Download CLIP Meeting January 31, 2008 - Climate Land Interaction Project

Maize and Bean Productivity changes in East Africa
due to climate change
Objectives: To look at:
1.
2.
System-based differences in productivity of
maize and bean in CLIP domain due to
climate change
What could be done to adjust for these
changes in the future
To estimate productivity we need to know where in reality
the crops are grown in a country
•
For simulations we used length of growing season -LGP (>60days) and
FAO soil suitability indices
–
Problem:
•
•
•
Could use Global Land cover Classification (GLC 2000)
–
Problem:
•
•
Grossly over estimates cropped area
Does not say where maize and bean crops are grown in a country
underestimates because of its inability to pick small-mosaics of crop land
In this study we used :
–
–
–
modified live-stock systems classification of Sere and Steinfeld (1996) by
incorporating cropping systems from Dixon and Gulliver (2001) leading to
mixed crop-livestock systems
Overlaid Maize and Bean mask to the mixed crop-livestock systems to
identify cropped area
This corresponded to systems classification: Mixed Rain fed Systems
Mixed Rain fed Systems
MRA
Mixed Rain fed Arid-semiarid
MRH
Mixed Rain fed Humid/sub-humid
MRT
Mixed Rain fed Temperate/tropical
highland
Maize cropping intensity 1999-2001 (You &
Wood, 2006)
System areas for Burundi, Kenya, Rwanda, Tanzania
and Uganda
Percentage Land Area
Total Area
(km2)
Mixed
Livestock
Cropping
Other
Burundi
87
0
1
12
27,278
Kenya
26
71
0
2
582,721
Rwanda
96
0
0
4
25,580
Tanzania
56
33
4
6
939,138
Uganda
68
16
1
14
244,318
Average
or Total
67
24
2
6
1,819,034
Assumptions used in the analyses
•
•
•
•
•
Maize is main crop grown at the start of growing
season
Bean comes only in those pixels where growing season
is long enough for maize and then for bean
Looking at indicative and directional change in
productivity as affected by climate change
Current national productivity is for 2004-2006 from FAO
Looking at national productivity and disaggregated
productivity in mixed systems MRA, MRH and MRT
GCMs used
•
•
•
•
HadCm3
ECHam4
CCSM (will include in future analysis)
SRES Scenarios: A1F1 (high emission) and A1B (low
emission)
Percentage production changes from current to 2030 and
2050 (HadCM3 model, Scenario A1) by country and system
Maize
National
Production
MRT
MRH
MRA
2030
2050
2030
2050
2030
2050
2030
2050
Burundi
9.4
9.6
11.8
13.5
1.7
-2.9
-
-
Kenya
15.4
17.6
32.3
45.3
-6.4
-14.0
-0.3
-8.8
Rwanda
11.9
16.9
16.2
22.9
8.2
9.9
0.1
1.7
Tanzania
-3.1
-10.1
4.7
3.0
-0.2
-6.5
-5.2
-13.2
Uganda
-2.5
-12.3
2.1
-3.7
-4.1
-16.8
-1.1
-5.7
Percentage production changes from current to 2030 and
2050 (HadCM3 model, Scenario A1) by country and system
BEANS
National
Production
MRT
MRH
MRA
2030
2050
2030
2050
2030
2050
2030
2050
Burundi
25.2
23.8
29.2
28.9
11.8
7.1
-
-
Kenya
12.6
16.2
14.6
20.7
0.7
-10.7
-
-
Rwanda
19.7
20.4
23.3
26.1
7.4
0.7
-
-
Tanzania
7.8
-5.0
34.0
54.0
7.0
-7.8
4.6
-12.0
Uganda
-4.9
-28.0
5.7
-9.9
-6.2
-31.1
-4.9
-16.9
Considerable spatial variation
Maize in Kenya
MRT
MRH
MRA
2030
2050
2030
2050
2030
2050
32.3
45.3
-6.4
-14.0
-0.3
-8.8
Increase in MRT but decrease in MRH and MRA
Considerable Temporal switches
(besides spatial effects)
Bean in Tanzania
MRT
MRH
MRA
2030
2050
2030
2050
2030
2050
34.0
54.0
7.0
-7.8
4.6
-12.0
MRH: 7% increase in 2030 from baseline (2000) followed by a
8% decrease in 2050
MRA: 5% increase in 2030 from baseline (2000) followed by a
12% decrease in 2050
Two basic types of response to overcome climate
change effects on crop productivity
1.
Internal shift: To offset projected decrease internal shifts
of production from lower producing systems to higher
producing systems
e.g. Shifting bean production from MRH (-11%) to MRT (+21%)
system in Kenya
(caution: It might have to replace / compete with high value crops presently grown
in MRT)
2. Agronomic or Management adjustments:
Maize and Bean yield decreased in all systems in
2050 in Uganda.
–
–
No internal shift possible to overcome since all systems
are affected
Are there any management adjustments possible to deal
with such changes?
o
Can evaluate several options such as application of
fertilizer, use longer duration crop varieties, irrigation
etc.
o
Validate with FEWS yield and precip data? Chris
Funk
To respond to overcome climate change
effects on crop productivity :
• Need to look at high-resolution impacts as
they vary both spatially and temporally
• Coping options vary depending on location
and situation
• There is no single blanket response