2010 aag washington, d.c. people and livestock in the changing landscape and climate of the east...

2010 AAG Washington, D.C.

People and Livestock in the Changing Landscape and Climate

of the East African Savannas Jennifer Olson1, David Campbell1, Mario Herrero2, Stanley Karanja2,

Joseph Maitima2, Simon Mugatha2, Claude Mong’ong’o3, Simon Mwansasu3, Joseph Ogutu4, Mohammed Said2, Thomas Smucker5,

Edna Wangui5 ,Ben Wisner6 and Pius Yanda3

1Michigan State University; 2International Livestock Research Institute, Kenya3University of Dar es Salaam, Tanzania; 4 University of Hohenheim, Germany

5 Ohio University, 6 Oberlin College

Biocomplexity in the Environment Award 0709671


Climate Change•Temperature•Precipitation•Droughts•Floods

SavannaVegetation

Local level•Ecosystem structure (spp., composition, ratio woody/ herbaceous)•Forage quant & quality (palatability)

Regional level•Length of growing period•Ecosystem structure•Productivity

Temporal & spatial lag effects, non-linear response. Resilience to droughts

Land ManagementGrazing Scale:• Intensity• Mobility - Household• Length of Orbit - CommunityFire Frequency - RegionalLand Use

Livelihood Systems

- Non-farm

- Crops

- Livestock

Income diversification strategies within dynamic socio-economic system.Household Level decisions on: herd size and composition, grazing strategy, drought response

Landscape Level: fire frequency, land use conversion

Figure 1. The savanna human-land-climate system loop.

The EACLIPSE Loop


Goals

How are livelihood systems of pastoralists and agro-pastoralists responding to climate and vegetation change in the context of the evolving socioeconomic system? – What is the role of societal differentiation on resilience and

response to drought and to climate change?– How do vulnerability and coping strategies to drought evolve? – How does the role of livestock change? – How does land management change, and what effects does that

have on vegetation?

How does savanna vegetation respond to a changing climate?What are the combinatory effects of human land management

and climatic change impacts on savanna vegetation?


4

The context• Communities consist predominantly of Maasai, the

majority of whom are pastoralists and agro-pastoralists dependent almost entirely on livestock.

• They are therefore vulnerable when faced by drought or disease.

• Over the past few decades, changes such as communal land sub-division, reduction in rainfall, increased cultivation, and delineation of protected areas for wildlife have reduced grazing areas.

• These changes have aggravated the effects of drought and reduced effectiveness of former drought coping strategies; the systems are rapidly changing.


Field sites in southern box

7 transects crossing land use intensity gradients.

Kajiado District, Kenya: Risa, Mbirikani, Empiron villages, Amboseli Park

Simanjiro District, Tanzania: Kitwai, Namalulu, Terat Villages, Tarangire Park


Approach

• Multi-scale data collection and analysis, from the individual person and plant to communities.

• Socioeconomic and ecological information collected along transects crossing land use intensity gradients (from within a park, to grazing only, to mixed grazing/ crops) and representing different livelihood types

Ecological (60 main plots): – Plant species composition, counts, cover etc. conducted in dry

and wet seasons (3 times)– Soil sampling– Survey of mangers/ users of the plot on their perception of

changes in vegetation, land management changes, etc.(40, of which 20 repeated).


Transects, Kajiado Kenya


Vegetation plots

• 10 plots/LU type. Plots are 50 x 100m. • 8 25x25m quadrats/plot; 16 1x1 m quadats/plot• GPS pts, photos on transects.

50 m

N

25mx25m

E100 m

1 m x 1m


Variables recordedPlot size (m) Herbaceous Shrub Tree

25x25 (8/plot) Ranked five dominant sp (grass & herbs

•Ranked five dominant sp •Ranked five dominant sp

•Sp count •Sp count •% cover •% cover •Greenness •DBH •Leafyness •Greenness •Burn & age of burn •Leafyness

•Burn & age of burn •Damage, agent & degree, age of damage

1x1m (16/plot) •% cover •% bare ground •Sp count •Ht (m) •% litter •% greenness •Burn •Grazing levl •Types & no. animals in site


“Wet” & dry season


Species area curve for grasses in 3 land use types

0

5

10

15

20

25

30

35

40

45

5 10 15 20 25 30 35 40 45 50

Area (m2) thousands

Cum

ulat

ive

gras

s sp

crop/livestock

w ildlife/livestock

w ildlife

Species area curve for herbs in 3 land use types

0

20

40

60

80

100

120

5 10 15 20 25 30 35 40 45 50

Area (m2) thousandsC

umul

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e he

rb s

p

crop/livestock

w ildlife/livestock

w ildlife

Species area curve for shrubs in 3 land use types

0

5

10

15

20

25

30

35

40

45

5 10 15 20 25 30 35 40 45 50

Area (m2) thousands

Cum

ulat

ive

shru

b sp

crop/livestock

w ildlife/livestock

w ildlife

Species area curve for trees in 3 land use types

0

10

20

30

40

50

60

70

5 10 15 20 25 30 35 40 45 50

Area (m2) thousands

Cum

ulat

ive

tree

sp

crop/livestock

w ildlife/livestock

w ildlife

Plant spp area curves by LU typeGrasses Herbs

ShrubsTrees

Mid-level disturbance has greatest diversity of shrubs, trees. Fewer grass & herb spp in park, but more rare/ declining.

Green=crop/ livestockRed=livestock/ wildlifePurple=wildlife


Socioeconomic data collectionVillage level (6 representing 3 livelihood types):– Community mapping (single gender groups), – Wealth ranking, – Time line of livelihood/ climate/ movements,

Household surveys stratified by livelihood type (180+).


Wealth Ranking

Wealth Ranking Criteria Identified by Discussion Participants

Distribution of Households by Wealth RankEmpiron Mbirikani Risa

Wealthy 18 (12%) 39 (37%) 14 (44%)Middle 68 (45%) 36 (34%) 7 (22%)Poor 64 (43%) 30 (39%) 11 (34%)

Wealth Class Empiron Mbirikani RisaWealthy >5 acres, not leased

out; > 100 cattle; has employees; takes children to ‘academies’

> 100 cattle andemployment

> 100 cattle andAt least 30 acresOver six wivesEducated children

Poor Landless; No livestock; Casual worker

Less than 10 cattle;No employment

Less than 10 cattle;No wife or children


Mbirikani Timeline• 1976-77: rainfall decreased;

leaves, not grasses; People begin businesses, buying/selling lstock, bush clearing/ burning for agriculture;

• 1984 – major drought, lstock to Tsavo; further ag expansion; improved breeds become common by ‘86;

• 1990 – sedentarization proceeds; GR cttee and community meet seasonally to decide on grazing pattern;

• 2003 – breakdown in seasonal grazing system; people settle in Olopololi (drivers: anticipation of subdivision; opposition politics; scarcity of building materials);


Road within Impiron

Temporary river mentioned by men as well

1

2

3

4

Curio shop

5

6

Community Mapping


Trends (1)• Progressive declines in rainfall as evidenced by longer

dry spells, shorter rainy seasons and/ or complete failure of a rainy season.

• Livestock forage has reduced (due to lower rainfall, higher livestock densities).

• Bush encroachment has increased (e.g., Kitwai in Tanzania and Kuku/Lenkiporoi in Kenya) perhaps due to fewer fires (less biomass to burn, govt policy).

• Unpalatable bush spp increasing.• Grass is declining, especially preferred forage grass

sp. (e.g Erikaru, enkarmalasiai).


• Grazing pressure has increased in some areas as forage declines, due to:– Less rainfall (unpredictable)– Subdivision of land– Population pressure (human & animals)– More wildlife in some areas (increased awareness

and surveillance amid declined food resource base).

Trends (2)


• Daily movements are longer because settled & need to return home at night (if nomadic stay nearer forage). Often need to go further for grass and water.

• Land tenure & land use changing– From group ranches to individual parcels

– Cropping in previously grazing areas

– Some abandonment of fields due to failure of short rains

Trends (3)


The field, 2007-2009


Impact of drought on wildlife, livestock


Bare ground, and shrubs


Drought coping /adaptation (1)• Fewer animals generally, some people abandoning

livestock keeping• Long distance movements, much competition over

grass & water (privatization, conflict)• Sheep & goats survive better, herd composition

shifting• Trying different livestock breeds

– More camels, new goat and cattle breeds from Somalia

• More Maasai cultivating to cope with frequent drought.


- Traditionally the Arkasis (rich) split their herds into smaller units and loaned them to the middle income or poor. In return the keepers drank the milk and kept some heifers.

- Today the Arkasis sell a few bulls and hire someone to care for their animals. The Arkasis are diversifying into business, especially by selling livestock and investing in enterprises such as mining, trading.

- As pasture declines, not only is livestock keeping threatened but also traditional institutions & mutual cooperation.

Drought coping /adaptation (2)


Potential paths of diversification• Decline in livestock as a dependable resource?• Cropping receding at the frontier of rainfed

cultivation? • Future of tourism?• Changing urban remittances?

How will these affect diversification at the extremes of the wealth spectrum?


Research issues, questions

• Unknown reasons for woody bush encroachment. Hypotheses —fire suppression, grazing intensity, CO2 enhancement.... Or because plant types recover differently following more frequent/ longer dry periods?

• Changing rainy seasons, plant phenologies affecting plant spp, types, biomes differently.

• How will livelihood systems change as drought coping evolves to climate change adaptation?


Thank you.


• General observations/ Tanzania– More species varieties in the unprotected area than the

protected area.– Some spp are disappearing/decreasing in the unprotected

area. Such as:

• -Brachiaria brizantha• -Chloris wodii• -Setaria verticillata• -Themeda triandra• -Dactyloctenium aegyptium• -Cynodon dactylon, etc.


–Some spp are emerging/increasing in the unprotected area. Such as:

• -Aristida adoensis• -Accacia melifera• -commiphora africana• -Crotalaria steudneri• -Euphobia cuneata• -Euphobia candelabrum• -Maytenus senegalensis• -Accacia nilotica, etc.