Download climate change - Geographical Association

Vulnerability and Climate Change - The
Development Challenge
Phil O’Keefe
The Geographical Association,
Newcastle, 2008
OVERVIEW
• The political economy of humanitarianism
• Climate Change
• Key Questions
• Exogenous and endogenous pressures
• Location of study area
• Methodology
• Key Hypothesis
• Important preliminary results
• Agricultural extensification, intensification and off-farm income
• How vulnerable are the Chagga to climate change?
The Political Economy of Humanitarianism
•1990-2005 from 500 million to 8 billion
•20 million refugees, 40 million IDPs
•From natural disasters to complex emergencies
•Reorganisation of the UN system
•Growth of international NGOs
•A need for pre-disaster planning
Climate Change Challenges
•IPPC 4 - Variability
•Stern - Project to Programme
•Post Kyoto
•Carbon footprint negotiations within and between
countries
CLIMATE CHANGE
• Synoptic Change; large scale system change
-Global movement of ITCZ; high pressure system
that dominates African weather
-Regional impact of El Nino(e.g.1997); movement
of the southern ocean oscillation
-Deglaciation of Kilimanjaro but competing
explanations; no ice in 25 years
Annual Rainfall
2500
2000
Rainfall (mms)
1500
1000
500
0
Annual Total Rainfall
Source: Kilimanjaro Meteorological Office
Rainfall Trend
Mean Yearly Temperature
31.0
30.5
Temperature °C
30.0
29.5
29.0
28.5
28.0
27.5
Mean Yearly Temperature
Source: Kilimanjaro Meteorological Office
Temperature Trend
Percentage precipitation change
20
15
Annual
Percent
10
June/July/August
5
September/October/November
December/Januay/Febuary
0
2030
2050
2100
March/April/May
-5
-10
Projected Temperature Increae °C
3
Degrees celcius
2.5
Annual
2
June/July/August
1.5
September/October/November
1
December/Januay/Febuary
March/April/May
0.5
0
2030
Source: URT 2003
2050
2100
Inter-Annual Short Rain Variability
400
350
Rainfall (mms)
300
250
200
150
100
50
0
November
December
Inter-Annual Long Rain Variability
1200
Rainfall mms
1000
800
600
400
200
0
March
Source: Kilimanjaro Meteorological Office
April
May
KEY QUESTION:
HOW WILL CLIMATE CHANGE AFFECT
AGRICULTURAL SMALL HOLDERS ON
KILIMANJARO?
• What is vulnerability?
 What is a bad year?
 What is more important; climate change or climate
variability?
• What are the pressures?
 Climate Change
 Changing commodity prices
 Government policy
• What are the coping mechanism?
 Can agricultural intensification decrease vulnerability?
 Can agricultural extensification decrease vulnerability?
 What is the role of off-farm income?
WHAT IS VULNERABILITY?
The extent to which a natural or social system is
susceptible to sustaining damage from climate
change, and is a function of the magnitude of
climate change, the sensitivity of the system to
changes in climate and the ability to adapt the
system to changes in climate
Bad Year Predictors
What is a Bad Year?
50
45
40
35
30
25
20
15
10
5
0
60
Percent
50
40
30
20
10
0
Bad Harvest Insufficient
Food for
Family
Low Crop
Prices
Other
Delayed Reduced
Seasonal Seasonal
Rains
Rainfall
Bad Year Food sources
60
50
40
30
20
10
0
No Rain
Extra
Warmer
Heavy & than Usual
Prolonged
Downpour
Other
WHAT IS MORE IMPORTANT;
CLIMATE CHANGE OR VARIABILITY?
• Climate variability used as proxy for climate change
• Therefore reducing vulnerability to climate variability is
decreasing risk to climate change
Exogenous Pressures Endogenous Pressures
• Climate change/
Climate variability
• Declining commodity
prices
• Government policy
Population increase
Deforestation
Fire risk
Subsistence food
insecurity
• Change of subsistence
food crop
•
•
•
•
Declining coffee price and production
40.0
35.0
3.00
30.0
2.50
25.0
2.00
20.0
1.50
15.0
1.00
10.0
0.50
5.0
0.00
1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006
Real Coffee Price
Kilimanjaro region
0.0
Killimanjaro as percentage of Tanzanian coffee production
Real Coffee Price (Price recieved/USD exchange Rate)
3.50
Projected Kilimanjaro Population
3500000
250
3000000
Total Population
2500000
150
2000000
1500000
100
1000000
50
500000
0
1967
0
1978
1988
2002
Population
Population per square kilometre
2014
Population Per Square Kilometre
200
LOCATION OF STUDY
•
•
•
•
Tanzania
Mt Kilimanjaro
Kilimanjaro region
Moshi rural and Rombo district
ROMBO PROFILE
Height (feet)
5,700
5,200
4,700
4,200
3,700
Rombo
4
3.75 3.5 3.25
3
3
2.75 2.5 2.25
2
2
1.75 1.5 1.25
1
0.75 0.5 0.25
0
Length (Miles)
Rombo A: Traditional
banana-coffee homegardens
Rombo B: Homegardens with
increase of maize plantations
Rombo C: Maize bean plantations
increase. Crops smaller due to lack of
water
Location: 37°34E to 37°38E at 3’11S
METHODOLOGY
•
•
•
•
•
•
•
•
•
2 profiles from south to east on Kilimanjaro
Built on Rufiji study
Questionnaire modification
Pilot survey
Enumerator Training
Enumerator monitoring
Data entry checking system
1,016 Household surveys completed over 3 weeks
(Map or diagram)
KEY HYPOTHESES
• Mark: How vulnerable are the Chagga to climate
change?
• Paul: How are capitals accumulated on Mt.
Kilimanjaro
• Zahra: What are the gender aspects of food
security on Mt. Kilimanjaro?
• Matt: What are the government responses to
famine?
OTHER DATA SOURCES
•
•
•
•
•
•
•
Secondary survey
Key informant interviews
Physical asset checklist
Structured observation
Transect walks
Theoretical context setting secondary data
Location specific secondary data
ACCESS TO WATER SOURCES AS VULNERABILITY INDICATOR
Rombo A
Rombo B
Rombo C
3% 1%
3%
18%
48%
39%
45%
57%
34%
Old Moshi
8% 1%
Marangu
52%
Lower Moshi
2% 2%
7%
30%
25%
25%
59%
71%
2%
23%
45%
LEVEL OF EDUCATION RELATED TO INFORMATION
Source of
information
Level Of Education (Percentages)
No
Adult
Primary
Secondary College
Schooling Education Education Education university Total
Agricultural
Extension Officer
Other Farmers
Seed Suppliers
Media
Nowhere
Total
23
28
20
40
4
45
100
3
37
100
32
32
4
4
28
100
44
20
10
5
21
100
50
9
18
5
18
100
32.6
30.1
4.8
3.8
28.8
100
Differentiation of women’s coping mechanism by age
Women’s
coping
mechanism
Age (percentages)
18-37 38-57 57+
Total
Petty Buisness
70
64
47
59
Remittances
13
15
30
20
Others
17
21
23
21
100
100
100
100
Total
DIVISION OF LABOUR IN COFFEE PRODUCTION
Coffee Harvester(s)
Coffee
Marketer (s)
Sex (percent)
Sex (percent)
Male
Female
Total
Male Parent
9
3
7
43
17
34
Female Parent
19
44
29
20
61
34
Male & Female Parent
42
23
35
31
13
25
Children
2
3
3
2
2
2
Parents & Children
25
22
24
4
5
4
Others
1
5
3
2
1
100
100
100
100
100
Total
Male Female Total
100
How many cattle owned?
How many cattle loaned from
others?
Number Frequency Percent
Number Frequency Percent
How many chickens owned?
Frequenc
Number y
Percent
0
510
50.2
0
881
86.8
0
261
25.7
1
233
23.0
1
84
8.3
1-4
286
28.2
2
174
17.1
2
34
3.3
5-9
237
23.3
3
57
5.6
3
5
0.5
10-19
156
15.4
4
28
2.8
4
5
0.5
20-29
46
4.5
5+
13
1.3
5+
6
0.6
30-39
12
1.2
Total
1015
100.0
Total
1015
100.0
40-49
9
0.9
50+
8
0.8
Total
1015
100.0
Total Income 2005
Money
Total Income 2006
USD
Percent
Money
USD
Percent
Median
133800
112
Median
178000
148
Mean
305523
255
Mean
370544
309
837
0.7
Per day
0.8
Total
310411786
258676
100
313728
100
Off-farm income
146569750
122141
47.2
Total
Off-farm
income
1015
37647320
4
16167852
5
134732
42.9
Remittances
45641650
38035
14.7
Remittances
53403000
44503
14.2
Bananas
40377900
33648
13
Bananas
50207600
41840
13.3
Milk
15106250
12589
4.9
Milk
28109200
23424
7.5
Livestock
22457500
18715
7.2
Livestock
24768600
20641
6.6
16822300
14019
5.4
Coffee
22500800
18751
6
Maize
12268536
10224
4
Maize
20040510
16700
5.3
Fruits
3634350
3029
1.2
Fruits
4692699
3911
1.2
Wood
2567500
2140
0.8
Beans
3661950
3052
1
Other farm
1670900
1392
0.5
Wood
3476000
2897
0.9
Beans
1550000
1292
0.5
Millet
1280600
1067
0.4
Per day
Coffee
Distribution of income
800000
700000
600000
TSH
500000
400000
300000
200000
100000
0
10
20
30
40
50
Percentiles
60
70
80
90
Are you aware of climate change?
Yes
953
94
39
4
24
2
No
Missing
What are the Impacts of
climate change?
Frequency
Percent
Shorter Rain Seasons &
Insufficient Rainfall
403
40
Insufficient Rainfall
237
23
Shorter Rain Seasons
164
16
Shorter Rain Seasons &
Flood/Drought INcreases
95
9
53
5
34
3
8
3
Flood/Drought Increases
Insufficient Rainfall &
Flood/Drought Increases
Others
CAN AGRICULTURAL EXTENSIFICATION
DECREASE VULNERABILITY?
Forest limits – national park
Bush Savannah no longer exists
Large scale farming constraints
Maize-bean shambas on lowlands due to availability of
water
• Finger Millet – Cow peas extreme drought adaptation,
illustrates the limits of cultivation without irrigation
• Population increase and landuse planning/ownership
limit extensification opportunities
•
•
•
•
CAN AGRICULTURAL
INTENSIFICATION DECREASE VULNERABILITY?
• Intensifying by cash cropping or diversifying
subsistence food production
• Is coffee rehabilitation possible?
WHAT IS THE ROLE OF
OFF-FARM INCOME?
• Options of movement
-Local
-Regional
-National
• Importance of transport
• Importance of education
What is the meaning of this case
study?
•Adaptation is evolution
•Coping mechanisms suggest involution
•The need for post Kyoto to be adaptation
focused
•The need for pre-disaster planning