COMBINED PRESENTATIONS

This section presents the first experimental step in compiling combined presentations for Australian agriculture in accordance with the SEEA AFF Framework. Some of the desired indicators within each account are not yet available and feedback is sought from users about the potential uses of these accounts, additional sources of data, and priority data gaps. See Approach taken and future plans section.


SEEA AFF FRAMEWORK: COMBINED PRESENTATIONS

Combined presentations are a powerful mechanism for bringing together data on complex topics where insights are required into the relationships between cross-cutting themes like employment, water use, production, consumption, and environmental impacts. They use consistent concepts and methods (e.g. reporting years, indexation), classifications (e.g. consistent industry standards) and units of measure to combine diverse indicators for initial analysis. This provides a window into the underlying detailed data.

These presentations integrate both physical and monetary data and are designed to display these data for analysis and the derivation of indicators. They aim to promote discussion between economists and scientists to bring narratives together. In addition, they show that a range of issues may be considered once sound underlying accounts are constructed, and provide an information base for the development of models. For these reasons, combined presentations are a key feature of the SEEA Central Framework. For more information on combined presentations, refer to Chapter 6 of the SEEA Central Framework.

There is much flexibility in terms of these presentation formats, depending on the questions of interest, the availability of data, and the topic of measurement. A number of alternative structures are shown in the Downloads tab, including:

• Combined presentation, Australia 2015-16 (Table 25.1)
• Activity and product specific inputs, Australia, 2015-16 (Table 25.2)
• Food product consumption and waste, Australia, 2015-16 (Table 25.3)
• Use of environmental assets, Australia, 2015-16 (Table 25.4)
• Cross industry and activity perspectives, Australia, 2013-14 (Table 25.5).

POLICY RELEVANCE AND USE

The Agriculture, forestry and fishing contribute significantly to feeding, clothing, and housing populations. Participants in these industries have a direct relationship with the natural environment.

Globally, the long-term business sustainability of agriculture, forestry and fishing activities is increasingly understood to be underpinned by environmental sustainability. For this reason, a variety of environmental information relevant to agriculture, forestry and fishing is collected by a wide range of organisations in Australia. This information sits alongside a range of data related to the socio-economic activities and benefits of Australian agricultural, forestry and fisheries industries.

Industry, policymakers, researchers and analysts have sought mechanisms to bring these data together to understand complex interrelationships between our economy and the environment. One of the main rationales for the SEEA is to facilitate the comparison of data across domains, particularly in comparing environmental stocks and flows with economic data such as production. This capability is provided by the SEEA Central Framework's combined presentations.

A number of specific policy drivers for measures covered in this discussion paper are outlined in each of the themed sections.


SELECTED COMBINED PRESENTATION EXAMPLES

Wheat and Beef

One of the benefits of combined presentations is the ability to draw together various indicators from a range of related variables. One method of displaying indicators with different units of measurement is by using an index. An index in this context expresses the difference between two measurements based on the percentage change to the base year (e.g. how measures move from a point in time). Graphs 1 and 2 below show an index of different variables related to wheat and beef production.

The gross value of wheat production decreased from 2013-14 at a faster rate than the physical production of wheat. This may be in part explained by the international wheat price falling in 2015-16 to the lowest level since 2009-10. As a result, there was less production, the areas of wheat crops were reduced and there was a decrease in greenhouse gas emissions.

	(a) Time series only available to 2014-15. Note: Index 2010-11 = 100

Graph 2 shows that the gross value of beef production increased at a higher rate compared to physical production and cattle holding numbers since 2010-11. This may be explained to a degree by the increase in the international price for beef over the period, combined with drought conditions that were less optimal for cattle farming. This led to an steady increase in physical production up to 2014-15, but an eventual decrease in physical production and cattle on holding.

	(a) Time series only available to 2014-15. Note: Index 2010-11 = 100

Greenhouse Gas Emissions and Livestock

The presentations below have been drawn from the activity and product specific inputs (Australia combined presentation data cube 25.2 in the Downloads tab). They display the gross value per emission of carbon dioxide equivalent in the livestock industry.

Graph 3 shows that beef production is the most emission intensive form of livestock per production dollar of gross value. Beef cattle have significantly more emissions in enteric fermentation than other livestock. In contrast, poultry have the lowest emission intensity per dollar than all other livestock. There is comparatively far less enteric fermentation in the activity surrounding egg and poultry meat production than there is in beef farming, as well as comparably lower emissions from manure management when compared to other livestock (see Table 21 in the Downloads tab).

Notably, the graph shows that the emission per dollar in beef production fell by 32% between 2012-13 and 2014-15. This may be due to a number of factors including the increase in the value of beef over the period and the reduction in cattle numbers based on prolonged drought conditions in Queensland (which is a major location for beef cattle production).

	(a) Dairy cattle emissions.

Graph 4 may support a better understanding of factors influencing the declining emissions per dollar in beef production. The graph illustrates the amount of greenhouse gases per tonne produced. It shows that for both cattle and sheep, the greenhouse gas emissions per tonne decreased from 2010-11 to 2014-15. For beef cattle, there was a 23% reduction over this period. This was not as significant as the reduction in greenhouse gas emissions per dollar of gross value (Graph 3 above) however, as presented earlier, the gross value far exceeded the physical production for beef cattle (Graph 2 above).

Emissions from pig meat production remained steady over the time series, although pigs have overall lower emissions intensity than sheep and beef cattle in physical production terms. Dairy emissions have also remained relatively steady.

	(a) Dairy cattle emissions. Milk production data was not available for 2010-11.

Gross Value of Production Per Employee

The combined presentation approach also enables the combining of different economic indicators, encouraging a systematic approach to understanding the economy surrounding the industries of agriculture, forestry and fisheries. Comparisons such as these can be made to understand the economic components of different sections of the industry.

For example, Graph 5 below shows gross value of production against number of employees (based on 2016 Census of Population and Housing). This is not an indicator of salary per employee and does not take into account the variety of expenses that are part of agricultural production beyond employee expenses. Variations could occur for a number of reasons, such as a return on capital investment from more automated tractors and other machinery (i.e. making the industry a less intense employer). The number of seasonal workers that have attributed themselves to a particular agricultural industry through Population Census reporting may be another factor.

Of the selected commodities, cotton has the highest gross value for every person employed in the industry while nurseries, cut flowers and cultivated turf have the least gross value.

	(a) Includes nurseries, cut flowers and cultivated turf. (b) Wool and meat products.

Gross Value of Production Across Industries

Graph 6 below shows the dollar per tonne of the top eight commodities in Australia from a gross value perspective. Wool has the highest value per tonne produced of these commodities, having a value of $8,351 per tonne produced. In contrast, wheat is lower at $277 per tonne, despite it having the second highest gross value of all agricultural commodities.

Crop Yield

Using land area and production data, it is possible to illustrate the area yield of different commodities (i.e. production per hectare). This can assist to track land efficiency over time, which may be useful for forecasting and analysing the agricultural market. Sugar cane has by far the highest physical yield in terms of physical production of all commodities, with over 90 tonnes per hectare in 2015-16, compared to 11 or less tonnes per hectare for other selected crops (Table 25.4 in the Downloads tab).

Graph 7 shows the yield of selected commodities indexed. The sugar cane yield per hectare decreased slightly over the five years between 2010-11 and 2015-16. While being more volatile, the wheat and maize yields have risen more significantly over this period.

	(a) Irrigated and non-irrigated. Note: Index 2010-11 = 100