rapid ex-ante environmental impact assessment of livestock
TRANSCRIPT
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: [email protected]
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