Hormonal exposures and the risk of intracranial meningioma in women: a population-based case-control study

Brian Custer firstname.lastname@example.com
Department of Epidemiology
School of Public Health and Community Medicine
University of Washington
SeattleWAUSA

Pharmaceutical Outcomes Research and Policy Program
School of Pharmacy
University of Washington
SeattleWAUSA

W T Longstreth firstname.lastname@example.com
Department of Epidemiology
School of Public Health and Community Medicine
University of Washington
SeattleWAUSA

Department of Neurology
School of Medicine
University of Washington
SeattleWAUSA

Leslie E Phillips
Department of Epidemiology
School of Public Health and Community Medicine
University of Washington
SeattleWAUSA

Thomas D Koepsell
Department of Epidemiology
School of Public Health and Community Medicine
University of Washington
SeattleWAUSA

Department of Health Services
School of Public Health and Community Medicine
University of Washington
SeattleWAUSA

Gerald Van Belle
Department of Environmental Health
School of Public Health and Community Medicine
University of Washington
SeattleWAUSA

Department of Biostatistics
School of Public Health and Community Medicine
University of Washington
SeattleWAUSA

BMC Cancer

Hormonal exposures and the risk of intracranial meningioma in women: a population-based case-control study
10.1186/1471-2407-6-152BioMed Central Page 1 of 9 (page number not for citation purposes) Research article Thomas D Koepsell -firstname.lastname@example.com; Gerald Van Belle -firstname.lastname@example.com * Corresponding author
Background:The role of exogenous hormone exposures in the development of meningioma is unclear, but these exposures have been proposed as one hypothesis to explain the over-abundance of such tumors in women.Methods:The association between oral contraception (OC) or hormone replacement therapy (HRT) and intracranial meningioma in women was investigated using a population-based, matched case-control study. Exposures for 143 cases and 286 controls matched on age within five years were obtained by interview. Diagnoses were confirmed histopathologically and estrogen and progesterone receptor assays conducted.Results: Although risk of meningioma appeared modestly elevated in past OC users (OR = 1.5, 95% CI 0.8 -2.7), and in current users (OR = 2.5, 95% CI 0.5 -12.6), the confidence intervals were wide. No significant association between meningioma risk and duration of OC use was found. Likewise, risk of meningioma was only weakly associated with past use of HRT (OR = 0.7, 95% CI 0.4 -1.3), and not at all with current use of HRT (OR = 1.0, 95% CI 0.5 -2.2). Of 142 available specimens, 2 (1%) expressed estrogen receptors, whereas 130 (92%) expressed progesterone receptors (PR). OC use was associated with increased risk of a meningioma expressing less rather than more PR (OR = 3.2, 95% CI 1.3 -8.0). Overall, in post menopausal women, HRT use appeared to confer a non-significant protective effect, and was not associated with low or high PR expressing meningiomas.Conclusion: This study found little evidence of associations between meningioma and exogenous hormone exposures in women but did suggest that some hormonal exposures may influence tumor biology in those women who develop meningioma.

Background

Meningiomas occur more frequently in women than men and have the highest incidence in the fifth and sixth decades of life [1,2]. Consistent with data from other studies in North America and Europe, we have previously reported the incidence of intracranial meningioma in western Washington State to be 3.2 per 100,000 personyears, with women comprising 69% of the meningioma diagnoses and the highest age-and gender-specific incidence of over 7 per 100,000 person-years in women 60 years or older [3].

Research has focused on the similarities and risk factors common to meningioma and other neoplasms in addition to other mechanisms. In particular, meningioma may be associated with breast carcinoma [4,5] but this association may not be a direct link and instead may rely on the common predispositions of gender, age, and reproductive factors. Hormonal exposures have a suspected role in the etiology of both neoplasms [6]. The Women's Health Initiative (WHI) study, a large randomized trial, found an increased risk for breast carcinoma in post-menopausal women using opposed hormone replacement therapy (estrogen and progestin) [7]. In a separate WHI analysis, results of unopposed estrogen exposure suggest a non-significant reduction in the risk of breast carcinoma [8].

Observational studies examining hormone replacement therapy and breast carcinoma have reported results generally in agreement with the randomized trials [9][10][11]. Evidence for an association between oral contraception and breast carcinoma remains equivocal [9,[12][13][14][15][16]. A recent report from a case-control study found few significant associations between reproductive or hormonal factors and the risk of meningioma [17]. However, results from the Nurses' Health Study cohort, suggest the risk of meningioma is increased among women exposed to either endogenous or exogenous sex hormones [18]. As part of a case-control study designed to investigate putative risk factors for intracranial meningioma, we evaluated the association between intracranial meningioma and sex hormone exposures, and in relation to hormone receptor expression in the tumors.

Methods

We conducted a population-based, matched case-control study of risk factors for intracranial meningioma, as detailed previously [3,19]. Institutional Review Boards at the University of Washington and the Fred Hutchinson Cancer Research Center approved the study. All interviewed subjects provided signed, informed consent before study participation. We identified cases with incident intracranial meningioma, histologically confirmed during life between January 1, 1995 and June 30, 1998, using the National Cancer Institute's Surveillance, Epidemiology, and End Results program for King, Pierce and Snohomish counties of western Washington State, which together had a population of nearly 2.8 million at the mid-point of the study. Using random-digit dialing or Medicare eligibility lists, we recruited two controls for each case matched on gender, age within 5 years, and county of residence. The participation proportion for each method of control recruitment was calculated as a percentage based on the number of participants divided by the number of subjects screened and found eligible using that recruitment method. All cases and controls were 18 years or older.

Exposure histories were obtained from all enrolled participants through a structured in-person interview and questionnaire that focused on the entire history of exposures before the reference date. Reference date was the date of the case's surgery that yielded histological confirmation and was the same for the case's matched controls. Seven of the 143 female cases identified for this study were unable to complete the interview due to disability or death. Proxy interviews of a spouse or next-of-kin were conducted for these cases, but were not conducted for the matched controls. For reproductive and medical history in women, we specifically asked about factors such as age at menarche, pregnancy, breastfeeding, and menstrual status in addition to other exposures common to both men and women. For use of oral contraceptives and hormone replacement therapy, we inquired about the type of prescription using visual prompts, the calendar time of use, and duration of use for any hormone therapy. Interview responses on the type of oral contraceptive preparation used were often incomplete, and so we were unable to examine the influence of the type of preparation on the risk of meningioma.

For all 143 cases, we confirmed the meningioma diagnosis by requesting tumor specimens and pathology reports from the resecting hospital. The study neuropathologist confirmed the diagnosis of meningioma. In addition, specimens were submitted to Phenopath Laboratories, Seattle, Washington, for estrogen and progesterone receptor analysis. New tumor tissue slices were prepared from specimens embedded in paraffin, pretreated in citrate buffer pH 6.0 in a steamer for 30 minutes, and placed on an autostainer. For estrogen receptor analysis, antibody clone 1D4 was used (Dako Corporation, Carpentaria, CA, USA). For progesterone receptor analysis, antibody clone 88 was used (BioGenex, San Ramon, CA, USA). Detection was performed using the labeled streptavidin-biotin system (LSAB+) with horseradish peroxidase followed by 3,3'-diaminobenzidine chromogen (DAB+). Receptor assays were successful in all but one case.

Analysis

We used conditional logistic regression to measure the association between each exposure and intracranial men-ingioma. For all analyses, we used never-exposed or no exposure as the referent category. Results are reported as odds ratios (OR) with 95% confidence intervals (CI). Where appropriate, tests for linear trend were conducted. Multiplicative interactions were assessed using the likelihood ratio (LR) test. Given their slow growth, most meningiomas have probably been present for a decade or more by the time a diagnosis is made [20]. Therefore each analysis was repeated for exposures beginning at least 10 years before the reference date. We also compared the conditional logistic regression results to unconditional results of models with the same variables. Because the results for these comparisons were not substantially different we elected to report the results using conditional logistic regression as it was the originally proposed methodology for the study. In exploratory analyses, we used polytomous logistic regression to compare hormone exposure categories for controls to cases with tumors that had abundant hormone receptor expression and to cases with tumors that had little or no hormone receptor expression. The odds ratios for these analyses measure the association between exposure and case-control status, examined separately according to the two case groups defined by receptor status rather than between exposure and receptor status among cases only. For both conditional logistic regression and the exploratory polytomous regression, we assessed whether other variables were potential confounders, such as age, education, smoking history, alcohol consumption, body mass index, age at menarche, and parity. When necessary in stratified analyses, we used unconditional logistic regression in order to prevent the loss of data for case-control groups that were concordant on the specific exposures of interest. Analyses were conducted using Stata (version 9, Stata Corporation, College Station, TX, USA).

Results

Although the 143 cases and 286 matched controls were similar on age, race and marital status, controls were more educated than cases (Table 1). Because education was a confounder, we included it in all multivariable models as a categorical variable: high school or less, some college or trade school, college graduate. Also, because on average cases were 0.9 years older than the first matched control and 1.6 years older than the second matched control, we included age in all multivariable models as a continuous variable to address residual confounding. Case participation was 84%. For controls identified through random digit dialing 55% participated, and for controls identified using Medicare eligibility 67% participated. On average cases were interviewed 410 days after the reference date and controls were interviewed 839 days after the reference date.

Oral contraception

With never-users of oral contraceptives as the referent group, the odds ratios for past users or current users on the reference date were both greater than 1.0 but not significantly so ( Table 2). A graded effect (linear trend) with years of use or initiation of use relative to the reference date was not apparent. Tests for interaction did not reveal significant interactions between oral contraceptive use and pregnancy, number of pregnancies, number of live births, body mass index, hormone replacement therapy, or breastfeeding.

Hormone replacement therapy

Analysis of the association between hormone replacement therapy and meningioma was restricted to postmenopausal women. Two hundred and seventy three women (101 cases, 172 controls) reported they were no longer menstruating on the corresponding reference date for each matched group. Of these women, 63 (62%) cases and 114 (66%) controls reported hormone replacement therapy use on or before the reference date.

We found no statistically significant association between hormone replacement therapy and meningioma. With never users of hormone replacement therapy as the referent group, the odds ratio for women reporting past use was lower than 1.0 but not significantly so (Table 3). Current use on the reference date was not associated with meningioma. A trend with increased years of use or initiation of use relative to the reference date was not apparent. Odds ratios for the type of hormone replacement therapy did not indicate a significantly increased risk of meningioma for either opposed or unopposed estrogen. * Reported exposure before reference date, which for a case and her two matched controls was the date the case had surgery for her meningioma. † Odds ratio (OR) and 95% confidence intervals (CI) estimated from multivariable conditional logistic regression including continuous age and three categories of education (high school or less, some college or trade school, and college graduate or graduate school) as confounding variables. None of the tests for linear trend was significant. Tests for interaction did not reveal significant interactions between hormone replacement therapy and smoking, previous pregnancy, number of pregnancies, number of live births, breastfeeding, oral contraceptive use, or body mass index.

We examined a potential combined effect of hormone replacement therapy and past oral contraceptive use in post menopausal women compared to never exposed women by grouping women into three categories: exposure to both, exposure to one or the other and never exposure, and we also examined duration of exposure as never, up to ten years, and ten or more years. In each analysis, point estimates and associated confidence intervals were not appreciably different than for hormone replacement therapy alone (results not shown).

Results for either oral contraception or hormone replacement therapy were unchanged when the seven cases in whom proxies interviews were used and their matched controls were removed from the analyses (results not shown).

Reproductive and related exposure categories

We evaluated several exposure categories related to reproduction and endogenous hormones, including age at menarche, number of live births, age at first live birth, history of breastfeeding and did not find significant associations with meningioma (Table 4). In addition we evaluated if reporting menstrual cycles or being post-menopausal on the reference date and also 10 years before the reference date were related to the risk of meningioma. In these analyses we used unconditional logistic regression, restricted to post-menopausal women who did not use HRT. The odds ratio for the risk of meningioma in women who were post-menopausal on the reference date was 3.1 (95% CI, 1.2 -7.9) compared to women who were menstruating and was 0.6 (95%, CI, 0.2 -1.9) in women who were post-menopausal ten years before the reference date even after adjusting for age and education.

We also assessed body mass index (BMI) grouped as under/normal weight (<25), overweight (25)(26)(27)(28)(29)(30), and obese (≥30) [21]. Compared to under/normal weight women on the reference date, the risk of meningioma in overweight women was 1.2 (95% CI, 0.7 -2.0) and was 1.5 (95% CI, 0.9 -2.4) in obese women. * Reported exposure before reference date, which for a case and her two matched controls was the date the case had surgery for her meningioma. † Odds ratio (OR) and 95% confidence intervals (CI) estimated from multivariable conditional logistic regression including continuous age and three categories of education (high school or less, some college or trade school, and college graduate or graduate school) as confounding variables. None of the tests for linear trend was significant. ** Odds ratio (OR) and 95% confidence intervals (CI) estimated from multivariable unconditional logistic regression including continuous age and three categories of education (high school or less, some college or trade school, and college graduate or graduate school) as confounding variables.

Hormone receptor expression

Progesterone receptor (PR) expression was common with 62 (44%) of tumors having >75% of cells expressing PR, 35 (24%) of tumors having 25-75 percent of cells expressing PR, 33 (23%) of tumors having <25% of cells expressing PR, and 12 (8%) of tumors with no cells expressing PR. In contrast, estrogen receptor (ER) expression was uncommon with only 1 tumor having >75% cells expressing ER and 1 tumor with <25% of cells expressing ER. The remaining 140 tumors (98%) did not express ER. In exploratory analyses we focused on associations between exposure categories and progesterone receptor expression dichotomized as low (<25% of cells expressing PR) or high (25% or more expressing PR). We were unable to compare never, current and past oral contraceptives or hormone replacement therapy use to PR expression due to insufficient numbers, so we compared never and ever oral contraceptive or hormone replacement therapy exposure (Table 5). We found a strong association between oral contraceptive use and risk of a tumor expressing low, but not high, PR compared to controls. We also found a positive association between number of live births and risk of a tumor expressing low, but not high, PR compared to controls. For post-menopausal women, we did not observe evidence of an association between hormone replacement therapy and a tumor expressing low or high PR. While we found evidence for an association between meningioma and menstruating 10 years before the reference date, we did not find a difference in risk for cases whose tumors expressed low or high PR.

Discussion

We used a population-based case-control study of risk factors for intracranial meningioma to assess hormonal *PR, progesterone receptor; OC, oral contraceptive; HRT, hormone replacement therapy † Odds ratio (OR) and 95% confidence intervals (CI) estimated from multivariable polytomous logistic regression including continuous age and three categories of education (high school or less, some college or trade school, and college graduate or graduate school) as confounding variables. None of the tests for linear trend was significant.

exposures and the risk of subsequent meningioma in women. Overall, the associations between meningioma and oral contraceptives or hormone replacement therapy in this study were relatively weak. The direction of association was toward higher risk of meningioma among past or current oral contraceptive users, and among users of combined estrogen-progestin hormone supplements in menopause, while the direction was toward lower risk among women who used unopposed estrogen during menopause. However, confidence intervals around these odds ratios were wide and included one. While current post-menopausal status was associated with an increased risk of meningioma, post-menopausal status 10 years before the reference date had a non-significant protective effect. Exposures in this time frame are consistent with the theory of meningioma development where symptoms and diagnosis often occur 10 or more years after the initial establishment of the tumor [19].

The finding that meningioma risk is increased among women who were postmenopausal on the reference date, but decreased among women who were postmenopausal 10 years prior to the reference date is curious and could be due to chance given the number of comparisons made. However, a potential explanation is that the risk of developing meningioma may be associated with changing hormonal levels as opposed to the presence or absence of female sex hormones. The interval of transition from premenopausal hormone production to reduced production of endogenous hormones may be a risk factor for meningioma growth. Women who do not develop an apparent meningioma at this time pass through this higher risk window and enter a lower risk window.

The frequency with which meningioma tumors express estrogen receptors remains unclear with researchers reporting between 0 to 94% prevalence [6]. In this study only 2 of 142 specimens expressed estrogen receptors for a prevalence of 1.4%, whereas 130 tumors (92%) expressed progesterone receptors. The presence of progesterone receptor expression in meningioma tissue has been observed in previous pathology studies [14,16,22]. We were able to consider the combination of progesterone receptor expression and hormone exposure history. Others have observed that the grade of meningioma and likelihood of recurrence are related to progesterone receptor expression with tumors lacking such expression more likely to be higher grade and to recur [16,23] Results for history of live births were similar to those observed for oral contraceptives, with these exposures significantly or near significantly associated with tumors that have little or no PR expression. Hormone use could accelerate, retard or have no effect on growth of a meningioma. Whether growth is accelerated or retarded would depend on the specific biochemical pathways that are activated by the receptor when a hormone is present, whereas hormone use might plausibly have no effect on growth in tumors that do not express receptors. Though our study was not designed to assess this question, these results could be used to form a hypothesis for a study that seeks to determine whether progesterone receptor expression is related to several exposure categories, and to determine whether prognosis based on PR expression may differ based on endogenous and exogenous hormone exposures.

Our results suggesting little evidence for associations between reproductive and related exposure categories and meningioma are similar to those recently reported by Hatch and colleagues from a hospital-based case-control study of women consisting of 151 meningioma cases and 436 frequency-matched controls [17]. In this study, the point estimates of the odds ratios between meningioma and current or past use of OC were somewhat higher than those from the Nurses' Health Study cohort but the associations were not statistically significant in either study [18]. We did not find significant evidence of increased risk of meningioma in women who are past and current hormone replacement therapy users as reported by Jhawar and colleagues. We believe our ascertainment and pathological confirmation of meningioma for all cases and structured interview including visual prompts to ascertain hormone therapy exposure provide reliable data on disease and exposure history. However, interpretation of these results is difficult due to small numbers, unstable estimates, and inconsistencies with prior works.

This study cannot rule out a modest association between the risk of meningioma and body mass index as this finding is similar in both our study and that of Jhawar and colleagues. However, both height and weight were selfreported during the interview and may be subject to reporting error [24]. Our body mass index categories are consistent with those typically applied to the U.S. population [21,25,26]. Although Jhawar and colleagues used BMI categories consistent with the World Health Organization categories, which have lower cut-off values for overweight and obese groups, in both studies the same magnitude of increasing risk of meningioma was observed with increasing BMI.

This study has limitations. Chiefly, while disease status was confirmed, all exposures are self-reported, and we did not attempt to validate these exposures using medical or pharmacy records. Point estimates for several exposure categories suggest either elevated or reduced risk of meningioma, but the available sample sizes were not sufficient for specific combinations of exposures to suggest a coherent pattern of association. Furthermore, due to incomplete responses for oral contraceptive preparations we were unable to assess whether there is a different risk of meningioma resulting from opposed versus unopposed estrogen preparations. Analysis of all oral contraceptive preparations together could obscure an association between specific hormone preparations.

One potential limitation is related to the recruitment of controls. Random digit dialing was used to identify controls. In persons 65 years or older, random digit dialing was observed to be inefficient, so Medicare eligibility lists were used to identify controls. In each case our participation proportion was over 50% of the eligible controls. These participation proportions are consistent with those reported for other epidemiologic studies [27]. However, we cannot rule out that selection bias could play a role in our generally non-significant conditional logistic regression findings.

Another limitation is the potential for differential recall based on the elapsed time from reference date to the interview. However, we believe the potential for differential recall is more apt to be related to the nature of the reference date as opposed to time between the reference date and the interview date. For cases the reference date is the date of surgical resection of the meningioma, whereas for controls it is the date of surgery for the matched case, which is unlikely to have inherent meaning for the controls. To limit differential recall participants were asked to focus on specific time periods of interest beginning with exposure that would have been years before the reference date. The trained interviewers used memory priming techniques to facilitate recall of events before initiation of the interviews. For sex hormone and reproductive history, both current and remote exposure histories were assessed.

Although the presence of an association between meningioma and breast carcinoma remains uncertain, evidence of consistent findings for the role of specific exposures for both categories of neoplasm is mounting. Reports suggest the association between either oral contraceptive use or postmenopausal hormone use and risk of breast carcinoma may differ in relation to histopathology [28,29]. However, similar to reports for breast carcinoma, postmenopausal women who used unopposed estrogen (estrogen replacement therapy) had a either a reduced or no observed increase in the risk of meningioma whereas women who used opposed estrogen therapy had a modest increased risk of meningioma [10,30].

Conclusion

The analyses of the association between meningioma and female sex hormones suggests that certain exposures may influence tumor biology and additional, larger studies that specifically assess whether hormone exposures and receptor expression are linked would help advance the understanding of why some women develop these rela-tively rare tumors while others do not. Overall the association between oral contraceptives or hormone replacement therapy and meningioma in women reported here is consistent with other studies and is not sufficiently evident to raise specific concerns about or suggest changes to current hormone therapy guidelines.

Table 1 :
1Demographic characteristics of women with intracranial meningioma and age and gender-matched controlsDemographic Characteristic
Cases N = 143 Number (Percent)
Controls N = 286 Number (Percent)

Age Group
< 40
21 (15)
51 (18)
40-49
39 (27)
77 (27)
50-59
32 (22)
58 (20)
60-69
23 (16)
50 (18)
≥ 70
28 (20)
50 (18)
Race
Caucasian
129 (90)
266 (93)
African American
2 (1)
7 (3)
Native American
3 (2)
4 (1)
Hispanic
2 (1)
4 (1)
Asian American
1 (1)
3 (1)
Other
6 (4)
2 (1)
Marital Status
Single
15 (10)
34 (12)
Married
90 (62)
189 (66)
Separated/Divorced
16 (11)
33 (12)
Widowed
22 (15)
30 (11)
Educational Attainment
Grade school
1 (1)
7 (3)
High school
54 (38)
72 (25)
Some college
74 (52)
165 (58)
Graduate school
14 (10)
42 (15)

Table 2 :
2Association between oral contraceptive use and intracranial meningioma in womenExposure*
Cases n
Controls n
OR (95% CI) †

Oral contraception (O C)
Never
48
103
Referent
Past
90
176
1.5 (0.8 -2.7)
Current use on reference date
5
7
2.5 (0.5 -12.6)
Years of OC use
Never
48
103
Referent
Up to 5 years
49
90
1.5 (0.8 -3.0)
More than 5 years
46
93
1.4 (0.7 -2.7)
First OC exposure relative to reference date
Never
48
103
Referent
1-9 years before
7
15
1.6 (0.3 -7.5)
10 or more years before
88
168
1.5 (0.8 -2.7)

Table 3 :
3Association between hormone replace therapy and intracranial meningioma in post-menopausal womenExposure*
Cases n
Controls n
OR (95% CI) †

Hormone replacement therapy (HRT)
Never
38
58
Referent
Past
40
73
0.7 (0.4 -1.3)
Current use on reference date
23
41
1.0 (0.4 -2.2)
Years of HRT use
Never
38
58
Referent
Up to 5 years
28
43
0.9 (0.4 -1.7)
More than 5 years
32
65
0.9 (0.5 -1.7)
First HRT exposure relative to reference date
Never
38
58
Referent
1-9 years before
30
44
0.9 (0.4 -1.9)
10 or more years before
31
62
0.9 (0.5 -1.6)
Type of HRT preparation
None
38
58
Referent
Estrogen
33
66
0.9 (0.5 -1.6)
Estrogen and Progestin
24
33
1.3 (0.6 -2.8)

* Reported exposure before reference date, which for a case and her two matched controls was the date the case had surgery for her meningioma.
 † Odds ratio (OR) and 95% confidence intervals (CI) estimated from multivariable conditional logistic regression including continuous age and three
categories of education (high school or less, some college or trade school, and college graduate or graduate school) as confounding variables. None
of the tests for linear trend was significant.

Table 4 :
4Reproductive history and related endogenous exposuresExposure*
Cases n
Controls n
OR (95% CI) †

Age at menarche
< 12
22
44
Referent
12 -14
100
212
0.9 (0.5 -1.7)
> 14
21
30
1.2 (0.6 -2.7)
Number of live births
None
18
58
Referent
1
22
28
2.0 (0.9 -4.6)
≥ 2
103
200
1.4 (0.7 -2.6)
Age at first birth
< 20
25
44
Referent
20 -29
86
159
1.2 (0.6 -2.4)
≥ 30
14
25
1.2 (0.4 -3.8)
Ever Breast Feeding
No
57
75
Referent
Yes
71
154
0.7 (0.4 -1.0)
Menstrual status on reference date**
Menstruating
21
72
Referent
Post-menopausal and not using
HRT

38
58
2.8 (1.1 -7.1)

Menstrual status 10 years before reference date**
Menstruating
35
83
Referent
Post-menopausal and not using
HRT

23
46
0.6 (0.2 -1.9)

Table 5 :
5Association between exposure categories and progesterone receptor expressionExplanatory
Variable

Controls
Cases with tumors expressing PR* in 0 to
25% of cells

Cases with tumors expressing PR* in =
order 25 to 100% of cells

n
n
OR (95% CI) †
n
O R ( 9 5 % C I )  †

OC* use
Never
103
15
Referent
33
Referent
Ever
183
31
3.2 (1.3 -8.0)
64
1.1 (0.6 -1.9)
HRT* use in post-menopausal women
Never
58
15
Referent
23
Referent
Ever
114
22
0.8 (0.4 -1.6)
41
0.9 (0.5 -1.6)
Current menstrual status
Menstruating
114
9
Referent
33
Referent
Post-menopausal
172
37
2.7 (1.2 -5.8)
64
1.3 (0.8 -2.1)
Menstrual status 10 years before reference date
Menstruating
158
21
Referent
62
Referent
Post-menopausal
126
23
0.5 (0.2 -1.5)
35
0.5 (0.2 -1.0)
Current menstrual status
Menstruating
72
4
Referent
17
Referent
Post-menopausal and
not using HRT

58
15
2.4 (1.2 -5.8)
23
3.1 (1.1 -8.6)

Menstrual status 10 years before reference date
Menstruating
83
8
Referent
27
Referent
Post-menopausal and
not using HRT

46
10
0.3 (0.1 -2.5)
13
0.8 (0.5 -1.3)

Smoking status 10 years before reference date
Non-smoker
144
29
Referent
48
Referent
Smoker
142
17
0.5 (0.3 -1.0)
49
1.0 (0.6 -1.5)
Body Mass Index on reference date
< 25
156
23
Referent
45
Referent
25 -30
66
12
1.2 (0.5 -2.5)
22
1.1 (0.5 -2.4)
≥ 30
64
11
1.1 (0.6 -2.0)
29
1.5 (0.8 -2.6)
Number of live births
None
58
2
Referent
16
Referent
1
28
5
4.0 (0.7 -22.3)
17
2.1 (0.9 -4.9)
≥ 2
200
39
4.3 (1.0 -18.8)
64
1.1 (0.6 -2.2)

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AcknowledgementsThis study was funded by a grant (CA 60710) from the National Cancer Institute, Bethesda, Maryland, USA. We gratefully acknowledge the time and expertise that Ellsworth C. Alvord, Jr. MD, Division of Neuropathology, Department of Pathology, University of Washington, provided to this study. Dr. Alvord independently confirmed the meningioma diagnosis for all cases. We thank Allen M. Gown, MD, Medical Director, Phenopath Laboratories, Seattle, WA and his employees for the hormone receptor analyses. The authors would also like to thank the following for their contributions: Jo-Ann Gehrels, MA who helped coordinate all aspects of the study; David B. Thomas, MD, DrPH, Terri Watson and Anne Morrison, Program in Epidemiology, Fred Hutchinson Cancer Research Center, Seattle, WA who were instrumental in the identification of cases for this study; Yvonne L. Griffin, Erin Moline, and Soleil Buchanan for interviewing subjects; and Cathy Papp and Maria King for the recruitment of control subjects using random digit dialing.Competing interestsThe author(s) declare that they have no competing interests.Authors' contributionsPre-publication historyThe pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2407/6/152/pre pub
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Old-growth Forests: Anatomy of a Wicked Problem
1 March 2011

Anthony Pesklevits firstname.lastname@example.com
School for Resource and Environmental Studies
Dalhousie University
6100 University Avenue Halifax, Nova ScotiaB3H 3J5Canada

Peter N Duinker email@example.com
School for Resource and Environmental Studies
Dalhousie University
6100 University Avenue Halifax, Nova ScotiaB3H 3J5Canada

Peter G Bush firstname.lastname@example.com
School for Resource and Environmental Studies
Dalhousie University
6100 University Avenue Halifax, Nova ScotiaB3H 3J5Canada

Old-growth Forests: Anatomy of a Wicked Problem
1999-49071 March 2011266D15643B60C250F8E871F73342713F10.3390/f2010343Received: 11 January 2011; in revised form: 12 February 2011 / Accepted: 18 February 2011 /old-growth forestswicked problemssustainable forest management
Old-growth forest is an often-used term that seems to be intuitively understood by ecologists and forest managers, and the wide-ranging discussion of its social and ecological values suggests it has currency among the general public as well.However, a decades-long discourse regarding a generally acceptable definition of old-growth, in both conceptual and practical terms, has gone largely unresolved.This is partially because old-growth is simultaneously an ecological state, a value-laden social concept, and a polarizing political phenomenon, each facet of its identity influencing the others in complex ways.However, the public, scientific, and management discourse on old-growth has also suffered from simplifying tendencies which are at odds with old-growth"s inherently complex nature.Such complexity confounds simple or rationalistic management approaches, and the forest management arena has witnessed the collision of impassioned and contradictory opinions on the "right way" to manage old-growth forests, ranging from strict preservationism to utilitarian indifference.What is clear is that management approaches that circumvent, trivialize, eliminate, or ignore old-growth"s inherent complexity may do so at the expense of the very characteristics from which old-growth derives its perceived value.We explore the paradoxes presented by the various approaches to old-growth description and definition and present some plausible paths forward for old-growth theory and management, with a particular focus on managed forests.

Introduction

In North America, for much of its history, industrial forestry has advanced on the premise that "maximizing economic efficiency in the short term was the path to maximizing social and economic benefits into the future" [1].The diversification of value drivers in industrial forestry to incorporate a broader suite of values than optimizing timber production has been a relatively recent occurrence [2], largely in response to shifting public expectations regarding the management of public lands and resources.Ecologists and forestry practitioners have responded with cohesive paradigms of ecosystem management [3], new [4] or ecological forestry [5], and sustainable forest management [6], which have shown some signs of traction within forestry practice in the last two decades.

The emergence of these new forestry paradigms has been paralleled by a rising interest in old-growth forests in the managed landscape, in part because of its increasing scarcity as old-growth forests have been liquidated and converted to young stands, often even-aged plantations.Old-growth has been a flashpoint for conflict across the continent.In political discourse, on the one hand, old-growth is a senescent and sub-optimal use of valuable tree-growing land; on the other, old-growth serves as a pure and natural foil that offers contrast to an artificial human-influenced forest, and is widely perceived to be of great biotic and aesthetic richness, representing an ecosystem state that offers people a "visual and emotional feast" [7].Though the debate over this natural-artificial construct is well-trodden (see Cronon [8] and Soulé & Lease [9]), polarizing, and seemingly intractable, the old-growth concept continues to have public currency and thus finds a unique place in sustainable forest management.

This public currency of old-growth-and its politicization-have both compelled and confounded the development of a coherent ecological theory of old-growth development, function, and management.It is possible that the deeply divisive public debate over old-growth management is itself responsible for having created a conceptual dichotomy between forests that are perceived to be either old-growth or not old-growth, though dichotomous classifications are a common feature of many attempts at scientific rationalization [7].

The is/is-not old-growth dichotomy, and efforts to reconcile it, are ongoing [7,10,[11][12][13][14][15].Some have called for stepped-up efforts to refine a definition of old-growth in a "systematic and universal manner" [11] in the interest of a "rational policy" [15] for conservation and management.Others have attempted to side-step the old-growth dichotomy by abandoning the term altogether in favour of more seemingly benign terms such as "old forest" (e.g., Moeur et al. [16]), or by accepting that old-growth is an intuitively understood phenomenon (e.g., Carey [17]).

Old-Growth as a Wicked Problem

We posit that the definition and management of old-growth is a fitting example of a wicked problem (sensu Rittel and Webber [18]) at the interface between values, science, and management.Wicked problems are not "bad" per se, inasmuch as they are irreconcilably tricky or perpetually vexing.They transcend disciplinary approaches, lack a definitive formulation, and can be approached from a "plethora of mutually contradictory approaches, each of which is plausible in a particular frame of reference" [19].In this vein, Carey [17] concluded that although the term has broad purchase in both the public mind and in the forest science and policy arena, old-growth has "metaphysics" that can never be fully addressed by science or management.

We propose that old-growth"s "wickedness" is not merely a product of some indefinable metaphysics, the divergence of its utilitarian and aesthetic values, or the politicized debate over its management, though these certainly are notable (for some excellent analyses see Lee [20], Proctor [21], Moyer et al. [22]).In our view, old-growth also suffers from the three confounding tendencies associated with forest researchers" and practitioners" model building and use identified by Bunnell and Huggard [23]: the need to simplify complexity; the willingness to use loose definitions; and the preference for discrete and hierarchical categorizations, rather than connections or continuous gradations.

In this essay we attempt to dissect some of the wickedness that marks old-growth theory and management, by examining some of the approaches to old-growth definition and the problems arising from their application in a forest management context.Our primary frame of reference is ecological rather than socio-political to the extent the two can be disentangled, and we draw our insights mainly from the managed temperate forests of North America, though we hope that whatever insights may arise for the reader will have relevance to forest management more generally.

Readers seeking a definitive problem formulation and conclusive solutions will be disappointed.Indeed, this is not the nature of wicked problems, they are never solved, though often revisited [18].Instead, we attempt to set out a number of plausible propositions respecting the definition and management of old-growth forests.We do so primarily as a conceptual rather than an empirical exercise, with an interest in invigorating a continued discussion of old-growth theory and its practical application in forest policy and management.

Old-Growth Definitions (and Their Problems)

Generic Definitions

Not including its indefinable spiritual quality-its perceived sacredness-old-growth has a plethora of descriptive synonyms.According to Lund [24], over a hundred definitions of old-growth use the terms ancient, antique, climax, late-successional, mature, old, original, overmature, primary, primeval, pristine, or virgin.Recognizing, as most old-growth theoreticians have, that the concept is layered and complex, in an attempt at parsimony Hunter [25] observed that the only satisfactory conceptual definition might be that old-growth forests are "relatively old and relatively undisturbed by humans".The "by humans" qualifier on the latter condition connotes at least some kinds of human activity as disqualifying a forest"s old-growthness, and that its consequences are differentiable from disturbances that are "natural".The additional qualifier of "relatively" introduces a suite of ambiguities about what components of human action qualify as unnatural.

Duchesne [11] proposed a lengthier but purposely generalized definition of old-growth for Canada involving seven conditions, reflecting others suggested previously [12,26] (numbers added): Old-growth forests consist of (1) climax or sub-climax ecosystems where dominant trees are close or older than their age of physiological maturity.(2) unique to each biogeoclimatic region, the old-growth stage of a forest (3) may be reached at different ages depending on site, ecosystem type, or dominant tree species.(4) relatively devoid of major recent anthropogenic influence, each old-growth type is (5) characterized by unique ecological processes, canopy structure, woody debris,flora, and fauna.(6) old-growth patches vary greatly in size but (7) the ecological influence of old-growth forests on animal and plant populations extends to the landscape scale.Even in its comprehensiveness, such a definition cannot transcend ambiguities.With the exception of the first, these conditions describe any forest that is relatively unaltered by humans.The first condition-that old-growth forests are dominated by trees near or above the age of maturity-is the only definitive condition that differentiates old-growth from not-old-growth, characterized by a climax or near-climax successional state and almost-or older-than-mature trees.

Other general definitions that imply old-growth is the "last" or "final" stage of forest development (e.g., [27,28]) are paradoxical, as the upper reaches of forest development are temporally indefinite and "last" is a term that is only given relevance by a conclusion or end.Using this definition alone, one could only be sure a forest was old-growth once it was gone.Furthermore, a stand or portions thereof may revert to earlier developmental stages throughout its development [29], and forests of any stage can be subjected to major disturbance, so any stage has the potential to be the final one in any given iteration of the development cycle.In a review of old-growth forest management in Australia, Burgman [30] found that disturbance does not, by itself, suggest that forest has lost all of the characteristics of an old-growth forest.

Threshold Definitions

Since generic old-growth definitions cannot escape ambiguity, Frelich and Reich [13] suggested that old-growth forests are simply forests that have reached some context-specific threshold that has been determined by a scientific or political process.The threshold approach defines a suite of characteristics-an idealized model-against which the characteristics of real forest stands are judged.Such thresholds may be derived from empirical observation, where some stands that seem to be ideal examples of old-growth are identified and studied, and their attributes used as the standard.This approach is tautological, in that the ideal example is defined before the definition process begins and the criteria used to define the ideal are derived from observing the ideal itself.Furthermore, what are perceived to be defining features may not be present, even in stands dominated by very old trees [31] or with other valued features.

Hunter and White [32] noted that under most circumstances, "no point along the continuum of succession, and no point along the continuum of disturbance severity, suggest themselves as clear, unambiguous thresholds" upon which to base an empirical definition of old-growth.There are numerous development pathways that can lead a piece of forest toward an old-growth condition [31].

These findings, and those of others (e.g., Franklin et al. [29]; Spies and Franklin [33]) suggest that models of old-growth that rely on discrete categorical thresholds cannot avoid arbitrariness.

As recourse, some have proposed multiple categories or an index of old-growthness, differentiating old-growth into several stages based on a forest"s fulfillment of a variety of criteria [34][35][36].This approach does not escape thresholds but merely diversifies their application to multiple rather than single discrete categories, which are then applied in concert in the same way as a single threshold.It is therefore still an elaboration of a tautological normative model.

Descriptive Approaches

Some empirical old-growth work has focused less on developing a normative model of old-growth and has taken a more observational and descriptive approach [28,37].Two basic tendencies of old-growth ecosystem behaviour dominate these observations: (1) the self-evident tendency toward larger structures as living and dead biomass continues to accumulate in the stand; and (2) the tendency toward increasing diversification of forest components, or increasing structural complexity [37].Structural complexity is the variability in the three-dimensional distribution of biomass in space [38].In the early stages of forest development following a homogenizing disturbance such as clearcutting, internal characteristics are kept relatively uniform by competitive interaction among stems [29].This homogeneity is what qualifies tracts of forest for definition as uniform and discrete areas of forestthat is, "patches" or "stands" in those terms" conventional usage.As stands age and autogenically develop heterogeneity of structure, internal uniformity of age and structure disintegrates.Prolonged periods of development offer a broad window of opportunity for small and intermediate-sized disturbances-not "stand-replacing" in the conventional sense-to introduce significant variability to stand structure [37].

Old-growth forests are therefore not only heterogeneous, but heterogeneously heterogeneous-that is, they exhibit spatial heterogeneity at multiple scales, in a non-uniform way.Furthermore, as a forest develops in the absence of major disturbance, the scale at which development processes occur shifts from the stand-to the within-stand or gap scale; thus, stands that have undergone this scale shift incorporate all structural development processes simultaneously [29].

Value-Based Definitions

A range of values, including biodiversity, scarcity, and visual and emotional impression, have been considered definitive aspects of old-growth forests.From a conservation perspective, old-growth forests derive some of their perceived value from their inherent complexity.Some definitions of biodiversity include structural diversity as a key component (e.g., Hunter [39]), and because structurally complex habitats provide more habitat niches and more-diverse ways of exploiting resources [40], forest structure has been identified as a measurable proxy for compositional or species-based biodiversity as well [17,41,42].Certain structures-for example, large-dimension dead wood or long-continuity forest patches within the broader landscape-act as keystone structures that can significantly enrich biodiversity capacity [40].

Old-growth forests also derive some of their perceived value from their current scarcity and perceived vulnerability.A long history of human settlement expansion, and forest use across North America under an industrial forestry paradigm, has greatly reduced the quantity of old-growth since European colonization [43,44].Because they are scarce, old-growth forests are perceived to be extraordinary and therefore valuable.

Some Propositions

We propose an approach to conceiving old-growth that, we hope, should help make it a less mysterious concept, less wicked, and more operational.We have no comprehensive solution or final definition, but rather offer prompts for a re-orientation of thinking.Old-growth forest is too important to ignore and too complicated to corral, so we encourage all forest researchers and practitioners to wrestle with its myriad dimensions and reconceptualize it frequently.

Forsake Virginity

We propose that the concept of virginity and its associated "purity tests" is a root cause of significant wickedness in old-growth theory, and in some cases as a potential obstruction to developing effective old-growth management strategies.The virginity criterion is an application of a broader principle that categorically separates human activity from "natural" forces.We see the debate surrounding this principle as truly mythological in character and will not wade further than ankle-deep into it, and we admit that these propositions fall squarely on one side of it.

Following from Holling et al. [45], we propose that the deadlock created by the purity criterion might be broken by incorporating the principle that humans need not be separated from ecosystems for the purposes of ecological study or ecosystem management.In other words, that an influence is human-caused does not make it categorically different from other influences, nor afford it any greater significance than other influences.What matters is the material nature and scale of the effect of an influence upon system behaviour-not its cause.

Purity criteria have utility in old-growth management only when the central focus of management is the outright preservation of extant forest, since any other management intervention would, by definition, be despoiling.This "museum approach" to old-growth management so narrows the forest practitioner"s range of options as to run the risk of undermining management or conservation objectives.This is in part because the purity criterion implies that "true" old-growth can never be actively created through management action, and also because preserved forest will inevitably cycle out of the old-growth state.

In regions of North America where old-growth was once common and is now scarce-in some areas critically-if old-growth values are to be an integral part of sustainable forest management, old-growth management strategies focused solely on preserving the "purest of what is left" would assure old-growth"s eventual eradication from the landscape.We do not imply that forests that have escaped significant direct anthropogenic influence are not valuable for a number of reasons, and preservation may indeed be the most appropriate management strategy for those forests.

We also regard the socio-political aspects of old-growth theory as fertile ground for scholarship.Indeed, the concept of old-growth virginity is highly relevant in the socio-political realm, and is particularly interesting as a value motivator.However, we believe virginity"s value as a concept is iconic and rhetorical, not ecological or operational, and to the extent the concept can be deliberately disentangled from ecological old-growth theory and on-the-ground management, it should be.

Reimagine Old-Growth as Ordinary, Not Extraordinary

The phenomenon of shifting baselines (sensu Pauly [46]), where that which is perceived to be normal, and alternatively, what is extraordinary, are redefined repeatedly on a human-generational time scale, is a significant influence on current interest in and perceptions of old-growth forests.Hunter and White [32] suggested that current scarcity of old-growth could play a useful role in shaping its definition.They proposed that arbitrariness might be deliberately turned into an advantage by using the definition itself as a tool to prompt interest in conservation, whereby a sufficiently narrow definition would keep old-growth rare enough to be perceived as valuable and unique, and therefore worthy of conservation.

This idea has drawbacks.While scarcity of old-growth may be historically definitive-that is, of an era, namely the present-old-growth is not ecologically extraordinary in many forest regions.It would be reasonable to expect its presence as a predictable part of the forest landscape.The persistence of old-growth was facilitated by landscape-scale disturbance dynamics and old-growth was an ordinary, and even predominant, forest state in many temperate regions (e.g., White and Mladenoff [47]; Lorimer and White [48]).

The paradox of scarcity as a value motivator is that which is valued must remain scarce in order to be valuable.A narrow definition may also serve to justify the lack of conservation interest in the majority of forests that don"t meet the narrow definition but are still of current or future conservation value.We propose that, where there is an ecological case to do so, old-growth be considered ecologically common, or at least ecologically predictable, for forest management purposes.That it is not actually common is not definitive of old-growth, but merely a consequence of management decisions.Were old-growth considered ecologically ordinary, forest management decision-making would always include the old-growth condition as a viable option for any single location in the forest landscape.

There is No Normal Old-Growth

Whereas early stages of forest development are dominated by the homogenizing legacy of a significant disturbance event, old-growth forests are an accumulation of legacies captured over long histories in non-deterministic ways.The multiplicity of overlapping processes associated with old-growth development, and the functional, compositional, and structural complexity these processes create, make complexity a defining feature of these forests [49].

It is therefore not surprising that attempts to develop a normative model of old-growth structure and function have encountered wickedness and gone largely unfulfilled.We see some of this wickedness arising from attempts to apply a normative model that attempts to separate out "noise" and define an average or normal old-growth state, where it is in fact the noise itself that is definitive of old-growth.

Because a stand is defined by uniform behaviour and spatial homogeneity and old-growth by a diverse, disaggregated suite of processes and spatial heterogeneity, old-growth stand appears to be, at least conceptually, an oxymoron-at least, where a stand is defined not so much on the basis of differences with neighbouring forest locations but rather on conditions within.We propose that a functional definition of old-growth may simply be forests in which the predictability of system behaviour disintegrates at the scale of the stand.In our empirical work in old-growth forests, we have come to view normative metrics-for example, median bole size or mean tree age-as largely meaningless except for the coarsest of comparisons, and metrics of diversity-for example, the range of tree ages or the variability of structural measures between neighbouring sample plots-as truly informative.In this sense we echo Jerry Franklin"s (quoted in [50]) proposition that "heterogeneity rules" the old-growth phenomenon.In recent years there have been a number of complexity-based forest metrics proposed (e.g., Zenner and Hibbs" [51] Structural Complexity Index).We have some optimism that these tools may open new insights and ways of describing old-growth.

Treat All Disturbance as Part of System Behaviour

Old-growth discourse has been challenged by the task of differentiating which types of ecosystem change add to old-growthness-for example, continuous gap formation-and which types subtract from or even eliminate it-for example, discrete stand-replacing disturbance events.We see these challenges as an artifact of viewing disturbance as a discrete event-that is, as something that happens to ecosystems.This emphasizes a static view of old-growth, rather than dynamic one.Recent meta-theoretical developments in systems ecology have proposed that the line separating exogenous and autogenic change is arbitrary.Holling et al."s panarchy model [45] internalizes the conventional concept of disturbance as an integral part of system behaviour, rather than as a discrete external influence that acts upon ecosystems-that is, disturbance is something the system does.Within this frame of reference, changes to system attributes are viewed as relatively slow or relatively rapid [48], rather than as continuous or discrete.

In this meta-model, there is no null state, but an accumulation of legacies affecting future system behaviour in a continuous and cyclical progression.We see recent forest development models, in which type of disturbance and subsequent system behaviour are linked and legacies are treated as significant (e.g., Franklin et al. [29]), as more consistent with this meta-model than with development models based on agricultural precedents in which forest development is a repetitive but discrete process that initiates in a null state [50].We believe broader adoption of the former into management practice is warranted.

This conceptual shift may also allow forest scientists and practitioners to transcend the concepts of threat and loss that have politicized the old-growth management discourse.There is, however, an opportunity for this re-framing to be abused; that is, if any kind of change is integral to system behaviour-in effect, "normal"-rather than disruptive, then any change caused by management actions is justifiable.We suggest that social choice discussions through management planning, not ecological theory, are the proper venue for such arguments, as duly informed by ecological knowledge.

In our view, if old-growth theory is to be of use to management decision-making, best efforts must be made to disentangle it from its politics.

Reimagine the Patch

In forest practice, both uniformity and difference in forests are interpreted through the lens of a forest patch"s provision of specific value.The measurements chosen to characterize and differentiate spatially discrete forest units in inventories, maps, or management plans are artifacts of the forest"s dominant use [52]-which is most often the extraction of timber.Regardless of the multiplicity of scales at which functional heterogeneity may be expressed across the forest landscape, management maps of forest landscapes rarely depict stands less than one hectare or greater than 100 hectares in size, because small units are merged together for efficiency, and reasons are found to split large ones up into manageable pieces [23].Therefore, in industrial forestry, stand or patch definition does not reflect the dynamics of forest ecosystems inasmuch as it represents the distribution of values across a landscape.

Internal uniformity and discrete temporal and spatial boundaries are self-validating assumptions in even-aged industrial forestry.Under a system of even-aged management where a defined spatial extent of standing forest is rapidly and near-completely harvested, discrete spatial and temporal edges are created.Internal variability of forest characteristics is first minimized through harvest practices, and then can be controlled by silvicultural intervention in subsequent forest development.The recognition of legacies as important determinants in stand behaviour is a relatively recent departure from the assumptions of classical forestry science, based as it was on agricultural precedents.

We propose that the concept of the stand as the spatial definition of a forest management unit be revisited and approached with greater nuance and sophistication than has historically been the case.For far too long, we have in North America been simplifying our forests to conform to our simplified models of forest development and utility.Theory, empirical analysis, and forest modeling technologies now support the application of silvicultural approaches built on the premise of actively propagating complexity within forest ecosystems (for example, see Puettmann et al. [53]).

Reconfigure the Birth-Old-Death Metaphor

Old-growth forests are, by logic and definition, old.Old is a relative measure of distance from a point of birth; the path between the two is linear and unidirectional.Forest development theory has until recently made use of a meta-model which sets homogenizing disturbance as the beginning (birth) and old-growth as the end (senescence or pre-death), and forest management still makes wide use of such a meta-model, for example in linear growth-and-yield models.

The stages of forest development of most interest to industrial forestry-that is, the homogenizing early stages during which optimal timber production occurs-continue to dominate research and management innovation.However, the criticisms leveled against microcosm experiments in ecology (e.g., Carpenter [54]) also apply to models that draw conclusions about "normal" forest development from a relatively small portion of the development cycle.In many temperate forest regions of North America, and in many forest types within others, time-to-maturity is a relatively small fraction of the potential longevity of late-successional species and the return interval of major disturbance, such that the "post-mature" stages of stand development often constitute the majority of the period between homogenizing disturbances [26].For example, Franklin et al. [29] noted that many stand-development models focused on early development in ideal even-aged stands such as plantations, and covered only 10% of the potential development process of a coastal Douglas-fir (Pseudotsuga menziesii) forest.In some temperate forest regions, disturbance events that are large and severe enough to be considered fully homogenizing at the stand scale are so infrequent under natural disturbance regimes-recurring at intervals of many centuries-that their recurrence transcends dozens of human generations, making them beyond the scope of the individual human experience [29,55].

If we accept that forest development is continuous and cyclical, any forest development stage is no more or less arbitrary a starting point for a forest development model.We propose on these grounds that for many forest types in many temperate forest regions in North America-or anywhere that old-growth may be of management interest-an adjustment to the basic structure of the forest development meta-model may provide a basis for expanding old-growth theory and management, and indeed sustainable forest management more generally.

Summary and Conclusion

Old-growth is a metaphor (sensu Proctor and Larson [56]).Its use as a common term and a conceptual nexus has value, particularly in a rhetorical and political sense (and in a colloquial sense, as it has been used throughout this essay).There is value in continuing to use old-growth as a relevant contemporary concept, but its application in forest management practice must be part of a more comprehensive effort to move beyond forest simplification and normalization through management.Until the sophistication of forest management practice matches the complexity of forest ecosystemsof which old-growth is the quintessence-old-growth management will continue to be an enigmatic prospect with the simplest strategy being the preservation of remnant patches.This is ultimately a zero-sum game for both old-growth theory-which would be relegated to the study of an isolated curiosity-and old-growth management.

Purely normative approaches to old-growth are, by themselves, largely unhelpful.We are encouraged by developments in the panarchy meta-model and by recent empirical tools and novel approaches for understanding complexity (e.g., Zenner and Hibbs [51], Staudhammer [57]), along with insightful applied approaches to silviculture and forest management based on complexity concepts (Puettmann et al. [53]).It is time to develop a forward-looking, richly nuanced old-growth theory with meaningful application to sustainable forest management in the 21st century.Such a theory would need to embrace fully the impending wickedness of climate change, for the influences of a changing climate on old-growth forest ecosystems poses potentially overwhelming challenges to our understanding of successional processes [58].

Old-growth"s "visual and emotional feast" [7] continues to captivate the public interest, and brings depth and richness to old-growth scholarship and to forest management discourse.However, when deeply entangled with its ecology, its value-rich "metaphysics" [17] create seeming intractable wickedness.We prefer to see this wickedness not as a frustrating obstacle to a rationalization of old-growth, but as an opportunity for forest scientists, policy-makers, and forestry practitioners to challenge conventional thinking-not just about old-growth itself but about forests and forest management.We see a need to bridge the gap between ecological science and theory, forest policy, and management practice through discourse that explores multiple plausible propositions in all their scientific, philosophical, and practical dimensions and to their logical ends.The application of this kind of transdisciplinary imagination (Brown et al. [59]) may be a most productive avenue for advancing a coherent theory of old-growth forest and securing its sustainability.The wickedness of the old-growth problem should continue to provide the opportunity to revisit, re-orient, and reinvest in the effort.
 AcknowledgementsWe greatly appreciate the contributions of numerous forest scientists and managers to the ongoing dialogue on old-growth ecology and management, in particular, the seminal work of Jerry Franklin, Tom Spies, and Mac Hunter.We also thank the many individuals whose reflections and ruminations in discussions both formal and informal nucleated the concepts elaborated upon in this essay.We are grateful for the comments of three anonymous reviewers which precipitated improvements to an earlier version of this essay.The Sustainable Forest Management Network of Centres of Excellence funded the old-growth forest research project from which this paper emerged, and we are grateful for its support.
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