Impact of climate change on the livestock component of mixed farming systems

Transcription

1 Impact of climate change on the livestock component of mixed farming systems Descheemaeker, Zijlstra, Ramilan, Senda, Timpong-Jones, Nenkam, Sajid, Singh, Baigorria, Adam, Shalandar, Whitbread

2 - Worldwide geographic spread Crop-livestock farming systems - Majority of livestock keeping households - Largest share of meat and milk production in the tropics - Livelihoods of many poor farmers Mostly rainfed in Africa Mostly irrigated in south Asia

3 Objectives Livestock model calibration and testing for typical smallholder systems of West and southern Africa, south India, and Indo- Gangetic Basin Assess the impact of climate change on the livestock component of crop-livestock systems Compare impacts for different types of households (later stage: assess effects of adaptation options on livestock)

4 Climate Change Effects on Mixed Systems Climate change Temperature, rainfall, CO 2 Crop Livestock Grazing land APSIM,DSSAT Maize Sorghum Groundnut Mucuna On-farm fodder availability LIVSIM Herd size Milk production Offtake Mortality Manure production Potential pasture intake APSIM Grass production Fertilizer rates Sowing dates Soil types Farm size Crop allocation Herd size Herd management Rangeland area Stocking rate Household information 160 households, 3 types

5 LivSim structure Parameters - Breed characteristics Cow Cow Cow Cow Inputs - Feed quantity and quality - Herd size & composition - Herd management Potential growth & intake Nutritive requirements - Maintenance - Growth - Gestation - Lactation Actual growth & intake Outputs - Milk - Calves and offtake - Manure Herd Model calibration and performance evaluation reported in Rufino et al., 2009; 2011

6 New breed calibrations Mali: Mere Ghana: Ghana Shorthorn Zimbabwe: Nkone Malawi: Malawi Zebu India IGB: Sahiwal South India: Cross-bred Jersey Pakistan: Nili Ravi 6

7 Calibration Nkone Breed, Zimbabwe 7

8 Calibration Milk production, Local breeds Zimbabwe Length of lactation 10 months, milk yield: 915 kg/lactation 8

9 Model testing Body weight + feed input data à Data hard to find (esp. for African system) à Work in progress From Rufino, 2009

10 Model comparison with survey data Comparison simulated output against reported data - Data from household survey - Farmer-reported yield, not observed! 10

11 Model performance test Mean simulated annual milk production: 860 kg / year Mean observed annual milk production: 584 kg / year Using length of lactation from secondary data: 305 days 11

12 Model performance test Mean simulated mortality rate: 0.11 Mean observed mortality rate:

13 Model performance test Mean simulated number of calves: 2.1 Mean observed number of calves:

14 Climate Climate model classification for Nkayi, Zimbabwe 5 climate scenarios - Middle - - Cool-dry - Hot-wet - Comparison with baseline Graph design by Alex Ruane 14

15 Feedbase Zimbabwe Seasonal variation in fodder availability IGB No feed gaps Intake variation in line with requirements Pasture Crop residues Roughage Concentrates 15

16 Grazing component standing biomass Rangeland productivity modelled with GRASP in APSIM Zimbabwe Mali

17 Grazing component Biomass intake Biomass intake ~ biomass availability, stocking density Zimbabwe 1.5 ha/tlu Mali 0.5 ha/tlu

18 On-farm fodder Zimbabwe Type 1: No cattle 1.4 ha Type 2: < 8 cattle 2.0 ha Type 3: > 8 cattle 2.6 ha Mali Type 1: <2 cattle 5.4 ha Type 2: >2 cattle 9.8 ha Type 3: >12 cattle 11.6 ha Type 4: >20 cattle 12.3 ha 18

19 On-farm fodder All crop components modelled - For baseline & future climate scenarios - For APSIM & DSSAT 19

20 On-farm fodder South India Type 1: Maize-based 0.9 ha Type 2: Rice-based 0.8 ha Type 3: Maize-Rice 2.0 ha IGB Type 1: < 1 ha Type 2: 1-2 ha Type 3: >2 ha 20

21 On-farm fodder South India Maize and rice (both irrigated) are modelled Grass and concentrates constant IGB Wheat (irrigated) is modelled Other crops linked to wheat Concentrates constant 21

22 Impact of climate change Zimbabwe Six example households 22

23 Zimbabwe Comparison between farm types 2 (< 8 cows) and 3 (>8 cows) Comparison between fodder input simulated with APSIM and DSSAT 23

24 South India Comparison between farm types 1 (maize-base), 2 (rice-based) and 3 (maize-rice) Comparison between fodder input simulated with APSIM and DSSAT 24

25 Challenges in modelling impact of climate change Asian systems - Irrigated forages - On-farm fodder supply > demand - Concentrates as fixed input àeffects of climate change mostly outside the system African systems - Grazing is major component, but uncertain - Data scarcity, especially on animal performance when under-fed 25

26 Conclusions Integrated modelling framework: assess effects on crops, rangeland and livestock Take into account farm heterogeneity LivSim captures indirect effects of climate change through changes in feed production Negative effect of dry climate change scenarios on rangeland productivity, on-farm fodder production for rainfed crops Negative effect of dry climate change scenarios on livestock productivity only in systems that depend on rainfed fodder resources

27 THANK YOU