0391-B4

Who's driving development of community sustainability indicators? Lessons from three journeys

Jeji Varghese and John Parkins ^*

Abstract

Forest-based communities can be exemplified in terms of remote subsistence dependence, park-based tourism dependence, or traditional logging dependence. In monitoring the sustainability of these places, researchers have struggled to develop relevant indicators that are responsive to their unique social, economic and environmental conditions. This study discusses the strengths and weaknesses of a number of methods used to identify appropriate indicators of sustainability within the Foothills Model Forest (FMF) in Alberta, the Prince Albert Model Forest (PAMF) in Saskatchewan and the Robson Valley Forest District (RVFD) in British Columbia. Indicators for the FMF focused on a suite of expert-defined indicators drawing on Statistics Canada census data. To address the uniqueness of three diverse communities in the PAMF, we employed a quality-of-life research framework for identifying appropriate social indicators and then we subjected these indicators to an evaluation framework. This framework provided criteria for ranking indicators according to their general effectiveness and their relevance to important dimensions of sustainability. This approach generated a number of unique indicators for each community. The RVFD project has elements of both approaches. Hence, the Alberta approach was expert driven, the Saskatchewan method was community driven and the British Columbia approach combined expert and community input. Lessons gleaned from these three processes are discussed.

Introduction

Forest-based communities can be exemplified in terms of remote subsistence dependence, park-based tourism dependence, or traditional logging dependence. In monitoring the sustainability of these places, researchers have struggled to develop relevant indicators responsive to their unique social, economic, and environmental conditions. This paper discusses the strengths and weaknesses of a number of methods used to identify appropriate indicators of community sustainability within the Foothills Model Forest (FMF) in Alberta, the Prince Albert Model Forest (PAMF) in Saskatchewan and the Robson Valley Forest District (RVFD) in British Columbia. This paper begins with a description of the three regions (see `points of origin'). This follows with a description of each approach (see `three journeys'). The paper concludes with an analysis of each approach and provides recommendations for future community-level social indicator work.

Points of Origin:

Foothills Model Forest¹, AB

The FMF consists of 2.75 million ha of land in west central Alberta. Three principal partners with land management interests include Weldwood of Canada, the Alberta Department of Sustainable Resource Development, and Jasper National Park. Three communities fall within its boundaries: the town of Hinton is a diversified resource-dependent community of about 10 000 residents, the Jasper town site consists of about 3 600 permanent residents and a large influx of visitors in the summer, Yellowhead Municipal District (#94) represents the rural region surrounding Hinton and consists of over a third of the population base of the FMF.

Prince Albert Model Forest², SK

The PAMF, located in central Saskatchewan, is 360 000 ha in size. Three communities located within the PAMF participated in a study to identify local-level indicators of community sustainability. The Resort Village of Candle Lake (hereafter referred to as Candle Lake) is a retirement and recreational community, Montreal Lake is a Cree Nation community and Waskesiu Lake is a seasonal resort community located within a national park.

Robson Valley Forest District³, BC

The Robson Valley Forest District covers approximately 1.4 million hectares in the British Columbia interior. It is a provincial government jurisdiction composed of two villages (Valemount and McBride) and numerous dispersed rural communities. These numerous dispersed rural communities are hereafter referred to as the Rural Valley.

Three Journeys:

The three studies under consideration in this meta-analysis are described below in chronological order. Table 1 provides a visual summary of these three approaches. The approaches are named based on who drives the indicator identification process. Recognizing the potentially contentious implications of the terms "expert' and `community' we use these terms simply to acknowledge the perspective from which this work was initiated. In all three cases, local organisations solicited input outside their communities from those with social science expertise. `Expert' thereby denotes a non-local social science perspective and `community' refers to input obtained at a local level.

Table 1: Process Comparison of Approaches

Foothills Model Forest: Expert-driven approach

Indicators for the FMF focused on a suite of standard indicators drawing on Statistics Canada. These indicators include (Parkins and Beckley 2001):

These broad categories where chosen for several reasons. First, published literature shows the repeated use of these indicators as highly relevant to the well being of rural communities. Second, data used to measure these indicators are readily available from existing sources. Trend data is also relatively easy to establish. Third, with minimal effort, these six indicators can be integrated with other indicators designed to measure sustainable development on a regional level. Comparisons are possible between other communities, regions, and provinces.

In addition to developing the comprehensive database of relevant statistical information, we realized a need to go beyond reporting the basic facts. These measures provide insight into current social and economic realities, but they do not provide any indication as to why certain conditions exist, and what the implications are for community residents. In an effort to provide a deeper analysis of social conditions, we included a major qualitative element to the study, thus providing an essential local context and local-level understanding of the social indicators in question. In large measure we used this qualitative or narrative information to inform the quantitative data. Using a snowball sampling method, we targeted 145 key informants within community sectors such as industry, government, social services and forest user groups. Computer software (NUD-IST) assisted in the identification of themes and major trends within the qualitative data. Combined with census data, these themes served to deepen our understanding of the social and economic dimensions of well being in these communities.

Prince Albert Model Forest: Community-driven approach

The three communities have distinct relationships with the forest ecosystem as a result of different histories, different socio-demographic profiles and as such have different goals and aspirations for future sustainability (Parkins et al. 2001a). To address these unique cultural, historical and socio-economic characteristics of communities in the PAMF, three tools were used by Parkins et al. (2001b) to identify and select local level indicators: workshops, an indicator evaluation framework, and community surveys (Refer to Figure 1).

Workshops provided the opportunity for residents to identify issues germane to community sustainability through a quality of life research framework. From these workshops, a list of social indicators were identified and subjected to an evaluation framework drawn from three sources (refer to Computer Research Laboratory for the Environment 1999; Flora et al. 1999; and Hart 1999). Two criteria were used initially: (1) effectiveness in terms of data understandability, availability, reliability, relevance, cost, sensitivity, and temporal comparability, (2) relevance to issues of community sustainability. Those indicators with relatively high scores for effectiveness and relevance to sustainability were then included in a short questionnaire administered to community members. From this survey we were able to assess the indicators on another dimension, specifically, the indicator's relative level of importance to the community. This approach generated a number of unique indicators and resulted in a unique suite of indicators for each community. For example, Montreal Lake's included indicators such as, spiritual well-being, access to traditional knowledge, opportunities to retain language and job opportunities in the natural resource sector. In Candle Lake, unique indicators included rate of local taxation, noise pollution and enforcement of recreational regulations. Unique indicators in Waskesiu Lake included accessibility of the poor to the community and national park, pedestrian friendly streets and levels of isolation or linkages with outside communities. Communities were also directly involved in monitoring the indicators. Refer to Hawkins and Varghese (2002) for details on this involvement and baseline data for two of the three communities. The third community requested that baseline not be made public. This raises an issue for further discussion, specifically, how to ensure that communities retain control over locally defined indicator data.

Robson Valley Forest District: Approach combined expert and community input

The RVFD suite combined both approaches (refer to Varghese, Parkins and Stedman in preparation). Workshops and interviews were first conducted to establish community priorities. Once community priorities were identified, a survey was developed and distributed to a larger segment of the population within the Robson Valley. The survey sample drawn by a polling firm ensured adequate representation from all valley communities. Results from the survey were evaluated based on the effectiveness and relevance to sustainability criteria used in the PAMF project and incorporated subsequent literature (such as Besleme et al. 1999; Sirgy et al. 2000; and Cobb 2000).

The villages of Valemount and McBride have similar priorities, however, the order of importance differs. As such, they share an indicator suite. The Rural Valley shares a large number of indicators in common with Valemount and McBride, however, differences in priority areas resulted in a few unique indicators within each suite. The level of overlap in the indicator suites reflects common priorities of Robson Valley residents, which contrasts with the indicators suites developed within PAMF. Indicators reflecting both community and expert input resulted in two suites of indicators (village and rural).

Journey Destinations

Comparison of the three methods in terms of the process, and strengths and weaknesses are summarised in Table 2. These are discussed below several thematic headings.

Comparability vs. uniqueness of indicator suite

One strength of the expert-driven approach is that the use of standard measures enables comparison across communities. Using census data helps keep costs down, and makes the data highly accessible, though the face-to-face interview data collected to supplement census data is time consuming and costly. Comparison across communities is useful from a policy level in ascertaining distribution of regional resources, for example. In addition, using standard measures can help bring social concerns to a resource management agenda, as the data tends to be more objective and easily measurable. However, at a community level, these indicators may not be as critical.

One assumption made by using a standard suite of measures is that every community is alike and has similar goals and visions. Obviously, this is not the case. Though there may be similarities as the RVFD study showed (many overlapping indicators and measures), the PAMF study indicates just how diverse communities can be (i.e. with three distinct indicator suites). The community-driven approach ensures that indicators are sensitive to community goals and that locally meaningful indicators and measures are developed. The downside to community-driven approaches is that the expense in developing and monitoring protocols for a large number of unique measures makes monitoring very costly to undertake. Indicator suites developed through combined community-expert approaches can mitigate these two extremes by ensuring both standard and locally meaningful measures are included within the indicator suite.

Community Representation

Representation varies among the different approaches. In the expert-driven approach, representation of community members' views on data collected was incorporated through the narrative component. However, members were not represented in choosing the set of indicators used. The community-driven approach was only representative of those who participated in workshops in term of both indicator and measure selection. A more concerted effort was made within the Robson Valley project to incorporate a larger segment of the population through workshop and survey work in indicator selection.

Comprehensive Evaluation Framework

The expert-driven approach was not assessed on a comprehensive evaluation frame, because an extensive literature review served to validate chosen indicators. The other two approaches benefited from this assessment. Table 3 contains a comparison of each indicator suite against Hart's (1999) community sustainability framework. One point was given for each indicator-measure that addressed a particular component. Obviously, the two approaches that integrated the framework did better across a number of different criteria. However, it is important to note that neither expert nor community driven approaches on their own spanned the broad set of criteria. Therefore, unless assessed on a comprehensive frame, suites may be skewed towards "key goals of the day," for example, economic at the expense of environmental or social, in the case of the community-driven approach or to those indicators with effective measures in the case of the expert-driven approach.

Monitoring

A challenge of using the expert-driven approach is that the relevance of the data to issues of sustainability may require social science interpretive expertise. For instance, what are the implications for declining levels of social cohesion or place attachment? Theoretical considerations are an important key to this response. The monitoring itself, however, does not require social scientists to undertake.

Within the community-driven approach, unique indicators require development of measures and monitoring protocols. These often requiring social science expertise and can be a costly, time-consuming endeavour initially. In addition, measurement and monitoring is difficult to sustain at local levels, especially in communities with a small population of year-round residents, for example in resort villages and national park communities.

Table 2: Strengths and Weaknesses of Indicator Approachs

Table 3: Sustainability criteria and evaluation of indicator suites

Social Science Role

Many of the weaknesses of community-driven approaches exist within the combined approach but they are mitigated by more active involvement of social scientists. For example, as a community-driven process, learning from other indicators projects is limited. Social scientists play an important role in bridging the learning gap across various communities by incorporated their experiences from other indicator initiatives.

Lessons/Recommendations

We found that community-driven approaches are more likely to employ less effective indictor suites (based on effectiveness criteria) than expert-driven approaches. However, expert-driven approaches are less likely to choose indicator suites relevant to the complete range of criteria for community sustainability. Combining these two approaches leads to suites of indicators that have more effective measures and more relevance to community sustainability than either approach on its own. Hence, our first recommendation is that expert and local level approaches be combined.

In order for indicators to be useful, they must inform decisions and policy developments. This truism in social indicators research requires strong buy-in from community leaders in defining relevant indicators and in commitments to ongoing monitoring. This commitment is fostered through more locally driven approaches that invite participation from the outset.

A shorter list of indicators that are more easily measured is likely to have more policy impact than a lengthy list of measures that are difficult to collect and interpret. Fewer indicators may not cover the entire range of sustainability concerns but they may push us beyond the standard income and employment statistics that are so common, yet grossly inadequate in assessing the well being of human communities.

A latent effect of indicator research is often building community capacity. Community-driven and combined approaches have the potential to build community capacity. If building community capacity is a goal of indicators research, then it should be built into the design of the project from the onset.

Literature Cited:

Computer Research Laboratory for the Environment. 1999. Sustainable community indicators [on-line]. University of Guelph, Guelph, ON. http://www.crle.uoguelph.ca/indicators/.

Flora, C. B., M. Kinsley, L. Luther, W. Milan, S. Odell, S. Ratner and J. Topolsky. 1999. Measuring community success and sustainability. An interactive workbook. Iowa State University, North Centr. Reg. Cent. Rural Dev., Ames, IA.

Besleme, Kate, Maser, Elisa, and Silverstein, Judith. 1999. "A community indicators case study: Addressing the quality of life in two communities" [on-line]. Available at http://www.rprogress.org/publications/pdf/CI_CaseStudy1.pdf.

Cobb, Clifford W. 2000. "Measurement tools and the quality of life." [on-line]. Available at

http://www.redefiningprogress.org/publications/pdf/measure_qol.pdf

Hawkins (Stovel), J. and J. Varghese. 2002. State of Local Level Community Sustainability for Two Communities Within the Prince Albert Model Forest. PAMF Ecosystem Health/Local Levels Indicator Working Group, Prince Albert Model Forest Association, Prince Albert, Saskatchewan. 65 p. Available online: http://www.pamodelforest.sk.ca/pubs/CL_WL_Baseline.pdf

Hart, Maureen. 1999. Guide to Sustainable Community Indicators. 2^nd Ed. Hart Environmental Data: North Andover, MA. 202p.

Parkins, J. and T. M. Beckley. 2001. Monitoring community sustainability in the Foothills Model Forest: a social indicators approach. Natural Resources Canada, Canadian Forest Service, Atlantic Forestry Centre, Fredericton, New Brunswick. Information Report M-X-211E. 148 p.

Parkins, J, J. Varghese, and R. Stedman. 2001a. Locally defined indicators of community sustainability in the Prince Albert Model Forest. Information Report NOR-X-379. Northern Forestry Centre, Edmonton, AB.

Parkins, J., R. Stedman, and J. Varghese. 2001b. Moving towards local-level indicators of sustainability in forest-based communities: A mixed-method approach. Social Indicators Research. 56(1):43-72

Sirgy, M. Joseph, Don R. Rahtz, Muris Cicic, Robert A. Underwood. 2000. Method for Assessing Residents' Satisfaction with Community-Based Services: A Quality-of-Life Perspective. Social Indicators Research 49(3): 279-316.

Varghese, J., J. Parkins, and R. Stedman. (in preparation) Local-level social indicators of community sustainability for the Robson Valley. Draft Report for the Robson Valley Forest District Forest Management Pilot Project.

^* Department of Rural Economy, University of Alberta, 515 General Services Building, Edmonton, AB, Canada T6G 2H1. [email protected]

¹ For more information visit http://www.fmf.ab.ca

² For more information visit http://www.pamodelforest.sk.ca

³ For more information visit http://www.for.gov.bc.ca/pgeorge/district/robson/home.htm and http://www.for.gov.bc.ca/pgeorge/district/robson/efmpp

⁴ No indicator-measures were deemed to be at the expense of another community or at the expense of global sustainability.

⁵ It is important to note that the sustainability criteria were not in place during this approach. However, applying it after the fact reveals gaps that we felt were useful to highlight in this manner.

⁶ These 7 indicators are monitored through 38 measures.