Principle - Society accepts responsibility for sustainability.

Criterion- There is equitable access to and distribution of economic rents.

Indicator – Number of communities with a significant forestry component in the economic base.

Box B: Definition:

The indicator measures the number of communities with a significant forestry component (heavily or moderately forest dependent) in the economic base. Communities are heavily forest dependent if more than 50% of the economic base employment is accounted for by forest industries, and moderately forest dependent if they rely on the forestry sector for 10-50% of their economic base. The economic base is simply defined as total employment in the community, stratified into forestry and non-forestry sectors.

Box D: Applicability to Different Landowners. Explain any differences.

This indicator applies to a small regional economy (e.g., a). It does not differentiate among landowners, but rather classifies business activities with respect to their relationship to forestry and their inclusion in the economic base.

Box E: Overlap:

CIFOR – BAG: L6, 1.2.2

CIFOR – ECON: C3.1.4, "Employment of local population in forest management";

CCFM: L8a, 5.3.2 (as revised), "Employment of local population in forest

management";

Notes:

This indicator is applied to human communities, which are included within the Study Area

Notes:

Clearly the indicator is diagnostic, but could also have predictive capability if time series trends are examined.

Notes:

This classification does not apply to socioeconomic systems.

Box I: Underlying Concepts:

As described by the Canadian Forest Service (1997), often, small forest-dependent communities face challenges that more diversified communities do not. For example, they are more vulnerable to short-term changes in product prices and to longer-term changes in the structure of their industry. Often their prosperity depends on the financial performance of a few firms. If a firm becomes unprofitable or technologically out of date, it may fail, leaving few other job possibilities for local residents. Also, poor management of the local resource base can threaten the long-term survival of the community. If the resource becomes depleted, the industry supporting the community will leave, seeking new sources of raw material. Small, undiversified rural communities also tend to be less able to adapt or respond to economic change. Globalization, urbanization and the "new economy" generally favor urban economies and structures.

The indicator draws from several theoretical premises relating resources to economic development, many of which are summarized by Rasker (1995).

Box J: Relevance to Sustainable/Unsustainable Management :

This indicator implies relationships between sustainable forestry and economies that are functionally dependent upon forest outputs of goods and services. It is not entirely clear what these relationships are. The most likely hypothesis is that the greater the economic dependence of a community upon forestry, or the greater the proportion of communities that are economically dependent upon forestry, the more likely it is that forests have sustainable management. For example, as people’s security is increased, their ability to take a long-term approach to resources is enhanced. Even so, the lack of clear cause-effect relationships between sustainable forest management and economic conditions of communities makes this premise debatable. Highly dependent economies may well be associated with unsustainably managed forests. In any event, there is probably at least a weak positive correlation between an economy with numerous substantial linkages to a forest and the sustainable management of that forest. The difference lies in not only the magnitude of dependence (e.g., the percent of total employment) but also the number of ways in which the economy is dependent (e.g., for timber products, recreational opportunities, water, forage for grazing, and non-traditional forest products).

Box K: Measurement Methods :

There is no explicit measurement indicating the relationship between the forest dependence of communities and sustainable forestry.

The measurement methods for this indicator, while relatively straightforward, do span a range of choices dealing with the definition "forestry-related" sectors and whether direct employment only is measured or if indirect employment is considered as well. These measurement choices are a subset of those applied to indicator L8a and are summarized in the following table.

Measurement method A3.

This measurement method interprets forestry-related sectors to be the timber and wood processing industries, and only direct employment in these sectors is considered.

Specific measurement methods would involve:

• Employment information for communities is stratified into two categories: forestry-related and all other. Forestry-related industries most likely include Standard Industrial Classification (SIC) industries 08 (Forestry) and 2400 (Wood Processing) and perhaps 2600 (Wood Manufacturing). In the study area, for example, a study similar to the McKetta and Robison (1996) could be commissioned or IMPLAN data could be obtained from MIG, Inc. for various 5-digit ZIP code areas corresponding to communities.
• If there is concern that local (or "place of residence") employment may be different that reported employment (at "place of work") due to commuting, the REIS "commuting adjustment factor" can be applied or explicit commuting patterns could be estimated as in McKetta and Robison (1996).
• The percent of total community employment accounted for by the forestry-related sectors is tallied for each community.
• The number of communities with dependency percentages of greater than 50% are deemed heavily dependent and those with percentages between 10 and 50% are moderately dependent.

Measurement method B3.

These measurement methods all interpret forestry-related sectors to include, besides the timber and wood processing industries, industries affected by rangeland forage grazing (e.g., SIC 02 Livestock Operations) and service sectors catering to the expenditures of recreation and tourism visitors to the study area such as lodging, food and transportation businesses. Again, only direct employment in these sectors is considered.

Specific measurement methods would involve:

• Employment information for communities is stratified into two categories: forestry-related and all other. Forestry-related industries most likely include SIC 08 and 24 sectors, range-fed cattle operations (SIC 02), and lodging, food and transportation businesses, as well as federal and state employment in forest, rangeland and recreation operations.
• A study similar to the McKetta and Robison (1996) could be commissioned or IMPLAN data could be obtained from MIG, Inc. for various 5-digit ZIP code areas corresponding to communities.
• If there is concern that local (or "place of residence") employment may be different that reported employment (at "place of work") due to commuting, the REIS "commuting adjustment factor" can be applied or explicit commuting patterns could be estimated as in Robison, et al (1996)
• The percent of total community employment accounted for by the forestry-related sectors is tallied for each community.
• The number of communities with dependency percentages of greater than 50% are deemed heavily dependent and those with percentages between 10 and 50% are moderately dependent.

Measurement method C3.

This measurement method interprets forestry-related sectors to be the timber and wood processing industries, and both direct and indirect employment in these sectors is considered.

Specific measurement methods would involve:

• Employment information for communities is stratified into two categories: forestry-related and all other. Forestry-related industries most likely include Standard Industrial Classification (SIC) industries 08 (Forestry) and 2400 (Wood Processing) and perhaps 2600 (Wood Manufacturing. In the study area, for example, a study similar to the McKetta and Robison (1996) could be commissioned or IMPLAN data could be obtained from MIG, Inc. for various 5-digit ZIP code areas corresponding to communities.
• Some type of economic multiplier model is required to estimate the indirect employment. Models such as those constructed with IMPLAN (MIG, Inc., 1996) or Robison, et al (1996) would serve well for this purpose.
• The percent of total community employment accounted for by the forestry-related sectors is tallied for each community.
• The number of communities with dependency percentages of greater than 50% are deemed heavily dependent and those with percentages between 10 and 50% are moderately dependent.

Measurement methods D3.

This measurement method interprets forestry-related sectors to include, besides the timber and wood processing industries, industries affected by rangeland forage grazing (e.g., SIC 02 Livestock Operations) and service sectors catering to the expenditures of recreation and tourism visitors to the study area such as lodging, food and transportation businesses. Again, both direct and indirect employment in these sectors is considered.

Specific measurement methods would involve:

• Employment information for communities is stratified into two categories: forestry-related and all other. Forestry-related industries most likely include SIC 08 and 24 sectors, range-fed cattle operations (SIC 02), and lodging, food and transportation businesses, as well as federal and state employment in forest, rangeland and recreation operations.. In the study area, for example, a study similar to the McKetta and Robison (1996) could be commissioned or IMPLAN data could be obtained from MIG, Inc. for various 5-digit ZIP code areas corresponding to communities.
• Some type of economic multiplier model is required to estimate the indirect employment. Models such as those constructed with IMPLAN (MIG, Inc., 1996) or Robison, et al (1996)) would serve well for this purpose.
• The percent of total community employment accounted for by the forestry-related sectors is tallied for each community.
• The number of communities with dependency percentages of greater than 50% are deemed heavily dependent and those with percentages between 10 and 50% are moderately dependent.

Box L: Data Required:

The statement of the indicator "Number of communities with a significant forestry component (heavily or moderately forest dependent) in the economic base" requires definition and data for four concepts: "community", "significance", "forestry component" and "economic base".

Obtaining data on employment by industrial sector at various scales may be problematic. For example, in the United States, the U.S. Department of Commerce’s Regional Economic Information System (REIS) includes time series information on employment at the state and county level, but includes no information at any lower scales such as individual communities (the complete time series for the US is available for $35 on CD). The highest level of industrial detail at which employment information in REIS is reported is 2-digit SIC (approximately 80 industry groups). Further, REIS reporting is subject to "non-disclosure" rules that prevent reporting statistics in such a way that information for individual businesses could be identified. As a result, information on employment for small counties is often incomplete, particularly with respect to forestry-related sectors. Information from the U.S. Bureau of Census is more complete, but is only compiled every ten years. Employment statistics are compiled by state governments as a way to track unemployment insurance collections (referred to as ES-202 programs). This information is highly specific, indicating employment in each firm (i.e., far more detailed than 4-digit NASIC). ES-202 data does not, however, include sole proprietorships and self-employed persons, and so it is incomplete. Further, ES-202 data is also subject to non-disclosure rules, and is usually unavailable for analytical purposes unless grouped and reported in a manner similar to the REIS data. Private sources of economic information can be very complete and comprehensive, but clearly more costly. For example the IMPLAN system (MIG, Inc., 1996) includes information for all U.S. states and counties with employment reported at the 4-digit SIC. These data sets are not subject to non-disclosure rules, and as a result are complete. Data availability in Canada and Mexico are probably similar or more restricted.

Economic multiplier models used to estimate the indirect employment component of some measurement methods can also be considered "data". Models such as those constructed with IMPLAN (MIG, Inc., 1996) or Robison, et al (1996) would serve well for this purpose.

Box M: Data Used for the North American Test:

A test of this indicator was not applied to the study area. Data on employment in forestry-related sectors is not presently available although the Payette National Forest has commissioned a study to assemble this information. For testing purposes, the indicator was evaluated for the counties in the study area rather than individual communities.

Box N: Example Results :

Dependency based upon direct employment in forestry-related sectors, by county (Measurement Method A3 using county rather than community data).

Box O: Assessing the Practicality :

This indicator can be relatively easily tracked over time given the availability of community-level economic information.

Box P: Assessing the Information Value:

The indicator can provide useful information for managers and stakeholders on the extent and degree of forest dependence among communities. The extent to which it conveys information about the relationship of economic conditions to sustainable forestry is suspect.

Box Q: Overall assessment :

Accepted -

Strengths:

1. It is a relatively easy, inexpensive indicator to measure.

2. Indicates direct relevance of community employment to forest management

Weaknesses:

1. The relationship between community economic dependence and sustainable forest management is unknown.
2. The indicator is very little different than indicator L8a "Employment of local population in forest management". This indicator simply computes percentages based on the data in indicator L8a, enumerating the number of areas falling into various strata.

Box R: Did you rewrite or revise to a new indicator. If so what?

No.

Box S: References:

• Canadian Council of Forest Ministers; Natural Resources Canada, Canadian Forest Service, Headquarters, Ottawa, Ont. 1992. National Forest Strategy. Sustainable forests: A Canadian commitment.
• Canadian Forest Service. 1997. The State of Canada’s Forests: Learning from History. Natural Resources Canada, Canadian Forest Service, Headquarters, Ottawa, Ont.
• U.S. Dept. of Commerce, Bureau of Economic Analysis. 1997. Regional Economic Information System, CD ROM. U.S. Government Printing Office, Washington DC.
• US Department of Commerce. 1987. Standard Industrial Classification (SIC) Manual. U.S. Government Printing Office, Washington DC.
• Robison, M. Henry, Charles W. McKetta, and Steven S. Peterson. 1996. A Study of the Effects of Changing Federal Timber Policies on Rural Communities in Northcentral Idaho. University of Idaho.
• Rasker, Ray. 1995. A New Home on the Range: Economic Realities in the Columbia River Basin. The Wilderness Society.
• MIG, Inc. (Minnesota IMPLAN Group, Inc), IMPLAN System (1995 data and software), 1940 South Greeley Street, Suite 101, Stillwater, MN 55082, www.implan.com, 1997.

Please record your notes on evaluating the indicator here.