disaster prevention andtargeted assistance or risk reduction such as early warning systems,better building codes, and drought resistant agriculture.

Other parts o the continentsuch as South Arica and the coastalregion o northern Aricahave high physical exposure to climatehazards, but are likely less vulnerable than other regions thanksto more robust social and political resources. Support or thesecountries should come in the orm o inormation-sharing to helpArican leaders mobilize domestic resources most eectively.

Locating cLimate insecurity:

W h e r e a r e t h e m o s t V u L n e r a b L e

P L a c e s i n a r i c a ?

a u t h o r s

Dr. Joshua W. Busby is an AssistantProessor at the LBJ School o PublicAairs and Distinguished Scholarat the Robert S. Strauss Center orInternational Security and Law.

[email protected]

Todd G. Smith is a PhD studentat the LBJ School o Public Aairsand Research Assistant on the

CCAPS program.

[email protected]

Kaiba L. White is a ResearchAssociate on the CCAPS programat the Robert S. Strauss Center orInternational Security and Law.

[email protected]

P o L i c y b r i e n o . 3 J u n e 2 0 1 1

Climate Change

and afriCan

PolitiCal Stability

Program


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2 | s t r a u s s c e n t e r

P o L i c y b r i e n o . 3

the destruction o inrastructure and interruption o

services can trigger such desperation that the populaceresorts to stealing or rioting to secure necessities. These

risks to state control are compounded i citizens exploitthe absence o a security presence to loot or personal

gain. Moreover, disasters may provide ocal pointsaround which government opponents may rally.

Extreme weather events also represent important security

concerns or external actors, with militaries requentlydeployed to provide humanitarian relie. This diversion

o military resources represents an opportunity cost bypreventing troops and equipment rom being deployed

or other purposes.

Third, and perhaps most importantly, climate-related

challenges are not uniormly distributed throughout

Arica. Research announcing that Arica is vulnerableto climate change, or even Ethiopia is vulnerable,without explaining which parts o Ethiopia are particularly

vulnerable and why, is o limited value to the internationalpolicy community. It is o even less use to Aricansthemselves, in helping them prioritize scarce resources.

Decision-makers need research that is evidence-basedand detail-oriented to help them target aid in the most

eective way possible.

With these issues in mind, the Strauss Centers programon Climate Change and Arican Political Stability (CCAPS)

set out to fll the gaps in current research. This studydevelops a model that identifes in detail which parts o

Arica are most vulnerable to climate changeand why.The aim is to provide a specifc, accurate methodology that

will help Arican leaders and international policymakersmanage their resources and deliver adaptation assistance

to the regions that need it most.

Africa: A Continent at Risk

Policymakers and scholars increasingly recognize that

climate change is more than an environmental problem: itconstitutes a security challenge that may be as signifcant

as any aced beore.

This is especially true or Arica, which is understood to beamong the continents most vulnerable to climate change.

Aricas vulnerability is driven partly by geographybythe act that its location and environmental eatures make

it susceptible to climate changes most severe physicaleects. But the continents vulnerability also derives rom

the low adaptive capacity o many Arican countriestheresult o longstanding challenges in countries economies,

healthcare and education systems, inrastructure,and governance.

Yet, even though climate change is widely recognized

as a threat to Arican security and stability, theongoing discussion is requently undercut by several

key limitations.

First, while policy analysts and academics alike haveexamined causal connections between climate change

and conict, and while many reports have assessedcorrelations between the expected eects o climate

changesuch as drought, rainall variation, disasters,and migrationand the onset o violent conict, the

applicability o these models has been limited by a lacko adequate data and mixed conclusions.

Second, experts have struggled to establish a common

defnition o what constitutes a security problem. Somereer to a concept o security that encompasses almost

any harm to human welare, and is consequently toobroad to be o practical use. Others propose an overly

narrow concept o security that ocuses only on violentconict and thus misses important security challenges

other than conict.

This is more than an issue o semantics.

In poor, ragile stateslike many o those in Aricaclimate shocks and swit-onset meteorological hazards

can pose severe threats to domestic security bycompromising a states monopoly o orce within its

borders. In the absence o eective humanitarian relie,

It is not enough to say

Ethiopia is vulnerablewithout explaining whichparts o Ethiopia areparticularly vulnerableand why.


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c c a P s P r o g r a m | 3

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including cyclone winds, oods, wildfres, and droughts.

For chronically arid areas, the study also measures thevariation in rainall to identiy areas that may experience

water stress even i they are not technically experiencingdroughts. The study also includes a measure o low-

elevation coastal zones that may be susceptible to uturesea level rise and higher storm surges. A complete list o

indicators used to assess vulnerability to climate-relatedhazards is included in Appendix A.

PoPulation denSity

This study includes population density as one o the

our key sources o vulnerability. All else being equal,policymakers will be more concerned when climate

change aects large numbers o people. In the evento an extreme weather event, large numbers o people

needing supplies and servicesincluding ood, water,shelter, and medical carecan overwhelm existing

acilities and resources. Additionally, i the eects oclimate change orce rural populations to migrate to

urban areas, the sudden population shit may put urtherstrain on local systems.

houSehold andCommunity reSilienCe

While physical exposure and population density areintegral parts o vulnerability, the impact o climate

change on Arican populations also depends on otheractors. The frst line o deense or many people will be

the resources they have at the household and communitylevel to protect themselves rom physical hazards and

respond in the event o climate-related emergencies likeoods, droughts, or wildfres.

Communities where many people are sick, or lack access

to health care and basic amenities, are likely to be lessresilient than those that are healthier and have greater

access to services. In areas with low levels o literacy andeducation, people may have ewer entrepreneurial skills

to help them avoid or cope with climate hazards.

This study uses a range o indicators measuring health,education, and access to healthcare and daily necessities

to assess vulnerability due to low household andcommunity resilience. See Appendix B or the complete

list o indicators.

From Geography to Governance:Identifying the Sources of

Vulnerability

What makes a place potentially vulnerable to climate

change?

As the literature on vulnerability has demonstrated,

vulnerability to extreme weather events is only partiallya unction o physical exposure. In addition to being

located in areas prone to ooding, drought, or otherhazards, communities may also be marginalized rom

services, inrastructure, and levers o power that mightotherwise help them in times o need. They may lack

adequate public inrastructuresuch as roads, pipedwater, sanitation, and electricityor access to healthcare,

education, and other basic services. These risks may becompounded by a lack o political representation, poor

governance, or a history o violence in the country.

With these actors in mind, this study identifed our mainsources or baskets o vulnerability: (1) physical exposureto climate-related hazards, (2) population density, (3)household and community resilience, and (4) governanceand political violence. These sources o vulnerability aredescribed as baskets since they typically each contain

multiple indicators. Within three o the our baskets,several dierent indicators were identifed that contribute

to that dimension o vulnerability.

PhySiCal exPoSure toClimate-related hazardS

Geographic location makes some countries more

susceptible than others to climate change impacts.Risk actors vary across the continent, as well as within

countries. For example, low-lying coastal areas arevulnerable to permanent or temporary ooding as sea

levels rise.

Because global climate models vary widely in theirprojections o uture local weather patterns or Arica,

the best proxy or uture vulnerability, at this point, ishistorical exposure.

This study draws on data measuring the historical

requency and magnitude o climate-related hazards,


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governanCe and PolitiCal violenCe

Whether individuals experience the worst eects oclimate-related events will partially depend on the

quality o governance in the country in which they live.Government support can help communities prepare

or and adapt to the expected impacts o climatechange. And when extreme weather events do occur,

national governments are oten called to respondsupplementing local communities eorts to save people

rom rising waters, rescue survivors rom rubble, andprovide emergency ood, water, and shelter.

Given these important responsibilities, weak governance

can lead to atal consequences. I governments areunable or unwilling to meet the needs o their citizens,

an otherwise manageable natural phenomenon canbecome a disaster, putting large numbers o people at

risk o death rom starvation, disease, or exposure to theelements. In such societies, disorder and instability mayalso ollow exposure to climate hazards.

A history o violence in a country can also complicate thetask o providing relie supplies.

To assess this dimension o vulnerability, this study

thus uses a range o indicators measuring governmentresponsiveness and eectiveness, political stability,

openness to external assistance, and violence. SeeAppendix C or the complete list o indicators.

Mapping VulnerabilityAcross Africa

Ater collecting data on physical hazards, population

density, household and community resilience, andgovernance and political violence, this study mapped

the impact o these actors across Arica. The compositepicture shows where chronic climate security vulnerabilityis locatedthat is, where these our sources o

vulnerability coalesce.

As Figure 1 shows, Aricas areas o most severe

composite vulnerability include Somalia, Sierra Leone,Guinea, Sudan, and parts o the Democratic Republic othe Congo (DRC).

The Mapping Process

This study identifed our main sources or baskets ovulnerability: (1) physical exposure to climate-relatedhazards, (2) population density, (3) household andcommunity resilience, and (4) governance and political

violence. These sources o vulnerability are describedas baskets since they typically each contain multipleindicators. Within three o the our baskets, severaldierent indicators were identifed that contribute tothat dimension o vulnerability.

Because each o the variables in this model was initiallymeasured using dierent scales, the frst step was tostandardize the values based on their distribution. Allo the variables within a given basket o vulnerabilitywere then summed and mapped to create compositemaps or physical exposure to climate-related hazards,household and community resilience, and governanceand political violence. Population density was mappedindividually and treated as its own basket.

Composite scores or each o the our baskets werethen standardized with values o one through fve,based on quintile rank. The our baskets (physicalexposure to climate-related hazards, population density,household and community resilience, governance andpolitical violence) were then summed together, witheach receiving equal weight, to create a compositevulnerability map. Finally, the composite vulnerabilityscores were classifed into quintiles, or fve parts witha roughly equal area in each, and mapped to create afnal composite vulnerability map (Figure 1). The frst

quintile represents the areas with the lowest vulnerabilityscores and the fth quintile represents the areas withthe highest vulnerability scores.

Each quintile represents the distribution o twentypercent o the observations. Each observation isa pixel, a square on the map o Arica, which can berepresented by a number, meant to represent anunderlying indicator like inant mortality. For example,the twenty percent o pixels with the lowest inantmortality rate go into Quintile 1, the best perormers.The next twenty percent o pixels with the second-bestinant mortality rate go into Quintile 2. The classifcationproceeds until the last twenty percent o observations,

the worst perormers, go into the fth quintile. All oArica is mapped in this ashion, except or unpopulatedareas that are excluded rom analysis.

In the process o creating the composite vulnerabilitymap, the impact o adding each basket was evaluated.Figure 6 shows the value-added o the more complexmap that incorporates social and political indicatorscompared to simpler rameworks based purely onphysical exposure and/or population.


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J u n e 2 0 1 1

Figure 1. The composite picture highlights chronic climate security vulnerability by identiying where these our sources ovulnerability coalesce.


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As Figure 2 illustrates, Somalias most vulnerable areas

are located in and around the capital o Mogadishu andthe ar north. From a policy perspective, assistance

in building basic governance and stability should bethe highest priorities, as little else can be achieved in

their absence.

Tailoring Policy Responses

By examining the sources o vulnerability, this holistic

approach can inorm more fnely-tuned policies andinterventions. Figure 1 highlights our regions o high

overall vulnerability: Somalia, Sierra Leone, Guinea,Sudan, and the DRC.

Somalia has the largest amount o its populated area in the

fth quintile o any country in Arica (nearly 26%), as shown

in Appendix D. While its physical exposure is moderate

rooted mostly in drought and persistently scarce rains, its

particular vulnerability is largely driven by low resilience

and very low levels o governance. Given the continued

absence o a unctioning government, Somalia ranked

among the highest in the composite index in terms o

vulnerabilities in both resilience and governance.

Figure 2. Somalias most vulnerable areas are located in and around the capital o Mogadishu and the ar north. Insecurity in

these areas is driven by all our dimensions o vulnerability, but particularly by low resilience and poor governance.

Mapping vulnerabilityoers evidence-based,detailed analysis to helptarget aid in the mosteective way possible.


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J u n e 2 0 1 1

Figure 4. Poor governance and high physical exposureprimarily rom

drought, persistent scarce rains, and wildresare the main drivers oclimate vulnerability in Sudan.

The West Arican countries o Sierra

Leone and Guinea are particularlyvulnerable to climate security concerns.

Figure 3 shows that overall vulnerabilityin Sierra Leone and Guinea is driven by all

our sources o vulnerability. More than10.6% o Sierra Leones populated area

is located in the fth most vulnerablequintile, while 4.7% o Guineas area is

located in the fth quintile o compositevulnerability. Their high physical

vulnerability is largely a product owildfres, droughts, and, in the case

o Sierra Leone, low-elevation coastalzones. Their low resilience stems romlow educational attainment, poor access

to clean water, and limited availability o

health care.

While all our sources o vulnerabilitycontributed to severe vulnerability inSierra Leone and Guinea, high population

density and low resilience were narrowlythe most important sources o both

countries areas o highest vulnerability,as shown in Appendix D. In both

countries, priority assistance shouldinclude investments in health to improve

local community resilience.

Southern Sudan, having voted orindependence in 2011, may fnd itsel

acing intense challenges associated withclimate change. In pre-partition Sudan,

8.5% o the populated areas were in thefth quintile o composite vulnerability.

Figure 4 shows that poor governanceand high physical exposureprimarily

rom drought, persistent scarce rains,and wildfreswere the main drivers o

Sudans vulnerability.

As Southern Sudans new governmentfnds its ooting, donors can prioritize

investments in early warning systems,fre protection, rainwater collection, and

other capacity-building measures thatprotect against water scarcity.

Figure 3. Vulnerability in Sierra Leone and Guinea is drivenby all our sources o vulnerability, but particularly high

population density and low resilience.


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Figure 5. Vulnerability in the DRC is driven principally by low household and community resilience and poor governance.

Other pockets o high vulnerability exist in Burundi,

Eritrea, Ethiopia, Angola, and Niger, where low scores onhuman development coincide with poor governance and

considerable climate hazard risks rom droughts, scarcerain, and wildfres.

As Appendix D depicts, most o these countriesexperienced a number o disasters in recent decades.

Finally, the DRC had more than 24% o its populated areas

in the fth quintile o vulnerability, with high vulnerabilitydriven principally by low household and community

resilience and poor governance. In terms o physicalexposure, the DRC was particularly drought prone in the

last two decades in the North and especially fre prone inthe South (see Figure 5).

As with Somalia, high-priority policy areas or the DRC

include a continued ocus on bringing an end to conictand improving basic governance capacity.


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J u n e 2 0 1 1

Assessing the Findings

The value-added o this more complex portrait o

vulnerability becomes clear when the contributionso all our sources o vulnerability (physical exposure,

population density, resilience, and governance) arecompared to just two sources (physical exposure and

population density). In Figure 6, researchers subtract thefrst two sources o vulnerabilityphysical exposure and

population densityrom the composite map shown inFigure 1. This new map in Figure 6 highlights the places

on the continent that become more (or less) vulnerablewhen measures o household and community resilience,

and governance and political violence, are included inthe overall analysis.

As Figure 6 shows, South Arica and the Mediterranean

coastline appear ar less vulnerable when measures o

resilience and governance are considered, whereas partso Niger, Sudan, and Somalia appear ar more vulnerable,

given their low levels o resilience and poor governance.

The assumption o additive, equally weighted baskets

is clearly a convenience and simplifcation. However,absent compelling reasons to change the weights, theequal weight assumption is common among composite

indices. Nevertheless, this study assessed the stability othe composite map by altering the weights. To the extent

that some areas remain in the top quintile o vulnerabilityacross multiple specifcations, these areas constitute

important regions o concern.

Figure 7 depicts our alternative weighting schemesand demonstrates that the countries and sub-regions o

concern remain consistent across various model weights.

Figure 6. South Arica andthe Mediterranean coastlineappear ar less vulnerable when

measures o resilience andgovernance are considered,

whereas parts o Niger, Sudan,and Somalia appear ar morevulnerable, given their low

levels o resilience and poorgovernance.


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1 0 | s t r a u s s c e n t e r


resolution may be equally important or a countrys ability

to address climate-related challenges.

Second, a number o countries in northern and southernArica may be more physically vulnerable to climate

change than others but possess more capacity at thehousehold and governance levels to cope with these

problems. Support or these countries should includemore inormation-sharing to help them address their

physical vulnerabilities largely through mobilization otheir own internal resources.

Third, more ocus should be placed on developing

systems or tracking weather patterns in Arica. Modelsand projections o uture climate risks in Arica have not

converged on a consensus about the expected eectsor much o the continent. Support or basic weather

monitoring, as well as more sophisticated climatemodeling, is essential.

Policy Implications

Analyzing sub-national climate security vulnerability

can help Arican and international policymakers identiy

potential trouble spots on the continent, and ocus

research, attention, and distribution o resources. Three

main policy implications emerge rom this mapping eort.

First, resources and attention should be directed to

the areas and countries where modest to high physicalvulnerability to climate change is likely to be most

damaging due to weak governance and low householdand community resilience. Unortunately, the countries

most in need o climate adaptation assistanceSomalia,Southern Sudan, the DRC, Sierra Leone, and Guinea

tend to have the lowest governance capacity to ensurethat the unds are spent well. While assistance or

disaster prevention and risk reduction is essential, supportor building basic government capacity and conict

Figure 7. Analysis usingdierent weighting schemes

highlights the parts o Aricathat remain in the top quintileo vulnerability across multiple

specications.

Data Sources: World Bank GocernanceIndicators; Polity IV Project; Political RegimeCharacteristics and Transitions; KOF Indexo Globalization; Armed Confict Locationand Event Data (ACLED); World HealthOrganization World Development Indicators;Food and Agriculture Organization o theUnited Nations Food Security Statistics;UNISEF Multiple Indicator Cluster Survey(MICS); Demographic and Health Surveys;UNEP/GRID-Europe; Global PrecipitationClimatology Center; DEM rom USGS;LandScan; CIESIN

Map Author: Kaiba White (2011)


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c c a P s P r o g r a m | 1 1

J u n e 2 0 1 1

hzd tp (w) D s y D ud

Cyclone Winds (.16) UNEP/GRID-Europe 1975-2007

Floods (.16) UNEP/GRID-Europe 1999-2007

Wildfres (.16) UNEP/GRID-Europe 1997-2008

Aridity (Coefcient o Variation) (.16) UNEP/GRID-Europe 1951-2004

Droughts (.16) Global Precipitation Climatology Center 1980-2004

Inundation (Coastal elevation) (.16) USGS DEM 1996

aPPendix a. ics us assss Psc eps C-r hs

aPPendix b. ics us assss hs C rsc

aPPendix C. ics us assss gc Pc vc

Vl (w) id (w) s y D ud

Education(.25)

Literacy rate, adult total (% o people ages 15 andabove) (.125)

World Development Indicators 2008; 2007 or Burkina Faso; 2006 or Algeria, Egypt,Mali and Senegal; 2005 or Niger; no data or Djibouti,Republic o the Congo, or Somalia

School enrol lment, primary (% gross) ( .125) World Development Indicators 2006-2009; 2004 or Gabon

Health(.25)

Inant mortality rate adjusted to national 2000UNICEF rate (.125)

CIESIN 1991-2003

Lie expectancy at birth (years) both sexes (.125) World Development Indicators 2008

DailyNecessities(.25)

Percentage o children underweight (more than twostandard deviations below the mean weight-or-agescore o the NCHS/CDC/WHO international reerencepopulation) (.125)

CIESIN 1991-2003

Population with sustainable access to improveddrinking water sources total (%) (.125)

USAID Demographic & HealthSurveys; UNICEF MultipleIndicator Cluster Surveys; WorldDevelopment Indicators

DHS 2000-2008; MICS 2005-2006; WDI 2008 orAlgeria, Botswana, Cape Verde, Comoros, Eritrea,Mauritius, and Tunisia; WDI 2005 or Equatorial Guinea;WDI 2000 or Libya

Access to Healthcare(.25)

Health expenditure per capita (current US$) (.125) World Development Indicators 2007; 2005 or Zimbabwe; no data or Somalia

Nursing and midwiery personnel density (per 10,000population) (.125)

World Development Indicators 2004-2008; 2003 or Lesotho; 2002 or Kenya

a P P e n D i c e s

Vl id (w) s y D ud

Government Responsiveness Voice and Accountability (.2) World Governance Indicators 2007, 2008, 2009

Government Response Capacity Government Eectiveness (.2) World Governance Indicators 2007, 2008, 2009

Openness to External Assistance Globalization Index (.2) KOF Index o Globalization 2009

Political Stability

Polity Variance (.1) Polity IV Project 1999-2008

Number o Stable Years(as o 2008) (.1)

Polity IV Project 1855-2008

Presence o ViolenceBattles and Violence AgainstCivilians (.2)

Armed Conict Location and EventsDataset (ACLED)

1997-2009

aPPendix d. as hs v

c % c Vll Ql tl % Pplda

Ql

# cl-rldcreD D

1995-2008cl-rldhzd ep

PplD

hld dc rl

gvd Vl

Angola 28.12 27.08 24.17 20.63 100 2.30 20

Burundi 25.42 30.55 24.32 19.72 100 14.85 23

DRC 21.99 23.05 25.20 29.76 100 24.15 18

Eritrea 22.10 29.38 24.77 23.75 100 5.92 4

Ethiopia 25.75 28.66 29.41 16.17 100 2.60 42

Guinea 23.04 27.72 26.43 22.81 100 4.73 7

Niger 14.24 30.56 31.10 24.11 100 0.47 13

Sierra Leone 22.12 28.67 24.77 24.44 100 10.65 5

Somalia 19.13 21.34 30.00 29.52 100 25.84 26

Sudan 27.26 23.67 18.58 30.48 100 8.53 25


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8 Alejandro Quiroz Flores and Alastair Smith, Surviving Disasters, unpublished manuscript (New York: New York

University, 2010). Available rom http://politics.as.nyu.edu/docs/IO/14714/Surviving_Disasters.pd.9 Joshua Busby, Who Cares About the Weather? Climate Change and U.S. National Security, Security Studies17, 3 (2008): 468-504.; Nigel Purvis and Josh Busby, The Security Implications o Climate Change or the UNSystem (Washington: Woodrow Wilson Center, 2004). Available rom www.wilsoncenter.org/topics/pubs/ecspr10_un-purbus.pd.; Joshua Busby, Climate Change and National Security: An Agenda or Action (New York: Councilon Foreign Relations, 2007).

10 The CCAPS program was initiated in June 2009, and development o this vulnerability assessment modelrepresents the frst eort at combined GIS-based sub-national climate security maps, using existing data sources.Other members o the CCAPS team are coding new data: team member Clionadh Raleigh has developedthe Armed Conict and Location Event Data (ACLED); team members Idean Salehyan and Cullen Hendrix arecoding data on a range o social conict events in their new Social Conict in Arica Database (SCAD); andteam members Catherine Weaver, J. Timmons Roberts, and Michael Tierney are geo-coding climate adaptationprojects under a collaboration between CCAPS and AidData.org.

11 The map o sub-national climate security vulnerability o Arica presented here updates an earlier version othis model rom all 2010 by including several new data sources and indicators including: (1) a new data sourceon droughts; (2) a new indicator or areas with chronic low rainall; (3) a new sub-national indicator o accessto improved water sources; (4) a new indicator or sub-national violence; (5) revised metrics o government

eectiveness and voice and accountability which reect a 3-year weighted average; and (6) an alternate, morefne-grained indicator o population density. The original model can be ound in: Joshua W. Busby et al.,Locating Climate Insecurity: Where Are the Most Vulnerable Places in Arica?(Austin: Robert S. Strauss Center orInternational Security and Law, 2010).

12 Basher and Briceo, Climate Change and Arica, 276.

13 The CCAPS research team is collaborating with climate modelers rom the Jackson School o Geosciences atthe University o Texas at Austin to produce mid 21st century regional climate projections or Arica. With morenarrow resolution and a nearer-term time horizon, this regional model is likely to have more applicability in policyplanning than the current global climate models. In the meantime, the frst point o departure is identiying whichplaces are historically most vulnerable to climate-related hazards.

14 The population density indicator utilized the LandScan (2008)TM High Resolution global Population DataSet copyrighted by UT-Battelle, LLC, operator o Oak Ridge National Laboratory under Contract No. DE-AC05-00OR22725 with the United States Department o Energy.

15 Two other climate vulnerability indices are available rom Maplecrot and One World Trust. However, theirchoice o indicator weights does not appear to have a strong empirical oundation. See www.maplecrot.com/themes/cc. Rob Davies and Stephanie Midgley, Health and Food Security Risk Prole Mapping in Southern Arica(Cape Town: One World Sustainable Investments, 2009).

locating climate insecurity in africa

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