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University of Nairobi. Causes and Impacts of Climate Change in East Africa: Links to Crops, Livestock, Natural Ecosystems, and Health. Jennifer Olson - PowerPoint PPT Presentation
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Causes and Impacts of Climate Change in East Africa:
Links to Crops, Livestock, Natural Ecosystems, and Health
Jennifer Olson
And Gopal Alagarswamy, Jeff Andresen, David Campbell, Declan Conway, Ruth Doherty, Jianjun Ge, Clair Hanson, Sarah Hession, Marianne Huebner, Brent Lofgren, Dave Lusch, Stephen Magezi, Joseph Maitima, Joseph Messina, Salome Misana, Nathan Moore, Sam
Mugisha, John Nganga, John Kaneene, Bryan Pijanowski, Jiaguo Qi, Philip Thornton, Nate Torbick, Jing Wang, Pius Yanda, Lijian Yang
NSF Awards 0308420 & 0308420, NIH Award 5R21GM084714-02
Universityof Nairobi
University of Dar Es SalaamUniversity of
Dar Es Salaam
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Climate Change Causes
Comparing relative importance of causes –
• Greenhouse Gases (GHG) from the global scale,
• Land use change from the local to regional scale
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•Rising temperatures•Changing precipitation patterns (location, timing, variability)•Extremes – droughts, floods, storms
1974 2007
And Effects
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Methodology
• Identify recent trends in climate• Calibrate regional climate model RAMS for East
Africa using climate and land surface data. – Higher resolution, better topography and landscape than
global circulation models;• Develop/calibrate land use change & crop
models;• Couple climate, land use & crop models to
simulate future climate (2050), compare climate vs. land use effects, and
• Identify impacts on crop yields, savanna vegetation, livestock productivity, households, and zoonotic diseases through ecological & socioeconomic field work, modeling.
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Arusha 1961-2005 (+1.1°C)Arusha mean annual temperature time series (1961 -2005)
y = 0.0248x - 29.127
R2 = 0.5132
18.5
19.0
19.5
20.0
20.5
21.0
21.5
1961 1965 1969 1973 1977 1981 1985 1989 1993 1997 2001 2005 2009
Years
Te
mp
era
ture
(C
)
Annual Linear Trend
5Source: Tanzania Meteorological Agency
Zanzibar 1961-2005 (+1.9°C)Zanzibar annual mean temperature time series (1961 - 2005)
y = 0.0423x - 57.902
R2 = 0.5755
23.0
23.5
24.0
24.5
25.0
25.5
26.0
26.5
27.0
27.5
28.0
1961 1965 1969 1973 1977 1981 1985 1989 1993 1997 2001 2005 2009
Years
Te
mp
era
ture
(C
)
Annual mean Linear Trend
Temperature Trends
Iringa 1961-2005 (+0.7°C)Iringa annual mean temperature time series (1961 - 2005)
19.0
19.5
20.0
20.5
21.0
21.5
22.0
1961 1965 1969 1973 1977 1981 1985 1989 1993 1997 2001 2005 2009
Years
Te
mp
era
ture
(C
)
Annual mean Linear Trend
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Precipitation Trends
Arusha 1961-2005Arusha annual rainfall time series (1961 -2005) y = -6.2175x + 13146
R2 = 0.0799
0
200
400
600
800
1000
1200
1400
1600
1800
1961 1965 1969 1973 1977 1981 1985 1989 1993 1997 2001 2005 2009
Years
Rai
nfa
ll (m
m)
Annual rainfall Linear Trend
Iringa annual rainfall time series (1961 - 2005)
y = -2.3913x + 5358.4
R2 = 0.0663
400
500
600
700
800
900
1000
1100
1200
1961 1965 1969 1973 1977 1981 1985 1989 1993 1997 2001 2005 2009
Years
Rai
nfa
ll (
mm
)
Annual rainfall Linear Trend
Iringa 1961-2005 Zanzibar 1961-2005Zanzibar annual rainfall time series (1961 -2005)
y = -0.792x + 3251.6
R2 = 0.0007
0
500
1000
1500
2000
2500
3000
1961 1965 1969 1973 1977 1981 1985 1989 1993 1997 2001 2005 2009
Years
Ra
infa
ll (
mm
)
Annual rainfall Linear Trend
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Experiments for exploring climate-land interactions
Land Cover Global Climate Comparison:
1: Current Current Baseline
2: Current 2050 decade Future climate effects only
3: 2050 decade Current Future land cover effects only
4: 2050 decade 2050 decade Synergistic effects
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Land Use Changes
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Differences in Temperature (RCM)
Climate Change (GHG) LCLUC Combined EffectsEffects Effects
1010
Differences in Precipitation (RCM)
Climate Change Land Use Change Synergistic Effects(GHG) Effects (LUC) Effects
1111
Win
d pa
ttern
cha
nges
du
e to
LC
LUC
1212
Summary of Projected Future• Near large bodies of water, rainfall changes due
to LUC are of similar magnitude to that associated with GHG. Farther from water, gains in rainfall from GHG may be offset by reduced rainfall due to LUC;
• All areas will see increases in variability of rainfall—intense storms, droughts and floods—due to GHG;
• CLIP results suggest the importance of sub-regional factors affecting climate and resulting impacts.
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Impacts
1. Agricultural systems2. Natural ecosystems
3. Health
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Impact on Crop Growth
• Temperatures – – more rapid phenology, shorter growing season– evapotranspiration higher so need more water
• Precipitation – – Frequency, timing and inter-annual variability.
Some crops highly sensitive to when rain falls during season (e.g., maize).
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•Rainfall and soils limit production•Model assumes low input levels
Deterministic process based simulation models (DSSAT CERES); CCSM v4 and WorldClim.
Maize yields under current climate conditions
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Difference in maize yields due to GHG and LUC 2000 to 2050
Green=increase in yieldsBrown=decline in yields
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• Warmer temperatures, especially Tmin, enhance maize yields.
• Possible shift to maize at the expense of high value tea, coffee.
• Reduced incomes
Highlands
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Lowlands, cropping systems• Warmer temperatures lead to more rapid
phenology, shortening the growing season and reducing yield;
• Warmer temperatures combined with similar or reduced rainfall leads to declining crop yields;
• Less water available for irrigation.
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Agro-pastoral systems• Warmer temperatures lead to vegetation drying
faster and water becoming scarce faster.• Savanna vegetation composition changing, bush
encroachment observed;• Forage productivity and palatability declining;• Droughts impacting faster, more severe;• Livestock and human diseases more frequent with climatic extremes.
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Adaptations, Agro-Pastoralists
• Changing livestock breeds– More camels, goats– New goat and cattle breeds from Somalia
• Distance traveled daily to water, forage longer, herding patterns changing
• Reduced burning (less biomass)• More pastoralists are cropping to cope
with frequent drought (but some fields abandoned due to failure of short rains)
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Natural ecosystemsSome wildlife highly sensitive to changes in
temperature and to water availability, e.g., hippos, fish. Local extinctions possible. Wildlife migration patterns disrupted.
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Highly Vulnerable Ecosystems (1)
• Wetlands: surface water will decline, yet usage will intensify. High concentrations of livestock and wildlife lead to land degradation.
• Highlands: rapid climate changes towards warmer temperatures. Risk of increased fire, loss of glaciers, altered vegetation composition.
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Highly Vulnerable Ecosystems (2)
• Coasts: higher rainfall, stronger storms and waves, sea level rise lead to erosion, inundation, salt water intrusion. Urban infrastructure affected.
• Coral reefs: ocean surface water warming fast, bleaching.
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Impacts on Zoonotic Diseases
1. Impacts of climate and land use change on Trypanosomiasis (sleeping sickness) distribution: A Dynamic Ecological Simulation Model of Tsetse transmitted Trypanosomiasis in Kenya (NIH)
2. Impacts of climate, land use and management change on Bovine TP: Modeling the Ecological and Socioeconomic Determinants of Tuberculosis Transmission in Humans, Livestock and Wildlife
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Educational Links
• Capacity building of teachers/ lecturers, and new curriculum modules for university / K-12 levels (science, math, social studies, etc.). Implemented by US and East African professors & teachers, will be online and distributed at state & national levels.
• New internet connected, computer assisted technologies in schools and communities in Tanzania (ICT Global Corps).
