3.1. Demographics and Frequencies
Respondents largely lived in urban areas (71.5%), with 22% living in suburban areas and 6.6% living in rural areas. The majority (71.5%) of respondents were male. The median respondent age was 55 years old, and 87.6% of respondents were white. Our respondents were highly educated; 67.8% had completed at least a 4-year degree. Nearly two-thirds (62.4%) of respondents made between $50,000 and $149,999 per year.
The ecosystem services most frequently rated as “extremely important” by all residential classifications were water quality, wildlife habitat, clean air, water quality and human-driven recreation. Over 80% of all respondents selected this ES as extremely important in the MBSNF. Conversely, the ecosystem services most frequently rated as “not important” for all respondents were providing minerals, oil, and fossil fuels; rangeland for grazing; food, wood, fuel, material for household use; and non-timber forest products. Fewer than 60% of all respondents rated these ES as very important (Figure 2
Sixteen of these services were rated significantly differently by participants from different residence classification. These included wood (F
(2, 1660) = 36.59, p
< 0.01), mining (F
(2, 1633) = 13.83, p
< 0.01), energy, (F
(2, 1636) = 30.24, p
< 0.01), rangeland (F
(2, 1624) = 8.76, p
< 0.01), non-timber forest products (F
(2, 1627) = 11.38, p
< 0.01), motorized recreation (F
(2, 1644) = 10.41, p
< 0.01), winter recreation (F
(2, 1670) = 4.13, p
= 0.02), horseback riding (F
(2, 1617) = 17.68, p
< 0.01), fish and game (F
(2, 1632) = 21.21, p
< 0.01), food, wood, fuels, and household materials (F
(2, 1611) = 33.11, p
< 0.01), roads and access (F
(2, 1622) = 13.29, p
< 0.01), freedom from people (F
(2, 1653) = 7.12, p
< 0.01), places for learning, science, and nature study (F
(2, 1649) = 4.47, p
= 0.01), historical sites (F
(2, 1641) = 9.71, p
< 0.01), designated wilderness (F
(2, 1657) = 11.76, p
< 0.01), and biological diversity (F
(2, 1643) = 4.40, p
= 0.01) (Figure 2
3.2. Preference Bundles
The ratings for these ecosystem services were entered into a principal component analysis using Varimax rotation. Items with factor loadings under 0.5 were suppressed. Six factors (what we will henceforth refer to as “preference bundles”) emerged that explained 63.1% of the variance (Table 1
). Several ecosystem services did not load strongly enough on a factor to be retained. Those items were “learning, science, and nature study”, “motorized recreation (ATV/motorbikes)”, “food, wood, fuel, household materials”, and “undeveloped areas to be free from other people”.
Preference bundle 1 (Cronbach’s α = 0.89) explained 19% of the variance and contained seven items related to the environmental qualities associated with the forest (Table 1
). It was named the “Environmental Quality” bundle. Preference bundle 2 (Cronbach’s α = 0.85), explained 15% of the variance and contained six items reflecting a utilitarian valuation of the forest. We called this the “Utilitarian” bundle. The third preference bundle (Cronbach’s α = 0.85) explained 10% of the variance and contained three items denoting cultural, spiritual, or historical significance; this was called the “Heritage” bundle. The next two preference bundles were related to recreational uses of the forest. The first (Cronbach’s α = 0.66) explained about 8% of the variance, contained four items related to a specialized use of the forest, and was called “Specialized Recreation”. The second (Cronbach’s α = 0.48) explained about 7% of the variance. It contained three items related to a generalist use of the forest and was called “General Recreation”. The last preference bundle accounted for 4.5% of the variance and contained only one item, which was “Roads and Access”.
3.3. Predictors of Preference Bundles
Demographics, including residential classification, explained minimal variance in preference bundles, as evidenced by the low R2
values (Table 2
). However, some trends were identified.
Having a higher education level, being female, and having lower income were weak, but significant predictors of the Environmental Quality bundle. Those who placed greater importance on the use of natural resources for human benefit (the Utilitarian bundle) were more likely to be less educated, have lower income, be older, and be more rural residents living near the MBSNF. Those who valued historic, cultural and spiritual sites (the Heritage bundle) were more likely to have lower incomes, and be less educated females. Neither recreation bundle was strongly predicted by demographics, likely because of their lower internal reliability, although the Specialized Recreation bundle tended to have higher income, less educated respondents, and the General Recreation bundle tended to have higher educated, female respondents. In sum, the Utilitarian bundle was the only bundle to be predicted by residential classification, but even this association was weak.
Our findings demonstrate that aggregate analyses of the MBSNF stakeholder population provide interesting information for how ES preferences bundle into six categories, and that the conceptualization of these bundles varies little by residential classification or other demographics. When we compared the stakeholder-derived preference bundles to those provided in the Millennium Assessment (MA), we noticed that the Environmental Quality values described by all participants mostly align with two of the six MA ES service types: regulating and supporting services [1
]. Provisioning services in the MA were most like the Utilitarian bundle expressed in our sample and cultural services in the MA were represented in two distinct categories of services for our sample: Heritage and Recreation. It was within these last two preference bundles that we noticed a divergence from the established framework in the global literature.
At a U.S. level, the preference bundles from this research also provided a more nuanced perspective for how forest managers might consider multiple uses across diverse stakeholders. The intent of the Multiple Use-Sustained Yield Act of 1960 was to institute a shift in forest management in the post-war era that emphasized instrumental (utilitarian or anthropocentric) values, especially timber. This act acknowledged the range of benefits and required foresters to assess trade-offs and consider all uses in making allocation decisions. While a step forward, the multiple use concept continued to have an anthropocentric flavor, with fish and wildlife being considered important often only for the benefit of human consumption, for example. The preference bundles identified here suggest that public preferences for ecosystem benefits are not entirely aligned with the original multiple use categories. Rather, our participants appeared to acknowledge both instrumental and non-instrumental (biocentric, aesthetic, spiritual) values throughout the preference bundles. The clustering of a range of ecological and human health values into the Environmental Quality preference bundle might suggest a shift away from a wholly instrumental view toward a fuller spectrum that also embraces biocentric functions. Further, the demarcation of cultural or heritage values in the ES preference bundles is something new and unexpected. Foresters typically manage heritage as a subset of recreation. Also, our results show that Recreation encompasses multiple forms and is more nuanced than originally conceived. Finally, the emergence of Access and Roads as a distinct bundle is interesting, suggesting the presence of a shared connection of individuals to the forest via roads, and this transcends or perhaps underlies other benefits.
Unlike prior research that has identified rural communities as prioritizing instrumental values, this study found that there were only modest differences in values related to the highest prioritization of specific ES (recreation for urban participants; vistas for suburban; and wildlife habitat, water quality and clean air for rural). Additionally, the fact that we found only weak, if any, socio-demographic correlates to the perceived relationships of ES within preference bundles is in contrast to our qualitative experiences with planning in the region, where vocal rural residents often associate “human-powered recreation” with urban conservationists, who have to escape the city to enjoy nature’s benefits. Based on the rhetorical arguments we overheard from urban and rural constituents engaged in the conflict-laden discussion about roads within a shared national forest, we expected to see strong socio-demographic predictors of the ES bundles. Yet, we were surprised to find that the ES preference bundles were equally identified across urban, suburban and rural classifications. We suggest that the value differences between urban and rural dwellers identified by the social forestry literature [25
] may still be present, but they are certainly not dominant across all residents of those residential classifications.
This consistency of preferences across residential classifications is an important finding that needs further exploration. It is possible that the lack of difference could be due to the opt-in nature of the study. However, this would contradict our experiences in the region. Generally, we find that those who participate in USFS social surveys do so to express their values and positions in response to the concern that they are treated differently from other social groups [43
]. As such, differences are often amplified in the voluntary participation approach. In this case, we believe that the large number of respondents, who were recruited through multiple outlets, demonstrated that despite tensions in the region, the majority of respondents held similar conceptualizations of how ES relate to each other.
When making resource management decisions for a particular management area, foresters factor in information from a variety of sources, including the best available scientific information, existing monitoring data, professional expertise, and local and national public sentiment within a broader policy context. Public meetings and other formats provide a way for constituents and stakeholders to weigh in on proposed plans and actions. In many instances, management actions can evoke conflict or tension between rural and urban communities or among various stakeholders with vested interests within the communities. The broad representativeness of these ES preference bundles could help foresters recognize that despite these tensions, the collective public conscious views the nuanced benefits of public forests similarly. Moreover, the collective conceptualization may not align with agency priorities as reflected by the multiple use policy. In light of this, foresters may want to create space for a fuller spectrum of values in public deliberations and recognize that their management strategies and targets may not align exactly with how people conceptualize their forest. Repeating this analysis on data from a rural forest would be interesting to see whether the ES preference bundles remained consistent.