Future rice productionin Madagascar

Where and how much ?

Robert Hijmans & Alice Laborte

International Rice Research Institute

Background

• Madagascar’s population is largely rural, very poor & dependent on agriculture

• Rice is the main crop and staple food & cassava is also important.

• Madagascar is a net rice importer. Government aims to double rice production between 2005 and 2012

• Production (kg) = Area (ha) * Yield (kg / ha)

• Area expansion (habitat loss?) or intensification (pollution?)

2 modeling approaches

• Regression: Where would area expansion take place?

• Simulation: Climate change effect on yield

Where is rice grown ?

BD50 IDFN1

Regression model

Rice area as function of:

a) biophysical factors

b) socioeconomic factors

c) biophysical + socioeconomic factors

d) bio. + soc. factors (2 regions: W, CE)

Biophysical variables

Socio-economic variables

Variable Unit 1 2 3

Intercept 17.039** 0.364** 12.469**

Elevation km -0.679** -0.490**

Slope deg -0.055** -0.063**

Slope – focal mean deg -0.147** -0.114**

Sqr(Slope) deg2 0.005** 0.005**

Rainfall m 0.757** 0.677**

Mean temperature °C -1.255** -0.851**

Sqr(Temperature) °C2 0.022** 0.013**

Distance to roads km -0.121** -0.114**

Distance to towns km -0.094** -0.091**

Population density person km-2 0.009** 0.002**

Population density – change

% -0.002**

Income million francs 1.458** 2.165**

D2 0.09 0.11 0.16

Area under ROC 0.70 0.73 0.76

AIC 26,930 26,382 24,928**Significant at 0%, * 5%

a b c

Model

**Significant at 0%, *1%

Model d

Variable Unit AS, MA, TL AV, FI, TM

Intercept 8.722** -14.417**

Elevation km -3.304** -4.306**

Sqr(Elevation) 2.007** 1.295**

Slope deg -0.071**

Slope – focal mean deg -0.125** -0.150**

Sqr(Slope) deg2 0.003** 0.005**

Flow accumulation – focal mean -0.012**

Rainfall m 1.817**

Mean temperature °C -0.328** 2.393**

Sqr(Temperature) °C2 -0.075**

Distance to roads km -0.150** -0.125**

Distance to towns km -0.097** -0.107**

Population density person km-2 0.009** 0.002**

Population density – change % -0.035** 0.011**

Income million francs 5.139**

D2 0.18 0.20

Area under ROC 0.78 0.79

Center-East West

Biophysical variables Socio-economic variables

Two regionsBiophysical & socioeconmic variables

Biophysical variables Socio-economic variables

Two regionsBiophysical & socioeconmic variables

Forest loss model

Business as usual:

Forest area reduced by

25% in 2032

50% by 2077.

Rice growth simulation model

Pot. yld.(t / ha)

BaselineClimate: 1960-1990 (CO2 = 340 ppm)Cultivar: IR72Model: Oryza

< 2.5 2.5 - 5 5 - 7.5 7.5 - 10 > 10

January April

July October

< 2.5 2.5 - 5 5 - 7.5 7.5 - 10 > 10

Current conditions2080A2a, Hadcm3

November planting of IR64, irrigated

IR64, rainfed

Implications?

Part of the climate change effects on yield potential can be easily dealt with (length of growing season)

Current yields are very low; Need for intensification; opportunities are not much affected.

Water supply, double cropping?

Resilience to extreme events (flooding, drought)

More rice in the central highlands? Or diversification to high value crops?

• Intensification:

– less pressure on the land;– more pollution, where would that be a threat?

• Extensification:

– Not necessarily in the forest areas– Rehabilitation of irrigation schemes– Need for alternative livelihoods