Colombia towards climate-smartnessAndy JarvisFlagship Leader for Climate Smart Agriculture (CCAFS)Research Area Director, Decision and Policy Analysis (CIAT)

Colombia – Senegal ExchangeCauca, Colombia

¿What is CCAFS?

CCAFS brings together the world's best researchers in agricultural science, climate science, environmental and

social sciences to identify and address the most important interactions, synergies and trade-offs between climate

change and agriculture.

Alliance

Quesungual Agroforestry System, Honduras

Andy Jarvis, Andy Challinor

Jim Hansen

Lini Wollemberg

Phil Thornton

Research Flagships

What is Climate-Smart Agriculture (CSA)?

CSA in Colombia – National context

Economic Relevance of Agriculture

People and Agriculture

GHG Emissions Agriculture GHG Emissions

CSA in Colombia – National context

Source: Agronet & CRU (http://badc.nerc.ac.uk/data/cru/)

Climate and agriculture: hand in hand

T-Max

T-Max

YieldYield

Rice crop

Neutral years

Tiempo térmico=2627°CicloT. Max=31°CT. Min=19.3°CEvapotranspiración=712Precipitación total=532mm + riego

Tiempo térmico=2596°CicloT. Max=32°CT. Min=19.3°CEvapotranspiración=714Precipitación total=635mm + riego

DK7088

P30F32

P30K73

FNC3056

FNC3059

FNC514

02468

10

Genotipo

Ren

dim

ient

o To

n/H

a

DK7088

P30F32

P30K73

FNC3056

FNC3059

FNC514

02468

10

Genotipo

Ren

dim

ient

o To

n/H

a

Maize – Buga(Valle del Cauca)

Location

Tolim

a

Cas

anar

e

Met

a

Cór

doba

Hui

la

(160)

(140)

(120)

(100)

(80)

(60)

(40)

(20)

-

Mill

ones

de

USD

$

Total: USD$ 427 millones al año

Sin cambiar el manejo

What is at stake for not understanding climate

Rice crop

CIAT/CCAFS-MADR Agreement

1.Avoid crop losses due to climate variability2.Close yield gaps through appropriate management of

the climate3.Produce food sustainably, synergistically with the

environment

Colombia’s own CCAFS Local Agroclimatic Committees

Improvedcrop varieties

Agroclimatic forecasts

Policies& NAMAs

Adaptation Plan for the Agricultural Sector

Farmers

Government Private sector

Producers’associations

Socioeconomic Scenarios

Climate-Site-Specific Management (CSMS)

Climate-Smart Villages

GHG measurements methods for smallholders

Scaling up activities

Component Department Municipality

RICE

Tolima Saldaña, Ibagué y EspinalHuila Palermo, AipeNorte Santander CucutaCésar ValleduparCordoba Montería, ceretéCasanare Yopal, Aguazul

Meta Villavicencio, Santa Rosa

Antioquia NechíSucre Majagual, San MarcosValle PalmiraGuajira Fonseca

BEANS

Santander VillanuevaAntioquia San VicenteNariño PastoCauca PopayánHuila El Pital

MAIZE

Córdoba Ciénaga de OroTolima EspinalValle del Cauca BugaQuindío BuenavistaSantander Sabana de TorresMeta Fuente de oro

BANANA

Magdalena Santa Marta, Rio Frio y Zona Bananera

Guajira Riohacha y Dibulla

LIVESTOCK

Boyacá San Miguel de Sema, Caldas y Chiquinquirá

Cundinamarca Simijaca

AtlánticoTubará, Piojó, Baranoa,

Manatí y Suán

Casanare Aguazul, Monterey, Pore, El Picón y Maní

Activities map CIAT/CCAFS-MADR Agreement Phase II

Córdoba: 56% (Riego)Temperatura en fase de llenado

Meta: 29% (Secano)Distribución de la precipitación en vegetativa

Casanare: 32% (Riego)Radiación en fase reproductiva

Tolima: 41% (Riego)Radiación en fase de llenado de grano

Huila: 28% (Riego)Temperatura en floración

How much yield variability can be explained by climate?

Meta: 61% (Riego)Temperatura en fase reproductiva

Mecanizada

Manual

Radiación solar acumulada (cal/cmt2)

Ren

dim

ient

o (k

g/ha

)

Humedad relativa (%)R

endi

mie

nto

(kg/

ha)

Córdoba Department

Location

Climate forecasts in some Colombian agricultural regions

Noviembre Diciembre Enero Febrero Marzo0

50

100

150

200

250

300

Promedio_Mensual Limite_Inferior

Prec

ipit

ació

n (m

m)

Noviembre Diciembre Enero Febrero Marzo0

50

100

150

200

250

300

Promedio_Mensual Limite_Inferior

Prec

ipit

ació

n (m

m)

Sugarcane

Precipitación – La Virginia

Precipitación - Guacarí

Precipitación - AeropuertoValle del Cauca

Noviembre Diciembre Enero Febrero Marzo0

50

100

150

200

250

300

Promedio_Mensual Limite_Inferior

Prec

ipit

ació

n (m

m)

Déficit

Normal

Exceso

CONVENCIONES

Agroclimatic Forecasts

01-Oct 08-Oct 15-Oct 22-Oct 29-Oct 05-Nov 12-Nov 19-Nov 26-Nov4000

4500

5000

5500

6000

6500

Fed2000 Fed733

Épocas de Siembra

Ren

dim

ient

o (K

g/ha

)Yield ForecastsMontería-Cerete (Córdoba)

National Agroclimatic Bulletin

Pronósticos Climáticos

Modelación agronómica

Conocimientolocal

Recomendaciones para los agricultores de medidas adaptativas a partir de la combinación del conocimiento local y científico

Local Technical Agroclimatic Committees

¿Cómo se afectarían los cultivos?

¿Qué variedades sembrar?

¿Qué habría que hacer?

¿Cuándo sembrar?

Local Agroclimatic Bulletins

Environmental Sustainability

(Water Footprint)

Partnership between different stakeholders to determine the impact of production systems in the use and quality of water

AMTEC Vs Manejo Convencional

Evaluación de híbridos con y sin riego

Conservación Vs Convencional

Huella hídricaBIODIESEL DE PALMA

LecheriaProducción más limpia

We are looking for ...Make more efficient use of resources

Para una región como el Departamento del Tolima esto implicaría agua para 28.000 hectáreas más de arroz

This is how Colombia is moving towards Climate-Smart Agriculture

Integrated approach of AFOLU sector in Colombia INDCs formulation -baseline analysis and mitigation scenarios models-

Countries can choose among a portfolio of growth-inducing technologies with different emission characteristics.

Countries are part of a global economic system, it is critical that LEDS are devised based both on national characteristics and needs, and with a recognition of the role of the international economic environment.

Objective: Determine what can be achieved given the global

economic environment

Technical Approach

a. IMPACT model: a global partial equilibrium model for agricultural commodities that provides plausible pressure for change in ag. prices and cropland areas,

b. A spatially-explicit model of land use choices: provides likely location of changes in ag. area and other land uses,

c. Crop model: provides yields, GHG emissions, and changes in soil organic.

Limited spatial resolution of macro-level economic models that operate through equilibrium-driven relationships at a global or national level with detailed models of biophysical processes at high spatial resolution.

Combines and reconciles: *

Essential components are: *

Results(1,000 hectares)

Case of Colombia

Policy ScenariosLand use policy scenarios after consultation with stakeholders

Scenario 1 Reduction of pastureland by 10 million hectares

Scenario 2 Total halt to deforestation the Amazon

Scenario 3 Total land allocated to palm production reaches a total of 1.2 million hectares

Additional investigation is necessary but, results unmistakably indicate the centrality of the livestock sector in emission reduction policies.

Source: AuthorsResults include: changes in SOC, above and below ground C caused by land use change;changes in emissions from cropland and livestock caused by land use change excluding burning;changes in revenue from crop and meat production.

Policy outcome comparison

*Includes changes in SOC, Above and Below ground C caused by land use change.**Changes in emissions from cropland and livestock caused by land use change. Exclude burning***Changes in revenue from crop and meat production

ScenarioChange C

Stock*(TgCO2eq)

Change in GHG

Emissions**(TgCO2eq)

DifferenceStock vs

Emissions

Change in Total

Revenue***(Billion USD)

1 272 25.2 246.8 40.6

2 168 -1.2 169.2 -2.5

3 64 19.9 44.1 -54.6

Results for each scenario

Livestock NAMA

Sustainable livestock: silvopastoral

Regional adaptation plans, aligned with national

Climate change regional plan for Valle del Cauca

Capacity strengthening local implementers and institutions on climate change challenges

Tools and instruments for CC adaptation and mitigation

Promote interinstituional collaboration

Link national policies with regional plans and strategies

Climate-Smart Village Approach

A community approach towards sustainable agriculture development

CCAFS works with the communities to develop Climate-Smart Villages. These are sites where researchers, local partners, farmers and policy makers work together to select and implement technologies and practices based on global knowledge and local conditions with the purpose of: a) increasing sustainable productivity and income, b) building resilience to climate change,

c) reducing GHG emissions and d) promoting food security and development goals.

CSVClimate-Smart Village

Climate information services

Climate-smart technologies

Local adaptation plans

Financial incentives and market access

Context specific conditions (social, economic, cultural, environmental)

Terr

itory

din

amic

s

Scaling up and outPoliciesPrivate sectorChampion cases are used in big initiatives

Continuous learning Stakeholder diversity Capacity building

Integrated management through a portfolio that responds to context-specific needs in the territory

CSVClimate-Smart Village

a.jarvis@cgiar.org

Thank you