3. Results of the case study

​​This section presents results for each of the indicators tested in this case study. The key uses and limitations of each indicator are explained, and conclusions are drawn as to its usefulness of the indicator for monitoring of changes in the forest industry.

The indicators are presented in four sections:

  • Characteristics of the forest industry;
  • Impacts of the forest industry on the broader community;
  • Impacts of the forest industry on its workforce; and
  • Impacts of the forest industry on Indigenous people.

3.1 Characteristics of the forest industry

The indicators in this section provide information on the following characteristics of the forest industry:

  • Direct employment in the forest industry;
  • Estimated value of forest industry production;
  • Estimated volume of forest industry production;
  • Efficiency of production (labour productivity); and
  • Consumption of wood and paper products.

These characteristics provide a useful basis for analysing how the forest industry is changing in terms of employment, production and consumption. These characteristics are important to track over time, as changes in characteristics of the industry are likely to be associated with changes in the social and economic impacts of the industry on its workers, and on local and regional communities.

3.1.1 Employment in the forest industry

Direct employment in the forest industry in the Green Triangle was measured in three ways, in which total employment and change in employment over time was measured for:

  • The forest industry as a whole;
  • The ‘forestry and logging’, and ‘wood and paper product manufacturing sectors’ of the industry; and
  • The plantation and native forestry sectors.

Each measure is useful as it provides an understanding of not just how many jobs there are, but where jobs are located within the industry.

The data presented are all based on ABS Census of Population and Housing data. These data are likely to exclude some contractors working in the forest industry, particularly silvicultural and transport workers. Based on Schirmer (2008), the total number estimated by the ABS may undercount direct reliance on forest industry employment by approximately 10 to 13%. Data on employment in the native forest and plantation sectors were based on a brief telephone survey of forestry firms in the region. All the data are based on where forestry workers live, rather than where they work as it draws on ‘place of usual residence’ data from the ABS5.

Employment in the forest industry as a whole

A total of 3,369 people were employed in the forest industry in the Green Triangle in 20066. Employment in different parts of the region is shown in Figures 3 to 4, and the rate of change over time in Figure 5. The large majority of forest workers – 2,777 – were based in the South East Statistical Division (SD), while 518 were based in the Western District SD and only 74 in the Wimmera SD. Within the South East SD, most forestry workers were based in Mt Gambier, Wattle Range and Grant. Most forestry workers in the Western District were based in Glenelg Shire.

Total employment in the forest industry in South Australia and Victoria followed similar trends to the Australia average over the period 1996-2006, with some growth in employment over 1996-2001, and decline over 2001-20067.

However, employment trends were quite different within the Green Triangle. In the South East region, employment grew more than the average over 1996 to 2001 and fell less than average over 2001 to 2006, indicating the industry has been growing more strongly in this region compared to others over this period. Employment in the Western District and Wimmera regions showed greater variability, growing over 1996 to 2001 and declining over 2001 to 2006. In most local areas within the Green Triangle employment in forestry either grew slightly over 1996 to 2001 and fell over 2001 to 2006, or fell over both periods8.

This is an image of a graph Figure 3 showing employment in the south-east South Australian forest industry, total all sectors, 1996, 2001, 2006. 

Figure 3: Employment in the south-east South Australian forest industry, total all sectors, 1996, 2001, 20069

this is an image of a graph Figure 4 showing employment in the Western District and Wimmera, Victorian forest industry, total all sectors, 1996, 2001, 2006. 

Figure 4: Employment in the Western District and Wimmera, Victorian forest industry, total all sectors, 1996, 2001, 2006

This is an image of a graph Figure 5 showing rate of change in employment in the forest industry, 1996, 2001, 2006. 

Figure 5: Rate of change in employment in the forest industry, 1996, 2001, 2006

Employment in the forestry and logging, and wood and paper product manufacturing, sectors

Total employment in the ‘forestry and logging’ and ‘wood and paper product manufacturing’ sectors is shown in Figures 6 to 11. Forestry and logging is defined as the activities of growing and managing forests, and harvesting trees. Wood and paper product manufacturing involves processing wood and paper products, and includes people who work in woodchip mills, sawmills, wood-based panel production, and pulp and paper production.

Overall, 82% of people who work in the forest industry work in wood and paper product manufacturing, while only 18% are employed in forestry and logging activities. The latter figure is likely to undercount the true level of activity that occurs prior to processing, with Schirmer (2008) finding that ABS data do not include many silvicultural contractors who work in activities such as ground and soil preparation, tree planting, fertilising and pest and weed control while plantations are growing. However, it is evident that the manufacturing sector supports the majority of employment in the forest industry in the Green Triangle.

In Australia, South Australia, Victoria and most parts of the Green Triangle, forestry and logging employment grew over 1996 to 2001, and subsequently declined, with the exceptions of (a) Portland, where there has been continuing growth in forestry and logging employment, and (b) Warrnambool, West Wimmera, and Wattle Range – West, where there has been consistent decline in forestry and logging employment10.

In both South Australia and Victoria, employment in wood and paper product manufacturing grew over 1996 to 2001 (similar to growth seen for Australia as a whole), but declined slightly over 2001 to 2006, compared to a slight increase in Australia.

Overall, the Green Triangle experienced greater decline and/or slower growth in wood and paper product manufacturing than the Australian, South Australian and Victorian averages over 1996 to 2006. Employment in wood and paper product manufacturing declined slightly in most parts of the Green Triangle over 1996 to 2006, with this decline occurring even in the South East region where most of those employed in wood and paper product manufacturing are located. Areas which did not experience decline typically had relatively low numbers of employees, meaning that an increase involved a small number of people.

This is an image of a graph Figure 6 showing employment in forestry and logging sector ? South Australia, 1996, 2001, 2006. 

Figure 6: Employment in forestry and logging sector – South Australia, 1996, 2001, 2006

This is an image of a graph Figure 7 showing employment in the South Australian wood and paper product manufacturing sector, 1996, 2001, 2006. 

Figure 7: Employment in the South Australian wood and paper product manufacturing sector, 1996, 2001, 2006

This is an image of a graph Figure 8 showing employment in forestry and logging sector ? Victoria, 1996, 2001, 2006. 

Figure 8: Employment in forestry and logging sector – Victoria, 1996, 2001, 2006

This is an image of a graph Figure 9 showing employment in the Victorian wood and paper product manufacturing sector, 1996, 2001, 2006. 

Figure 9: Employment in the Victorian wood and paper product manufacturing sector, 1996, 2001, 2006

This is an image of a graph Figure 10 showing Rate of change in employment in forestry and logging sector, 1996, 2001, 2006. 

Figure 10: Rate of change in employment in forestry and logging sector, 1996, 2001, 2006

This is an image of a graph Figure 11 showing rate of change in employment in wood and paper product manufacturing sector, 1996, 2001, 2006. 

Figure 11: Rate of change in employment in wood and paper product manufacturing sector, 1996, 2001, 2006

Employment in the native forest and plantation sectors

The majority of people working in the forest industry in the Green Triangle work in the plantation sector, as can be seen in Figure 12 and 1311 . In total approximately 82% of forest industry workers work in the softwood plantation sector, 12% in hardwood plantations, 3% in native forestry, and the sector in which the remaining 3% of people work is unknown.

These data do not include many silvicultural contractors, and it is likely that once contracting employment is included, employment in hardwood plantations would be higher, as much of the work currently generated in this sector is undertaken by silvicultural contracting firms. The large majority of employment in the softwood plantation sector is in the processing sector; as hardwood plantations in the region are only just beginning to be harvested in 2008, there is as yet little to no work generated by the processing of hardwood plantations. This is expected to change in coming years as harvest volumes grow rapidly.

The proportion of workers in each sector varies by individual LGAs (Figure 13). The small proportion of native forest-based employment in the Green Triangle occurs in the Victorian part of the Green Triangle. Hardwood and softwood plantation employment are spread across the region, with most LGAs having a mix of employment in both sectors, with the exception of Mt Gambier and Grant where forest industry employment is almost totally based on softwood plantations.

This is an image of a graph Figure 12 showing number of forestry workers in plantation and native forest sectors by LGA, 2006. 

Figure 12: Number of forestry workers in plantation and native forest sectors by LGA, 2006

This is an image of a graph Figure 13 showing proportion of employment in plantation and native forest sectors by LGA, 2006. 

Figure 13: Proportion of employment in plantation and native forest sectors by LGA, 2006

3.1.2 Estimated value of forest industry production

The value of production of an industry provides important information about its economic impact on the region in which it operates, as the value of production is a useful indicator of the economic activity generated by the industry.

The estimated value of production of the forest industry can be measured at several points in the chain of production:

  • Gross value of log production (roundwood);
  • Gross value of sawnwood;
  • Gross value of wood based panels; and
  • Gross value of paper and paperboard.

Growth in the value of production was slower in South Australia and Victoria than in Australia as a whole over 2000-01 to 2006-07, and the value of production declined in South Australia over 2003-04 to 2006-07, as can be seen in Figures 14 and 15.

The Green Triangle contains most of South Australia’s wood production, and so the figures for South Australia can be considered to reflect trends in the South Australian side of the Green Triangle. In Victoria, however, the forest industry is spread across many regions, and only a small part of production occurs in the Green Triangle. It is therefore not possible to identify if Victorian trends reflect trends in the Green Triangle over this time period.

Information on value of production was only obtained at national and state level, with specific data on the Green Triangle not able to be obtained12. While forestry processors in the region were asked to provide information on their production, most declined to provide this information for confidentiality reasons, and also because the data can be complex to provide – many wood and paper manufacturers produce a wide variety of products with differing values. In addition, confidentiality concerns mean that it is often not possible to report value of production for local regions, as there are often less than three businesses producing particular products in an SLA or SD, and the business may be individually identifiable if data were presented at these scales.

This is an image of a graph Figure 14: Estimated value of forest industry production ? gross roundwood equivalent, 2000-01 to 2006-07. 

Figure 14: Estimated value of forest industry production – gross roundwood equivalent, 2000-01 to 2006-07

This is an image of a graph Figure 15: Average annual change in value of forest industry production ? gross roundwood equivalent, 2000-01 to 2003-04 and 2003-04 to 2006-07. 

Figure 15: Average annual change in value of forest industry production – gross roundwood equivalent, 2000-01 to 2003-04 and 2003-04 to 2006-07

3.1.3 Estimated volume of forest industry production

The volume of production of an industry provides important information about its economic impact on the region in which it operates, as the volume of production is a useful indicator of the economic activity generated by the industry. When combined with information on value, it can provide useful data on trends in the industry.

The estimated volume of production of the forest industry can be measured at the following points in the chain of production as initial products such as roundwood are value added to produce products such as paper, sawnwood and wood based panels:

  • Volume of roundwood;
  • Volume of sawnwood;
  • Volume of wood based panels; and
  • Volume of paper and paperboard.

Similarly to the results for value of production, there was higher growth in the volume of log production in Australia as a whole compared to South Australia and Victoria over 2000-01 to 2006-07, as can be seen in Figures 16 and 17. Over 2003-04 to 2006-07, the volume of log production fell in South Australia, grew in Victoria, and grew in Australia at a higher rate than in Victoria.

Information on volume of production was only obtained at national and state level, with specific data on the Green Triangle not able to be obtained13. While forestry processors in the region were asked to provide information on their production, most declined to provide this information for confidentiality reasons, and also because the data can be complex to provide – many wood and paper manufacturers produce a wide variety of products. In addition, confidentiality concerns mean that it is often not possible to report value of production for local regions, as there are often less than three businesses producing particular products in an SLA or SD, and the business may be individually identifiable if data were presented at these scales.

This is an image of a graph Figure 16: Estimated volume of forest industry production ? gross roundwood equivalent, 2000-01 to 2006-07. 

Figure 16: Estimated volume of forest industry production – gross roundwood equivalent, 2000-01 to 2006-07

This is an image of a graph Figure 17: Average annual change in volume of forest industry production ? gross roundwood equivalent, 2000-01 to 2003-04 and 2003-04 to 2006-07. 

Figure 17: Average annual change in volume of forest industry production – gross roundwood equivalent, 2000-01 to 2003-04 and 2003-04 to 2006-07

3.1.4 Efficiency of production (labour productivity)

The efficiency of production of an industry is a key measure of economic efficiency, with increases in productivity often indicating increased investment in technology and skills that enable higher production per labour unit, and hence improved competitiveness in the marketplace. From a social viewpoint, changes in efficiency of production may have implications for the number of jobs available in an industry, or the skills required of workers.

This indicator is measured by dividing the volume of output produced by the units of labour required to produce it.

An attempt was made to measure this indicator using data from ABARE’s Forest and Wood Product Statistics, in which the employment required per unit of gross roundwood equivalent produced was calculated. However, the productivity estimates varied widely, most likely because each region produces different types of wood and paper products, and differing amounts of labour are required to produce different products. For example, based on gross roundwood equivalent (GRWE) and total employment in the forest industry, in 2006-07 (ABARE Forest and Wood Product Statistics):

  • 370 cubic metres of GWRE were produced per forestry worker in Australia;
  • 345 cubic metres of GWRE were produced per forestry worker in South Australia;
  • 326 cubic metre of GWRE were produced per forestry worker in Victoria; and
  • 1170 cubic metres of GWRE were produced per forestry worker in Tasmania.

The productivity measure will be most useful if measured separately for different types of wood and paper products, rather than as a generic measure based on gross roundwood equivalent.

It is therefore recommended that efficiency of production be measured using data from direct survey of forestry businesses, and:

  • Be specifically calculated for different types of wood and paper products; and
  • Be calculated separately for the native forest and plantation sectors.

This means this indicator may not be feasible to monitor regularly, and may instead need to be measured based on occasional studies.

It also means it was not possible to identify labour productivity for the Green Triangle forest industry based on currently available data.

3.1.5 Consumption of wood and paper products

Consumption of wood and paper products is a key indicator of demand for these products, and hence of likely trends in forest industry production. Changes in consumption may indicate shifts in social impacts of the forest industry.

The rate of consumption of wood and paper products per capita can only be measured at national scale in Australia, as consumption data are not available at smaller scales.

National consumption per capita is shown in Figure 18 for sawnwood, wood based panels, and paper and paperboard, per 1,000 people, for Australia. It can be seen that:

  • After growing for most of the period of 1995-2003, sawnwood consumption fell over 2004-2007;
  • Consumption of paper and paperboard has grown overall, but not steadily over time, with some decreases in consumption at some points in time; and
  • Consumption of wood based panels has grown over time, with some variation in trends in individual years.

The average annual rate of change in consumption for the periods 1994-95 to 1999-00, and 2000-01 to 2006-07, are shown in Figure 19. Growth in consumption of wood based panels and paper and paperboard was relatively similar across these two periods, while growth in the rate of sawnwood consumption fell considerably in the latter period.

National wood and paper consumption data provide useful information relevant to the Green Triangle region. As the wood and paper products produced in the Green Triangle, particularly from softwood plantations, are sold into national (as well as international) markets, forest industry production in the region is likely to be influenced by domestic consumption trends. Decreases in sawnwood consumption in recent years may at least partly explain the slower rates of growth and, in South Australia, decrease in volume and value of wood production in the Green Triangle, with sawnwood a major product produced by Green Triangle forest industry manufacturers.

This is an image of a graph Figure 18: Consumption of wood and paper products per 1,000 people, 1995-95 to 2006-07. 

Figure 18: Consumption of wood and paper products per 1,000 people, 1995-95 to 2006-07

This is an image of a graph Figure 19: Average annual change in consumption of wood and paper products per 1,000 people, 1995-95 to 2006-07. 

Figure 19: Average annual change in consumption of wood and paper products per 1,000 people, 1995-95 to 2006-07

3.2 Impacts of the forest industry on the broader community

The following indicators provide information that can assist in monitoring the social and economic impacts of the forest industry on the communities in which it is situated:

  • Dependence on the forest industry (% employment);
  • Social characteristics of forestry dependent regions;
  • Location of forest industry employment;
  • Impact of forest industry on rural population; and
  • Values, uses and perceptions of forestry activities.

These indicators provide a picture of how dependence of different communities on the forest industry is changing over time, and also how forestry-dependent communities are changing in terms of their key socio-demographic and economic characteristics.

Change in social characteristics may be an indicator both of impacts of the forest industry on a community, and provide important understanding of how characteristics of the communities in which the industry operates may influence the industry. For example, if forestry-dependent communities have low levels of unemployment this may partly reflect job creation in the forest industry, but may also be a result of changes to employment in a range of industries. Low levels of unemployment may indicate the forest industry will have difficulty recruiting workers to fill new jobs, constraining its capacity to expand.

The indicators in this category provided a limited but useful understanding of key characteristics of forestry-dependent communities. They should be accompanied by in-depth studies which examine how people experience and interact with the forest industry, and the impacts of changes to the forest industry.

3.2.1 Dependence on the forest industry (% employment)

A first step in understanding the social and economic impacts of the forest industry is to identify the extent to which different regions depend on the forest industry. This indicator measures dependence by identifying the percentage of the workforce in a given area who depend directly on the forest industry for their employment14.

Within the Green Triangle, the highest dependence on the forest industry occurs in the South East region (see Figures 20 to 23, and Appendix 2 for graphs showing average annual rate of change in dependence over time). The SLAs of Grant, Mount Gambier, Wattle Range – East and Wattle Range – West all have very high dependence on forestry employment, with over 11% of the workforce, and up to 16%, working in the forest industry in 200615. This level of dependence is much higher than the Australian or South Australian average.

In the Western District, parts of Glenelg Shire have a higher than average dependence on forestry employment, with Glenelg – Heywood and Glenelg – North having between 4% to 6% of their labour force employed in forestry over time, although this is still lower than for the four South East region SLAs.

Overall dependence on the forest industry has fallen over time in almost all regions, with some experiencing slight growth over 1996-2001 followed by decline over 2001-2006. The only regions with growth in dependence over 2001-2006 were those which had a very small number of forestry employment, such that this reflected very little real change in dependence.

Dependence on the plantation and native forest sectors could only be measured for 2006 (Figure 23). As the majority of employment in the region is based around softwood plantation forestry, the greatest proportion of dependence is also located in this sector, although in Wattle Range there is higher dependence on hardwood plantation derived products than in other areas.

Overall, there is considerable variability in dependence on the forest industry in the Green Triangle, with the highest dependence occurring in the South East part of the region. This may change in coming years as harvesting of hardwood plantations begins, as this process is likely to generate new types of employment based on the forest industry in the region.

The overall decline in dependence reflects both change in the forest industry, with some decline in overall forestry employment in the region in recent years, and also growth in the overall size of the labour force and other industries in parts of the region.

This is an image of a graph Figure 20: Proportion of labour force employed in the forest industry, 1996, 2001 and 2006. 

Figure 20: Proportion of labour force employed in the forest industry, 1996, 2001 and 2006

This is an image of a graph Figure 21: Proportion of labour force employed in forest industry - South Australia, 1996, 2001 and 2006. 

Figure 21: Proportion of labour force employed in forest industry - South Australia, 1996, 2001 and 2006

This is an image of a graph Figure 22: Dependence on the forest industry, measured as proportion of labour force employed in Victoria, 1996, 2001 and 2006. 

Figure 22: Dependence on the forest industry, measured as proportion of labour force employed in Victoria, 1996, 2001 and 2006

This is an image of a graph Figure 23: Dependence on the forest industry, measured as proportion of labour force employed in different forest industry sectors by LGA, 1996, 2001 and 2006. 

Figure 23: Dependence on the forest industry, measured as proportion of labour force employed in different forest industry sectors by LGA, 1996, 2001 and 2006

3.2.2 Social characteristics of forestry-dependent regions

It is possible that forestry-dependent communities have different social characteristics to other communities. These differences may or may not be a result of forest industry activities; either way, they are important to understand as they may influence the ability of a community to adapt to changes in the forest industry.

To better understand whether this is the case, this indicator measures key characteristics believed to be related to a region’s ability to adapt to change, namely whether the total amount, and change, in the following differ for regions with higher and lower dependence on forestry:

  • Total population;
  • Unemployment rate;
  • Educational qualifications (proportion of over 15 population with (a) no post-school qualifications, (b) certificate/diploma, (c) bachelor degree or higher);
  • Median age;
  • Median household income;
  • Dependency ratio, which shows the ratio of population age <15 years and >65 years to the working age population aged 25-64 years; and
  • Economic diversity (measured as proportion of total employed labour force working in the top three employing industries).

Areas within the Green Triangle were classified as having low, medium and high dependence on forestry based on the proportion of the labour force employed in forestry, with:

  • Low = <2% of labour force employed in forestry;
  • Medium = 2% to 5% of labour force employed in forestry;
  • High = 5% to 10% of labour force employed in forestry; and
  • Very high = >10% of labour force employed in forestry.

Based on this classification, the classification shown in Table 2 was identified.

Table 2: Classification of regions by level of dependence on the forest industry

Level of dependence

Region/s

Low dependence

Large scale: Australia, South Australia, Victoria

Regional scale: Western District, Wimmera

SLAs: Kingston, Naracoorte & Lucindale, Robe, Tatiara, Warrnambool (C)16, Corangamite (S) – North, Corangamite (S) – South, Moyne (S) - North-East, Moyne (S) - North-West, Moyne (S) – South, S. Grampians (S) – Hamilton, S. Grampians (S) – Wannon, S. Grampians (S) Bal, West Wimmera (S).

Medium dependence

SLA: Glenelg (S) - Portland

High dependence

SLAs: Glenelg (S) – Heywood, Glenelg (S) - North

Very high dependence

Regional scale: South East (SA)

SLAs: Grant (DC), Mount Gambier (C), Wattle Range (DC) – East, Wattle Range (DC) – West.

Information on social characteristics of each region are presented in Table 3. For each, two figures are presented: the level in 2006, and rate of change over 1996-2006. This enables identification of whether regions with higher dependence on forestry have different characteristics (e.g. higher/lower unemployment rate) than other regions, and whether they have been changing in the same ways as other regions.

When characteristics of low, medium and high dependence forestry regions were compared for the Green Triangle, only three differences were observed between areas with differing levels of dependence:

  • In areas with medium or high dependence on forestry, a slightly higher proportion of the adult population had a bachelor degree or higher qualification, than in areas with low dependence on forestry;
  • Median age was slightly younger on average in regions with high or very high dependence on forestry compared to those with low dependence on forestry. However, some individual SLAs with low dependence on forestry had a median age as low as that in areas with high or very high dependence on forestry; and
  • Median household income grew at a slightly slower rate in areas with higher dependence than the average for regions with low dependence on forestry.

In all three cases, it is entirely possible these differences are due to factors unrelated to the forest industry. The size of difference is relatively small, and it is not possible to identify to what extent the forest industry may either contribute to or be affected by these differences.

No other consistent differences were observed between areas with different levels of dependence on the forest industry, indicating that areas with high dependence on the forest industry have few differences in social characteristics compared to those with less dependence located nearby.

While areas with high dependence on forestry were rarely different to others, it is useful to identify whether the Green Triangle as a whole has different characteristics to the Victorian, South Australia, or Australian average. When examining the data in Table 3, it is apparent that:

  • Areas within the Green Triangle which had a fairly small population (typically under 5,000) generally experienced a gradual loss of population over 1996 to 2006, while areas with a large population or near regional cities (e.g. Mt Gambier, Grant), and areas experiencing an influx of ‘seachangers’ such as Robe, experienced population growth;

  • The overall unemployment rate in most parts of the Green Triangle was lower than the Australian unemployment rate in 2006, with the exception of Glenelg – Portland, and Mount Gambier, which had higher unemployment rates than the average for Australia, South Australia or Victoria;

  • Unemployment rates fell in all regions examined over 1996-2006 with the exception of Naracoorte and Lucindale where there was a very low unemployment rate throughout this period;

  • The proportion of the population aged over 15 with no post-school qualifications fell in all regions over 1996 to 2006, while the proportion of the population with a bachelor degree or other postgraduate qualification grew, similar to the average for Australia, South Australia and Victoria;

  • Median age grew in all areas over 1996-2006 across all regions;

  • Median household income was lower in most parts of the Green Triangle regions, and in South Australia, than the Australian and Victorian average, with the exception of Corangamite (both SLAs) and Grant; and

  • While the overall dependency ratio – the proportion of the population aged under 15 and over 65 compared to those aged 25-64 – grew in Australia over 1996-2006, in most Green Triangle regions it either fell, or grew more slowly than the Australian average. Where the dependency ratio is falling, this indicates a growing number of working age people compared to ‘dependent’ aged population (whether child or retirement age); slow growth indicates that the proportion of children and elderly are increasing as a proportion of the population.
Table 3: Social characteristics of Green Triangle study region

Forestry dependence

Region

2006 - Total population

Change in population 1996-2006

2006 – Unemployment rate

Change in unemployment rate 1996-2006

2006 - % population with no post-school quals

Change in population with no post-school quals, 1996-2006

Low

Moyne (S) - North-East

2331

-0.61

2.57

-6.25

69.64

-0.88

Low

Moyne (S) - North-West

2707

-0.85

2.90

-4.60

67.19

-1.11

Low

West Wimmera (S)

4356

-1.17

2.67

-5.72

71.89

-0.92

Low

S. Grampians (S) - Wannon

2251

-1.12

4.16

-4.07

68.23

-1.14

Low

Naracoorte and Lucindale (DC)

7901

0.10

3.21

0.02

67.93

-1.13

Low

Wimmera (Vic)

48441

-0.53

4.75

-3.36

69.02

-1.05

Low

Corangamite (S) - South

7467

-0.07

3.04

-3.23

67.86

-1.12

Low

Moyne (S) - South

10221

0.62

3.59

-5.54

65.20

-1.47

Low

Warrnambool (C)

30199

1.06

5.23

-5.18

63.86

-1.33

Low

Corangamite (S) - North

8911

-0.56

4.32

-4.33

70.34

-0.88

Low

Robe (DC)

1716

3.44

3.17

-7.22

72.65

-0.20

Low

S. Grampians (S) Bal

5200

-0.32

2.77

-5.97

61.86

-1.46

Low

Australia

19855288

1.18

5.24

-4.29

60.58

-1.34

Low

Victoria

4932423

1.17

5.41

-4.25

60.20

-1.34

Low

South Australia

1514336

0.54

5.24

-4.93

63.34

-1.16

Low

S. Grampians (S) - Hamilton

9205

-0.05

4.64

-4.78

65.86

-1.28

Low

Glenelg (S) - Portland

10246

0.03

7.78

-3.96

68.30

-0.86

Low

Western District (Vic)

98855

0.07

4.68

-4.70

66.73

-1.18

Medium

Glenelg (S) - Heywood

5891

-0.22

4.43

-3.68

67.63

-1.12

High

Glenelg (S) - North

3227

-1.20

5.23

-3.49

72.27

-1.11

High

South East (SA)

62214

0.24

4.88

-2.94

70.14

-1.02

V. High

Wattle Range (DC) - East

3107

-0.43

3.78

-2.66

70.83

-1.06

V. High

Grant (DC)

7691

0.34

3.50

-5.23

67.73

-1.19

V. High

Mount Gambier (C)

23272

0.56

7.10

-2.00

69.23

-0.99

V. High

Wattle Range (DC) - West

8366

-0.51

5.86

-2.71

72.67

-0.89

 

Table 3: Social characteristics of Green Triangle study region (cont.)

Forestry dependence

Region

2006 - % population with bachelor degree or higher

Change in % population with bachelor degree+ 1996-2006

2006 - Median age

Change in median age 1996-2006

Low

Moyne (S) - North-East

8.60

7.40

42

1.05

Low

Moyne (S) - North-West

8.18

6.29

39

0.54

Low

West Wimmera (S)

6.60

4.29

43

1.32

Low

S. Grampians (S) - Wannon

7.73

5.99

44

1.00

Low

Naracoorte and Lucindale (DC)

7.52

5.07

37

0.57

Low

Wimmera (Vic)

8.21

5.26

42

1.35

Low

Corangamite (S) - South

8.09

5.40

38

1.52

Low

Moyne (S) - South

10.25

5.99

39

1.14

Low

Warrnambool (C)

11.63

4.52

36

1.25

Low

Corangamite (S) - North

7.97

4.71

42

1.35

Low

Robe (DC)

6.18

2.71

42

1.05

Low

S. Grampians (S) Bal

12.13

6.97

41

0.79

Low

Australia

15.59

4.96

37

0.88

Low

Victoria

17.19

4.84

36

0.91

Low

South Australia

12.97

4.90

38

0.86

Low

S. Grampians (S) - Hamilton

9.87

5.19

41

1.71

Low

Glenelg (S) - Portland

8.09

4.25

38

1.88

Low

Western District (Vic)

9.54

5.40

39

1.14

Medium

Glenelg (S) - Heywood

7.89

6.01

40

1.11

High

Glenelg (S) - North

6.81

8.56

45

1.54

High

South East (SA)

6.73

4.97

37

0.88

V. High

Wattle Range (DC) - East

7.88

5.49

37

0.57

V. High

Grant (DC)

7.02

5.60

38

1.18

V. High

Mount Gambier (C)

7.46

4.19

36

1.25

V. High

Wattle Range (DC) - West

5.23

5.53

39

1.47

 

Table 3: Social characteristics of Green Triangle study region (cont.)

Forestry dependence

Region

2006 - Median household income

Change in median household income 1996-2006

2006 - Dependency ratio

Change in dependency ratio 1996-2006

Low

Moyne (S) - North-East

739

5.79

0.67

0.37

Low

Moyne (S) - North-West

914

8.24

0.55

-0.60

Low

West Wimmera (S)

728

6.43

0.66

0.37

Low

S. Grampians (S) - Wannon

651

5.21

0.67

-0.95

Low

Naracoorte and Lucindale (DC)

925

7.59

0.53

-0.94

Low

Wimmera (Vic)

728

5.26

0.65

-0.07

Low

Corangamite (S) - South

1035

8.22

0.58

-0.19

Low

Moyne (S) - South

935

7.71

0.56

-1.06

Low

Warrnambool (C)

874

7.34

0.55

0.08

Low

Corangamite (S) - North

695

5.11

0.67

0.23

Low

Robe (DC)

796

6.86

0.61

0.59

Low

S. Grampians (S) Bal

986

9.80

0.56

-0.51

Low

Australia

1027

6.59

0.50

2.41

Low

Victoria

1021

6.26

0.49

-0.28

Low

South Australia

885

6.42

0.51

-0.30

Low

S. Grampians (S) - Hamilton

765

6.11

0.60

-0.44

Low

Glenelg (S) - Portland

836

5.71

0.55

-0.51

Low

Western District (Vic)

850

7.14

0.60

-0.22

Medium

Glenelg (S) - Heywood

980

7.13

0.52

-0.98

High

Glenelg (S) - North

643

4.45

0.73

0.38

High

South East (SA)

874

5.95

0.55

-0.25

V. High

Wattle Range (DC) - East

853

5.51

0.52

-0.71

V. High

Grant (DC)

1063

6.53

0.49

0.01

V. High

Mount Gambier (C)

816

4.95

0.53

-0.10

V. High

Wattle Range (DC) - West

810

4.67

0.60

0.23

3.2.3 Location of forest industry employment

The location of jobs can provide important information on their social impact, and on what types of towns will be most impacted by a change in employment in an industry. Recent studies have indicated that many people believe the majority of jobs in the forest industry are located in larger towns and regional centres, and fewer in small towns and villages, and this perception has been recorded in the Green Triangle region (Schirmer et al. 2008c). Identifying where forest industry employment is located can help identify whether these perceptions are correct, and also whether the location of forest industry jobs is changing over time.

This indicator compares the proportion of forestry employment located in different sized towns versus the proportion of (a) employment in the agricultural sector, and (b) overall employment. Town size was classified into groups of rural areas towns with:

  • Rural land and localities with < 200 population;
  • 200-499 population;
  • 5,00-999 population;
  • 1,000-1,999 population;
  • 2,000-2,999 population;
  • 3,000-4,999 population;
  • 5,000-9,999 population; and
  • > 10,000 population.

This range of town sizes was selected as many of the towns in the areas being studied had a population of less than 5,000, and so it was considered useful to ensure several categories of town size were included.

Overall, the distribution of forest industry employment in the Green Triangle in 2006 was somewhat similar to the distribution of the total labour force across differently sized towns (Figures 24 and 25)17.

The key difference is that a moderately higher proportion of forest industry employment is located in towns with more than 10,000 population and less are located in towns with less than 200 residents and rural land compared to the distribution of the labour force overall. This confirms the perception that forest industry employment is typically centred in larger towns/cities within the Green Triangle region.

Forest industry employment in the Green Triangle is much more urbanised than the location of agricultural employment. This indicates that any shift from traditional agriculture to forest industry-based employment is likely to be accompanied by some shift of employment to regional centres.

This is an image of a graph Figure 24: Proportion of forestry, agricultural and total employment in localities of different sizes in the South East region of South Australia, 2006. 

Figure 24: Proportion of forestry, agricultural and total employment in localities of different sizes in the South East region of South Australia, 2006

This is an image of a graph Figure 25: Proportion of forestry, agricultural and total employment in localities of different sizes in the Western District and Wimmera regions of Victoria, 2006. 

Figure 25: Proportion of forestry, agricultural and total employment in localities of different sizes in the Western District and Wimmera regions of Victoria, 2006

3.2.4 Impact of forest industry on rural population

In recent years, concerns have been expressed that expansion of plantations may lead to change in the population of small rural towns and on rural land. This indicator compares rural population change in areas experiencing different rates of plantation expansion, to identify if there are identifiable differences in rural population change in areas experiencing rapid rates of plantation expansion compared to the average rate of change in rural population. Rural population is defined as the population living on rural properties and in localities (small towns and settlements) with less than 200 residents. This social indicator relates to plantation forestry only, as these concerns have been expressed exclusively about plantation expansion and do not relate to native forestry.

The rate of expansion of plantations18 and average annual rate of change in rural population over 1996 to 2006 are shown in Figures 26 to 27. When the rate of plantation expansion is compared to change in rural population, no apparent pattern is seen – areas with higher rates of plantation expansion did not experience higher rates of population decline, and vice versa. Rural population declined somewhat in most regions, irrespective of whether they were experiencing plantation expansion, and rates of rural population decline were not higher in areas experiencing the most plantation expansion.

This indicates that, at the SLA scale, the expansion of plantations in recent years in the Green Triangle has not had an impact on overall rural population levels that is able to be distinguished from other factors influencing rural population. While it is still possible that plantation expansion led to loss of population, at the SLA scale this decline was no greater than that caused by other trends in the region, such as amalgamation of farms.

It is possible that at more localised scales, plantation expansion has been associated with loss of rural population, as the SLA scale is still reasonably large – a single SLA may include a large number of rural properties, only a small number of which will have been established to plantation over a given period.

This is an image of a graph Figure 26: Area of plantation establishment and average annual rate of change in rural population, 1996-2006 ? South East region, South Australia. 

Figure 26: Area of plantation establishment and average annual rate of change in rural population, 1996-2006 – South East region, South Australia

This is an image of a graph Figure 27: Area of plantation establishment and average annual rate of change in rural population, 1996-2006 ? Western District and Wimmera regions, Victoria. 

Figure 27: Area of plantation establishment and average annual rate of change in rural population, 1996-2006 – Western District and Wimmera regions, Victoria

3.2.5 Values, uses and perceptions of forestry activities

Perceptions of the Green Triangle population about forestry were not identified for this study, as this would require a survey of the communities within the region, which was not possible to undertake for this consultancy. It is important to understand how the following are changing over time:

  • Attitudes and values held about different types of forestry - what overall values and attitudes do people hold regarding forestry in general, and acceptability of different forestry practices? How do these differ between people with different characteristics and living in different regions?;
  • Uses of forests – are different people changing the ways they use the forest, for example the types of recreational activities undertaken and access for uses such as firewood collection? Is frequency of use changing? Are the types of people using forests changing over time?; and
  • Perceptions of forestry activities – what are the differing perceptions of forest industry activities and how are these changing over time? This may include examining access to information sources and how these influence perceptions.

A recent study by Williams et al. (2008) surveyed residents living in a region which encompassed the Green Triangle. They focused on understanding perceptions of different types of land use change in the region, including land use change to blue gum (hardwood) plantations. Key findings included that land use change to plantations was viewed more negatively than the other types of land use change studied. Compared with other land use changes such as expansion of dairy farming, expansion of cropping and growth in rural residential development, more people thought that expansion of blue gum plantations led to population loss, fewer jobs, lower levels of community involvement, road damage and wildfire risk. These perceptions varied widely, however. Less than 50% of respondents viewed blue gum plantations as a negative land use overall, with others either unsure or viewing them positively.

This indicates that expansion of hardwood plantations in the region remains controversial and its impacts are widely debated. There is no ‘consensus’ view about the impacts of plantations, with different people holding different opinions.

It would be useful to undertake a similar survey in the future once hardwood plantations have matured and a harvesting and processing industry is developed, to identify if this is associated with any change in perceptions of hardwood plantations in the region.


5 This differs to some other reports – for example, Schirmer (2008) reports employment by place of work. Place of usual residence is a useful measure as it gives an indicator of where forest industry workers live and hence are likely to interact with others in their community, spend a large proportion of their income, and develop a range of social and economic networks.
6 The forest industry is defined as those employed in forestry and logging and wood and paper product manufacturing.
7 See Appendix 1 for graphs showing the exact average annual rate of change in employment for each local area within the Green Triangle.
8 The only exceptions to this trend were in Corangamite and Moyne Shires, both of which had very small numbers of forestry workers overall, such that it is possible randomisation of data by the ABS has influenced the trends observed. The ABS randomises data to preserve confidentiality of individuals. While this does not impact on trends where there are large numbers of people involved, where small numbers are involved (particularly where there are less than 10 people being reported), randomisation may have a strong influence, and trends should be considered subject to influence by the randomisation process.
9 Figures 4 and 5 present data on total employment for different parts of the study region. The scale on the y-axis of the graphs is the same to ensure the information in the graphs can be easily compared. This is done through this report – wherever a particular type of data is presented over multiple graphs, the y-axis is standardised to ensure easy comparison of data across the graphs.
10 See Appendix 1 for graphs showing the average annual rate of change in employment in forestry and logging and wood and paper product manufacturing for each local area within the Green Triangle.
11 Data on employment in the plantation and native forest sectors were gathered by asking forestry businesses what proportion of their activities occurred in each sector. Where a business did not provide information, local industry experts were asked their knowledge of (a) which sector a business operated in and (b) the broad size of its overall operations in terms of number of employees. This information was gathered based on the location of the forestry business. ABS data on forest industry employment by place of residence then had to be adjusted to estimate the proportion of employment in each sector. This requires making an estimate based on knowledge of where forest industry workers typically live in relation to the location of their place of employment. Based on Schirmer (2008), it was assumed that a large majority of forestry workers live in the same local government area (LGA) as their place of work, or in a neighbouring LGA, and that relatively few live more than one LGA away from their place of employment. The data in Figures 12 and 13 are also based on the wood source used by a business, whether or not that wood was sourced from within the region. Some processors source timber from some distance away, or import a wood-derived product and process it to a further stage. The data should be taken as a broad indication of location of plantation and native forestry employment, rather than a precise estimate.
12 Data from the Australian Bureau of Agricultural and Resource Economics (ABARE) Forest and Wood Products Statistics series were used to estimate value of forestry production over time, comparing trends in Australia, South Australia and Victoria.
13 While data were obtained from some wood and paper product manufacturers within the Green Triangle, almost half did not provide information on volume produced. Because of this, data from the Australian Bureau of Agricultural and Resource Economics (ABARE) Forest and Wood Products Statistics series were used to estimate volume of forestry production over time, comparing trends in Australia, South Australia and Victoria.
14 The indicator is measured by calculating the proportion of the working labour force employed in the forest industry. The data used were sourced from the ABS Census of Population and Housing, based on place of usual residence data. Note that it would also be possible to measure dependence using ‘place of employment’ data, as was done by Schirmer (2008). Dependence was measured based on a person’s place of usual residence here because this reflects where people live, and hence where they are likely to spend a large proportion of their income.
15 If all contractors were included in ABS forestry data, the total dependence on forestry would be higher; For example, ABS data indicate that in Tasmania as a whole, 2.53% of the workforce are employed in forestry, whereas Schirmer (2008) estimated the figure to be 3.08% once all contractors were included in estimates. That said, ABS data are likely to accurately reflect changes over time in forestry employment as data have been measured the same way over time.
16 As described previously, (C) refers to ‘city’, (S) to ‘Shire’, and (DC) to ‘District Council. Vic and SA refer to the states in which particular regions are located.
17 It was only possible to measure these data for 2006, as data for earlier years were not able to be accessed from the ABS within the timeframe of the consultancy.
18 Initially, average annual change in plantation area was calculated. However, this proved to be a poor indicator of rate of change, as some areas which experienced expansion of plantations of only 400 hectares over this period (eg Moyne – South) experienced a much higher rate of change in plantation area (32,000% as the area of plantations at the beginning of the period was less than one hectare) than those which experienced a greater expansion of plantations (for example, plantation area in Glenelg – North grew from 760ha to 21,560ha over the same period, but the average annual rate of change was only 275%). It is therefore more appropriate to use the area of expansion of plantations, rather than the average annual rate of change, as a measure of plantation expansion. This indicator can only be measured meaningfully at local scale, so includes only SLAs and not larger regions.