Rapid ex-ante environmental impact assessment of livestock intensification strategies on mixed crop-livestock and agro-pastoralist farmers in Tanga region, Tanzania

Birthe K. Paula, Celine Birnholza, Jessica Kogea, Simon Fravalb, Jamie McFadzeanc, Amos Omoreb, An Notenbaerta

Background

• Livestock production supports around 600 Mio. smallholders in the developing world

• Environmental impacts include water pollution, global warming, soil degradation, water use and pollution, and biodiversity loss

• Long-term sustainability needs to be assessed before designing large-scale livestock development projects, but data is sparse and quick results needed

• Therefore, a quick ex-ante environmental impact assessment tool was developed, focusing on soil nutrient balances and greenhouse gas emissions1

Results

Materials and Methods

• A participatory GIS exercise2 in June 2014 in Lushoto, Tanga region, Tanzania, resulted in two types of farming systems: intensive mixed crop-livestock systems and extensive agro-pastoral systems (Figure 1 and 2)

• Representative farms of both types were visited and interviewed in May 2015 in Lushoto (mixed crop-livestock) and Handeni (agro-pastoral). Data was complemented with a previously conducted feed assessment in the area3. Data described agro-ecology, crops, land use, inputs, livestock herd, manure, and livestock feeding

• Intervention scenarios were based on village development plans from both sites: improved breeds, improved feeding, and increased animal health

• Modeling of farm-level GHG emissions was based on IPCC tier 2 guidelines4

• Nutrient balances were calculated using the NUTMON method5

Figure 2. Farming systems in Lushoto and Handeni as mapped by the participants of a

participatory GIS workshop (from Morris et al. 2014)

Results and discussion

• Enteric fermentation is the largest contributor to GHG emissions

• Emission intensities are higher for mixed crop-livestock systems when

measured per area, but lower per liter milk produced

• N balances are negative for mixed farming, and positive for agro-

pastoralists due to the manure produced by the relatively big herd

• Livestock intensification strategies result in almost all cases in lower

emission intensities, especially in the agro-pastoral system

• Further work: outscaling to regional level, flagging risks into

low/medium/high, feeding results into regional/national dairy platforms

AcknowledgementsThis research was funded by the Bill and Melinda Gates Foundation (CLEANED project), USAID

Linkage funds, BBSRC International Partnering Award, and a BSAS travel research grant. The

work took place under the CGIAR Research Program on Livestock and Fish.

A International Center for Tropical Agriculture (CIAT), Kenya; b International Livestock Research Institute (ILRI), Tanzania;c Rothamsted Research North Wyke (Rres-NW), UK

*Corresponding author, e-mail: B.Paul@cgiar.org

References1. Notenbaert, A., Lannerstad, M., Herrero, M., Paul, B., Fraval, S., Ran, Y., Mugatha, S., Barron, J. (2014). A framework forenvironmental ex-ante impact assessment of livestock value chains. All African Animal Agriculture Conference Paper.

2. Morris, J., Fraval, S., Githoro, E., Mugatha, S., Ran, Y. (2014). Participatory GIS expert workshop report in Lushoto. SEI, ILRI.3. Mangesho, W., Loina, R., Bwire, J., Maass, B.L., Lukuyu, B. (2013). Report of Feeding System Assessment (FEAST) in Lushoto.TALIRI, CIAT, ILRI.4. International Panel for Climate Change (IPCC) (2006). IPCC Guidelines for National Greenhouse Gas Inventories, Prepared by theNational Greenhouse Gas Inventories Programme, Eggleston H.S., Buendia L., Miwa K., Ngara T. and Tanabe K. (Eds).5. Vlaming, J., van den Bosch, H., van Wijk, M.S., de Jager, A., Bannink, A., van Keulen, H. (2001). Monitoring nutrient flows andeconomic performance in tropical farming systems. Annex. Alterra, the Netherlands.

Figure 1. Manure heap in mixed crop-livestock system (left); agro-pastoralist family (middle);

zero-grazing unit in mixed crop-livestock farm (all pictures Jessica Koge, CIAT)

Figure 3. Baseline GHG per farm type in per area and milk basis (left); baseline sources of

GHG emissions in % for the different farm types (right)

C. Birnholz C. Birnholz

C. Birnholz C. Birnholz

Enteric

fermentation-Methane

80%

Manure-

Methane 2%

Manure-

Direct N2O2%

Manure-

Indirect N2O2%

Soil-Direct

N2O9%

Soil-Indirect

N2O1%

Burning

0%

Rice

production-Methane

0% Carbon stock

changes-SOC4%

Agropastoralist

Enteric

fermentation-Methane

71%Manure-Methane

5%

Manure-

Direct N2O4%

Manure-

Indirect N2O3%

Soil-Direct

N2O6%

Soil-Indirect

N2O2%

Burning

9%

Rice

production-Methane

0%Carbon

stock changes-

SOC

0%

Mixed crop-livestock0.0

200.0

400.0

600.0

800.0

1000.0

1200.0

1400.0

baseline

kg C

O2-e

q h

a-1

GHG per area

Agropastoralist

Mixed crop-

livestock

0.0

0.5

1.0

1.5

2.0

2.5

3.0

baseline

kg C

O2-e

q k

g F

PC

M-1

GHG per milk produced

Agropastoralist

Mixed crop-

livestock

Figure 5. Nitrogen balances for baseline and scenarios (left); cropping system diversity in

mixed crop-livestock system (right)

-60

-40

-20

0

20

40

60

80

100

baseline Improvedbreeds

Improvedfeeding

Increasedanimal health

kg N

ha-1

N balance per area

Agropastoralist

Mixed crop-livestock

Figure 4. Livestock kraal in agropastoral system (left); changes in GHG emission intensity

Nutrient balances of baseline and scenarios (right)

-50

-40

-30

-20

-10

0

10

20

Improvedbreeds

Improvedfeeding

Increasedanimal health

% c

hange o

f kg C

O2-e

q k

g F

PCM

-1

com

pare

d to b

aseline

% change in GHG per milk produced

Agropastoralist

Mixed crop-livestock