Transitioning to climate resilient development: Perspectives from

communities in Peru and EcuadorFrank Sperling, Environmental Specialist, AFTS4 (Climate Change Team,

ENV), The World BankWith contributions from: Corinne Valdivia, University of Missouri Columbia, MURoberto Quiroz, Division of Natural Resource Management, The International

Potato Center, CIP

Climate Risk Management• In light of climate change, it is increasingly being

recognized that development processes need to address current and future climate risks if they are to be sustainable

• Communities, characterized by high levels of poverty, limited social, economic and human capital, require an emphasis on the near term-vulnerabilities

• The challenges lie in connecting community level capacity building needs with the right institutional framework, which addresses these near term issues, while also avoiding incentives for adaptation measures which are mal-adaptive in the long-run

TFESSD Project: Adaptation Strategies to the Environmental and Socioeconomic Impacts of El Niño

for Rural Communities in Ecuador and Peru

• Objective: Identify the conditions necessary for improving the adaptive capacity of rural communities in Ecuador and Peru to impacts associated with El Nino events and general climate variability

TTL: Climate Change Team (ENV)Partners:SUM, CICEROPeru: CIP with CIRNMA & ITDGEcuador: ESPOLWorld Bank: add. input from HMU, LAC country offices

Specific Goals

• To better understand the perceptions of communities of their exposure to environmental risks and hazards

• To identify the use and dissemination of information to prepare for climatic risks

• To learn about current coping strategies employed by communities to climatic impacts

• To explore constraining factors and possible opportunities for better addressing climate risks

Peru & Ecuador – Under the spell of ENSO

• The El Niño Southern Oscillation exerts a dominating influence on the climate of much of Peru and Ecuador.

• The recurrent nature of climatic changes associated with El Niño and La Niña events reveal insights into the coping capacity of communities and needs for institutional support

Coastal Ecuador and N-Peru• The climate is

fluctuating between the two modes of ENSO.

• El Niño events are associated with excessive moisture, rainfall and flooding events.

• La Niña events are associated with drier than normal or drought conditions.

Source: Source: RosselRossel/ CAF/ CAF

Monthly Precipitation Averages for Guayaquil for hydrologogical years 1962-2000 and during the evolution of selected El Nino

events (1982/83, 1986/97 and 1997/98)

0.0100.0200.0300.0400.0500.0600.0700.0800.0900.0

1000.01100.01200.0

Jul

Aug

Sep Oct

Nov

Dec Ja

nFe

bM

arA

prM

ay Jun

Jul

Aug

Sep Oct

Nov

Dec Ja

nFe

bM

ay Apr

May Ju

nJu

lA

ug

Sep

tO

ct

Nov

Dec Ja

nFe

bM

arA

prM

ay Jun

Month

Prec

ipita

tion

(mm

)

Monthly Avg.1982-83-841986-87-881997-98-99

Guayaquil, coastal Ecuador

Esparanza, Bajo Piura

Esperanza: Monthly Precpitation for January, February and March, 1960-2000

0.0

50.0

100.0

150.0

200.0

250.0

300.0

350.0

1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005

Year

Prec

pita

tion

(mm

)

JanFebMar

2001 April Non El Niño Year1998 April El Niño Year

1998 April El Niño Year

Piura Piura

Wet and dry conditions in the Altiplano

Dry (often associated with El Nino conditions)

Moist-cool

Subsidence

dry-warm Moist-warm

Wet

90 W 90 W70 W 50 W 70 W 50 W

Adapted from Adapted from GarreaudGarreaud et al. 2003et al. 2003

Example Peru: A multi-hazard environment impacting on development processes

• Focus: PiuraStrong ENSO signal influencesthe regional climate (Nino 1.2 )El Nino: excessive rainfall, floodsNormal/La Nina years: dry or drought

conditions (Coastal Ecuador similar)

• Focus: PunoAltiplano, multi-hazardENSO signal less clear, but El Ninotends to promote droughtconditions. Other hazards include floods, hail,cold spells and snow. Compoundingeffects of multiple hazards

Economic Impacts – Examples1997-98 El Niño:

• Estimated loss of 7.5 billion USD in the Andean countries (ECLAC 2000)

• Loss in Peru: about 4.5 % of GDP (CAF 2001); Impacted sectors: Agriculture, fisheries, infrastructure, transportation, energy

To consider in this context:

• 54.8% of Peru’s people live in poverty• 24.4% in extreme poverty (World Bank 2005)• Poverty is particularly a major challenge in the rural areas of Peru

As many assets are non-monetary, some of the impacts of El Nino are masked in the above assessments, while constituting a real challenge to the livelihoods of the poor and their chanceto escape from poverty.

Institutional Preparedness

There is an increasing national level emphasis on preventive and adaptive measures related to El Nino, climate variability and change.

At the regional level the Centro International de Investigación sobre el Fenómeno del El Niño (CIIFEN)has the task to improve the regional coordination and dissemination of forecasts concerning El Niño.

Approach

Approach• Workshop to agree on application of participatory methods

• Communities were selected in areas under the influence of El Niño and other climate related hazards

• Community assessments carried out in 5 coastal and rural communities in Ecuador, and 4 rural communities in Piura, Northern Peru and 6 rural communities of the Altiplano region of SouthernPeru.

• Participatory approaches are aimed at identifying the i) perceptions of disaster risk and changing climatic conditions, ii) use of official climate information, iii) local and traditional knowledge in preparing for El Niño events, iv) current coping and adaptation strategies, and those required to build adaptation.

• Multi-stakeholders workshops

Piura Piura –– ParticipatoryParticipatory Rural Rural AssessmentAssessment

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TAMBO GRANDE FRIAS

PIURACASTILLA

CATACAOS

CURA MORILA ARENA

LA UNION EL TALLAN

VICE BELLAVISTA DE LA UNION

RINCONADA DE LLICUAR BERNAL

CRISTO NO S VALGA

SECHURA

CHULUCANAS

LA MATANZA

SANTO DOMINGO

CHALACO

SANTA CATALINA DE MOSSA

YAMANGOMORROPONLALAQ UIZ

BUENOS AIRES

SAN JUAN DE BIGOTESALITRAL

CANCHAQUE

SAN MIGUEL DE EL FAIQ UE

HUARMACA

ZONA MARINO COSTERA DE L A B AH IA D

E SECH

URA

OCEANO PA CIFICO

SUBCUENCA SAN FRANCISCO

SUBCUENCA YAPATERA

VALLE BAJO PIURA

ZONA MARINO COSTERABAHIA DE SECHURA

500000

500000

520000

520000

540000

540000

560000

560000

580000

580000

600000

600000

620000

620000

640000

640000 660000 680000

93400009360000

PROG RAMA DE FO RTALECIMIENTO DE CAPACIDADES NACIONALES PARAMANEJAR EL IMPACTO DEL CAMBIO CLIMATICO Y

CONTAMINACION DEL AIRE - PROCLIM

IN TER MEDIATE TEC HNO LOGY D EVELOPMEN T GROUPPROGR AMA DE PR EVENC IO N D E D ESASTRESY GOBER NAB ILIDAD LOCAL

IN G. LU IS POZO AN CH ANTE

PATRO NES DE RIESG OS DE DESASTRE ASOCIADOS CON LOS EFECTOS LOCALESDEL CAMBIO CLIMATICO GLOBAL EN LA REGION PIURA:PROCESOS SOCIALES, VULNERABILIDAD Y ADAPTACION

ZONA 17PROYECCION UTMWG S 84

ESCALA GRAF ICAFECHA: JUNIO 2004

11AREAS DE INTERES DE LA CUENCA DEL RIO PIURA

660000 680000

9340

000

9360

000

9380

000 9380000

9400

000 9400000

9420

000 9420000

9440

000 9440000

9460

000 9460000

9480

000 9480000

N

EW

S

Central SierraCentral Sierra

DryDry ForestForest

Bajo Piura: Bajo Piura: IrrigationIrrigationandand CropsCrops

Caleta Pescadores: Caleta Pescadores: ParachiqueParachique

º

Communities represent the diversity of environmental, populationand productive agroecosystems.

University of Missouri Columbia MUUniversity of Missouri Columbia MU

FisheriesFisheries TownTown ITDGITDG

Lake, CropLivestockDairy Cattle

Mainly CropsSome Livestock

LivestockCrop

Crop Livestock

Lake, Crops and Informal Trade

SouthernSouthern PeruPeru –– ParticipatoryParticipatory Rural Rural AssessmentAssessmentCommunities represent ethnicities, agroecosystem and productive

diversity of Peru’s Altiplano

University of Missouri Columbia MUUniversity of Missouri Columbia MU

ParticipatoryParticipatory WorkshopWorkshop MethodsMethods

Time Line Development

Large Groups

Participatory MappingCommunity ParticipatoryAssessments

Focus Groups

Participatory Assessments

KEY FINDINGS

Climate Events: Impacts in the North

– Floods during El Niño – Floods also during non

Niño heavy rains– Dry and Cold spells of

consecutive years (two, three, or four years)

– Forest fires following Niño years

– Disease outbreaks during Niño Years

– Concerns vary according to location, production activities, technological alternatives

Southern Highlands Rural Communities Southern Highlands Rural Communities

Multiple ShockEventsMultiple ShockEvents

DroughtsFrostsFloodsHailSnow

DroughtsFrostsFloodsHailSnow

Multiple Successive Multiple Successive

YearsYears

FINDINGSFINDINGS

Climate Events: Impacts in the South

– Spatial variability in the presentation of droughts, floods, frosts, and hail events

– Droughts during Niño years– Floods during wet years

from the Lake – Upper respiratory diseases

during cold spells– Concerns vary according to

location, production activities, technological alternatives: loss of animals, loss of crops, raw materials

Perceptions of ChangeExample: Altiplano

Farmers suggest there is change in the timing of the rainy season.

In general, communities in Ecuador, N-Peru and S-Peru have the impression that the environmental conditions around them are changing.

Climatological Averages of Precipitation totals for January, February, March and April in Puno

020406080

100120140160180200

Jan Feb Mar AprMonth

Prec

ipita

tion

(mm

)

1901-1930:1941-1970:1961-1990:1971-2000:1973-2002:

Local environmental knowledge Physical and biological indicators are used to predict:

• Climate (i.e. for planting season)Examples: Brightness of Pleiades abundance of rain (altiplano), Hot Nov & Dec

rainy Feb & March; whirlwinds from N to S instead from S to N rain (coast), location of bird’s nests dry or wet

• Weather (short-term), e.g. extremely dark clouds hail;

While communities display a general awareness of a variety of indicators, explicit knowledge and concrete responses appear limited to few individuals.

However, in the coast, El Nino radio forecasts tend to be compared with environmental conditions usually indicative of the local manifestations of evolving El Nino conditions. If these observations do not align,communities usually do not to trust the radio forecasts (related problem: different understanding / definitions of El Nino)

Coping StrategiesIn the Northern Coast• Selling of livestock• Over-harvesting in dry

forest - deforestation• Collective strategies

during floods• Individual strategies

during droughts• Migration of adult males

and youth to the jungle and the coast

Southern Altiplano• Selling of livestock• Selling of wool and

handcrafts• Stinting on food in the

family• Informal trade• Migration of male adults

and youth • Non market institutions:

access land, seed, labor (social reciprocity relations)

Local/traditional adaptations

• Coastal Ecuador: AlbarradasU-shaped detention ponds build on semi-permeable soil. Turns excessive moisture during El Nino years into advantage by recharging aquifer for dry years.

• Altiplano: Waru warus, q’ochas

Role of Climate Information

Information About El Niño• Awareness and trust in the North• Radio is a trusted source• Official forecasting sources “not

trusted” despite the fact they are the source of the forecasts

• Scale is a constraint in the forecasts for the Altiplano region

• El Niño forecasts listened to in radio in the Altiplano are perceived as “belonging” to the coast

• While there is a connection between El Niño and drought occurrence in the Altiplano, this connection is not realized by the communities because of high variability due to other factors

Local Knowledge Indicators• Local scale biological and physical

indicators in the North and the Altiplano

• Developed an inventory of indicators developed for the south and north

• There are perceptions that climate is changing, difficulties “reading”the indicators

• Local knowledge exists for agriculture and fisheries

• Loss of knowledge among the youth

• Use knowledge differs among the North and the Altiplano

Barriers to AdaptationIn All Communities• Limited understanding and

access to local and regional governance structures

• Progressive loss of assets leading to poverty trap

• Lack of access to credit• Lack of insurance mechanisms• Lack of technological

alternatives• Lack of trust on information of

forecasts• Erosion of social structures

due to migration (local knowledge)

In the Altiplano• Multiple and consecutive

shock events- uncertainty• Lack of knowledge,

understanding, of the hail, frost, and flood events: occurrence and presentation

In the North Coast• Isolation during periods of

drought• Flood relocation conflicts• Long periods of stress during

dry years

Selected Recommendations

• Local Level – Small scale enterprise: building materials and construction of

shelters for livestock– Awareness raising on hazards, and strengthening of local

level organizations and knowledge networks– Local market development, articulation to government social

programs: Milk and children food programs

• Education– Integration of climate risk management in school curricula– Promoting community knowledge, capacities for diversification

opportunities– Skills development for youth in response to push migration

Selected Recommendations-II• Institutional

– Information about employment opportunities to support migration– Connecting existing local and regional institutions to rural communities to

strengthen disaster preparedness, and market opportunities aimed at building asset accumulation, and resilience

– Climate information should be continuous and more event focused building extension systems to promote trust

– Access to credit – Improving access to data for validation

• Research– Validation of biological and physical indicators, and impact of environmental

change on reliability – Merging local and official climate forecasts; Identification of entry points

for dissemination of information– Research on traditional water management systems (i.e. waru waru, albarradas)

and their transferability to other localities– Post-harvest storage for crops– Credit and insurance mechanisms

Next Steps

Linking with institutional efforts• Liaise with on-going efforts, promoting

integrated approaches• Training on climate information needs to engage

institutions in a dialogue process with communities to identify appropriate dissemination formats

• Training efforts should aim to take a comprehensive view to identify effective risk mitigation optionsFeed-back process will provide guidance to

institutions on how to structure information and design practical measures.

Training … addressing information demand for:• natural resource management & agricultural practices

best suited for the climate characteristics of the region (suitable crops, planting techniques, pest management

• markets for local produce• institutional support mechanisms

Note: The training provided needs to be considered as one of the information components utilized by the communities in the communal and individual decision-making processes

Strengthening existing knowledge networks by:

• Providing climate information which is continuous and not solely focused on El Nino years

• Promoting the fusion of local knowledge and scientific climate information in support of communal decision making processes for the planting season

• Increasing the capacity of the government to provide climate risk management measures adapted to local contexts

• Responding to the technology and market training needs identified in the joint process.

Acknowledgements• The presentation is part of a TFESSD supported study Adaptation

Strategies to the Environmental and Socioeconomic Impacts of El Niño for Rural Communities of Ecuador and Peru.

• We are very grateful to the communities that willingly participated in the assessment sharing their knowledge and concerns. Without them this project would not have been possible.

• We acknowledge the contributions of CIRNMA and ITDG in Peru. Especial thanks to Lenkiza Angulo, Roberto Valdivia, and their supporting staff, as well as Jorge Marcos and Pilar Cornejo of ESPOL for conducting the assessments in Ecuador.

• We are also grateful for the input of Liliana Sanchez, Víctor Mares, Jorge de La Cruz, Hugo Li Pun, Martha Huanes and Oscar Hidalgo from CIP.

• The input of Jemima Garcia-Godos, Desmond McNeill (SUM) and Karen O’Brien and Lars Otto Naess (CICERO) on institutional analysis and perspectives on seasonal forecast is gratefully recognized

• Frank Sperling would like to thank Ian Noble (World Bank) for his leadership and advice. The support of Renan Poveda (Peru) and Garbriela Arcos (Ecudador) is greatly appreciated.

Thank you.

Please send comments, recommendations to Frank Sperling

fsperling@worldbank.org