the links between industrial, community, and ecological sustainability: a forestry case study

©1999 Blackwell Science, Inc.

COMMENTARY

.

The Links Between Industrial, Community, and Ecological Sustainability: A Forestry Case Study

Aleck Ostry

Department of Health Care and Epidemiology and Center for Health Services and Policy Research, University of British Columbia, Vancouver, British Columbia, Canada

ABSTRACT

According to Harold Innis, Canada’s economic history hasbeen based on the discovery of natural resources, conse-quent community formation to facilitate their extraction,resource depletion, and finally, community disappearance.This model links industrial change and development in theresource sector with both community and ecological out-comes but neglects detailed exploration of the industry/ecosystem linkage. The purpose of this paper is to adaptthe ecological footprint concept in order to make the eco-logical impact of economic and technological change in aCanadian resource industry (sawmilling) explicit. This in-vestigation utilizes a large cohort of sawmill workers gath-ered in 14 British Columbia (B.C.) mills, a study that mea-sured the ecological footprint in several of these mills, anda labor adjustment study conducted by Statistics Canadato explore the links between technological change anddownsizing in this resource industry and both community

and ecological sustainability. The ecological footprint con-cept is adapted for use in a resource-extracting industry.This allows moving the estimation of the ecological foot-print from its usual place, an urban consuming population,to the site of natural capital transformation (the sawmill)thereby linking the costs and benefits of this transforma-tion with site or region-specific ecosystem exploitation. Re-sults demonstrate that the recession of the early 1980seliminated over 40% of the sawmill workforce and stimu-lated increased replacement of labor by capital, thus in-creasing productivity and the ecological footprint of saw-mills. The new technical infrastructure now in place in mostsawmills is accelerating the pace of forest ecosystem draw-down while at the same time producing less economicbenefit for the local community. Adaptation of the ecologi-cal footprint for use at the site of the transformation ofnatural capital makes these trade-offs more specific.

.

INTRODUCTION

According to Rapport (1998a,b), “healthy ecosys-tems are characterized by their capability to sus-tain healthy human populations.” The fishing toextinction of Canada’s east coast cod and theattendant collapse of outport communities is agraphic illustration of the dependence of humanpopulations on the health of ecosystems. Such alink is most visible and immediate in communitiesdirectly dependent on the extraction and primary

processing of the natural products of local ecosys-tems. Canada is unique among western industrial-ized countries in having large numbers of com-munities involved in direct exploitation of nature.

According to Harold Innes, much of Canada’seconomic history has been based on the discoveryof natural resources, consequent community for-mation to facilitate their extraction, resource deple-tion, and finally community disappearance (Hayter& Barnes 1990). The historical pattern of this In-nesian “cycle of destruction” has been well docu-mented from the fur trade in the 16th centurythrough to the Newfoundland cod fishery in ourown century.

Address correspondence to: Dr. Aleck Ostry, Department of Health Care and Epidemiology, 5804 Fairview Avenue, Van-couver, BC, Canada, V6T 1Z3; E-mail [email protected].

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Ecosystem Health Vol. 5 No. 3 September 1999

The strength of Innes’s model is that it linksindustrial change and development in the re-source sector with both community and ecologi-cal outcomes. However, the model’s focus is onthe economic history of industry/community in-teractions rather than on industry/ecosystems in-teractions. Ecologists have increasingly becomeconcerned about the linkage between ecosystemhealth and the health of economies. According toRapport (1995), “healthy ecosystems must notonly be ecologically sound, but must also be eco-nomically viable and able to sustain humanhealthy communities.”

The purpose of this article is to explore thelinkage between ecosystems and economy by de-veloping and using an adapted form of the eco-logical footprint tool to make explicit the ecologi-cal impact of economic and technological changein a Canadian resource industry (sawmilling).This article also develops the industry/commu-nity component of the Innis model.

BACKGROUND

The forest ecosystems that sustain British Colum-bia’s (B.C.) forest products industry, including saw-milling, are under increasing pressure. In B.C., forexample, “50% of all the public timber cut hasbeen felled in the last 13 years. The most rapid ac-celeration has primarily been in the B.C. interior,with 50% of the total cut being done since 1977.The northern regions of Prince George and PrinceRupert have an even faster acceleration rate”(Travers 1993). In addition, “much of this accelera-tion has been above the Ministry of Forest’s own es-timates of the sustainable yield” (Travers 1993).

At the same time, employment in forest-basedmanufacturing in most towns has shrunk to recordpost-war lows. The increased rate of natural capitaldepletion using a smaller industrial workforce hasbeen made possible because of the dramatic tech-nological changes that began in the forest prod-ucts manufacturing sector, including sawmillingand the pulp and paper industry, in the late 1970sand early 1980s. Large segments of the industryhad, by the early 1980s, moved from “Fordist” as-sembly line mass production methods to “flexible”methods of production and work organization.This was made possible largely by a combination ofnew markets and new computerized productiontechnology (Barnes & Hayter 1995).

The increasing rate of tree consumption com-bined with a diminishing labor force poses a twinsustainability challenge. On the one hand, forestry-

based communities receive less revenue in theform of direct wages and municipal taxes from localmills (Regional Data Corporation 1994). If there isno economic diversification within the affectedcommunity the economic base is reduced shrinkingthe local labor market and increasing pressure—particularly in single industry mill towns—on work-ers to leave the community in order to find work inother cities. Shrinking local revenues and down-ward pressure jobs both act to reduce communitysustainability. At the same time, sawmills, mademore efficient by recent technological enhance-ment, increase pressure on the ecosystems fromwhich logs are extracted which may act to reduceecological sustainability.

From a traditional economic perspective sucha scenario may be acceptable because greaterthroughput of raw logs and more efficient tech-nology in mills means greater productivity andshort-term wealth generation. Viewed through asustainability lens, however, increased productiv-ity in sawmills could lead to increased pressureson forests, permanent job loss, and reduced com-munity viability. From the ecosystem and commu-nity perspective, enhanced industrial productiv-ity is desirable only if it leads to lower resourcethroughput.

In this investigation, the changing ecologicalfootprint of several major sawmills in the provinceis examined. The ecological footprint is an esti-mate of a specific population’s consumption ofmajor resources measured in terms of the amountof land

in continuous production

that is necessary tosustain the group’s rate of consumption (Wacker-nagel & Rees 1996). In this study an attempt hasbeen made to adapt the concept to a resource-extracting industry. Accordingly, the sawmill, ratherthan a population group, is the unit of consump-tion, and because turning trees into lumber is arelatively crude primary manufacturing process,most of the footprint can be assessed directly bymeasuring lumber production.

However, it should be emphasized that thisapproach will result in a conservative estimationof the “true” ecological footprint of a sawmill be-cause mill lumber production is an underestimateboth for the number of trees consumed each yearand the total energy required by a mill to converttrees to lumber. The ecological footprint esti-mated on the basis of lumber production alonedoes not include the wastage involved in convert-ing trees to lumber, the energy required for log-ging the trees, building logging roads and otherinfrastructure, and the energy required to oper-

Ostry: A Forestry Case Study

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ate the sawmills. This calculation also does not in-clude the size of the land base required for a con-stant flow of trees to a sawmill, which will dependon factors such as logging intensity, general for-estry, and silviculture policies and will expand asaccessible stands of this largely nonrenewable re-source are logged off.

This analysis is based on a database of approx-imately 26,000 B.C. sawmill workers, gathered toinvestigate the occupational effects of antifungalchemicals, in combination with sawmill produc-tion data gathered during this time (Hertzman

etal.

1997). The job history information in the data-base was used to determine changing employ-ment patterns in these mills. For mills located inforestry-dependent communities, changing em-ployment opportunities have direct effects on theeconomic sustainability of the community. Thus,employment change can be linked with commu-nity sustainability. In addition, using a survey ofemployed and laid off forest industry workers dur-ing the period 1978–1985, the economic impacton the community of technological restructuringin sawmills was estimated (Cohen & Allen 1988).Finally, a study was conducted to determine theecological footprint for these mills.

The time period for this study covers theyears 1950–1985 as this is the time frame of origi-nal cohort study. However, the focus of this inves-tigation is on the years between 1978 and 1985 be-cause this is when the largest recession and majorindustrial restructuring took place. It should benoted that the technological revolution in the in-dustry has continued and the results shown forthe time period under investigation may underes-timate current effects. For example, according toMarchak (Marchak 1995), “in gross terms 966 cu-bic metres per year of timber supported a job in1980, but 1,300 cubic metres per year was re-quired in 1993. In the major employment area,sawmilling and plywood production, 48% moretimber is required to support a job in 1993 thanin 1980, including jobs in management, plants,production, transportation, and infrastructure.”

THE EMPIRICAL BASE

The empirical basis for this investigation consistsof a cohort of sawmill workers, a study that mea-sured the ecological footprint of several of thesemills, and a forestry-worker labor adjustment studyconducted by Statistics Canada (Cohen & Allen1988).

SAWMILL WORKERS’ COHORT

The cohort was gathered between 1987 and 1992in order to investigate the effects of an antifungalchemical, chlorophenol, on sawmill worker health.It consists of 26,487 men who worked for at leastone year between 1950 and 1985, in at least one of14 large sawmills located in four regions of theprovince: the Lower Mainland, the Interior, Van-couver Island, and the Southern B.C. MainlandCoast. Complete information on job history wasavailable in 11 of the study mills for the time pe-riod 1950–1985, so that temporal and regionalchanges in employment could be tracked. Becausethree of the mills were not built until the 1960s,data for early time periods are missing.

FOREST SECTOR LABOUR ADJUSTMENT STUDY

Produced in 1988 for Employment and Immigra-tion Canada, this longitudinal study linked Statis-tics Canada and Revenue Canada files for theyears 1978 to 1985 in order to study incomechanges among Canadian forestry workers (Co-hen & Allen 1988). Data was individually linkedbut is presented in grouped form for confidential-ity reasons. Income data for workers and theirspouses and unemployment data for workers inthe B.C. sawmill workforce are available for theperiod 1978–1985. This is convenient as this timeframe straddles the major restructuring period inthe industry and overlaps with the last few years ofthe sawmill workers’ cohort study. By linking thecohort study data with the economic study, demo-graphic changes occurring between 1978 and1985 were translated into likely economic impactsfor sawmill workers and their families at the com-munity level.

LABOR DEMOGRAPHY FOR THE COHORT

Three mills built in the 1960s were excluded fromthe initial analysis; the remaining 11 study millsreflect the demographic reality of the larger, es-tablished sawmills for the entire time period of1950–1985.

Figure 1 shows that in all 11 mills employ-ment grew by approximately 30% during theboom in the 1960s, peaking in 1973. From 1973–1979, employment remained high and fairly sta-ble, but from 1979–1985, employment droppedby about 40%. In exact terms, employment in the11 mills dropped from 8,457 to 4,896 workers, a

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total of 3,561. In 1982 alone, 1,078 workers losttheir jobs. Based on patterns of employment loss,the post-1979 period appears unique.

Of the 3,561 workers who lost their jobs be-tween 1979 and 1985, 2,232 were actively termi-nated and 1,329 retired or were retired. In a labormarket where layoffs usually proceed in terms ofstrict seniority, one would expect younger work-ers to bear the brunt of employment layoffs. Theextent to which older workers were affected byemployment downturns depended on the degreeto which mills adopted policies of encouraged orforced early retirement. These data indicate that,during the recession of the early 1980s, aboutone-third of workers were let go through bothnormal and possibly early retirements.

In fact, however, most job losses were activeterminations, meaning that the downturn af-fected mainly the younger segment of the work-force. Because community viability is directly re-lated to the ability of younger workers to obtainlocal employment, the age-specific changes in ter-mination profile across time periods and regionsare informative. Figure 2 shows the change in therate of active terminations for the sawmill cohortfrom 1955–1985. Layoffs are considered activeterminations, while terminations due to illness,disability, or retirement are not. Active termina-tions are emphasized because these are morelikely to reflect the size of the real “bite” of eco-nomic change in the workforce.

Using a life-table approach, age-specific per-son-years of employment were constructed withactive termination rates for three time periods be-tween 1950 and 1985. In order to compare activetermination rates of older workers with youngerworkers, the number of person-years of employ-ment were standardized for mortality using 1981–1985 cohort mortality rates. In this way, the im-pact of mortality on person-years of employmentis removed allowing for a more effective compari-son of active termination rates between youngand old workers.

In Figure 2, active termination rates are mod-eled over time by showing the decline in the num-ber of person-years worked for 10 age groups inthree different time periods. Active terminationsreduced the person-years worked in 1981–1985 by20% compared to 1961–1965. Seventy-eight per-cent of these lost person-years were within the agegroups 15–35, with particularly hard losses forthose under the age of 25. Again, this is not sur-prising given that the order of layoffs is strictly se-niority-based and the absolute number of jobs lostwas very high.

These data indicate that employment lossesfollowing the recession of 1981 were more drasticthan for any other recessionary era after 1950.And workers under the age of 35 appear to havebeen most affected. It is likely that job losses amongyoung workers will have more impact on commu-nity viability, particularly in forestry-dependent

FIGURE 1. Total number of workers in eleven study mills by year.


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towns, than losses among older workers becausethe elimination of employment opportunities foryouth, particularly in single-industry towns, is likelyto cause young workers to leave these communi-ties in order to find work elsewhere. The commu-nity impact of these labor force changes is ana-lyzed in more detail in the next section.

COMMUNITY SUSTAINABILITY

The impact of labor structure change and mobil-ity will be most noticeable in mill towns, that is,towns in which the sawmill is the only large em-ployer. Towns such as Tahsis, Chemainus, andYoubou on Vancouver Island are mill towns thathistorically have depended primarily on their saw-mills. Port Alberni, Harmac, and Powell River arelarger mill towns in which the sawmill has histori-cally been a less important part of an integratedforest products manufacturing complex. Finally,the mills in Vancouver are a small part of a com-plex urban labor market.

According to this hierarchy of communitiesin our database, sustainability in small mill townsmay be more directly assessed by examining thefate of their sawmills. It is more difficult to makethe connection between the fate of labor forcesand the fate of a community in complex labormarkets. However, insofar as changes in sawmilllabor demography reflect broader shifts in theforest products manufacturing labor force, theyprovide indicator data on the potential commu-

nity impact of these changes. Such data are stron-gest for the most mill-dependent towns.

Most of the sawmills in this study initiated ma-jor capital investments in technology in the late1970s and early 1980s. The dramatic shift in em-ployment after the recession of the early 1980srepresents a combination of cutbacks in produc-tion and replacement of labor by capital-intensiveequipment. Absolute, regional, and age-specificemployment after years of fairly stable employ-ment patterns show a dramatic shift by 1985.

The cohort study indicates that about 60% ofthe sawmill workforce employed during the peakyears in the 1970s remained employed in themills after the recession of the early 1980s. Theseresults are similar to those found in the ForestrySector Labour Adjustment Study, which indicatesthat 56% of B.C. sawmill workers employed in1978 were still employed in a sawmill in 1985 (Co-hen & Allen 1988). The latter study found that, ofthe 100 workers who had a sawmill job in 1978,44% had lost their sawmill jobs by 1985. (Table 1)They found that 62% of these workers managedto find another job by 1985. However, of these,only 16% found employment somewhere in theforestry industry other than a sawmill. Eighty-fourpercent of those who managed to find anotherjob found one outside the industry. By linkingthis information to income tax files, they wereable to ascertain that workers who found jobselsewhere within the forestry industry kept theirincomes stable. However, those who obtained

FIGURE 2. Comparison of person-years worked by age for three time periods standardized to 1981–1985 mortality rates.

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jobs outside the industry were earning 33% less in1985 than their sawmill jobs had paid in 1978,$21,147 compared with $31,435. In addition, a to-tal of 17% of the workers employed in a sawmillin 1978 were unemployed by 1985.

When one combines the information fromboth the cohort study and the Labour Adjustmentstudy, it is clear that there has been a large loss ofjobs from the sawmill and forestry sector, and thatthis job loss has the most severe impact on young

workers and those near retirement. It is also clearthat even for those who obtained reemployment,income levels earned in 1985 were drastically re-duced from 1978 levels. (Table 2.)

If one assumes that no migration took placein the affected communities between 1978 and1985, there is a net income loss of $83,991,816just in terms of personal income. This does not in-clude lost municipal tax revenue and any associ-ated downturn in local economic activity.

TABLE 1

1985 Status of 100 Sawmill Workers Who Were Employed in B.C. Sawmills in 1978

# of workers in 1978 # of workers in 1985 Income of workers in 1985

1

100 56 (still in mills) 35,9066 (in other f.p.i.

2

) 33,76121 ( jobs outside f.p.i.) 21,1472 (EI) 6,306

15 (no job/no EI) 0

1. Core workforce in 1985 was 56% of its size in 1978 and in 1985 had an average income of $35,906.2. Only 6% of workers in sawmills in 1978 were able to move “sideways” into another high income sector of the forest

products industry.3. If we assume the people on employment insurance (EI) and with jobs outside the forest products industry are available

potentially as a “peripheral” workforce for the sawmills, this peripheral labor market operates at an average wage level 45% less than the core ($19,850 vs. $35,906).

1

All incomes in 1985 Canadian dollars.

2

f.p.i.

5

Forest products industry.

TABLE 2

Estimated Income in 1978 and 1985 for Sawmill Workers in the Cohort Assuming Rates of Layoff and Subsequent Income Levels from the Forest Sector Labour Adjustment Study

1978 1985

Estimated wages from 12 mills

1

332,238,218 186,053,042Income from workers who obtained other f.p.i.

2

jobs 19,934,293Income from workers who obtained non-f.p.i. jobs 41,091,370EI income 1,166,988Totals 332,238,218 248,246,402

Net Loss 83,991,816

1

All incomes in 1985 Canadian dollars.

2

f.p.i.

5

Forest products industry.


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Labor demographic changes for small saw-mill towns are more directly translatable to com-munity sustainability than for urban regions andmore diversified mid-size towns such as Port Al-berni. Given this fact, and combining the cohortstudy with the Forestry Sector Labour ForceStudy, it is clear that the approximately 40% em-ployment losses in the sawmill cohort probablytranslated to a minimum 25% income loss for thecommunity, assuming that the unemployed work-ers did not out-migrate.

If one also assumes out-migration took place,and this is a much more likely scenario in single-mill towns, then overall economic loss to the com-munity was likely more than 25%. In addition, asthe termination-by-age-group data indicates, thebrunt of employment loss was borne by youngworkers. The elimination of entry points for youngworkers into industry in single or restricted indus-try towns may force these workers to look for workin other communities leading to premature eco-nomic and demographic community senescence.

Besides these direct losses, there are a num-ber of less direct fiscal and health-related losses.There are costs to the municipality in lost forestcompany taxes, as well as losses to municipal, pro-vincial, and federal governments in other taxshortfalls resulting from the employment down-turn. For example, according to a recent surveyby the Regional Data Corporation, municipal taxrevenue in Powell River dropped by 15% between1990 and 1993. The same study indicates an in-crease in the economic dependency ratio, whichis a measure of the extent to which transfer in-come from other levels of government enters thecommunity in order to replace the income lostfrom industry layoffs.

Unemployment creates indirect costs for alllevels of government. Both the anticipation of un-employment in employed groups of workers andunemployment itself have been linked to a rangeof disease outcomes including heart disease andpsychiatric disorders (D’Arcy & Siddique 1985; Jin

et al.

1995; Mattiasson

et al.

1990; Westin

et al.

1989). In 1995, the suicide rate among the unem-ployed in B.C. was 11 times that of the total laborforce (B.C. Division of Vital Statistics. 1995). Thesuicide rate for young males is usually high, but theimpact of unemployment may render this groupeven more vulnerable. The health consequences ofunemployment are enormous. They are paid forby tax dollars, but the cost is not usually includedin the accounting process when the cost of techno-logical change in industry is measured.

Direct and indirect health and other welfare-related costs of labor force reduction can beviewed as a public subsidy to labor force structuralchange carried out within the private sector. If to-tal company income remains stable or even in-creases after these structural changes in the laborforce, and if the taxpayer covers the health andwelfare costs incurred by these changes, then amassive public subsidy of the private sector willhave occurred. Furthermore, it will have occurredwithin an ideological and political atmosphere inwhich the federal government has been withdraw-ing massive funds from health, welfare, unem-ployment insurance, and labor force retraining,placing the burden of this hidden public subsidyincreasingly on the provincial government. In ad-dition, the subsidy will have occurred in the polit-ical environment of the 1980s and 1990s, whenprivate enterprise unfettered by government isthe supposed panacea for modern economicwoes.

Clearly, changes in mill technology affect la-bor force demography and community sustain-ability. Because long-term sustainability of the for-est-based community ultimately depends on thelong-term sustainability of the forest ecosystemsthat supply its mills with logs, it is important toground changes in technology, labor demogra-phy, and community sustainability within a con-struct of ecosystem health. The first step is to at-tempt to gauge the changing ecological footprintof these mills over time.

ECOSYSTEM SUSTAINABILITY

In B.C. the pressure on forest ecosystems has in-creased dramatically. The Annual Allowable Cut(AAC), the volume of trees the Ministry allows tobe cut on forest tenures in the province, amountedto 60.8 million cubic meters in 1975. By 1980 thishad increased to 66.7 million cubic meters. By themiddle of the decade it was up to 67.3 million cu-bic meters, and by the end of the decade it was 74.3million cubic meters. This amounts to an increaseof volume allocated in forest tenures of about 1million cubic meters per year since 1976. By the1980s “the capacity of current operating mills ex-ceeded the AAC by about a third” (Marchak 1995).

It is clear, therefore, that after the mid-1970sthere was a significant increase in the rate at whichthe carrying capacity of the B.C. forests has beenappropriated. This increase has, for the entire de-cade, hovered above the Ministry’s own estimatesof ecosystem sustainability. In effect, ecological ap-

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propriations above an ecologically sustainable limithave helped fuel the shift toward a more technol-ogy intensive industrial system.

One way of measuring the impact of such achange is to determine the ecological footprint ofeach mill, or the quantity of logs each mill con-sumes over time. Ideally one would want to knowthe exact quantity of logs consumed per unit time.This information is not available, but estimates ofannual mill production are available for 8 of the 14study mills for selected years from 1950–1985(Miller Freeman 1986). These data can be used toexamine the mill’s changing impact on the ecosys-tems that supply them with logs.

The ecological footprint is therefore propor-tional to the volume of lumber produced per millduring each of the five time periods for whichdata are available (Figure 3). The eight largecoastal mills show a greater than 60% increase intheir production volume from 1949 to 1965 and,therefore, a 60% increase in ecological footprint.Thereafter the rate of increase slows, but the foot-print per mill in 1985 is still nearly twice its 1949size. As an aside, it should be emphasized that anincreased rate of production of wood means in-creased logging which, in turn, means more roadbuilding and encroachment into wilderness areas,with consequent impacts on forest sustainability.

During this time period of 1949–1985, the

number of workers in these mills first increased,reaching a peak in the late 1970s, and then de-creased drastically in the early 1980s. It is thereforeinstructive to consider the changing ecologicalfootprint of a sawmill worker, expressed as millionsof board feet (Mbf) per worker, for this time pe-riod. (Figure 4). Clearly, by 1985, technology hadincreased the ecological footprint of each sawmillworker from 154 Mbfm to 330 Mbfm.

The rate of increase in lumber production permill accelerated fastest between 1956 and 1965 asthe industry moved away from recession and en-tered the boom period of the 1960s and 1970s.Over the 20-year period, 1965–1985, lumber pro-duction at the eight coastal mills increased by only10%. Lumber production increased more rapidlythan this in the industry as a whole, probably be-cause rates of increase were faster in the Interior,which was the first to move to new sawmill technol-ogy. Thus, our sample of eight large coastal mills isreally a snapshot of production in a less technolog-ically advanced sector of the sawmill industry.

The eight mills do not show a startling in-crease in the rate of draw-down of natural capitalin an era when the rest of the industry consumedmore of B.C.’s forests than ever before. In fact,these data show that the large increases in pro-duction occurred in the late 1950s and early1960s. However, Figure 4 illustrates that on a per

FIGURE 3. Lumber production per mill for eight large coastal sawmills from 1949–1985.


201

worker rather than a per mill basis, the increasein productivity, or the individual worker’s ecologi-cal footprint, between 1976 and 1985 is the larg-est in the history of these mills.

CONCLUSIONS

The sawmill is a site where raw natural capital istransformed rather than consumed. Furthermore,the ecological footprint is usually assigned to thepopulation which is the site of consumption of themill’s lumber. Assigning an ecological footprint tothe site of transformation rather than consump-tion, decouples the link between the consumptionof specific population groups and its impact on theecosystem.

The inherent danger in using the ecologicalfootprint in this way is that its utility as an educa-tional and analytical tool may be blunted. Duringthe 1980s and 1990s, for example, Japan has be-come the final destination for an increasing num-ber of trees processed in B.C. coastal mills. Thesechanges in the B.C. lumber market result in an in-creased ecological footprint for Japan in generaland for various Japanese cities and regions in par-ticular. By focusing on transformation rather thanfinal consumption, the specific links between con-sumption in Japan and ecosystem draw-down inB.C. are not made explicit.

There are advantages, however, in assigningecological footprints to the site of the extractionand transformation of natural capital. First, for anation like Canada which engages heavily in directnatural resource extraction with minimal value-added manufacturing and export, the trade-off be-tween ecosystem depletion and community benefitneeds to be explicit in order to determine the sus-tainability of the transformation process, both forcommunities engaged in the process and ecosys-tems supplying the natural resource.

Second, the ecological footprint as it is gener-ally used is calculated from a range of essentialitems and expressed in land area needed to pro-duce them. The power of the concept lies in its abil-ity to make explicit the impact on ecosystems of thegeneral consumption patterns of a defined popula-tion. While the ecological footprint links consump-tion patterns to nature, and expresses the impact ofconsumption in terms of land area needed to sup-port it, there is no identification of the location ortype of land-bases or ecosystems that are being ex-ploited. Because it is primarily a planning and edu-cational tool, the ecological footprint focuses onthe final consuming population rather than thespecific ecosystem being consumed or the popula-tion groups engaged in transforming natural prod-ucts on their way to the final site of consumption.

Canadian industries such as sawmilling, fish-ing, and mining, which are heavily reliant on the

FIGURE 4. Lumber production per worker for eight large coastal sawmills from 1949–1985.

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direct harvesting and minimal processing of prod-ucts of natural ecosystems and which have commu-nities that are highly dependent on these indus-tries, lend themselves to a particular adaptation ofthe ecological footprint. The approach is centeredon the specific ecosystems and associated commu-nities engaged in their extraction and transforma-tion rather than on the population consuming theproducts. The focus on minimally transformed nat-ural products such as the number of fish caught orthe quantity of lumber produced, produces arough indication, albeit an underestimation, of thedirect draw-down of natural capital as well as locat-ing the site of this draw-down. This approach linksthe costs and benefits of transformation with

site orregion-specific

ecosystem exploitation.The measure of community sustainability

used in this study was also somewhat crude, beingbased on the number of hourly pay jobs in saw-mills. In spite of the crudeness of the measure ofcommunity sustainability used in this investiga-tion, it is clear from other studies of sawmills dur-ing the recession of the early 1980s, that the lossof hourly pay jobs in mills were largely mirroredby reductions in salaried positions, contractedwork, and office staff, indicating that fluctuationsin hourly pay mill jobs are a fairly valid indicatorof changes in community benefit from mill em-ployment (Grass & Hayter 1989).

The discussion has until now focused on un-derlying methods and their limitations. But whatare the main findings of this investigation? Thecase study, involving about 20% of workers in thecoastal sawmill industry, showed that the down-turn of the early 1980s was particularly hard onyounger workers. In part, this was because of theseniority-based system in the mills which ensuredthat those with less seniority, who are generallythe younger workers, are most likely to be laid off.

The increased personal ecological footprintof those workers who remained in the industry isa function of a new industrial strategy that re-places labor investment with capital. New technol-ogies enable workers to be more productive.While each worker can transform more trees intolumber than ever before, as a group there wereabout 40% fewer of them after the recession.Even with this drastically reduced and more agedworkforce, the ecological footprint of the eightcoastal mills increased between 1976 and 1985,principally because of increased productivity perworker.

A classical or neoclassical economist might bepleased with such productivity increases, but an

ecological economist might see it in a less positivelight. The new technical infrastructure now inplace in most sawmills is more capable than everof accelerating the pace of forest ecosystem draw-down. This enhanced production capacity was es-tablished at a time when B.C.’s coastal forest eco-systems, which have historically been overhar-vested, are under increasing pressure from otherforest sector uses such as tourism.

This is the Innes’s cycle in action. As this inves-tigation shows, the infrastructure left in place inthe coastal mills is the most efficient the industryhas ever seen. The irony of this situation is that thecoastal forest ecosystems are moving into theirleast productive phase at a time when a more effi-cient industry is creating intense production pres-sure. The efficiency of production methods en-sures that forest ecosystems will come under moreintense stress from harvesting activity.

These technological changes in the forestproducts industry will effect forest communities.The direct impact is job loss, reduced incomes, anda smaller tax base. The indirect losses range fromincreased migration of younger workers, increasedcommunity instability, and increased health andwelfare costs associated with community instabilityand employment losses. These losses are likely par-ticularly strong in small, highly dependent millcommunities. Indirect costs such as these are notusually part of the accounting procedure. The ex-tent to which the government must step in to dealwith health and social costs incurred in industrialrestructuring amounts to a public subsidy which isusually unrecognized by the private sector.

Calculation of the ecological footprint usedin conjunction with measures of community sus-tainability can usefully illuminate the links andtradeoffs that occur in some industries at the levelof ecosystem and community health. While theresults of this particular case study may be not beencouraging, the development and application ofnew planning and conceptual tools like these mayat least begin the process of making explicit thecosts of industrial change and development. Per-haps in this way, Innes’s seemingly inevitable andvery Canadian cycle of destruction will be madeboth more explicit and remediable.

ACKNOWLEDGMENTS

I would like to acknowledge the support and in-tellectual guidance of Dr. Clyde Hertzman in thisproject. To the B.C. Health Research Foundation


203

and the Canadian Institute of Advanced Researchfor their financial support. To the University ofBritish Columbia Task Force on Planning Healthyand Sustainable Communities.

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the links between industrial, community, and ecological sustainability: a forestry case study

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