A Eitzinger - Climate Change Adaptation and Mitigation in the Kenyan Coffee Sector

Pic by Neil Palmer (CIAT)

Climate Change Adaptation and Mitigation in the Kenyan Coffee Sector

CIAT – International Center for Tropical Agriculture

• CIAT: Part of Consultative Group on International Agriculture Research

• Mission: To reduce hunger and poverty, and improve human health in the tropics through research aimed at increasing the eco-efficiency of agriculture.

DAPA: Decision and Policy Analysis

What we do: Spatial Analysis, climate change, Impact analysis models.

Project-Team: A. Eitzinger, Dr. Peter Laderach, O. Ovalle, J. Ramírez and Dr. A. Jarvis

Content

• A: Introductions• B: Research questions• C: Methods and data generation• D: Results of analysis in Kenya

– Regional changes– Site-specific changes

• E: Conclusions and recommendations

Introductions

Study objectives:Elaboration of future climate

scenarios to indicate the impact of climate change on adaptability of coffee in Kenya which will be accessible and available for international and regional organizations such as the Coffee Research Foundation and the 4C Association.

A

Climate Change Adaptation and Mitigation in the Kenyan Coffee Sector

Research questions

• Where will coffee grow in the future?• Where will coffee not grow any more?• Where can coffee still grow with adapted mgt? • What are the decisive factors to manage?

B

Pics by Neil Palmer (CIAT)

Methods and data generation

• Historical climate generation

• Future climate

• Suitability prediction

C

Historical climate generation

WorldClim (www.worldclim.org) database(Hijmans et al, 2005)

• Base line for climate change calculations• Meteorological Stations with data of:

• Worldwide:precipitation: 47,554Mean temp.: 24,542Min/max temp: 14,835

• For Kenya:Precipitation: 736Mean temp.: 708Min/max temp: 61

C

http://www.worldclim.org/

Future climate

• Global circulation models (GCM)

Calibrated in the past (using time-series), and projected to the future

• Intergovernmental Panel on Climate Change - IPCC (http://www.ipcc.ch/)

Fourth Assessment Report, based on the results of 21 global climate models (GCMs)

C

• Generation of future climate

Downscaling to provide higher-resolution surfaces if the likely impacts of climate change on agriculture are to be forecast

http://www.ipcc.ch/

Global circulation models (GCM)

• 20 models (different institutions)

C

bioclimatic variables

• Bio1 = Annual mean temperature• Bio2 = Mean diurnal range (Mean of monthly (max temp - min temp))• Bio3 = Isothermality (Bio2/Bio7) (* 100)• Bio4 = Temperature seasonality (standard deviation *100)• Bio5 = Maximum temperature of warmest month• Bio6 = Minimum temperature of coldest month• Bio7 = Temperature Annual Range (Bio5 – Bi06)• Bio8 = Mean Temperature of Wettest Quarter• Bio9 = Mean Temperature of Driest Quarter• Bio10 = Mean Temperature of Warmest Quarter• Bio11 = Mean Temperature of Coldest Quarter• Bio12 = Annual Precipitation• Bio13 = Precipitation of Wettest Month• Bio14 = Precipitation of Driest Month• Bio15 = Precipitation Seasonality (Coefficient of Variation)• Bio16 = Precipitation of Wettest Quarter• Bio17 = Precipitation of Driest Quarter• Bio18 = Precipitation of Warmest Quarter• Bio19 = Precipitation of Coldest Quarter

C

Generation of future climate

• Current climate from worldclim (1km resolution)– Prec, temp min/mean/max

• Future climate– Calculate anomaly (future – current)– Downscale (spline interpolation)– Add to current climate (worldclim)

– Calculate 19 bioclimatic variables

C

Current climate + Climate-Change = Future climate

Suitability prediction• finding the probability distribution of maximum entropy (MAXENT)

C

Currentclimate

Futureclimate

Relation

Projection

Evidence data ofcoffee crops today

Prediction ofFuture

evidence ofCoffee crops

19 bioclim variables

Key of investigation

MAXENT is generally considered to be the most accurate model (Elith et al. 2006) and was selected for the analyses of the present study after an initial iteration of analysis in the study region using all four models.

Methodology – the process

• Compilation of evidence data.• Generation of future climates.• MaxEnt: Future suitability predictions for each model

– 3 measurements of uncertainty to exclude outliers:• agreement among models as percentage of models predicting

changes in the same direction• mean suitability: upper and lower 95% confidence intervals (C.I.)• the coefficient of variation (CV) among models.

– Final run with confirming models• Prediction of future coffee distribution.• Identification of decisive growth factors.

– Stepwise regression of suitability-shift per data point

C

Results of analysis: Regional changes

• Evidence data:805 Arabica coffee farms in Kenya644 collected using GPS161 collected by desk studies

D


• Annual precipitation 2020– rainfall increases from 1405 millimeters

to 1435 (+30)– The maximum number of cumulative

dry months keeps constant in 4 months

D


• Annual precipitation 2050– rainfall increases from 1405 millimeters

to 1575 (+ 170)– The maximum number of cumulative dry

months keeps constant in 4 months

D


• Annual temperature 2020– temperature increases by 1°C

D


• Annual temperature 2050– temperature increases by 2.3°C– temperature range increases

from 15.6 °C to 15.9 °C

D


• The maximum temperature of the year increases from 28.6°C to 31.2°C in 2050• The minimum temperature of the year increases from 9.8°C to 12.0°C in 2050• The wettest month gets wetter with 330 millimeters instead of 305 millimeters in 2050• The driest month keeps constant with 30 millimeters in 2050

D


• Current suitability of coffee– according to the MAXENT model, the

most suitable of them are concentrated in the higher areas of:

Bungoma, Embu, Kericho, Kiambu, Kirinyaga, Kisii, Machakos, Meru, Muranga, Nithi, Nyamira, Nyeri and Trans-Nzoia.

D


• Coffee suitability in 2020– in general decreases– go up higher

D


• Coffee suitability in 2050– in general decreases quite seriously– decreases to between 30 and 50%

today 60 - 80%!– go up higher– gaining suitability (20 – 30% by 2050) in:

Rift valley

D


• Change of suitability in 2020

D


• Change of suitability in 2050

D

Results of analysis: Relation of suitability & altitude

• Areas at higher altitudes become suitable for producing coffee:• Optimum coffee-producing zone:

– current between 1400 and 1600 masl– between 1600 and 1800 masl at 2050– altitudes around 1200 masl will suffer the highest decrease– areas around 2000 masl the highest increase in suitability

D

Results of analysis: model agreement

Measure of agreement of models predicting changes in the same direction as the average of all models at a given location

D

Results of analysis: model agreement

Mean coefficient of variance of bioclimatic variables

D

Results of analysis: stepwise regression

• in general– increasing temperature– increase of rainfall

• as drivers of the predicted negative suitability shifts

D

Results of analysis: site-specific changes

• Annual precipitation 2050

D

Results of analysis: site-specific changes

• Annual temperature 2050

D

Bungoma Embu Kericho

Kiambu Kirinyaga Kisii

Machakos Meru Murang'a

Nithi Nyamira Nyeri Trans-Nzoia

Results of analysis: site-specific changesD

Conclusions and recommendations

• Overall conclusions– changes in suitability are site-specific– solution is site-specific management– there will be differnt sites:

• become unsuitable to grow coffee farmers will need to identify alternative crops

• remain suitable, but agronomic management need to adapt to changed conditions

• in future will become suitable for coffee need strategic investments to develop coffee production

– climate change will bring not only bad news but also a lot of new potential.

– the winners will be those who are prepared for change and know how to adapt.

E


• Specific conclusions– How will the climate in the project area change by the

year 2050?• yearly/monthly rainfall will increase progressively by 2050• yearly/monthly minimum and maximum temperatures will increase

progressively by 2050• overall climate will become less seasonal in temperature/precipitation• maximum number of cumulative dry month will stay constant at 4 months• precipitation for specific districts will increase by 135 to 205 mm by 2050• temperatures for specific districts increase by 2050 between 2.2 and 2.4 °C

E


• Specific conclusions– What impact will climate change have for suitability of

coffee and how will coffee areas change?• by 2050 suitability of 13 municipalities in general decreases quite seriously• areas that still are suitable decreases to between 30 and 60% (today 50-

70%)• optimum coffee-producing zone in 2050 increases to 1700 masl (today

1600 - compensates for the increase in temperature)• areas around 1300 masl will suffer the highest decrease in 2050• areas around 2200 masl the highest increase in suitability

E


• Specific conclusions– What are the climatic factors that determine the

suitability for coffee?• by 2050, decrease of precipitation of driest month and increase of

minimum temperature of the coldest month are main negative factors driving suitability together with increasing precipitation of the coldest quarter

• the positive suitability shifts at the highest altitudes of the present growth range of coffee, on the other hand, were mostly driven by increasing temperatures

E


• Recommendations– It would be possible to make much more precise

predictions by using expert knowledge to refine the results presented here.

– Local experts and community need to be made aware of the results of this study and the likely effects on livelihoods

– Road maps for each specific areas should be defined, e.g.:

• Identification of alternative crops• Adaptation of agronomic management such as shade,

varieties, irrigation, etc.• Strategic planning for areas with new potential for coffee

production.

E

Pic by Neil Palmer (CIAT)

DAPA – Decision and Policy Analysis group of CIAT:A. Eitzinger, Dr. P.Laderach

O. Ovalle, J. Ramírez and Dr. A. Jarvis

Thank you!

A Eitzinger - Climate Change Adaptation and Mitigation in the Kenyan Coffee Sector

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