Approaches to Activity data collection in livestock systems Ed Charmley, CSIRO Townsville Hayley Norman, CSIRO Perth

ED.CHARMLEY@CSIRO.AU

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BEEF DAIRY PIGS BUFFALO CHICKENS SMALL RUMINANTS

OTHER PUOLTRY

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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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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

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 unpublished)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 DMI R² = 0.96 n = 1000

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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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Proxies for Methane: NIR – tried and tested

FNIRS for methane (Dixon and Kennedy, unpublished)

y = 0.6139x + 53.038 R² = 0.631

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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 you Agriculture Flagship

Ed Charmley Group Leader t +61 7 4753 8586 e ed.charmley@csiro.au w www.csiro.au

AGRICULTURE FLAGSHIP