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Annex 3: Detailed methodologies for source or sink categories
Annex 3.A The agriculture sector
New Zealand's methodology uses a detailed livestock population characterisation and livestock productivity data to calculate feed intake for the four largest categories in the New Zealand ruminant population (dairy cattle, beef cattle, sheep and deer). The amount of CH4 emitted is calculated using CH4 emissions per unit of feed intake. An overview of the model is presented in Figure A3.1 with detailed information provided in the following sections.
3A.1 Enteric methane emissions
Livestock Populations
The New Zealand ruminant population can be separated into four main categories: dairy cattle, beef cattle, sheep and deer. For each livestock category, population models that further sub-divided the principle categories were developed. These models reflect New Zealand farming systems with regard to the timing of births, timing of slaughter of growing animals and the transfer of younger animals into the breeding population.
Animal numbers are provided by Statistics New Zealand from census and survey data. As shown in the tables, three-year rolling averages are used throughout the agricultural sector for population numbers.
For sheep, dairy cattle, non-dairy cattle and deer the three-year average populations are adjusted on a monthly basis to take account of births, deaths and transfers between age groups. This is necessary because the numbers present at one point in time may not accurately reflect the numbers present at other times of the year. Goats are also included in the analysis, but a separate model has not been developed. This is because goats represent only a very small proportion of the total animal population and numbers have dropped significantly in recent years.
Livestock productivity data
For each livestock category, the best available data were used to compile the inventory. To ensure consistency, the same data sources have been used each year. This ensures that the data provide a time-series that reflects changing farming practices, even if there is uncertainty surrounding the absolute values.
Obtaining data on the productivity of ruminant livestock in New Zealand, and how it has changed over time, is a difficult task. Some of the information collected is robust i.e. the slaughter weight of all livestock exported from New Zealand are collected by the MAF. This information is used as a surrogate for changes in animal liveweight. Other information is collected at irregular intervals or from small survey populations. In general, no routine comprehensive surveys are conducted except for slaughter weight of animals.
Livestock productivity and performance data are summarised in the time-series tables accompanying the agriculture sector (Chapter 6). The data includes average liveweights, milk yields and milk composition of dairy cows, average liveweights of beef cattle (beef cows, heifers, bulls and steers), average liveweights of sheep (ewes and lambs), average liveweights of deer (breeding and growing hinds and stags) and monthly energy concentrations of the diets consumed by beef cattle, sheep, dairy cattle and deer.
Dairy cattle: data on milk production were provided by the MAF. These data include the amount of milk processed through New Zealand dairy factories plus an allowance for town milk supply. Annual milk yields per animal are obtained by dividing the total milk produced by the total number of milking dairy cows and heifers. Milk composition data were taken from the Livestock Improvement Corporation (LIC) national statistics. For all years, lactation length was assumed to be 280 days.
Average weight data for dairy cows were obtained by taking into account the proportion of each breed in the national herd and its age structure based on data about breed and age structure from the LIC. Dairy cow liveweights are only available from 1996 onwards. For earlier years in the time-series, liveweights are estimated using the trend in liveweights from 1996 to 2002 together with data on the breed composition of the national herd. Growing dairy replacements at birth are assumed to be 9% of the weight of the average cow and 90% of the weight of the average adult cow at calving. Growth between birth and calving (at two years of age) is assumed to be linear. The birth date of all calves was assumed to be mid-August.
No data are available on the liveweights and performance of breeding bulls and an assumption was made that their average weight was 500 kg and that they are growing at 0.5 kg per day. This was based on expert opinion from industry data. For example, dairy bulls range from small Jersey's through to large framed Continentals. The assumed weight of 500 kg and growth rate of 0.5 kg/day provide an average weight (at the mid point of the year) of 592kg. This is almost 25% higher than the average weight of a breeding dairy cow but it is realistic given that some of the bulls will be of a heavier breed/strain (e.g. Friesian and some beef breeds). Because these categories of animal make only small contributions to total emissions e.g. breeding dairy bulls contribute 0.089% of emissions from the dairy sector, total emissions are highly insensitive to the assumed values.
Beef Cattle: the principle source of information for estimating productivity was livestock slaughter statistics provided by the MAF. All growing beef animals are assumed to be slaughtered at two years of age and the average weight at slaughter for the three sub-categories (heifers, steers and bulls) was estimated from the carcass weight at slaughter. Liveweights at birth are assumed to be 9% of an adult cow weight for heifers and 10% of the adult cow weight for steers and bulls. Growth between weight at birth and slaughter is assumed to be linear.
Weights in slaughter statistics from the MAF do not separate carcass weights of adult dairy cows and adult beef cows. Thus a number of assumptions [Number of beef breeding cows assumed to be 25% of the total beef breeding cow herd; other adult cows slaughtered assumed to be dairy cows. Carcass weight of dairy cattle slaughtered was estimated using the adult dairy cow liveweights and a killing out percentage of 40%. Total weight of dairy cattle slaughtered was then deducted from the national total carcass weight of slaughtered adult cows. This figure was then divided by the number of beef cows slaughtered to obtain an estimate of the carcass weight of adult beef cows; liveweights are then obtained assuming a killing out percentage of 45%.] are made in order to estimate the liveweights of beef breeding cows. A total milk yield of 800 litres per breeding beef cow was assumed.
Sheep: livestock slaughter statistics from the MAF are used to estimate the liveweight of adult sheep and lambs, assuming killing out percentages of 43% for ewes and 45% for lambs. Lamb birth liveweights are assumed to be 9% of the adult ewe weight with all lambs assumed to be born on 1st September. Growing breeding and non-breeding ewe hoggets are assumed to reach full adult size at the time of mating when aged 20 months. Adult wethers are assumed to be the same weight as adult breeding females.
No within year pattern of liveweight change was assumed for either adult wethers or adult ewes. All ewes rearing a lamb are assumed to have a total milk yield of 100 litres. Breeding rams are assumed to weigh 40% more than adult ewes. Wool growth (greasy fleece growth) was assumed to be 5kg/annum in mature sheep (ewes, rams and wethers) and 2.5kg/annum in growing sheep and lambs.
Deer: liveweights of growing hinds and stags are estimated from MAF slaughter statistics, assuming a killing out percentage of 55%. A fawn birthweight of 9% of the adult female weight and a common birth date of mid-December are assumed. Liveweights of breeding stags and hinds are based on published data, changing the liveweights every year by the same percentage change recorded in the slaughter statistics for growing hinds and stags above the 1989 base. No within year pattern of liveweight change was assumed. The total milk yield of lactating hinds was assumed to be 240 litres (Kay, 1985).
Goats: enteric CH4 from goats is not a key source category. There is no published data on which to attempt a detailed categorisation of the performance characteristics in the same way as has been done for the major livestock categories. CH4 emissions from goats for all years are assumed to average the same per head as the average sheep in 1990 (i.e. total sheep emissions/total sheep number). The goat value was not indexed to sheep over time because there is no evidence to support the kind of productivity increases that have been seen in sheep.
Dry matter intake calculation
Dry matter intake(DMI) for the classes (dairy cattle, beef cattle, sheep and deer) and sub-classes of animals (breeding and growing) was estimated by calculating the energy required to meet the levels of performance assumed and dividing this by the energy concentration of the diet consumed. For dairy cattle, beef cattle and sheep, energy requirements are calculated using algorithms developed in Australia (CSIRO, 1990). These are chosen as they specifically include methods to estimate the energy requirements of grazing animals. The method estimates a maintenance requirement (a function of liveweight, the level of productivity and the amount of energy expended on the grazing process) and a production energy requirement - influenced by the level of productivity (e.g. milk yield and liveweight gain), physiological state (e.g. pregnant or lactating) and the stage of maturity of the animal. All calculations are performed monthly.
For deer, an approach similar to that used for cattle was adopted using algorithms derived from New Zealand studies on red deer. The algorithms take into account animal liveweight and production requirements based on the rate of liveweight gain, sex, milk yield and physiological state.
Monthly energy concentrations
A single set of monthly energy concentrations of the diets consumed by beef cattle, dairy cattle, sheep and deer was used for all years in the time-series. This is because there is no comprehensive published data available that allows the estimation of a time-series dating back to 1990.
Methane emissions per unit of feed intake
There are a number of published algorithms and models [For example Blaxter and Clapperton,1995; Moe and Tyrrel, 1975; Baldwin et al., 1988; Djikstra et al., 1992; and Benchaar et al., 2001 - all cited in Clarke et al., 2003.] of ruminant digestion for estimating CH4 emissions per unit of feed intake. The data requirements of the digestion models make them difficult to use in generalised national inventories and none of the methods have high predictive power when compared against experimental data. Additionally, the relationships in the models have been derived from animals fed indoors on diets dissimilar to those consumed by New Zealand's grazed ruminants.
Since 1996, New Zealand scientists have been measuring CH4 emissions from grazing cattle and sheep using the SF6 tracer technique (Lassey et al, 1997; Ulyatt et al, 1999). New Zealand now has one of the largest data sets in the world of CH4 emissions from grazing ruminants. A database of these data are being constructed and systematically examined to obtain generalised relationships between feed characteristics and CH4 emissions. As an interim measure, published and unpublished data on CH4 emissions from New Zealand were collated and average values for CH4 emissions from different categories of livestock obtained. Sufficient data were available to obtain values for adult dairy cattle, sheep more than one year old and growing sheep (less than one year old). These data are presented in Table 3A1 together with IPCC (2000) default values for percent gross energy used to produce CH4. The New Zealand values fall within the IPCC range and are adopted for use in this inventory calculation. Table 3A.2 shows a time-series of CH4 implied emission factors for dairy cattle, beef cattle, sheep and deer.
Not all classes of animals are covered in the New Zealand data set and assumptions had to be made for these additional classes. The adult dairy cattle value was assumed to apply to all dairy and beef cattle irrespective of age and the adult ewe value was applied to all sheep greater than one year old. A mean of the adult cow and adult ewe value (21.25g CH4/kg DMI) was assumed to apply to all deer. In very young animals receiving a milk diet, no CH4 was assumed to arise from the milk proportion of the diet.
Table 3A.1 Methane emissions from New Zealand measurements and IPCC defaults
| Adult dairy cattle | Adult sheep | Adult sheep < 1 year | |
|---|---|---|---|
New Zealand data (g CH4/kg DMI) |
21.6 |
20.9 |
16.8 |
New Zealand data (%GE) |
6.5 |
6.3 |
5.1 |
IPCC (2000) defaults |
6 ± 0.5 |
6 ± 0.5 |
5 ± 0.5 |
In the 2001 inventory, changes to the emission factors from the previous fixed emission factors for sheep, deer and goats caused significant differences. The downward revision for sheep was explained by:
- A fall of 15 to 20% in the estimate of CH4 emissions per unit of intake in older sheep.
- An almost 30% decrease in the estimated emissions per head in younger sheep.
- The ewe and lamb liveweights assumed for the earlier emissions factor are 10% higher than those in the 2001 inventory.
- The previous model kept animal numbers constant throughout the year and had only three categories (ewes, lambs and growing sheep) whereas the revised 2001 model takes into account ewe and lamb mortality and has nine classes. Several of the animal classes have lower intakes and consequently lower CH4 emissions than the growing sheep class.
- Technical errors were also made in the previous estimates of CH4 emission per head from deer and goats. These errors are corrected.
Table 3A.2 Time-series of implied emission factors for enteric fermentation (kg methane per animal per annum)
3A.2 Uncertainty of animal population data
Details of the most recent surveys and census is included to provide an understanding of the livestock statistics process and uncertainty figures. The information documented is from Statistics New Zealand.
2003 Agricultural Production Survey
The target population for the 2003 Agricultural Production survey was all businesses engaged in agricultural production activity (including livestock, cropping, horticulture and forestry) with the intention of selling that production and/or which owned land that was intended for agricultural activity during the year ended 30 June 2003. The estimated proportion of eligible businesses responding to the 2003 Agricultural Production Survey is 85 percent. These businesses contribute 87 percent of the total agricultural output. The sample error and percentage imputed are shown in Table 3A3.
2002 Agricultural Production Census
The target population for the 2002 Agricultural Production census was all units that were engaged in agricultural production activity (including livestock, cropping, horticulture and forestry) with the intention of selling that production and/or which owned land that was intended for agricultural activity during the year ended 30 June 2002. The target population also includes businesses and persons commonly referred to as 'lifestylers' engaged in agricultural production activity. The response rate was 81 percent. Statistics New Zealand imputed values for farmers and growers in the 2002 Agricultural Production Census who have not returned a completed questionnaire. The method of imputation is random 'hot deck' imputation.
Table 3A.3 Provisional sampling error and imputation levels for the 2003 Agricultural Production survey
1999 Livestock Survey
The frame for the 1999 Agricultural Production survey was based on a national database of farms called AgriBase which is maintained by AgriQuality New Zealand Ltd (formerly MAF Quality Management). A sample survey was conducted to obtain estimates of livestock on farms and area sown in grain and arable crops for the 30 June 1999 year. Questionnaires were sent to approximately 35,000 farms. The overall response rate for the survey was 85.7 percent. The remaining units were given imputed values based on either previous data or on the mean value of similar farms. Table 3A4 gives the sample errors based on a 95% confidence level for the survey data collected in 1999.
Table 3A.4 Agricultural sector sample errors based on 95% confidence level
| Variable (total population) | Survey design error (%) | Achieved sample error (%) |
|---|---|---|
Dairy cattle |
1 |
1.0 |
Beef cattle |
1 |
0.9 |
Sheep |
1 |
0.7 |
Goats |
1 |
1.5 |
Deer |
1 |
1.4 |
Pigs |
1 |
0.9 |
Annex 3B Research on the carbon stocks in soils, scrub and natural forests
Major work in the LUCF sector includes research and implementing monitoring of the carbon stocks and fluxes in soils, shrublands and indigenous forests. This research was initiated by the MfE in 1996 and is being carried out jointly by two of New Zealand's Crown Research Institutes - Landcare Research and Forest Research. The research has provided information to fill some major gaps in the current inventory for LUCF including impacts of land-use change (including abandonment of managed lands). This five-year research project had the following objectives:
- The estimation of carbon storage in soils, shrublands and indigenous forests in 1990.
- The development of a national system to determine soil carbon changes associated with land-use change.
- The development of an effective information system to manage the above information.
Provisional results are available from the work under the first objective. Hall et al. (1998) have estimated that in 1990 carbon stored in indigenous forests was 933 MtC, while 527 Mt C was stored in shrublands and other woody mixed-vegetation. Forest floor litter carbon is estimated separately, based on Tate et al.(1997), as containing 570 Mt C for all natural vegetation (i.e. both forest and scrub areas). These estimates are highly sensitive to both the accuracy of mapped areas and heterogeneity within mapped classes. Current (very provisional) estimates for soil carbon at soil depth intervals of 0-0.1, 0.1-0.3 and 0.3-1m are 1300±20, 1590±30 and 1750±70 Tg C respectively (Tate et al., 2003). Some soil cells are still poorly represented in the database and additional field work is being undertaken. Further information on this project and initial estimates of carbon stocks at 1990 are found in Coomes et al. (2002), Lawton and Barton (2002), Lawton and Calman (1999) and Hall et al. (1998).
In 1999, the soil and vegetation carbon monitoring systems (CMS) developed during the first three years of the project were reviewed by an international panel of forestry and soil experts. The panel's report concluded that the systems being developed for New Zealand's indigenous forests are consistent with current forest inventory practices in other countries. Furthermore, the soils that the system represented are measured in a significantly advanced methodology as compared with the IPCC default method (Theron et al., 1999). The international review of the system was held in time for the key recommendations of the review to be undertaken before the development phase was concluded.
The statistical design of the vegetation CMS provides for the establishment of 1400 permanent field plots on an 8x8 km grid across indigenous forest and shrublands for territorial New Zealand (Coomes et al., 2002). This includes the North and South Islands, Stewart Island, the Chatham Islands and other offshore islands. The vegetation CMS records a range of standard tree and other botanical measurements and site characteristics for each 20x20m plot. The soil CMS analyses soil samples to a depth of 0.3m for carbon content. One in every three of the vegetation plots is sampled for soils.
The CMS's for soil and vegetation are currently moving from design to implementation. The first year's fieldwork for the operational vegetation CMS commenced in January 2002 and was completed in early 2003. The second year's fieldwork began in March 2003. Fieldwork over at least three more years will be required to install the complete network of field plots. Following this, another five-year round of sampling will be required to validate the implementation and begin monitoring of any changes. The current intention is then to repeat these measurements every ten years.
For the soil CMS, 40 soil-paired plots sites will be established to monitor key changes in soil carbon when land-use changes, i.e. scrub to grassland, grassland to Kyoto forest and vice versa. The first four paired plots sites were established in 2003.
A nationwide Land Cover Database (LCDB1) which contains 18 land cover types was completed in 2000. SPOT satellite imagery from 1996/1997 provided the key information inputs to LCDB1. A further national mapping exercise for LCDB2 will be completed by July 2004. LCDB2 increases the number of land cover classes mapped (to 43) and improves the thematic depth for forest classes. LCDB2 is also likely to draw on ancillary land use data from annual landowner surveys.
