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Presentation at workshop: Reducing the costs of GHG estimates in agriculture to inform low emissions development November 10-12, 2014 Sponsored by the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) and the Food and Agriculture Organization of the United Nations (FAO)
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Approaches to Activity data collection in livestock systems
Ed Charmley, CSIRO TownsvilleHayley Norman, CSIRO Perth
ED.CHARMLEY@CSIRO.AU
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BEEF DAIRY PIGS BUFFALO CHICKENS SMALL RUMINANTS
OTHER PUOLTRY
Mill
ion
to
nn
es C
O2
-eq
uiv
Total livestock emissions • 7.1 gigatonnes CO2 -equiv
• 14.5% of global anthropogenic emissions
Global estimates of GHG emissions
Source: Tackling Climate Change through Livestock, FAO 2013
Global emissions intensity
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Beef Dairy Smallruminants
meat
Smallruminants milk
Pork
Kg
CO
2 –
eq
uiv
/kg
pro
tein
Source: Tackling Climate Change through Livestock, FAO 2013
Overview
1. Estimating animal numbers, weight, physiological state
2. Temporal/spatial distribution/scale Seasonality
Selective grazing
3. Measurement techniques for benchmarking Laser
4. Methane proxies F-NIRS
Intake
5. Cost effective methods for benchmarking and mitigation
Estimating cattle numbers, weight, physiological state
Bovine livestock units density in the year 2000 (from Herero et al 2013).
Problems
• How many animals?• National and regional statistics
• Market information
• Processed feed consumption
• How large are the animals?• Body weight
• Herd structure
• Body condition
• Physiological state• Growing
• Mature
• Lactating
• gestating
Some thoughts on estimating animal numbers
• Census data is unreliable (snapshot in time)
• What are the alternatives?• Catch and release methodology?
• Arial surveillance of animals?
• landscape condition
• Landscape condition = grazing pressure / pasture growth
• Pasture growth = land class x rainfall
Temporal/spatial distribution,scale
Measurement across scale and uncertainty
In vitro Chamber Poly tunnel Laser ModelMethane Map for Australia after Bentley
Diet selection – intensity and availability
An issue of scale
100 ha 500 ha
1500 ha
25000 ha
Replicated experiment
>50 ha per animal
15 ha per animal
5 ha per animal
Spatial grazing behaviour
Australia’s spatial distribution of methane
Methane emissions by bovines in the year 2000 (from Herero et al 2013).
Measurement techniques for benchmarking
A strong relationship between intake and methane production (Charmley et al. unpublished)
y = 21. 6 x DMIR² = 0.96n = 1000
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Met
han
e (
g/d
)
DMI (kg/d)
Can we predict intake?
From Herrero et al. 2013
Using laser to measure methane emissions at Douglas Daly Research Station, NT
•Field based remote measurement
•Open path laser
Spatial variability
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Tropic of Capricorn
Average methane emissions across 6 properties in N. Australia (equated to 450 kg beast)
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Met
han
e (g
/d)
Property
?242 g/d
Proxies for Methane:NIR – tried and tested
FNIRS for methane (Dixon and Kennedy, unpublished)
y = 0.6139x + 53.038R² = 0.631
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Pre
dic
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/da
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Reference_CH4_L/day
Pred_CH4/day
NIRS method for international methane inventory • Reference open circuit respiration chambers
• South America, Africa, Australia, SE Asia
• Faecal and feed samples associated with individual animal measurement collected, stored and processed under standard methods
• Each feed/faeces sample set associated with individual animal methane emission (g/kg DMI)
• Standardised in country NIRS capability• Does not require high level technical competency
• Machines linked into international network
• Centralized data processing
• All data into a global correlation
• Clustring of like samples to improve predictions.
• Centralized NIRS expertise (e.g. CSIRO, INRA, other)• Wet chemistry to help with predictions
• NIRS for plant quality simultaneously.
• Can we predict CH4 from diet?
A CSIRO plan for Australia – extend to international?• That CSIRO, either independently or in collaboration with others, should develop a program of
research to develop a robust faecal NIR method for the estimation of livestock methane emissions for Australia
• CSIRO have the equipment and technical capability at the Floreat Lab in Perth to undertake a broad-scale analytical/NIR study of faeces and feeds collected from cattle and sheep studies where methane production has been measured directly using open circuit respiration chambers.
• The dataset is increased by negotiating access to all samples and data generated under:
The Livestock Methane Research Cluster. Cluster members have already been discussing this idea and are keen to take it further.
Negotiation with the National Livestock Methane Program to access samples generated as part of that research program to further expand the database.
• The main components of the work would involve:
Collection of samples and associated data on intake and methane emission related to each feed/faecal sample pair.
Processing and running samples through Spectrastar NIR equipment in Perth
Timeframe would be November 2014 to June 2015.
Approximate budget would be in the $40,000 to $50,000 range.
Thank youAgriculture Flagship
Ed CharmleyGroup Leadert +61 7 4753 8586 e ed.charmley@csiro.auw www.csiro.au
AGRICULTURE FLAGSHIP
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