United States

Department of

Agriculture

Forest Service

Pacific Northwest

Research Station

General Technical

Report

PNW-GTR-570

April 2003

Delimiting Communities in the

Pacific Northwest

Ellen M. Donoghue
Ellen M. Donoghue is a research social scientist, Forestry Sciences Laboratory,

P.O. Box 3890, Portland, OR 97208-3890.

Author
Donoghue, Ellen M. 2002. Delimiting communities in the Pacific Northwest. Gen. Tech.

Rep. PNW-GTR-570. Portland, OR: U.S. Department of Agriculture, Forest Service,

Pacific Northwest Research Station. 51 p.

The paper presents an approach for delimiting communities in the Northwest Forest Plan

(NWFP) region of the Pacific Northwest that responds to the need to assess impacts

and issues associated with broad-scale ecosystem management. Census block groups

are aggregated to provide an alternative to more commonly used geographic delimitations of communities, specifically census places. With the block group aggregation

approach, census data can be applied to almost 1.5 million more people in the NWFP

region than would be represented by using census places. The delimitation of community boundaries is intended to facilitate future research on understanding and characterizing conditions, structures, and change. Factors to consider in conducting social science

research at the small scale are discussed. Ways in which communities have been defined for social assessments and monitoring are identified. The influence of data availability on determining the unit of analysis and research focus at the small scale is

discussed.

Keywords: Community, ecosystem management, Northwest Forest Plan, social assessment, socioeconomic monitoring.

Abstract
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1

The shift from timber management to ecosystem and landscape management in the

Pacific Northwest, as well as other regions of the United States, has heightened demand

for biophysical and socioeconomic information at the broad scale. Understanding conditions and trends within large watersheds, landscapes, and political jurisdictions has

become a research and management priority. Human systems are increasingly being

recognized as part of ecological systems. As such, understanding the conditions and

trends associated with human residents is increasingly recognized as a component of

ecosystem management. For the social sciences, this is reflected in an increased emphasis on social assessments and the development of strategies for socioeconomic

monitoring at a variety of scales.

Issues associated with scale hierarchy are as prevalent in the social sciences as they

are in the biophysical sciences. Socioeconomic processes and structures are examined

at individual, household, community, county, state, regional, national, and international

levels. Understanding the links up and down scales is important to understanding the

impacts and magnitude of change. The community level, in particular, is acknowledged

as an appropriate level for better understanding human and natural resource interactions

across large geographic areas and over time (Force and Machlis 1997). It prevails, however, as the level of analysis most wrought by methodological challenges.

A pervasive challenge for scientists and professionals working on social assessments

and socioeconomic monitoring is how to define community as the unit of analysis. This

is compounded by the need to draw links from community back down to the household

level and up to the regional, or ecosystem, level. For community-level research, commonalities among geographic boundaries, data sources, data availability, and research

questions can be elusive. Researchers may know what region they want to study but

may find that the lack of available data at the small scale restricts how they define a

community. Or, they may know what constructs or processes they want to study but

may have difficulty developing measures based on secondary data that adequately reflect them. This can lead to questions and concerns about what is driving the research.

Are research questions driving the identification of the unit of analysis, data collection,

and analysis? Or, does data availability dictate the geographic boundary of the unit of

analysis, and thus influence how constructs, processes, and structures are understood?

In many cases, it is a combination of factors that drives research, as scientists balance

resources, time, and scope of a study. Insufficient attention to the unit of analysis, however, may lead to confusion about whose well-being and what causal relations are being

assessed or monitored (Kusel 2001).

Defining the community as the unit of analysis can be thought of as a two-part process

that involves establishing boundaries and determining qualities or characteristics of a

community. This dual distinction is not always explicitly addressed in social science

research at the small scale. For instance, emphasis may be placed on sociological

structures and processes without full explanation and consideration of the geographic

areas within which those processes occur. A closer look at the meaning of the verb “to

define,” and its synonym “to delineate,” illustrates this dual distinction. One meaning

pertains to marking the limits of, or indicating by drawing lines in the form of. For social

assessments and monitoring, this entails establishing the geographic boundaries of the

communities to be studied. In this context, the term community pertains to localities, or

communities of place, rather than communities of interest, such as people who belong to

a national environmental association, or mobile communities, such as migrant workers

who follow the work in the woods. The second meaning of “to define” is to determine the

essential qualities of, or to characterize or distinguish. For assessments and monitoring,

this entails identifying the conditions, processes, and structures that will be studied and

Introduction
2

selecting indicators, measures, and analytical processes to study them. These two aspects of defining community as the unit of analysis may be concurrent or separate processes. What is important is that both are considered as researchers weigh the factors

that influence social science research at the community level. For broad-scale social

assessments and socioeconomic monitoring, this means clarity about the specific geographic boundaries within which socioeconomic conditions and trends are examined.

This paper presents a block group aggregation (BGA) approach for delimiting communities in the Pacific Northwest that was developed to facilitate social science research.

The focus is on the first part of the two-part process for defining communities—delimiting

meaningful boundaries around place-based communities. A place-based community may

be an appropriate unit of analysis for assessing ecosystem management at the landscape level (Force and Machlis 1997). However, it is not the only form of community that

is affected by resource management actions. Assessments that address the conditions

and trends of other forms of community, such as mobile communities and communities

of interest, are needed but remain beyond the scope of this work. The approach to delimiting communities was intentionally designed to use census data in delimiting the boundaries. The influence of census data on defining community, and other issues pertaining

to secondary data are discussed.

The approach was developed to provide an alternative to more commonly used geographic delimitations of communities, specifically census places. It was designed to

represent a greater percentage of the rural population than would be represented by using census places and thus more accurately reflect the social and economic conditions

of the human residents of an ecosystem. The delimitation of community boundaries is

intended to facilitate future research on understanding and characterizing conditions,

structures, and change associated with ecosystem management on public lands. Admittedly, not all sociological processes are reflected by a single boundary of a community.

Indeed, boundaries may be quite different for one construct, such as civic leadership,

compared to another, such as economic diversity. The delimitations presented in this

paper may be more generic or baseline; however, they are based on analysis involving

population size, roads, school districts, land ownerships, proximity to populated places

and public lands, and other measures that depict ways in which people in an area connect and relate. The intent is that this more generic delimitation of community boundaries may be useful for assessing key sociological conditions and trends and developing

typologies of communities in the region. This information will then provide a context for

selecting communities for more indepth investigation, where the boundaries may be

modified to better reflect specific sociological constructs. This work may have direct

application for monitoring socioeconomic conditions and trends in the Pacific Northwest,

in particular, the area commonly referred to as the Northwest Forest Plan (NWFP) region. It also may contribute to further development of typologies of forest-based communities in the Pacific Northwest (Gale 1991).

Recently in the West, several interagency, multidisciplinary, broad-scale assessments

were conducted in response to, or in anticipation of, changes in resource management.

These assessments include those conducted by the Forest Ecosystem Management

Assessment Team (FEMAT 1993), the Sierra Nevada Ecosystem Project (SNEP 1996),

and the Interior Columbia Basin Ecosystem Management Project (ICBEMP) (Quigley

and Arbelbide 1997). Social assessments were conducted as part of these bioregional

assessments (Doak and Kusel 1996, Harris et al. 2000). Many dimensions of human life

were reported on, including culture, the history of human-natural resource interactions,

socioeconomic conditions and trends, and measures of community resiliency and

capacity.

Assessments and

Monitoring
3

Each social assessment identified community, or locality, as the unit of analysis. These

were operationalized in different ways, reflecting the availability or applicability of secondary data. The intent was to conduct assessments at a scale that was agreeable with

local residents. Although the following assumptions were not explicitly stated in these

social assessments, they are reflected in how the units of analysis were defined. The

first assumption is that people within a community identify with the same geographic

area and therefore have a uniform interpretation of what is meant by “community.” An

example of this assumption is that even if one person defines her community as a broad

network of people related to her children’s school and another person defines it as the

networks associated with his job at a mill, these networks intersect to represent more or

less the same geographic boundary. The second assumption is that the boundary of the

community is constant across the range of sociological processes to be studied. And,

the third assumption is that the boundary is constant across time, or at least across the

period of the research. There are many situations in which these assumptions falter.

Turnover in civic leadership, commuting to jobs outside the area, and the effect of

inmigration, to name a few, may affect how residents define their community. Given that

social assessments tend to focus on vast geographic areas, the use of more generic

delimitations of communities may facilitate understanding of broad trends and identification of areas for further research. This does not suggest, however, that less refined delimitation of community can give way to vague delimitations. On the contrary, clear

explanation and treatment of the unit of analysis are important not only to set a foundation for follow-on inquiry but also to make more transparent the policy and management

actions that may result from broad-scale social assessments.

Social assessments, by design, focus on aspects of community well-being, such as

measures of socioeconomic status and measures of a community’s ability to adapt to

change (Doak and Kusel 1996, Harris et al. 2000). A common product of such analyses

is the ranking of communities relative to one another, based on measurements of socioeconomic constructs such as resiliency and capacity. Information provided by a ranking

system is intended to assist community leaders, economic development specialists,

policymakers, and resource managers in prioritizing community development activities,

and resource management and mitigation strategies. Some research designs pay careful

attention to the development of meaningful boundaries of communities (Doak and Kusel

1996), partially out of concern for how inferences will be drawn. Given the ways social

assessments could influence community development or the labeling of communities,

the demand for additional information may be sufficiently high to merit follow-on research

(Reyna 1998). Precise information about boundaries of the unit of analysis is necessary

for accurately attributing meaning to results of social assessments.

Concurrent with the implementation of regional social assessments is an ongoing discussion among researchers, resource managers, and nongovernmental organizations

about the need for, and approaches to, socioeconomic monitoring at the community level

(Force and Machlis 1997, Parkins et al. 2001, Rasker et al. 1994, Sommers 2001). In

the NWFP region, the record of decision for the NWFP directs agencies to conduct three

types of monitoring—implementation, effectiveness, and validation—to detect desirable

and undesirable changes as a result of ecosystem management (USDA and USDI 1994).

This has led to an interagency research and management monitoring effort for the NWFP

region (USDA Forest Service 2002a). Whereas other monitoring frameworks describe the

human ecosystem as the interactions between critical resources and the human social
4

system (Machlis et al. 1997), the NWFP effort separates social and biophysical components into distinct monitoring frameworks (USDA Forest Service 2002a). These discussions and efforts reflect the increasing demand for socioeconomic information at the

small scale that are comparable at broader scales and related to natural resource management.

Monitoring has achieved heightened importance at the international level as well. Nine

coordinated strategies for assessing progress toward sustainable forest management

are occurring around the world, involving up to 150 nations. These strategies involve the

development and implementation of criteria and indicators across a range of biophysical

and human factors. The United States is 1 of 12 signatory nations to the Montréal Process Criteria and Indicators (Montréal Process Working Group 1998). As the lead

agency of a multiagency group, the Forest Service and its agency partners are preparing a report on progress toward sustainable forest management (USDA Forest Service

2002b). The Montréal criteria cover a range of issues, from biodiversity to forest health

to legal and institutional issues. One criterion, in particular, focuses on the maintenance

and enhancement of long-term, multiple socioeconomic benefits to meet the needs of

society. Delimiting the unit of analysis, particularly at the small scale, and analyzing

conditions and trends based on secondary data will be critical to the criteria and indicator process.

Concurrent with discussions about social assessments and socioeconomic monitoring

is an evolving body of literature on understanding the relation between resource management actions and community socioeconomic well-being (Beckley 1995; Doak and Kusel

1996; Force and Machlis 1997; Fortmann et al. 1989; Kusel and Fortmann 1991; Lee

1989, 1990; Machlis and Force 1988; Machlis et al. 1997; Richardson 1996; Richardson

and Christensen 1997; Schallau 1989). The literature reflects a long history and evolving

debate about (1) what constructs to use to understand the relation between communities

and forests, (2) how to measure constructs, (3) what happens over time, and (4) what

causal inferences can be drawn. One outcome of these debates is that researchers and

practitioners have placed increasing emphasis on the complex, dynamic, and interrelated aspects of rural communities and the natural resources that surround them. This

also has led to recognition of the difficulty in attributing causal relations between federal

resource management and socioeconomic conditions (Carroll et al. 1999; Freudenberg

et al. 1998, 1999).

The NWFP was developed in 1993 to help end gridlock over management of forests in

the Pacific Northwest. Through multiagency coordination, the NWFP uses an ecosystem-management approach to address resource management issues on 9.7 million hectares (24 millions acres) of federally managed land. The region includes the area that is

the range of the northern spotted owl (Strix occidentalis caurina) and counties that were

eligible for economic assistance through the Economic Adjustment Initiative. For the

purposes of this paper, the NWFP region consists of 72 counties in western Washington, western Oregon, and northern California.

Comprising of three components—forest management, economic development, and

agency coordination—the NWFP has influenced and continues to influence forest management and the relation between people and natural resources (Tuchmann et al. 1996).

The region experienced considerable change in timber harvest and employment from the

late 1980s through the 1990s (Raettig and Christensen 1999); for instance, timber harvests across all ownerships fell from 15.6 billion board feet in 1989 to 8.4 billion board

feet in 1994. These changes and the transitions that have ensued are a result of changing societal values. The NWFP, through forest management and development assistance

The Northwest Forest

Plan Region
5

to communities, is aimed at achieving long-term societal goals in a way that considers

the needs of people and the needs of the environment. Many social and biophysical outcomes of the NWFP remain unknown, including how the various forms of communities

have been affected.

The concept of community is a sociological phenomenon that continues to be shaped by

differing interpretations of social structures, processes, relations, actions, and change.

The social science literature contains various definitions of community. They range from

terms used in discussions about human populations that, for the most part, lack operational meaning to terms with empirical and theoretical grounding. Three forms of community are commonly described. The first form depicts community as a geographic entity.

The second form focuses on common norms and values that make up a community. The

third form focuses on communal actions that express some shared interest. Table 1

presents four authors’ definitions of these three common forms of community. Hillery’s

(1955) definition resulted from an examination of almost 100 studies on community in

order to classify a range of definitions of community. The forms of community described

by Wilkinson (1979, 1991) and Luloff (1998) are derived from empirical and theoretical

work in rural sociology. All forms of community share the general notion of being place

based. And although the terms differ, the three forms of communities are similarly defined among the authors.

There is general agreement that the various forms of community are complex, interdependent, (Carroll 1995, Machlis and Force 1988), and shaped by internal, as well as

external, factors. For instance, communities of place can be viewed as mechanisms that

structure other forms of community, such as cultural or occupational communities (Force

et al. 2000). Other forms of community are based on evidence of social interaction,

where the interactions make up the community, not simply the place (Kaufman 1959,

Luloff 1998, Wilkinson 1991). “Communities of interest,” the term commonly used to

represent a community based on shared norms or values, is not a place-based form of

community. In general, people within a community of interest, such as a Save the Dolphins group, come from diverse geographic locations. Social scientists who study relations between natural resource management and communities have examined communities in many forms. For instance, empirical work to delineate among functional communities (Jakes et al. 1998), occupational communities (Carroll and Lee 1990), isolated

and autonomous communities (Reyna 1998, Russell and Harris 2001), and locally defined communities (Doak and Kusel 1996) has contributed to better understanding social

conditions, processes, and functions as they relate to forest management. Broad-scale

social assessments face the challenging task of combining the relational and territorial

components of community, where the interconnections of people and place constitute

the community (Gusfield 1975, Luloff 1998).

In the United States, social science research at the small scale has been heavily influenced by the availability of census data and other secondary data. The influence is on

setting the geographic boundary of the unit of analysis and identifying indicators and

measures used in characterizing conditions and processes—both parts of the two-part

process of defining communities. Throughout the 1950s and 1960s, many studies on

rural America were restricted to census places or incorporated places with a population

of less than 2,500 because that is what the census had available (Fuguitt 1968,

Johansen and Fuguitt 1984). During this period, the census did not report unincorporated

places with a population under 1,000 people. Even in contemporary studies on rural

places, however, data availability continues to drive delimitation of communities and

subsequent socioeconomic characterizations (Doak and Kusel 1996, Harris et al. 2000,

Defining Community

The Influence of

Secondary Data on

Community Research
6

Reyna 1998, Russell and Harris 2001, Tolbert et al. 2002). For instance, a frequently

used cutoff point for studies addressing social and economic well-being at the small

scale is a population of 2,500 people or greater (Force et al. 2000, Tolbert et al. 2002).

Although this often is due to data availability or limitations posed by data disclosure,

there has been little empirical work to suggest that a cutoff of 2,500 people makes sense

in terms of understanding dimensions of social and economic well-being, particularly in

the context of regional assessments. Defining upper and lower limits to population size

is a challenge for social science research at the small scale, so much so that establishing somewhat arbitrary limits seems the norm. And, there are legitimate reasons why

very small towns may not possess sufficient institutional structure to meet the needs of

residents (Wilkinson 1991). Social assessment and monitoring research would be wellserved by making explicit how data availability or theoretical premise, or both, drive the

definition of the unit of analysis.

Another commonly used designation for small towns are census places. These include

incorporated places and census-designated places (CDPs), which are unincorporated

communities that meet a certain criteria. To qualify as a CDP in the 1990 census, an

unincorporated community had to have (1) 1,000 or more persons if outside the boundaries of an urbanized area, (2) 2,500 or more persons if inside the boundaries of an urbanized area, or (3) 250 or more persons if outside the boundaries of an urbanized area

and within the official boundaries of an Indian reservation.1

 For the 2000 census, CDPs

did not need to meet a minimum population threshold to qualify for tabulation of census

data. In the assessment of communities for the interior and upper Columbia River basin,

Harris et al. (2000) used incorporated places with a population of less than 10,000 and

CDPs that were associated with towns on reservations. The rationale for the limited use

of CDPs was that the boundaries had no legal status and thus CDPs lacked elected

officials to serve what would otherwise be considered a municipal boundary. They also

stated that most of the CDPs were excluded from their analysis because many CDPs

Table 1—Three forms of community as defined by authors

Hillery (1955) Wilkinson (1979) Wilkinson (1991) Luloff (1998)

Area Territorial unit or Locality Locality or

place geographic area

Common ties System of norms Local society Human-life dimension

and institutions or social organization

to satisfy human needs

Social interaction Interconnections and Community Processes for localityaction action oriented social actions

1 In 1990, Alaska and Hawaii were the exceptions to

the way CDPs were designated. In Alaska, a community

was designated a CDP if it had 250 or more persons

outside an urbanized area and 2,500 or more inside an

urbanized area. For Hawaii, 300 or more persons were

the basis for designating a community as a CDP, regardless of whether a community was inside or outside an

urbanized area.
7

were suburbs of cities, and thus the fate of those CDPs would rise and fall with that of

the larger city. Not all CDPs are suburbs of cities, however, and it remains to be tested

as to whether CDPs lack independent social structures and processes to warrant their

exclusion from social assessments. Another consideration for broad-scale social assessments is that state laws on incorporation differ. Thus, multistate, regional assessments that focus largely on incorporated places may overlook other functional

communities.

Understanding scale linkages is increasingly being recognized as important to assessing socioeconomic well-being at the community level. This is particularly true when broad

spatial and temporal assessments are conducted to inform management of large ecosystems (Force and Machlis 1997). The county remains an important unit of analysis for

setting context to finer scales. Consistent, long-term economic and demographic data at

the county level allow for assessments of conditions and trends across large geographic

areas (Christensen et al. 2000, Horne and Haynes 1999). However, recognition of the

hierarchy, or “nestedness” (Beckley 1998), of scales is important when assessing the

relation between communities and natural resource management. County-level data,

particularly from large heterogeneous counties, may obscure important distinctions

among communities (Beckley 1998, Doak and Kusel 1996). Further inquiry is needed to

determine when counties serve as effective proxies in community analyses (Force et al.

2000, Overdevest and Green 1995).

Two other units of analysis, census tracts and census block groups, are less commonly

used in social assessments and social science research, although both have potentially

useful applications. Census tracts are relatively stable from one census to the next.

Population growth is usually dealt with by dividing census tracts—a procedure that does

not severely impact longitudinal analyses. However, census tracts are relatively large. In

the 2000 census, census tracts ranged from 1,500 to 8,000, with an optimum size of

4,000. Although relatively permanent designations, census tracts may not be particularly

meaningful at the community level, but may have some uses for other subcounty analyses. Block groups are the next smallest census designation and have been used in

some recent social assessments (Doak and Kusel 1996, 1997). One reason, however,

that block groups have not been used more frequently is that they may have to be aggregated to be considered meaningful units of analysis. Depending on the size of the region

being studied, this process could take considerable time and resources.

Over the past 30 years, the census has altered the units of small-area geography. The

1990 census defined a block group as a cluster of blocks, generally containing 250 to

550 housing units, or an average of 700 people. In 1970 and 1980, enumeration districts

were used in most but not all states. Unfortunately, enumeration districts do not consistently coincide with block groups. The 2000 census also used block groups, although

some of the boundaries were modified based on changes in population. Figure 1 displays

the hierarchy of geography for the 1990 census.2

 Below the county level are tracts and

places. Tracts differ in spatial size and contain between 2,500 and 8,000 people. Block

groups contain 250 to 550 housing units or an average of 700 people. Blocks, the smallest geographic unit for the 1990 census, contain an average of 30 people. Only census

short-form data are available at the block level, owing to confidentiality issues. Blocks

and block groups are nested within tracts. There is no relation between place boundaries

and block group or tract boundaries.

The Utility of Census

Block Groups

2

 Geographic units are the same for the 2000 census,

but the population ranges for blocks, block groups,

and tracts differ (U.S. Department of Commerce, Bureau

of the Census 2002, hereafter Census Bureau).
8

There are some distinct advantages to block groups. They are the smallest unit for all

census summary statistics, including short-form data (100 percent of the population)

on population and housing characteristics as well as long-form data (sample of population) that includes social characteristics such as education, ancestry, and disability, and

economic characteristics such as income, employment, place of work, and public assistance. For the 1990 census, the Census Bureau delineated most block group boundaries.3

 Block-group boundaries, particularly in rural areas, follow along roads, telephone

lines, fences, streams, and other geographic features and do not necessarily coincide

with socially meaningful geographic places. Fortunately, block groups are small enough

that they can be aggregated into something more representative of a community but not

so small that aggregating them creates an unruly data management task.

Figure 1—Hierarchy of census geographic areas.

3 For the 2000 census, the Census Bureau invited local

and tribal officials to review and revise the block groups

as part of the Census Bureau’s Participant Statistical

Areas Program (Census Bureau 2002).

Block

Block group

Tract Place

County

State

Division

Region

United States
9

Census block groups are a useful mechanism for examining demographic information

at a very small scale. They have been used to understand environmental justice issues

(U.S. Environmental Protection Agency 2002) and to describe socioeconomic conditions

as part of regional social assessments (Doak and Kusel 1996). In the social assessment

for the SNEP, Doak and Kusel (1996) developed a process for combining adjacent block

groups into aggregations of block groups that represented meaningful social units. The

BGAs were developed with input from planners and local experts familiar with census

data and county demographics. Through an iterative process, researchers and local experts aggregated 720 block groups into 182 BGAs that more closely represented locally

defined communities. This approach offers some useful applications for social science

research outside of the Sierra Nevada region. Thus, the remainder of this paper presents

an approach used for aggregating block groups in the NWFP region.

The large size of the NWFP region and the subsequent high number of block groups

would not allow for replication of the BGA approach used by Doak and Kusel (1996),4

within the limits of available resources. However, the idea of developing a meaningful unit

of analysis at the small scale that not only corresponded with census data but also represented a greater percentage of the population than would be represented by census

places was appealing. Although census tracts were considered as a unit of analysis for

delimiting communities, they were judged to be too large (between 1,500 and 8,000

people). Block groups, because of their small size, could be aggregated to represent

both small and larger communities and would have wider applications for socioeconomic

research and monitoring activities. Thus, an approach was developed for aggregating

7,776 block groups, from the 1990 census, within the 72 counties of western Washington, western Oregon, and northern California. Unlike the SNEP social assessment (Doak

and Kusel 1996), local experts did not participate in the aggregation process for the

NWFP region. The approach combined geographic information system (GIS) analyses

with a considerable amount of visual verification. Verification was made through consultation of information about roads, school districts, population size, public lands, census

designations, and other spatial and demographic features, including the geographic

names information system (GNIS) list of populated places. The GNIS was developed

by the U.S. Geological Survey and the U.S. Board on Geographic Names and contains

information about almost 2 million physical and cultural geographic features in the United

States. Census 2000 data at the block group level were scheduled to be released during

fall 2002. Although changes in block group boundaries are expected, there may be an

opportunity for longitudinal analysis at the BGA level in the NWFP region.

Census block groups were aggregated into BGAs based on criteria comprising GIS

analysis and visual verification (fig. 2). Four types of GIS analyses were performed. The

first GIS analysis was to identify, aggregate, and separate block groups that we would

then define as metropolitan areas. First, urbanized areas, as defined by the 1990 census, were identified. These areas comprised one or more census place and adjacent

densely settled surrounding areas that together had a minimum of 50,000 people. Because we wanted to keep places that had between 50,000 and 100,000 people in our

analysis of communities, we selected only those urbanized areas with a population

greater than 100,000 people. The polygons for these urbanized areas became layer 1

in the GIS analysis. Census places that fell within this layer were identified. All block

groups containing these points were selected. Block groups with 50 percent or more of

Aggregating Census

Block Groups

4

 Doak and Kusel (1997) used a similar method for their

assessment of communities in the region surrounding

the Klamath National Forest in California.
10

their polygon within the urbanized area also were selected (layer 2). And, block groups

that were less than 50 percent within the urbanized area but with a population density

greater than 1,000 persons per square mile also were considered metropolitan (layer 3).

In addition, a buffer of 2.4 kilometers (1.5 miles) was placed along major roads within the

urbanized area. Block groups that were 50 percent or more within the buffer were identified (layer 4). Percentages and buffer distances that were used in each GIS analysis to

determine where to place block groups were reasonable judgments that would facilitate

additional aggregating while minimizing overaggregating. In the GIS analysis for metropolitan areas, block groups that were contiguous or very near an urbanized area were

assumed to have strong connections to that urbanized area. However, percentages and

buffers were intentionally set relatively small to allow for the opportunity to delimit communities outside of metropolitan areas. Once a block group was designated as inside a

Figure 2—Block group aggregation process. GIS = geographic information system.
11

metropolitan area, no further delimitations were conducted. Therefore, erring on the side

of relatively smaller metropolitan BGAs provided flexibility to further aggregate adjacent

BGAs into a metropolitan BGA in the future. The four layers were combined to create a

single layer comprising 10 metropolitan BGAs5 that were then visually verified.6Metropolitan BGAs comprised 3,712 block groups in the region, leaving 4,064 block groups for

delimiting into BGA communities in the NWFP region.

With the identification of metropolitan BGAs complete, the primary focus was on delimiting nonmetropolitan BGA communities. This involved additional GIS analyses and visual

verification. In a second GIS analysis, block groups were aggregated based on their

proximity to census places. Points for census places and GNIS-populated places were

selected, and block groups where these points fell were identified (layer 1).7 Census

place polygons were then selected, and block groups where 50 percent or more of the

polygon fell within the census place polygon were added to the aggregation (layer 2).

Block groups that fell less than 50 percent within a census polygon but with a population

density higher than 1,000 persons per square mile were identified (layer 3). In addition, a

1.6-hectare (4-acre) buffer was placed around the census place polygons. Block groups

that were more than 50 percent within the buffer were identified and assigned to the BGA

that contained that highest proportion on the block group (layer 4). All four layers were

combined to create additional aggregations that were then visually verified. In general,

aggregations outside of metropolitan areas contain only one census place. A few exceptions were made where block group shapes favored the inclusion of more than one

census place.

The purpose of the third GIS analysis was to aggregate block groups of less than 250

persons. It was assumed that a block group containing less than 250 persons would not

have the social, physical, and economic infrastructure to support a community. Again,

this number was set intentionally small to allow for relatively small block groups, around

250 to 500 persons, to be designated as single communities if appropriate. In addition to

small population size, location of school district boundaries was used to aggregate census block groups. First, block groups with a population of less than 250 persons were

selected. An analysis was conducted of the proportion of each of these block groups

that was contained within nearby school districts. A block group was aggregated with the

adjacent block group within the school district that contained the highest proportion of

the block group. In areas with no available data on school districts, a visual interpretation

5

 The 10 metropolitan areas include San Francisco,

Santa Rosa, and West Sacramento, California;

Portland, Eugene, and Salem, Oregon; and Bremerton,

Richland-Kennewick-Pasco, Seattle, and Tacoma,

Washington. These names do not reflect all the

census place names that are included within a given

metropolitan BGA. Also, some metropolitan areas

extend into counties that are beyond the region of this

project.

6

 The process of visual review is similar for all four of

the GIS analyses and is described later in the paper.

7

 Although the database of GNIS-populated places had

more locality names than the census offered, there

was some concern over the accuracy of the GNIS

spatial data. Thus, identifying the location of localities

within block groups was based on information present

in DeLorme atlas quadrangles (DeLorme 1998a,

1998b, 1998c) rather than the GNIS spatial data.
12

was applied. Block groups with less than 250 people were joined with aggregations that

shared the same road. Transportation corridors represented not only ways that people in

an area connect but also served as geographic features that are compatible with the GIS

methods for aggregating block group polygons. Only eight exceptions were made to the

criterion that a BGA had to have more than 250 persons and at least one census or

GNIS-populated place.

We wanted to maintain the option to relate socioeconomic data at the county level to the

BGAs, given the availability of secondary data at the county level. County-level data can

provide context to socioeconomic conditions and trends at the community level. Thus,

we purposefully did not aggregate block groups across county boundaries, except in

cases where it clearly made sense to do so. Only six BGAs cross county lines. Aggregating block groups for Indian and military reservations, e.g., required crossing county

boundaries.

In the fourth GIS analysis, block groups within Indian reservations that were not already

aggregated based on the census places were combined. In areas where limited road

access separates localities within a reservation, more than one aggregation may exist

within an Indian reservation.

On completion of the four GIS analyses, a visual verification of the BGAs was conducted

to determine if additional aggregation or separation of block groups was necessary. Information about population size within block groups; the presence, absence, and position

of census places; and GNIS-populated places were considered, along with land ownership and the shape of the aggregation and adjacent block groups. There were some accuracy concerns pertaining to the GNIS spatial data. To address these concerns, the

GNIS place locations were verified by using the DeLorme atlas and gazetteer (1998a,

1998b, 1998c) collection of quadrangular maps at 1:150,000 scale. Transparencies, at

the same scale, of block groups, roads, school districts, and county borders were used

to identify localities and provide other information useful for the aggregation process. The

visual verification led to additional aggregations. For instance, a block group with greater

than 250 population was aggregated with an adjacent block group if (1) no census or

GNIS place was present, (2) the block shape favored aggregation with an adjacent block

group, (3) all or most populated places within a block group and an adjacent block

group(s) were along a border, or (4) the block group fell largely within a school district

boundary covering an adjacent aggregation. As another example, if a spatially large

block group contained a census place, but the shape of the block group practically surrounded a smaller block group that also contained a census place, those block groups

most likely were aggregated. If, however, they were in separate school districts and were

served by different roads, they were probably left apart.

Although efforts were taken to limit the number of census places in nonmetropolitan

BGAs to one, in many cases, this could not be accomplished. Census place polygons

often adjoin one another; for instance, several CDPs may surround an incorporated

place, particularly in urbanized areas. Census place borders do not coincide with block

group borders, but rather bisect block groups. Each occurrence where census places

adjoined outside of urbanized areas was examined on a case-by-case basis. Aggregations were designated to include only one census place if the block group borders were

fairly consistent with the census place polygon border, and the neighboring block groups
13

were part of a different school district. Aggregations were designated to include multiple

census places when the census place boundaries were very irregular and bisected the

block groups.

Each BGA exists in the form of a polygon and a point. Both forms facilitate future analysis and display of socioeconomic research. Polygons depict the size and shape of the

BGAs. As they are contiguous, BGA polygons cover the entire region. Points have been

used in developing other measures, such as distance from the BGA to service centers.

Both polygons and points are useful in creating measures of proximity to public lands.

These measures will be used in future work on defining and characterizing communities

in the NWFP region. The BGA polygon shape is an artifact of the process of aggregating smaller polygons (block groups) into larger ones (BGAs). Points had to be assigned

for all BGAs. For BGAs containing census places, points were placed on or near the

census place point. If more than one census place existed within a BGA, the point

was placed on the census place with the greater population. For BGAs without census

places, points were placed along a road near a GNIS-populated place. If such BGAs

contained several GNIS-populated places, the location of the point was based on which

block group had the higher population and was nearer to a major road.

Seven thousand seven hundred and seventy-six block groups were aggregated into 1,324

BGAs, which includes 10 metropolitan BGAs, in the NWFP region (fig. 3). The appendix

lists the names assigned to the BGAs, including the 10 metropolitan BGAs, as well as

the number of block groups within each BGA, the county name, and the 1990 population

(based on census long-form data). Each BGA name is a composite of the names of incorporated places, CDPs, GNIS-populated places, and occasionally geographic features

within a BGA boundary. A composite name may not identify all locality names within a

given BGA. It may reflect the geographic extent of a BGA or the larger populated localities within a BGA. The points assigned to each BGA are depicted in figure 4. Because

many BGAs contain several populated places, the BGA points should not be misinterpreted to reflect the only location of population within a BGA.

The BGA delimitations represent a larger percentage of the population than would have

been represented by using more common units of analysis, namely census places. Indeed, the BGA approach reflects the entire population. In 1990, 517 nonmetropolitan

census places existed in the NWFP region. Socioeconomic data at the census place

level can be attributed to 2.5 million people in the NWFP region in 1990. With the BGA

designation, the same indicators can be applied to almost 4.0 million people residing

within the 1,314 nonmetropolitan BGAs. Figure 5 shows the polygon shape for census

places in the NWFP region. A comparison of figures 4 and 5 reveals an increase in the

number of rural places represented by the BGA approach, as compared to the census

place level designations.

In general, when the criteria to aggregate did not point to an obvious aggregation of block

groups, we tended not to aggregate. Thus, there are numerous, relatively small BGAs.

Thirty-six percent of the nonmetropolitan BGAs had populations of less than 1,000 in

1990. Just over half, or 52 percent, had between 1,000 and 5,000 people. Only 1.5 percent had between 25,000 and 115,000 people. This is consistent with our objective to

delimit rural and small communities in the region—places that may not be represented

by using other units of analysis. Also, from a data-management perspective, we decided

that it would be easier to further aggregate BGAs, rather than disaggregate them. Thus,

additional aggregation is possible and may be best served with input from local experts.

Block Group

Aggregations for

the Northwest

Forest Plan Region
14

Figure 3—Block group aggregations in the Northwest Forest Plan region.
15

Figure 4—Block group aggregation points and Northwest Forest Plan (NWFP) counties.
16

Figure 5—Census places in the Northwest Forest Plan (NWFP) region.
17

This paper responds to the growing awareness that human systems are part of ecosystems and that ecosystem-based approaches to resource management have resulted in a

heightened demand for socioeconomic information at the broad scale. Although social

assessment and monitoring strategies are increasingly being used to understand the

impacts and emerging issues resulting from ecosystem-based approaches, the dilemma

of the small-scale unit of analysis prevails. If understanding conditions and trends for

people living within ecosystems remains a societal goal, then units of analysis such as

the BGA delimitation may serve as a useful alternative to other commonly used units of

analysis, such as census places. The BGA method counts everyone, as opposed to

census places, which count only people residing in incorporated places or CDPs. A wide

range of social and economic census data are available at the BGA level. And, as a geographically defined shape and point, BGAs offer various ways to develop, analyze, and

represent socioeconomic as well as spatial data.

To the extent possible, the BGA approach attempted to identify communities that reflected some of the three forms of community depicted in table 1. The polygons associated with the census block group designations provided the geographic boundary—the

place. We tried to build the boundary by aggregating adjacent polygons together in a

way that reflected common ties, social interaction, or interconnections (Hillery 1955,

Wilkinson 1979) without having the opportunity to collect primary data or conduct indepth

case studies. Given the size of the region, we developed a more automated approach.

By building spatial displays that included population size, school districts, county

boundaries, land ownerships, census places, GNIS-populated places, and other features, we attempted to aggregate block groups in a meaningful way.

The BGA approach, like other place-based forms of community, has its limitations. First,

the impacts of ecosystem management on nonplace-based communities, such as mobile communities and communities of interest, cannot be assessed or monitored by

using the BGA unit of analysis. More work is needed to understand the impacts of resource management on these forms of communities at the broad scale. Individual case

studies have a role, but additional work that sets cases into a broader context may be

necessary to address the need for information at the broad scale. Second, the BGA

approach is intentionally a generic, less refined, delimitation of community boundaries.

The intent is for it to be useful in assessing key socioeconomic conditions and trends

within a large region by using census data on socioeconomic indicators and GIS data on

distances to service centers and proximity to public lands. This information will then

provide a context for selecting communities for more indepth investigation. However, the

community boundaries delimited by the BGA approach may not be suitable for all forms

of community and all sociological constructs. Shared identities, community structures,

and community processes will likely extend across the boundaries of BGAs. In some

cases, slight modifications of these boundaries may facilitate the study of some of these

processes; in other cases, the boundaries will be less functional. Fortunately, there is

room for additional work to further refine and modify the BGAs. Finally, although block

groups were first designated at a national level in 1990 and again in 2000, longitudinal

analyses will be complicated by inevitable changes to block group boundaries that will

be done to reflect population change. Some changes, such as one block group being

divided in half owing to population growth, will not be too difficult to deal with over time.

Other changes, such as two block groups becoming three block groups, will be more

problematic.

Conclusion
18

Several management implications have emerged from this work of developing the BGA

approach. Social assessments require considerable resources and time and tend to be

conducted at critical junctures in resource management. As such, expectations for social assessments seem high, and emphasis seems placed on the development of some

type of community ranking. The strength of social assessments lies in the identification

of key trends, critical geographic areas, and further avenues for investigation. A realistic

expectation for assessments, therefore, may be that they function as a foundation for a

multipronged strategy for understanding impacts and anticipating emerging issues associated with ecosystem management. Combined with indepth case studies, assessments

of nonplace-based communities, and other forms of assessment such as communitylevel social impact assessment (Burdge 1998), broad-scale social assessments have

much to contribute. Social assessments may not adequately meet the demand for information at the broad scale, however, if they are relied on as the sole source for placebased, community-level, socioeconomic information across vast landscapes.

This work has several implications for research as well. There is the need to test whether

the BGA delimitations provide a distinctly different framework for selecting cases for follow-on research than would have resulted by using another designation, such as census

places. There are also implications for longitudinal research. In many respects, social

science research is about striking a balance between research questions, scale, available data, and available resources to conduct the research. This becomes increasingly

complicated in social assessment and monitoring research where links across spatial

and temporal scales are expected. More work is needed to understand how we can incorporate the dynamic nature of communities—the spatial and relational qualities—into

long-term assessment and monitoring.

Thanks to Anne Schneider, USDA Forest Service, and Gosia Bryja, Pacific Meridian

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Appendix

Table 2—Block group aggregations in the Northwest Forest Plan region

Identifying Number Population,

number Block group aggregation namea County State of BGsb 1990

1 Arbuckle Colusa CA 1 2,435

2 College City - Harrington Colusa CA 1 815

3 Colusa Colusa CA 7 6,753

4 Grimes - Graino - Millers Landing Colusa CA 1 657

5 Maxwell - Delevan - Cortena Colusa CA 1 1,395

6 Stegeman - Princeton Colusa CA 1 494

7 Stonyford - Lodoga - Sites Colusa CA 1 551

8 Williams city Colusa CA 3 3,175

9 Crescent City - Crescent City North CDP Del Norte CA 10 17,382

10 Fort Dick - Tyron Corner Del Norte CA 1 1,244

11 Gasquet - Patrick Creek - Idlewild Del Norte CA 1 660

12 Hiouchi - Douglas Park Del Norte CA 1 743

13 Klamath CDP Del Norte CA 1 1,382

14 Smith River Del Norte CA 2 2,049

15 Butte City - Afton Glenn CA 1 535

16 Elk City - Dogtown Glenn CA 1 658

17 Fruto - Copper City - Newville Glenn CA 2 595

18 Hamilton City CDP - Mills Orchard Glenn CA 2 3,299

19 Norman - Logandale - Glenn Glenn CA 1 512

20 Ordbend - Bayliss Glenn CA 1 958

21 Orland Glenn CA 8 8,674

22 Willows Glenn CA 8 7,901

23 Wyo Glenn CA 2 1,666

24 Arcata Humboldt CA 17 19,160

25 Arcata (part) - Korblex - Maple Creek Humboldt CA 1 983

26 Beatrice Humboldt CA 1 320

27 Benbow - Cooks Valley - Whitethorn Humboldt CA 1 899

28 Berry Glenn - Orick Humboldt CA 1 509

29 Blue Lake Humboldt CA 2 1,655

30 Bridgeville - Dinsmore Humboldt CA 1 746

31 Bull Creek - Honeydew - Ettersburg -

Thorn Junction Humboldt CA 1 816

32 Carlotta - Riverside Park Humboldt CA 1 883

33 Eureka - Myrtletown CDP - Cutten CDP -

Bayview CDP - Pine Hills CDP -

Humboldt Hill CDP Humboldt CA 46 44,066

34 Ferndale city - Port Kenyon - Waddinton -

Capetown Humboldt CA 3 2,865

35 Fieldbrook Humboldt CA 1 943

36 Fortuna Humboldt CA 13 10,123

37 Freshwater Humboldt CA 2 1,992

38 Garberville Humboldt CA 1 900

39 Glendale Humboldt CA 1 672

40 Hoopa Valley Indian Reservation Humboldt CA 3 2,624

41 Hydesville CDP Humboldt CA 1 1,370

42 Korbel - Fernwood Humboldt CA 1 519

43 Larabee - Fort Seward - Alderpoint Humboldt CA 1 917
24

Table 2—Block group aggregations in the Northwest Forest Plan region (continued)

Identifying Number Population,

number Block group aggregation namea County State of BGsb 1990

44 Lolita - Table Bluff - Hookton Humboldt CA 1 1,194

45 McKinleyville CDP Humboldt CA 11 10,936

46 Orleans, CA Humboldt CA 1 686

47 Pepperwood - Shively - Holmes Humboldt CA 1 443

48 Petrolia Humboldt CA 1 434

49 Phillipsville - Briceland Humboldt CA 1 1,184

50 Redway CDP Humboldt CA 1 1,221

51 Rio Dell Humboldt CA 4 4,302

52 Shelter Cove Humboldt CA 1 393

53 Weott - Myers Flat - Miranda Humboldt CA 1 1,093

54 Westhaven-Moon CDP - Trinidad -

Trinidad Rancheria Humboldt CA 3 2,695

55 Willow Creek CDP Humboldt CA 2 1,575

56 Castle Rock Springs Lake CA 1 302

57 Clearlake Lake CA 20 12,443

58 Clearlake Oaks CDP Lake CA 4 2,347

59 Cobb CDP Lake CA 2 2,015

60 Enterprise - Parramore Springs -

Saratoga Springs Lake CA 2 560

61 Glenhaven Lake CA 1 425

62 Hidden Valley Lake CDP Lake CA 1 1,027

63 Hidden Valley Lake CDP (part) -

Military Reservation (part) Lake CA 1 1,050

64 Hough Springs - Barkerville Lake CA 1 370

65 Kelseyville CDP Lake CA 13 8,700

66 Lakeport Lake CA 13 8,478

67 Loch Lomond - Seigler Springs Lake CA 3 1,503

68 Lower Lake CDP Lake CA 8 3,238

69 Lucerne CDP - Nice CDP Lake CA 8 4,522

70 Middletown Lake CA 4 1,367

71 Pepperwood Grove Lake CA 1 661

72 Upper Lake Lake CA 5 1,623

73 Belfast - Litchfield - Crest Lassen CA 2 418

74 Bieber - Nubieber - Pumpkin Center Lassen CA 1 761

75 Buntingville Lassen CA 1 969

76 Coppervale - Lasco - Westwood Junction Lassen CA 1 406

77 Doyle - Scotts - Plumas Lassen CA 1 1,028

78 Halls Flat - Jelico - Little Valley Lassen CA 1 511

79 Hot Springs - Leonard - Hayden Hill Lassen CA 1 364

80 Janesville Lassen CA 1 1,529

81 Johnstonville Lassen CA 1 1,873

82 Madeline - Termo - Ravendale Lassen CA 1 318

83 Milford Lassen CA 1 406

84 Sierra Army Depot - Wendel - Herlong Lassen CA 2 1,421

85 Spalding - (Eagle Lake) Lassen CA 1 280

86 Standish Lassen CA 1 762

87 Susanville Lassen CA 7 10,075

88 Westwood CDP Lassen CA 2 2,279

89 Bivalve - Marconi - Ocean Roar Marin CA 1 957

90 Bolinas CDP - (Bolinas Point) Marin CA 3 1,665

91 Dillon Beach Marin CA 1 308
25

Table 2—Block group aggregations in the Northwest Forest Plan region (continued)

Identifying Number Population,

number Block group aggregation namea County State of BGsb 1990

92 Inverness CDP Marin CA 2 1,392

93 Lagunitas-Forest Knoll CDP Marin CA 2 1,449

94 Nicasio Marin CA 1 510

95 Point Reyes Station Marin CA 1 815

96 Stinson Beach - (Mount Tamalpais) Marin CA 3 1,062

97 Tocaloma - Olema - Sacramento Landing Marin CA 1 628

98 Tomales - Fallon Marin CA 1 627

99 Woodacre CDP Marin CA 3 1,937

100 Andersonia - Leggett - Cummings Mendocino CA 1 656

101 Boonville Mendocino CA 1 857

102 Calpella Mendocino CA 2 609

103 Caspar Mendocino CA 2 2,925

104 Cleone Mendocino CA 1 588

105 Comptche - Navarro - Cape Horn Mendocino CA 1 1,032

106 Covelo CDP - Round Valley Indian

Reservation Mendocino CA 1 2,018

107 Fort Bragg Mendocino CA 10 8,639

108 Gualala - Anchor Bay - Fish Rock Mendocino CA 1 1,742

109 Hopland - Nacomis Indian Rancheria -

The Oaks Mendocino CA 2 1,745

110 Inglebrook - Redwood Lodge - Northspur Mendocino CA 1 1,908

111 Laytonville CDP / Laytonville Indian

Reservation Mendocino CA 1 1,122

112 Little River - Albion - Elk Mendocino CA 1 1,745

113 Longvale - Hearst - Crowley Mendocino CA 2 3,175

114 Manchester Mendocino CA 1 506

115 Mendocino Mendocino CA 1 887

116 Nashmead - Dos Rios - Farley Mendocino CA 1 863

117 Orrs Springs Mendocino CA 1 522

118 Philo Mendocino CA 1 812

119 Pine Grove, CA Mendocino CA 1 773

120 Point Arena Mendocino CA 1 1,140

121 Potter Valley Mendocino CA 3 2,456

122 Presswood Mendocino CA 1 1,501

123 Redwood Valley - Laughlin Mendocino CA 3 5,154

124 Ridge Mendocino CA 1 1,899

125 Rockport - Westport - Kibesillah Mendocino CA 1 515

126 Talmage Mendocino CA 1 1,048

127 Tan Oak Park - Branscomb Mendocino CA 1 887

128 The Forks Mendocino CA 2 2,381

129 Ukiah Mendocino CA 20 20,789

130 Vichy Springs Mendocino CA 2 1,484

131 Whiskey Springs - Melbourne Mendocino CA 1 711

132 Willits Mendocino CA 7 7,256

133 Adin - Day - White Horse Modoc CA 1 829

134 Alturas Modoc CA 1 4,276

135 Canby - Ambrose Station - (Warm Springs

Valley) Modoc CA 1 660

136 Cedarville - Eagleville - (Surprise Valley) Modoc CA 1 976

137 Fort Bidwell - Lake City Modoc CA 1 434

138 McArthur - Likely Modoc CA 1 892
26

Table 2—Block group aggregations in the Northwest Forest Plan region (continued)

Identifying Number Population,

number Block group aggregation namea County State of BGsb 1990

139 New Pine Creek - Willow Ranch - Davis Creek Modoc CA 1 429

140 Newell - Homestead - Hackamore Modoc CA 1 1,182

141 Aetna Springs Napa CA 1 708

142 American Canyon CDP Napa CA 5 7,893

143 Angwin CDP Napa CA 4 4,648

144 Atlas - [Moskowite Corners] Napa CA 1 1,624

145 Calistoga Napa CA 5 5,189

146 Cuttings Wharf Napa CA 1 949

147 Deer Park CDP Napa CA 2 1,758

148 Knoxville - (Lake Berryessa) - (Pope Valley) Napa CA 1 343

149 Napa Napa CA 67 71,752

150 Napa Soda Springs Napa CA 4 1,881

151 Oakville - Rutherford - Zinfandel Napa CA 2 1,864

152 Spanish Flat Napa CA 3 1,130

153 St. Helena Napa CA 7 5,538

154 Yountville Napa CA 5 5,488

155 Anderson city Shasta CA 15 16,384

156 Bella Vista Shasta CA 3 3,400

157 Big Bend - Hillcrest - Roaring Creek Indian

Rancheria Shasta CA 1 513

158 Burney CDP Shasta CA 3 3,431

159 Cassel - Old Station - Doyles Corner Shasta CA 1 915

160 Castle Crag - Fisher - Delta Shasta CA 1 631

161 Centerville Shasta CA 1 1,077

162 Central Valley CDP Shasta CA 7 8,967

163 Cloverdale - Olinda Shasta CA 3 3,709

164 Cottonwood CDP Shasta CA 4 4,855

165 Fall River Mills - Glenburn Shasta CA 1 936

166 Fern - Whitmore Shasta CA 1 477

167 French Gulch - Minnesota - Matheson Shasta CA 1 512

168 Ingot - Oak Run Shasta CA 2 2,803

169 Johnson Park Shasta CA 1 872

170 Lakehead - Sugarloaf - O’Brien Shasta CA 2 1,139

171 McArthur - Pittville - Spalding Corner Shasta CA 1 1,168

172 Millville - Redwoods - Inwood Shasta CA 1 1,497

173 Montgomery Creek - Montgomery Creek

Indian Rancheria - Round Mountain Shasta CA 1 1,027

174 Mountain Gate Shasta CA 2 1,893

175 Obie - Cayton - Four Corners Shasta CA 1 834

176 Ono - Gas Point - Knob Shasta CA 1 903

177 Palo Cedro Shasta CA 2 1,756

178 Redding Shasta CA 52 72,440

179 Redding (part) - Buckeye Shasta CA 2 2,315

180 Redding (part) - Keswick Shasta CA 2 1,380

181 Redding (part) - Loomis Corners Shasta CA 2 2,442

182 Redding (part) - Pine Grove Shasta CA 1 1,528

183 Redding (part) - Silverthorn Shasta CA 1 1,598

184 Shasta - Whiskeytown - Iron Mountain - Kett Shasta CA 1 883

185 Shasta (part) - Igo Shasta CA 1 1,361

186 Shingletown Shasta CA 1 1,799

187 Viola - Summertown - Manzanita Lake Shasta CA 2 1,591
27

Table 2—Block group aggregations in the Northwest Forest Plan region (continued)

Identifying Number Population,

number Block group aggregation namea County State of BGsb 1990

188 Big Springs - Bolam Siskiyou CA 1 1,817

189 Clear Creek - Somes Bar - Hamburg Siskiyou CA 1 669

190 Deetz - Upton Siskiyou CA 1 1,188

191 Dorris Siskiyou CA 2 2,020

192 Dunsmuir Siskiyou CA 3 2,706

193 Etna Siskiyou CA 1 600

194 Etna (part) - Callahan - Sumerville Siskiyou CA 1 1,066

195 Etna (part) - Greenview - Cheeseville Siskiyou CA 1 1,800

196 Fort Jones Siskiyou CA 1 1,634

197 Grenada - Gazelle Siskiyou CA 1 848

198 Happy Camp Siskiyou CA 1 1,000

199 Hilt - Gottsville - Hornbrook Siskiyou CA 1 802

200 McCloud CDP Siskiyou CA 2 1,728

201 Montague Siskiyou CA 2 2,681

202 Montague (part) - Little Shasta - Grass Lake Siskiyou CA 1 953

203 Mount Shasta Siskiyou CA 4 5,519

204 Seiad Valley - Horse Creek - Klamath River Siskiyou CA 1 1,117

205 Tulelake Siskiyou CA 1 1,467

206 Weed Siskiyou CA 4 3,998

207 Yreka Siskiyou CA 8 9,918

208 Annapolis - Los Lomas Sonoma CA 1 569

209 Black Oaks - Mercuryville Sonoma CA 1 1,027

210 Bloomfield - Valley Ford Sonoma CA 1 1,641

211 Bodega Bay CDP - Bridgehaven -

Salmon Creek Sonoma CA 3 2,554

212 Cadwell - Cunningham Sonoma CA 3 2,281

213 Chianti Sonoma CA 1 863

214 Cloverdale city Sonoma CA 6 6,593

215 Duncan Mills Sonoma CA 1 280

216 Forestville CDP Sonoma CA 4 5,190

217 Fort Ross - Walsh Landing - Jenner Sonoma CA 1 1,278

218 Geyserville - Cozzens Corner - Jimtown Sonoma CA 2 2,447

219 Glen Ellen CDP Sonoma CA 3 3,531

222 Hacienda - Hollydale - Summerhome Park Sonoma CA 3 2,089

223 Healdsburg Sonoma CA 11 16,402

224 Hessel Sonoma CA 1 1,602

225 Kellogg Sonoma CA 1 582

226 Knowles Corner Sonoma CA 1 1,131

227 Lytton Sonoma CA 1 1,117

228 Mark West Spring Sonoma CA 2 2,448

229 Monte Rio CDP Sonoma CA 2 1,852

230 Monte Rio CDP (part) - Montesano - Cazadero Sonoma CA 2 1,741

231 Occidental CDP Sonoma CA 2 2,068

232 Petaluma Sonoma CA 44 52,019

233 Petaluma (part) - McNear - Lakeville Sonoma CA 1 2,808

234 Roblar - Turner Sonoma CA 1 843

235 Sears Point - Wingo - Shellville -

(Naval Reservation) Sonoma CA 1 863

236 Sebastopol Sonoma CA 17 16,122
28

Table 2—Block group aggregations in the Northwest Forest Plan region (continued)

Identifying Number Population,

number Block group aggregation namea County State of BGsb 1990

237 Sonoma city - Eldridge CDP - Fetters Hot

Springs-A - Boyes Hot Springs CDP -

El Verano CDP - Temelec CDP Sonoma CA 26 31,136

238 Stewarts Point - Sea Ranch Sonoma CA 1 594

239 Temelec CDP (part) - Big Bend Sonoma CA 1 781

240 Two Rock - Two Rock Ranch Station

Military Reservation Sonoma CA 1 1,869

241 Abbott - Tudor - Wilson Sutter CA 1 1,068

242 Live Oak Sutter CA 4 5,946

243 Marchant - Cunard - Karnak Sutter CA 1 410

244 Meridian - Tarke - Tisdale Sutter CA 2 794

245 Nicholaus -East Nicholaus - Trowbridge Sutter CA 1 802

246 Pennington - Encinal - Sanders Sutter CA 1 806

247 Pleasant Grove - Riego - Counsman Sutter CA 1 850

248 Rio Oso Sutter CA 1 969

249 Robbins - Kirkville - Cranmore Sutter CA 2 538

250 Sutter CDP Sutter CA 1 1,205

251 Sutter CDP (part) - West Butte Sutter CA 1 1,983

252 Verona - Joes Landing Sutter CA 1 340

253 Yuba City - Tierra Buena CDP - South

Yuba City CDP Sutter CA 38 48,704

254 Bend Tehama CA 1 957

255 Corning Tehama CA 9 8,637

256 Dairyville Tehama CA 2 2,214

257 Dales - Manton - Campbellville Tehama CA 3 1,376

258 Henleyville - Paskenta - Sunnyside Tehama CA 1 1,697

259 Hooker Tehama CA 2 3,011

260 Kirkwood Tehama CA 1 508

261 Las Flores-Gerber CDP Tehama CA 1 1,193

262 Los Molinos Tehama CA 3 2,261

263 Proberta Tehama CA 1 744

264 Rawson Tehama CA 1 1,042

265 Red Bank Tehama CA 1 1,155

266 Red Bluff Tehama CA 16 17,545

267 Red Bluff (part) - Blunt Tehama CA 2 2,232

268 Richfield - El Camino Tehama CA 1 961

269 Rosewood - Cold Fork Tehama CA 2 1,149

270 Squaw Hill Tehama CA 1 2,028

271 Tehama Tehama CA 1 451

272 Vina Tehama CA 1 464

273 Big Bar - Del Loma Trinity CA 1 301

274 Burnt Ranch Trinity CA 1 287

275 Carrville - Trinity Center - Trinity Alps Trinity CA 2 812

276 Douglas City Trinity CA 2 997

277 Hayfork CDP Trinity CA 5 2,549

278 Helena - Junction City Trinity CA 1 675

279 Hyampom Trinity CA 1 301

280 Lewiston CDP Trinity CA 1 1,352

281 Ruth - Zenia - Kekawaka Trinity CA 4 840

282 Salyer - Trinity Village - Denny Trinity CA 2 965

283 Weaverville CDP Trinity CA 4 3,695
29

Table 2—Block group aggregations in the Northwest Forest Plan region (continued)

Identifying Number Population,

number Block group aggregation namea County State of BGsb 1990

284 Wildwood - Forest Glen - Peanut Trinity CA 3 289

285 Capay - Guinda - Rumsey Yolo CA 2 947

286 Clarksburg - Arcade - Central Yolo CA 1 653

287 Davis Yolo CA 17 49,489

288 Davis (part) - El Macero Yolo CA 2 2,604

289 Davis (part) - Merritt - Webster Yolo CA 1 1,400

290 El Rio Villa Yolo CA 1 898

291 Esparto CDP Yolo CA 3 1,836

292 Greendale - Sorroca - Valdez Yolo CA 1 952

293 Hershey - Dunnigan Yolo CA 1 774

294 Jacobs Corner Yolo CA 1 1,554

295 Knights Landing Yolo CA 1 567

296 Madison - Citrona - Arroz Yolo CA 1 755

297 Plainfield Yolo CA 1 808

298 West Sacramento (part) - Beatrice - Kiesel Yolo CA 1 391

299 Winters Yolo CA 4 5,495

300 Woodland Yolo CA 23 40,844

301 Woodland city (part) - Sugarfield - Conaway Yolo CA 1 550

302 Yolo - Dufour Yolo CA 2 1,404

303 Zamora - Tyndall Landing Yolo CA 2 432

304 Adair Village Benton OR 1 1,502

305 Alsea Benton OR 3 2,060

306 Corvallis Benton OR 35 48,328

307 Corvallis (part) - Lewisburg Benton OR 3 3,053

308 Dawson - Glenbrook - Alpine - Bellfountain Benton OR 1 744

309 Fern Road Benton OR 1 1,243

310 Kings Valley - Blodgett - Harris Benton OR 1 1,083

311 Monroe Benton OR 2 1,954

312 North Albany CDP Benton OR 4 4,394

313 Palestine Benton OR 1 1,369

314 Philomath Benton OR 3 3,108

315 Wren Benton OR 2 1,973

316 Alder Creek - Cherryville Clackamas OR 2 2,633

317 Anderson Clackamas OR 1 1,505

318 Barlow Clackamas OR 2 625

319 Boring Clackamas OR 1 1,483

320 Bull Run - Marmot Clackamas OR 1 947

321 Canby Clackamas OR 8 9,614

322 Canby (part) - O’Neil Corners Clackamas OR 1 1,453

323 Carus Clackamas OR 2 3,642

324 Carver Clackamas OR 1 1,342

325 Cedardale - Dickey Prairie - Fernwood Clackamas OR 1 1,632

326 Cedarhurst Park - Logan Clackamas OR 1 1,288

327 Central Point Clackamas OR 1 429

328 Colton - Clarkes - Timber Grove Clackamas OR 1 1,617

329 Cottrell - Kelso Clackamas OR 2 3,335

330 Currinsville Clackamas OR 1 773

331 Damascus - Wetzels Corner - Wilson Corner Clackamas OR 5 6,986

332 Dodge - Springwater Clackamas OR 1 1,166

333 Douglass Ridge Clackamas OR 1 1,821

334 Eagle Creek - Barton Clackamas OR 2 2,457
30

Table 2—Block group aggregations in the Northwest Forest Plan region (continued)

Identifying Number Population,

number Block group aggregation namea County State of BGsb 1990

335 Estacada Clackamas OR 3 3,091

336 Faraday Clackamas OR 1 750

337 Firwood - Dover Clackamas OR 1 1,299

338 Fishers Corner - Beaver Creek - Echo Dell Clackamas OR 1 2,960

339 Garfield - Tracy - Whitewater Clackamas OR 1 1,248

340 George - Bissell Clackamas OR 1 505

341 Government Camp - Timberline Lodge Clackamas OR 1 537

342 Highland - Upper Highland - Viola Clackamas OR 3 3,480

343 Hillsview Clackamas OR 1 1,746

344 Hoodview - Mulloy Clackamas OR 1 503

345 Kokel Corner Clackamas OR 1 824

346 Ladd Hill Clackamas OR 1 1,052

347 Lone Elder - Macksburg - Dryland Clackamas OR 2 2,160

348 Marquam - Wilhoit Clackamas OR 1 1,693

349 Molalla Clackamas OR 4 5,321

350 Mount Hood Village CDP Clackamas OR 3 2,445

351 Mulino Clackamas OR 2 1,865

352 Old Colton - Elwood Clackamas OR 1 1,337

353 Paradise Park Clackamas OR 1 863

354 Redland - Fishers Mill Clackamas OR 2 4,219

355 Rural Dell - Yoder - Ninety-One - Needy Clackamas OR 2 3,831

356 Sandy Clackamas OR 6 6,553

357 Stafford Clackamas OR 2 1,938

358 Union Mills Clackamas OR 1 1,643

359 Whiskey Hill Clackamas OR 1 1,090

360 Wilsonville Clackamas OR 5 8,659

361 Astoria Clatsop OR 9 10,671

362 Brownsmead - Westport - (Tenasilahe Island

and others) Clatsop OR 1 976

363 Cannon Beach Clatsop OR 5 1,230

364 Fern Hill Clatsop OR 1 1,436

365 Gearhart Clatsop OR 3 1,595

366 Hammond - Warrenton (part) Clatsop OR 1 682

367 Jewell - Elsie - Hamlet Clatsop OR 2 927

368 Knappa - Knappa Junction - (Karlson Island) Clatsop OR 1 1,050

369 Necanicum Clatsop OR 1 506

370 Olney Clatsop OR 1 955

371 Seaside Clatsop OR 10 5,728

372 Svensen - (Russian Island) Clatsop OR 1 674

373 Warrenton Clatsop OR 3 2,432

374 Warrenton (part) -Miles Crossing Clatsop OR 3 2,467

375 Glenwood - Sunset Beach - Westlake Clatsop -

Clackamas OR 2 1,964

376 Beaver Homes - Goble Columbia OR 1 825

377 Clatskanie Columbia OR 1 1,159

378 Clatskanie (part) - Swedetown - Apiary Columbia OR 1 1,226

379 Columbia City - St. Helens Columbia OR 8 9,329

380 Deer Island - Reuben Columbia OR 1 1,116

381 Delena - Downing Columbia OR 1 1,067

382 Inglis - Quincy Columbia OR 1 939

383 Kerry - Marshland Columbia OR 1 1,007
31

Table 2—Block group aggregations in the Northwest Forest Plan region (continued)

Identifying Number Population,

number Block group aggregation namea County State of BGsb 1990

384 Locoda - Woodson - (Wallace Island) Columbia OR 1 559

385 Prescott - Ranier (part) Columbia OR 2 1,723

386 Rainier city Columbia OR 2 1,767

387 Rainier city (part) - Alston - Mayger Columbia OR 1 829

388 Scappoose - (N. Sauvie Island) Columbia OR 6 6,161

389 Spatenberg Columbia OR 2 2,205

390 St. Helens city (part) - McNutty Columbia OR 2 1,805

391 Trenholm - Waterview- Yankton Columbia OR 2 1,755

392 Vernonia Columbia OR 3 3,136

393 Warren Columbia OR 1 949

394 Allegany - Dellwood - Fairview Coos OR 1 1,086

395 Bandon Coos OR 3 2,577

396 Bandon (part) - Twomile - Fourmile Coos OR 2 1,560

397 Barview CDP - Crown Point Coos OR 1 1,572

398 Bullards - Randolph Coos OR 1 594

399 Cheney - Bridge - Remote Coos OR 1 839

400 Coos Bay city - Bunker Hill CDP Coos OR 20 18,250

401 Coos Head Naval Facility - Charleston Coos OR 1 789

402 Cooston Coos OR 1 715

403 Coquille Coos OR 5 4,958

404 Coquille (part) - Leneve - Coaledo Coos OR 1 995

405 Cordes - Hauser - (Saunders Lake) Coos OR 1 1,603

406 Glasgow Coos OR 1 1,053

407 Lakeside Coos OR 2 1,414

408 Lakeside (part) - Templeton Coos OR 1 377

409 Libby - Southport Coos OR 1 1,263

410 McCormac Coos OR 1 1,113

411 Myrtle Point Coos OR 2 1,949

412 Myrtle Point (part) - Arago Coos OR 1 873

413 Myrtle Point (part) - Estabrook - Warner Coos OR 1 880

414 Myrtle Point (part) - Norway - Sitkum -

McKinley Coos OR 1 842

415 North Bend Coos OR 10 9,636

416 Overland - Delmar - Green Acres Coos OR 1 1,200

417 Powers Coos OR 1 966

418 Prosper - Parkersburg - Winterville Coos OR 2 807

419 Riverton Coos OR 1 627

420 Shorewood Coos OR 1 1,033

421 Sumner Coos OR 1 702

422 Lakin Place - (Ochoco Reservoir) Crook OR 2 1,515

423 Powell Butte - O’Neill - Forest Crossing Crook OR 1 1,290

424 Prineville Crook OR 12 10,946

425 Roberts - Post- Paulina - Suplee Crook OR 2 360

426 Agness - Illahe - Marial Curry OR 1 122

427 Brookings Curry OR 6 7,086

428 Gold Beach Curry OR 3 2,583

429 Harbor CDP Curry OR 5 4,426

430 Ophir Curry OR 2 217

431 Pistol River - Carpenterville Curry OR 3 669

432 Port Orford Curry OR 2 1,800

433 Sixes - Denmark - Langlois Curry OR 2 959
32

Table 2—Block group aggregations in the Northwest Forest Plan region (continued)

Identifying Number Population,

number Block group aggregation namea County State of BGsb 1990

434 Wedderburn - Nesika Beach Curry OR 1 1,465

435 Alfalfa Deschutes OR 1 959

436 Bend city Deschutes OR 39 36,756

437 Cloverdale - Plainview Deschutes OR 3 2,386

438 Deschutes - Deschutes Junction Deschutes OR 1 2,056

439 Deschutes River Woods Deschutes OR 3 3,205

440 Elk Lake - Lava Lake Resort Deschutes OR 2 645

441 Hampton - Brothers - Millican - Paulina Lake Deschutes OR 4 1,150

442 La Pine Deschutes OR 9 4,779

443 Prinveville Junction Deschutes OR 1 771

444 Redmond Deschutes OR 13 11,450

445 Sisters Deschutes OR 5 2,340

446 Sunriver Deschutes OR 2 1,121

447 Terrebonne Deschutes OR 3 3,010

448 Three Rivers CDP Deschutes OR 5 1,689

449 Tumalo Deschutes OR 2 2,641

450 Anlauf - Curtin Douglas OR 1 1,081

451 Ash Douglas OR 1 406

452 Azalea - Galesville - Fortune Branch Douglas OR 1 684

453 Camas Valley - Reston - Olalla - Tenmile Douglas OR 3 2,529

454 Canyonville Douglas OR 1 1,410

455 Cleveland - Elgarose - Callahan Douglas OR 1 1,553

456 Days Creek Douglas OR 1 959

457 Dillard - Carnes Douglas OR 1 532

458 Dixonville Douglas OR 1 1,013

459 Dole Douglas OR 1 1,009

460 Drain Douglas OR 1 1,098

461 Drain (part) - Skelley Douglas OR 1 519

462 Elkton Douglas OR 2 646

463 Gardiner - Kroll - Sulphur Springs Douglas OR 6 592

464 Glendale city - Fernvale Douglas OR 2 1,421

465 Glide - Idlewild Douglas OR 3 2,539

466 Green CDP Douglas OR 3 5,076

467 Hawthorne - Nonpareil Douglas OR 1 702

468 Kellogg - Tyee Douglas OR 1 764

469 Lookinglass Douglas OR 2 2,166

470 Melrose Douglas OR 1 1,110

471 Milo - Tiller - Drew Douglas OR 1 739

472 Myrtle Creek Douglas OR 5 4,562

473 Oaks - Glengary - Round Prairie Douglas OR 1 647

474 Peel - Steamboat Douglas OR 1 1,083

475 Quines Creek Douglas OR 1 617

476 Reedsport Douglas OR 5 3,918

477 Reedsport (part) - Winchester Bay Douglas OR 1 1,736

478 Rice Hill - Isadore Douglas OR 1 686

479 Riddle Douglas OR 2 2,140

480 Roseburg - Roseburg North CDP Douglas OR 26 24,668

481 Roseburg (part) - Riversdale Douglas OR 2 3,951

482 Scottsburg Douglas OR 1 427

483 Stephens - Akin Douglas OR 1 675

484 Surprise Valley Douglas OR 1 1,120
33

Table 2—Block group aggregations in the Northwest Forest Plan region (continued)

Identifying Number Population,

number Block group aggregation namea County State of BGsb 1990

485 Sutherlin - Oakland Douglas OR 6 8,838

486 Tokatee Falls - Clearwater - Diamond Lake Douglas OR 1 263

487 Tri City CDP Douglas OR 3 3,880

488 Umpqua - Millwood - Green Peak Douglas OR 1 416

489 Wilbur - Redbell Douglas OR 2 802

490 Winston Douglas OR 3 4,090

491 Yoncalla Douglas OR 1 1,004

492 Yoncalla (part) - Elkhead Douglas OR 1 578

493 Cascade Locks Hood River OR 2 948

494 Dee - Winans - Summit Hood River OR 2 1,487

495 Hood River Hood River OR 9 6,126

496 Mount Hood - Parkdale - Trout Creek Hood River OR 3 2,265

497 Oak Grove - Rockford Hood River OR 2 2,229

498 Odell - Lenz Hood River OR 1 1,057

499 Pine Grove Hood River OR 3 1,912

500 Windmaster Corner Hood River OR 2 879

501 Applegate Jackson OR 1 1,212

502 Ashland Jackson OR 18 18,384

503 Buncom Jackson OR 1 649

504 Butte Falls Jackson OR 1 454

505 Central Point city Jackson OR 7 10,964

506 Colestin Jackson OR 2 620

507 Eagle Point Jackson OR 2 5,008

508 Foots Creek Jackson OR 3 3,704

509 Gold Hill Jackson OR 2 3,130

510 Jacksonville Jackson OR 4 5,704

511 Lakecreek - Brownsboro Jackson OR 1 811

512 LIncoln - Climax - Steinman Jackson OR 2 1,453

513 Medford Jackson OR 25 49,990

514 Medford (part) - White City CDP (part) Jackson OR 2 2,046

515 Phoenix Jackson OR 4 10,135

516 Prospect - Cascade Gorge - McLeod Jackson OR 1 1,080

517 Rogue River Jackson OR 3 2,984

518 Ruch - McKee Bridge - (Applegate Lake) Jackson OR 2 1,688

519 Shady Cove Jackson OR 1 1,552

520 Shady Cove (part) - Rogue Elk Jackson OR 1 1,314

521 Spikenard - Trail Jackson OR 1 472

522 Starvation Heights Jackson OR 1 944

523 Table Rock - Beagle Jackson OR 4 3,260

524 Talent Jackson OR 3 5,185

525 Tolo Jackson OR 4 3,917

526 Voorhies Jackson OR 2 1,497

527 White City CDP Jackson OR 1 6,065

528 Wimer - Bybee Springs Jackson OR 2 2,167

529 Camp Sherman Jefferson OR 1 251

530 Culver city - Opal Springs - Opal City Jefferson OR 1 1,368

531 Gateway - Grizzly - Donnybrook Jefferson OR 1 307

532 Grandview Jefferson OR 2 938

533 Madras Jefferson OR 6 5,125

534 Madras Station Jefferson OR 2 1,281

535 Mecca - Paxton Jefferson OR 1 742
34

Table 2—Block group aggregations in the Northwest Forest Plan region (continued)

Identifying Number Population,

number Block group aggregation namea County State of BGsb 1990

536 Metolius Jefferson OR 2 1,274

537 Bridgeview - Holland Josephine OR 1 918

538 Cave Junction Josephine OR 4 2,915

539 Cave Junction (part) - Dryden Josephine OR 1 1,058

540 Galice - Rand Josephine OR 2 902

541 Grants Pass city - Harbeck-Fruitdale CDP -

Redwood CDP Josephine OR 28 34,144

542 Jerome Prairie Josephine OR 3 2,930

543 Merlin Josephine OR 3 3,099

544 Murphy Josephine OR 2 2,731

545 New Hope Josephine OR 1 1,697

546 O’Brien Josephine OR 1 610

547 Pleasant Valley - Three Pines - Hugo Josephine OR 2 2,377

548 Provolt Josephine OR 1 1,093

549 Selma Josephine OR 2 1,430

550 Sunny Valley - Placer - Golden - Speaker Josephine OR 1 686

551 Takilma Josephine OR 1 716

552 Wilderville - Wonder Josephine OR 2 2,052

553 Williams Josephine OR 2 1,626

554 Winona Josephine OR 2 1,242

555 Wolf Creek - Leland Josephine OR 1 423

556 Algoma - Shady Pine Klamath OR 1 740

557 Beatty - Sprague River Klamath OR 2 988

558 Bonanza (east) - Bly - Langell Valley Klamath OR 2 1,521

559 Bonanza (west) - Hildebrand - Yonna Klamath OR 1 1,159

560 Chemult - Beaver Marsh - Diamond Lake

Junction Klamath OR 1 330

561 Chiloquin Klamath OR 2 2,351

562 Crescent - Rosedale Klamath OR 1 574

563 Crescent Lake Junction - Mowich Klamath OR 1 339

564 Falcon Heights Klamath OR 1 384

565 Fort Klamath - Sand Creek - Yamsay Klamath OR 2 407

566 Gilchrist - Little River Klamath OR 1 1,179

567 Keno - Worden Klamath OR 3 2,196

568 Klamath Falls - Altamont CDP Klamath OR 49 39,750

569 Klamath Falls-Altamont (part) - Pine Grove -

Olene Klamath OR 1 1,391

570 Malin Klamath OR 1 1,155

571 Merrill Klamath OR 3 2,306

572 Midland Klamath OR 1 573

573 Rocky Point - Lake of the Woods Klamath OR 2 359

574 Ada - Siltcoos - Canary Lane OR 1 377

575 Alvadore Lane OR 2 2,246

576 Bear Creek - Cheshire - Franklin - Goldson Lane OR 2 2,127

577 Blue River - Finn Rock - Nimrod Lane OR 1 911

578 Cloverdale Lane OR 1 989

579 Coburg Lane OR 2 2,050

580 Cottage Grove Lane OR 11 10,818

581 Creswell Lane OR 7 6,924

582 Crow Lane OR 1 943

583 Deadwood - Triangle Lake - Blachly Lane OR 1 979
35

Table 2—Block group aggregations in the Northwest Forest Plan region (continued)

Identifying Number Population,

number Block group aggregation namea County State of BGsb 1990

584 Dexter Lane OR 1 1,123

585 Dorena - Culp Creek - Disston Lane OR 1 955

586 Dunes City Lane OR 2 1,061

587 Eugene (part) - (Bailey Hill) - (Spencer Creek) Lane OR 3 3,759

588 Fall Creek - Unity Lane OR 1 964

589 Firo - Swisshome - (Deadwood Creek West) Lane OR 1 600

590 Florence Lane OR 12 7,809

591 Gap Lane OR 2 1,618

592 Glenada - Westlake Lane OR 1 969

593 Goshen Lane OR 2 1,854

594 Horton Lane OR 1 1,039

595 Jasper - Trent Lane OR 1 976

596 Junction City Lane OR 8 6,145

597 Lancaster Lane OR 1 1,011

598 Leaburg - Deerhorn Lane OR 1 1,417

599 London - (Black Butte) Lane OR 1 521

600 Lorane Lane OR 1 803

601 Lowell Lane OR 1 776

602 Lowell (part) - Minnow - Crale - Winberry Lane OR 1 731

603 Mabel - Wendling Lane OR 1 733

604 Mapleton - Tiernan - Nekoma Lane OR 1 894

605 Marcola Lane OR 2 1,644

606 Maywood Lane OR 1 632

607 Mohawk Lane OR 1 1,528

608 Oakridge Lane OR 4 3,424

609 Pleasant Hill, OR Lane OR 3 2,507

610 Pryor - Kitson Hot Springs - Frazier Lane OR 1 707

611 Rainbow - McKenzie Bridge - Belknap Springs -

Foley Springs Lane OR 1 642

612 Richardson - Alma - Wolf Creek Lane OR 1 629

613 Sailor - Elrus - Long Tom - Vaughn Lane OR 1 1,032

614 Searose Beach - Minerva Lane OR 1 439

615 Veneta Lane OR 3 3,138

616 Veneta (part) - Elmira Lane OR 3 3,762

617 Vida Lane OR 1 970

618 Walker - Saginaw - Royal Lane OR 1 1,652

619 Walterville Lane OR 2 1,667

620 Walton - Noti - Penn Lane OR 1 966

621 Westfir Lane OR 1 447

622 Depoe Bay Lincoln OR 2 919

623 Elk City - Burnt Woods - Harlan - Siletz

Indian Reservation (part) Lincoln OR 1 1,016

624 Fruitvale Lincoln OR 1 485

625 Lincoln City Lincoln OR 17 7,620

626 Lincoln Beach CDP Lincoln OR 5 2,171

627 Newport Lincoln OR 15 10,269

628 Otter Rock - Beverly Beach Lincoln OR 1 450

629 Rose Lodge CDP Lincoln OR 3 2,156

630 San Marine Lincoln OR 1 305

631 Seal Rock - Ona Lincoln OR 1 391

632 Siletz - Siletz Indian Reservation Lincoln OR 2 2,371
36

Table 2—Block group aggregations in the Northwest Forest Plan region (continued)

Identifying Number Population,

number Block group aggregation namea County State of BGsb 1990

633 Tidewater Lincoln OR 1 423

634 Toledo Lincoln OR 5 4,879

635 Waldport Lincoln OR 6 4,147

636 Yachats Lincoln OR 2 1,287

637 Albany Linn OR 27 32,288

638 Berlin - (McDowell Creek) Linn OR 1 654

639 Brewster - Griggs Linn OR 1 1,306

640 Brownsville Linn OR 2 2,565

641 Cartney - Miller - Rowland Linn OR 1 1,150

642 Cascadia - Santiam Junction - Marion

Forks (part) Linn OR 2 333

643 Crabtree Linn OR 4 1,244

644 Crawfordsville - Union Point Linn OR 1 1,203

645 Fawn - Jordan - Fox Valley Linn OR 1 1,130

646 Greenville - Narrows - Santiam Terrace Linn OR 1 1,268

647 Halsey Linn OR 2 1,773

648 Harrisburg Linn OR 2 2,048

649 Holley - Calapooia - Dollar Linn OR 1 925

650 Idanha (part) - Gates (part) Linn OR 1 726

651 LaComb - Marion Forks (part) Linn OR 2 1,855

652 Lebanon city - South Lebanon CDP Linn OR 17 16,557

653 Lyons Linn OR 1 1,069

654 Mill City Linn OR 2 1,468

655 Millersburg Linn OR 3 2,017

656 Orleans, OR Linn OR 1 739

657 Pirtle - Riverside Linn OR 1 835

658 Scio Linn OR 2 1,895

659 Shelburn - Kingston Linn OR 1 1,598

660 Sodaville Linn OR 1 1,245

661 Spicer - Tallman - Irvinville Linn OR 1 941

662 Sweet Home Linn OR 10 9,169

663 Tangent Linn OR 2 1,889

664 Waterloo Linn OR 1 1,337

665 Aumsville Marion OR 1 1,741

666 Aurora Marion OR 2 2,865

667 Broadacres Marion OR 1 707

668 Brooks - Waconda - Lakebrook Marion OR 2 2,468

669 Champoeg - Fairfield Marion OR 1 920

670 Detroit Marion OR 1 383

671 Donald city Marion OR 1 1,032

672 Fargo - Butteville - Curtis Marion OR 1 1,208

673 Fruitland - Geer Marion OR 1 907

674 Gates Marion OR 1 645

675 Gervais Marion OR 1 1,205

676 Hazel Green - Labish Village Marion OR 1 2,395

677 Hubbard Marion OR 3 2,582

678 Idanha Marion OR 1 248

679 Jefferson Marion OR 3 3,047

680 Marion Marion OR 3 1,824

681 Mill City (part) - Mehama Marion OR 1 1,298

682 Mount Angel Marion OR 4 4,518
37

Table 2—Block group aggregations in the Northwest Forest Plan region (continued)

Identifying Number Population,

number Block group aggregation namea County State of BGsb 1990

683 Pratum - North Howell Marion OR 1 1,124

684 Salem (part) - Rosedale Marion OR 1 1,828

685 Scotts Mills Marion OR 1 1,279

686 Shaff - West Stayton - North Santiam Marion OR 2 1,657

687 Shaw - Macleay Marion OR 1 1,203

688 Silver Falls City - Drake Crossing Marion OR 2 2,680

689 Silverton Marion OR 6 7,778

690 St. Paul Marion OR 1 752

691 Stayton Marion OR 9 6,694

692 Sublimity Marion OR 2 2,904

693 Sunnyside - Orville Marion OR 1 1,179

694 Talbot - Sidney Marion OR 3 1,048

695 Turner Marion OR 3 5,711

696 Woodburn Marion OR 12 15,721

697 Woodburn (part) - Saint Louis Marion OR 1 860

698 Holbrook - (Sauvie Island) Multnomah OR 2 2,097

699 Latourell - Warrendale - Bonneville Multnomah OR 2 770

700 Portland-Vancouver (part) - Burlington -

Folkenberg Multnomah OR 1 478

701 Portland-Vancouver (part) - Corbett -

Springdale Multnomah OR 3 2,996

702 Portland-Vancouver (part) - Orient -

Pleasant Home Multnomah OR 3 4,242

703 Ballston - McCoy - Walkers Corner Polk OR 1 1,313

704 Boyer - Grand Ronde - Gold Creek Polk OR 1 1,382

705 Dallas Polk OR 6 7,518

706 Dallas (part) - Ellendale Polk OR 2 4,033

707 Dallas (part) - Rickreal - Orr Corner Polk OR 1 1,389

708 Falls City Polk OR 1 1,398

709 Fern Corner - Bridgeport - Airlie Polk OR 2 1,642

710 Independence - Monmouth Polk OR 8 11,308

711 Oak Grove - Bethel - Bethel Heights Polk OR 1 939

712 Parker - Buena Vista - Hopville - Modeville Polk OR 1 926

713 Salem-Keizer (part) - Eagle Crest Corner -

Zena - Lincoln Polk OR 1 3,949

714 Valsetz Polk OR 1 347

715 Willamina (part) - Buell - Fort Hill Polk OR 1 932

716 Grass Valley - Moro Sherman OR 1 873

717 Rufus Sherman OR 1 459

718 Wasco Sherman OR 1 586

719 Bay City Tillamook OR 4 1,927

720 Beaver - Hemlock - Sand Lake Tillamook OR 1 902

721 Cloverdale - Hebo - Dolph - Winema Beach Tillamook OR 2 963

722 Fairview Tillamook OR 2 1,316

723 Garibaldi Tillamook OR 3 1,082

724 Manzanita - Nehalem (part) Tillamook OR 3 1,383

725 Nehalem (part) - Salmonberry Tillamook OR 1 499

726 Neskowin Tillamook OR 1 311

727 Netarts - (Netarts Bay) Tillamook OR 3 1,378
38

Table 2—Block group aggregations in the Northwest Forest Plan region (continued)

Identifying Number Population,

number Block group aggregation namea County State of BGsb 1990

728 Oceanside - Cape Meares - Bayocean Tillamook OR 2 489

729 Pacific City - Woods Tillamook OR 3 816

730 Pleasant Valley - Blaine Tillamook OR 1 558

731 Rockaway Beach Tillamook OR 3 1,102

732 South Prairie Tillamook OR 1 1,018

733 Tierra del Mar Tillamook OR 2 487

734 Tillamook Tillamook OR 7 5,580

735 Tillamook city (part) - Jordan Creek Tillamook OR 1 830

736 Wheeler Tillamook OR 2 929

737 Antelope - Shaniko Wasco OR 1 217

738 Celilo - Petersburg- Boyd Wasco OR 1 381

739 Chenoweth CDP - Rowena Wasco OR 5 4,252

740 City of the Dalles Wasco OR 15 11,538

741 Dufur Wasco OR 2 1,192

742 Maupin Wasco OR 1 553

743 Mosier Wasco OR 1 676

744 Ryan Corner Wasco OR 2 859

745 Tygh Valley - Pine Grove - Dant Wasco OR 2 1,262

746 Warm Springs CDP - Warm Springs Indian Wasco -

Reservation Jefferson OR 3 3,143

747 Banks Washington OR 1 1,834

748 Chehalem - Middleton Washington OR 2 1,719

749 Cherry Grove - (South Henry Hagg Lake) Washington OR 1 745

750 Christie - Greenville - Starkey Corner Washington OR 3 2,645

751 Cochran - Glenwood - Timber Washington OR 1 760

752 Cornelius - Forest Grove Washington OR 9 23,585

753 Farmington - Hazeldale - Jacktown Washington OR 3 3,877

754 Gales Creek - Kansas City - Thatcher Washington OR 2 1,580

755 Gaston Washington OR 2 3,466

756 Laurel Washington OR 1 868

757 Manning - Scofield - Tophill Washington OR 1 1,357

758 Meacham Corner Washington OR 1 618

759 Midway - Scholls Washington OR 1 1,241

760 Mountaindale Washington OR 1 894

761 North Plains Washington OR 2 3,428

762 Sherwood Washington OR 2 3,434

763 Stimson Mill Washington OR 1 992

764 Wilsonville (part) - Tonquin Washington OR 1 823

765 Amity Yamhill OR 1 1,193

766 Bellevue Yamhill OR 1 1,247

767 Briedwell - Winch Yamhill OR 1 520

768 Carlton Yamhill OR 1 1,632

769 Carlton (part) - Yamhill (part) Yamhill OR 1 977

770 Dayton Yamhill OR 1 1,850

771 Dewey - (Chehalem Mountain) Yamhill OR 1 1,609

772 Dundee Yamhill OR 1 2,195

773 Eola Crest - Hopewell - Yampo Yamhill OR 1 1,535

774 Fairdale - Pike Yamhill OR 1 754

775 Grand Ronde Agency - Midway Yamhill OR 2 957

776 Lafayette Yamhill OR 2 2,156

777 Lunnville - Cove Orchard - Dellwood - Wapato Yamhill OR 1 2,163
39

Table 2—Block group aggregations in the Northwest Forest Plan region (continued)

Identifying Number Population,

number Block group aggregation namea County State of BGsb 1990

778 McMinnville Yamhill OR 13 18,975

779 McMinnville (part) - Orchard View Yamhill OR 1 1,429

780 Newberg Yamhill OR 10 14,517

781 Pleasantdale Yamhill OR 1 678

782 Rex - (Parrett Mountain) Yamhill OR 1 1,850

783 Sheridan Yamhill OR 4 5,139

784 Sunnycrest Yamhill OR 1 1,181

785 Unionvale - Wheatland Yamhill OR 1 807

786 Willamina (part) Yamhill OR 1 1,209

787 Yamhill Yamhill OR 1 978

788 Hatton town Adams WA 1 515

789 Keystone - Palm Lake - Rockwell - Tokio Adams WA 1 333

790 Koren - Simensen - Bruce - Shano Adams WA 1 585

791 Lind town Adams WA 2 713

792 Moody - Marcellus - Paha Adams WA 1 467

793 Othello Adams WA 8 8,730

794 Ritzville Adams WA 3 1,773

795 Washtucna town Adams WA 1 487

796 Apricot Benton WA 2 2,187

797 Badger - Kiona Benton WA 1 1,727

798 Benton City Benton WA 4 4,148

799 Benton City (part) - Gibbon Benton WA 1 480

800 Finley CDP - Yellepit - Barian Benton WA 6 5,467

801 North Prosser - Whistran - Chaffee Benton WA 1 1,814

802 Prosser Benton WA 5 5,270

803 West Richland Benton WA 2 3,371

804 Whitcomb - Patterson - Plymouth Benton WA 1 539

805 Holden - Lucerne - Sunnybank - (Lake Chelan) Benton -

Chelan WA 2 401

806 Ardenvoir - Winesap Chelan WA 1 638

807 Cashmere Chelan WA 6 6,045

808 Chelan Chelan WA 6 4,161

809 Chelan (part) - Azwell Chelan WA 1 645

810 Coles Corner - Chiwaukum - Chumstick Chelan WA 1 761

811 Dryden Chelan WA 1 652

812 Entiat city Chelan WA 1 910

813 Greens Landing - Manson Chelan WA 3 2,173

814 Leavenworth Chelan WA 4 3,864

815 Malaga Chelan WA 1 1,031

816 Monitor Chelan WA 1 581

817 Peshastin Chelan WA 1 790

818 South Wenatchee CDP (part) - Wenatchee

Heights Chelan WA 1 1,562

819 Sunnyslope CDP - Wagnersville Chelan WA 1 1,220

820 Wenatchee - West Wenatchee CDP -

South Wenatchee CDP - Sunnyslope CDP

(part) Chelan WA 30 26,268

821 Winton - Nason Creek - Berne - Trinity Chelan WA 6 548

822 Agnew Clallam WA 1 1,128

823 Blyn Clallam WA 2 1,566

824 Carlsborg Clallam WA 4 3,906
40

Table 2—Block group aggregations in the Northwest Forest Plan region (continued)

Identifying Number Population,

number Block group aggregation namea County State of BGsb 1990

825 Crane Clallam WA 1 1,132

826 Dungeness Clallam WA 1 1,494

827 Elwha - Snug Harbor - Olympic Hot Springs -

(South Lake Crescent) Clallam WA 1 790

828 Forks Clallam WA 5 4,647

829 Jamestown Clallam WA 1 1,266

830 La Push - Mora Clallam WA 1 566

831 Neah Bay CDP - Makah Indian Reservation Clallam WA 2 1,238

832 Old Town Clallam WA 1 1,276

833 Ozette - Clallam Bay - Twin Clallam WA 2 1,662

834 Port Angeles city - Port Angeles East CDP Clallam WA 28 23,822

835 Quilayute - Shuwah - Sappho Clallam WA 3 1,699

836 R Corner - Little Oklahoma - King Hill Clallam WA 1 1,805

837 Sequim Clallam WA 8 6,390

838 Sequim city (part) - Port Williams - Washington

Harbor Clallam WA 1 360

839 Shadow - Coville - Fairholm - (North Lake

Crescent) Clallam WA 2 1,717

840 Alpine - Venersborg Clark WA 1 1,767

841 Battle Ground Clark WA 5 9,316

842 Blurock Landing - (Vancouver Lake) Clark WA 2 642

843 Brush Prairie CDP Clark WA 5 5,719

844 Camas Clark WA 15 12,259

845 Camp Bonneville Military Reservation Clark WA 1 1,308

846 Charter Oak Clark WA 1 2,054

847 Creswell Heights - Ireland Clark WA 1 1,851

848 Dole - Lucia Clark WA 1 1,139

849 Etna - Fargher Lake - Highland Clark WA 1 2,085

850 Good Hope Clark WA 2 3,099

851 Hockinson Clark WA 2 1,598

852 La Center Clark WA 2 3,830

853 Little Elkhorn Clark WA 1 1,890

854 Meadow Glade CDP Clark WA 1 2,122

855 Pioneer Clark WA 1 1,609

856 Portland-Vancouver UA (part) - Proebstal Clark WA 1 1,553

857 Portland-Vancouver UA (part) - Salmon Creek

(part) - Knapp Clark WA 1 4,916

858 Ridgefield Clark WA 3 3,647

859 Sara Clark WA 1 1,481

860 Washougal Clark WA 7 7,651

861 Yacolt Clark WA 3 4,630

862 Arial Cowlitz WA 1 1,135

863 Bunker Hill - Stella Cowlitz WA 1 471

864 Carrolls - Rose Valley - Vision Acres Cowlitz WA 3 2,476

865 Castle Rock Cowlitz WA 4 3,407

866 Coal Creek - Longview city (part) Cowlitz WA 1 1,352

867 Cougar - Woodland Park - Yale Cowlitz WA 1 618

868 Eufaula - Eufaula Heights - Longview (part) Cowlitz WA 1 1,179

869 Headquarters Cowlitz WA 1 709

870 Kalama Cowlitz WA 4 3,312

871 Kelso Cowlitz WA 19 15,055
41

Table 2—Block group aggregations in the Northwest Forest Plan region (continued)

Identifying Number Population,

number Block group aggregation namea County State of BGsb 1990

872 Kid Valley - Harrington Place -

Pigeon Springs- Toutle Cowlitz WA 2 1,317

873 Longview city - West Longview CDP -

LongviewHeights CDP -

West Side Highway CDP Cowlitz WA 50 42,094

874 Oak Point Cowlitz WA 1 344

875 Olequa Cowlitz WA 1 1,387

876 Pleasant Hill Cowlitz WA 1 588

877 Ryderwood Cowlitz WA 1 308

878 Sandy Bend Cowlitz WA 2 1,305

879 Silver Lake Cowlitz WA 2 1,363

880 Woodland city Cowlitz WA 5 3,699

881 Baird - McCarteney - Sims Corner Douglas WA 1 159

882 Bridgeport Douglas WA 2 1,516

883 Bridgeport town (part) - Brandts Landing -

Dyer - Beebe Douglas WA 1 523

884 Downing - Rocky Butte Douglas WA 1 787

885 East Wenatcheeá- East Wenatchee Bench Douglas WA 18 17,468

886 Leahy - Niles Corner - Osborne Corner Douglas WA 1 361

887 Mansfield Douglas WA 1 442

888 Orondo Douglas WA 1 767

889 Palisades - Appledale - Bonspur - Voltage Douglas WA 1 349

890 Rock Island Douglas WA 2 1,744

891 Waterville Douglas WA 3 2,089

892 Burr - Redd - Sagemoor Franklin WA 1 653

893 Glade - Eltopia Franklin WA 1 675

894 Kahlotus Franklin WA 1 381

895 Mathews Corner Franklin WA 1 2,012

896 Mesa (part) - Basin City - Edwards Franklin WA 2 2,586

897 Mesa (part) - Connell Franklin WA 3 2,556

898 Beverly - Schwana - Wanapum Village Grant WA 1 704

899 Coulee City - Hartline Grant WA 2 1,292

900 Ephrata Grant WA 6 5,728

901 George Grant WA 1 1,226

902 Gloyd - Mitchell Grant WA 1 626

903 Grand Coulee - Electric City Grant WA 3 2,252

904 Lakeview Park Grant WA 1 1,263

905 Mae Grant WA 1 1,219

906 Mattawa Grant WA 1 2,323

907 Moses Lake - Moses Lake North CDP -

Cascade Valley CDP Grant WA 17 21,581

908 Moses Lake city (part) - McDonald - Sieler Grant WA 1 805

909 Naylor Grant WA 1 1,346

910 Quincy Grant WA 3 3,894

911 Quincy city (part) - Trinidad - Crater Grant WA 1 1,217

912 Royal City Grant WA 2 3,074

913 Soap Lake Grant WA 3 1,579

914 Warden Grant WA 1 1,669

915 Warden town (part) - Ritell - Tiflis - Barham Grant WA 1 1,009

916 Wilson Creek - Krupp (aka Marlin) Grant WA 1 813

917 Winchester Grant WA 1 1,138
42

Table 2—Block group aggregations in the Northwest Forest Plan region (continued)

Identifying Number Population,

number Block group aggregation namea County State of BGsb 1990

918 Aberdeen Grays Harbor WA 20 17,004

919 Aberdeen - Hoquiam Grays Harbor WA 1 925

920 Aloha - Ocean Grove - Iron Springs - Carlisle Grays Harbor WA 1 299

921 Central Park CDP Grays Harbor WA 2 2,703

922 Cohassett - Ocosta - Grayland Grays Harbor WA 2 1,982

923 Copalis Beach Grays Harbor WA 1 419

924 Cosmopolis Grays Harbor WA 2 1,992

925 Cosmopolis (part) - Junction City Grays Harbor WA 1 263

926 Elma Grays Harbor WA 4 5,301

927 Elma (part) - Satsop Grays Harbor WA 1 663

928 Fuller - South Elma - Porter - Lankner Grays Harbor WA 1 1,339

929 Gray’s Harbor Grays Harbor WA 1 407

930 Hoquiam Grays Harbor WA 8 8,719

931 Humptulips - Newton - Tulips - Gray Gables Grays Harbor WA 1 1,293

932 McCleary Grays Harbor WA 1 1,042

933 McCleary (part) - Hillgrove - Sine Grays Harbor WA 1 729

934 McCleary (part) - Rayville - Garden City Grays Harbor WA 1 1,172

935 Moclips - Sunset Beach - Highland Heights -

Pacific Beach Grays Harbor WA 1 566

936 Montesano Grays Harbor WA 4 3,728

937 Montesano (part) - Aberdeen (part) -

Brady - Grisdale Grays Harbor WA 1 2,519

938 New London - Nisson - Greenwood - Wishkah Grays Harbor WA 1 1,550

939 Ocean City - Sampson - Copalis Crossing Grays Harbor WA 1 800

940 Ocean Shores Grays Harbor WA 3 2,280

941 Quinalt - Neilton - Weatherwax Grays Harbor WA 1 705

942 South Arbor - Markham Grays Harbor WA 1 303

943 South Montesano - Arctic - Vesta - Weikswood Grays Harbor WA 1 645

944 Westport Grays Harbor WA 3 1,842

945 Oakville city - Chehalis Village CDP -

Chehalis Indian Res (part) Grays Harbor -

 Thurston WA 2 1,721

946 Bretland - Indian Beach -

(South Camano Island) Island WA 5 2,322

947 Camano Island WA 1 980

948 Clinton CDP Island WA 5 4,742

949 Cornet Island WA 2 2,321

950 Coupeville - (Naval Air Station) Island WA 4 5,452

951 Freeland CDP Island WA 5 3,304

952 Freeland CDP (part) - Baby Island Heights -

Saratoga Island WA 2 1,406

953 Greenbank Island WA 1 424

954 Juniper Beach - Sunrise Point

(aka Lona Beach) - (Livingston Bay) Island WA 3 1,775

955 Keystone Island WA 2 744

956 Langley Island WA 1 928

957 Langley city (part) - Freeland CDP (part) -

Bayview Island WA 1 776

958 Madrona Beach Island WA 2 1,142

959 Oak Harbor city - Ault Field CDP Island WA 22 32,271

960 Sunlight Beach Island WA 1 498
43

Table 2—Block group aggregations in the Northwest Forest Plan region (continued)

Identifying Number Population,

number Block group aggregation namea County State of BGsb 1990

961 Utsalady - English Boom - Terrys Corner Island WA 2 1,110

962 Beaver Valley - Port Ludlow - Mats Mats -

Chimwaucan Jefferson WA 3 2,145

963 Brinnon Jefferson WA 1 346

964 Cape George Military Reservation Jefferson WA 1 1,285

965 Duckabush Jefferson WA 1 500

966 East Quilcene - Dabob - Camp Discovery -

Coyle Jefferson WA 1 392

967 Fort Flagler - Nordland - (Marrowstone Island) -

(Indian Island) Jefferson WA 1 740

968 Gardiner - Port Discovery - Uncas -

Discovery Junction Jefferson WA 1 512

969 Hadlock-Irondale CDP Jefferson WA 3 2,266

970 Hadlock-Irondale CDP (part) - Glen Cove -

Adelma Beach - Eaglemount Jefferson WA 1 1,914

971 Hoh Indian Reservation Jefferson WA 1 116

972 Leland Jefferson WA 1 748

973 Oil City - Hoh - Clearwater Jefferson WA 2 393

974 Port Townsend Jefferson WA 7 7,155

975 Quilcene Jefferson WA 1 478

976 Shine-Gri-La (aka Stine) Jefferson WA 2 962

977 Taholah CDP - Quinault Indian Reservation Jefferson -

Grays Harbor WA 4 1,542

978 (Maury Island) King WA 1 1,764

979 (Vashon Island) King WA 7 7,545

980 Bagley Junction - Edgewick - Denny Creek King WA 2 546

981 Bayne - Cumberland - (Green River) King WA 5 4,266

982 Black Diamond King WA 6 5,605

983 Carnation King WA 2 2,869

984 Duvall King WA 3 5,748

985 Ellisville - Ernies Grove King WA 1 911

986 Enumclaw King WA 10 11,018

987 Fall City CDP King WA 1 1,588

988 Fall City CDP (part) - Pleasant Hill King WA 1 860

989 Green River King WA 1 1,974

990 Hobart - Atkinson King WA 2 1,591

991 Issaquah city (part) - Fall City (part) King WA 1 1,602

992 Issaquah city (part) - High Point King WA 1 1,310

993 Maple Valley CDP King WA 6 5,967

994 Mirrormount CDP King WA 2 2,606

995 Newaukun King WA 2 2,967

996 North Bend - Snoqualmie King WA 10 11,909

997 Novelty - Stuart - Stillwater King WA 2 2,057

998 Selleck - Kangley - Kanasket - Landsburg -

Trude King WA 1 1,654

999 Skykomish King WA 1 561

1000 Spring Glen - Preston King WA 1 1,491

1001 Upper Preston - Kerriston King WA 1 406

1002 Wabash King WA 1 641

1003 Wilderness King WA 1 1,660
44

Table 2—Block group aggregations in the Northwest Forest Plan region (continued)

Identifying Number Population,

number Block group aggregation namea County State of BGsb 1990

1004 Bangor - Olympic View Kitsap WA 1 1,753

1005 Bangor Trident Base C CDP Kitsap WA 1 4,426

1006 Burley Kitsap WA 3 5,711

1007 Fort Ward - South Beach Kitsap WA 1 592

1008 Holly - Hintzville - Crosby - Hite Center Kitsap WA 1 1,472

1009 Indianola CDP - Port Madison Indian

Reservation Kitsap WA 2 1,733

1010 Kingston CDP Kitsap WA 5 3,495

1011 Lofall Kitsap WA 2 2,360

1012 Olalla Kitsap WA 2 3,110

1013 Port Gamble - Four Corners - Breidsblick Kitsap WA 1 1,025

1014 Port Gamble Indian Reservation Kitsap WA 1 555

1015 Poulsbo Kitsap WA 7 7,889

1016 Poulsbo city (part) - Vinland Kitsap WA 1 1,080

1017 Scanda - Pearson - Virginia Kitsap WA 2 3,277

1018 South Colby - Southworth - Banner - Fragaria Kitsap WA 2 5,569

1019 Streibel’s Corner Kitsap WA 1 1,353

1020 Suquamish CDP - Port Madison Indian

Reservation Kitsap WA 3 3,105

1021 Twin Spits - Hansville Kitsap WA 1 1,256

1022 Warrenville - Seabeck - Camp Wesley Harris

Naval Reservation Kitsap WA 3 4,461

1023 Wildcat Lake - Naval Depot Junction Kitsap WA 1 1,655

1024 Wildwood - Glenwood Kitsap WA 3 3,344

1025 Winslow city - (Bainbridge Island) Kitsap WA 11 15,254

1026 Cle Elum - South Cle Elum Kittitas WA 4 2,476

1027 Ellensburg Kittitas WA 18 17,587

1028 Horlick - Thorp Kittitas WA 1 733

1029 Kittitas city (part) - Regal Kittitas WA 1 800

1030 Kittitas city (part) - Renslow - Vantage Kittitas WA 3 1,124

1031 Levering - Yakima Firing Center Kittitas WA 3 417

1032 Martin - Easton - Lavender - Nelson Kittitas WA 1 582

1033 Roslyn Kittitas WA 4 1,888

1034 Roza - Umtanum Kittitas WA 1 389

1035 Thrall - East Kittitas - Beverly Junction - Hillside Kittitas WA 1 1,146

1036 Appleton - Pitt Klickitat WA 1 548

1037 Bickleton - Sundale - Roosevelt - McCredie Klickitat WA 1 505

1038 BZ Corner - Husum - Panakanic - Snowden Klickitat WA 1 763

1039 Centerville - Swale Klickitat WA 1 361

1040 Dallesport - Murdock - Smithville - Warwick Klickitat WA 1 1,001

1041 Glenwood - Yakima Indian Reservation Klickitat WA 1 517

1042 Goldendale Klickitat WA 4 3,659

1043 Klickitat Klickitat WA 1 722

1044 Lyle - Klickitat Springs Klickitat WA 1 665

1045 Maryhill - Towal - Goodnoe Hills - Pleasant

Valley Klickitat WA 1 965

1046 Trout Lake Klickitat WA 1 973

1047 Wahkiacus - Blockhouse - Firwood Klickitat WA 2 1,156

1048 White Salmon - Bingen Klickitat WA 5 4,378

1049 Wishram - Wishram Heights Klickitat WA 1 403

1050 Adna - Claquato - Littell Lewis WA 2 1,874
45

Table 2—Block group aggregations in the Northwest Forest Plan region (continued)

Identifying Number Population,

number Block group aggregation namea County State of BGsb 1990

1051 Alpha - Cinebar - Silver Creek Lewis WA 1 635

1052 Bunker - Ceres - Dryden Lewis WA 1 979

1053 Carlson - Mineral Lewis WA 1 625

1054 Centralia city - Fords Prairie CDP Lewis WA 19 17,695

1055 Chehalis Lewis WA 12 9,211

1056 Cispus - Glenoma Lewis WA 1 1,132

1057 Curtis Lewis WA 1 1,568

1058 Doty - Klaber - Boistfort - McCormick Lewis WA 1 890

1059 Evaline - Saint Urban Lewis WA 1 907

1060 Klaus - Marys Corner - Salkum Lewis WA 3 3,680

1061 Kopiah - Nulls Crossing Lewis WA 1 883

1062 Lacamas Lewis WA 1 1,686

1063 Morton Lewis WA 3 2,013

1064 Mossyrock Lewis WA 2 1,347

1065 Mossyrock city (part) - Bremer - Harmony Lewis WA 1 698

1066 Napavine Lewis WA 1 1,294

1067 Newaukum Lewis WA 1 1,246

1068 Onalaska - Phillips Lewis WA 1 968

1069 Packwood Lewis WA 3 1,351

1070 Pe Ell Lewis WA 1 779

1071 Randle - Silver Brook Lewis WA 2 1,806

1072 Toledo city Lewis WA 2 2,186

1073 Vader Lewis WA 2 2,020

1074 Winlock Lewis WA 2 1,885

1075 Agate - Graham Point Mason WA 4 2,214

1076 Allyn-Grapeview Mason WA 4 2,519

1077 Arcadia Mason WA 1 476

1078 Belfair Mason WA 2 1,968

1079 Dewatto Mason WA 2 418

1080 Forbes - Marmac - Stimson - (Kamilche Valley) Mason WA 1 749

1081 Forest Beach Mason WA 1 765

1082 Hartstene - Ballow - (Hartstene Is) -

(Squaxin Is) - (Hope Is) Mason WA 1 598

1083 Kamiliche - New Kamilche Mason WA 1 1,475

1084 Little Hoquiam - (Mason Lake) Mason WA 3 684

1085 Matlock - Dayton - Deckerville - Frisken Wye Mason WA 2 3,348

1086 Mohrweiss Mason WA 1 821

1087 Potlatch - Hoodsport - Eldon - Triton Mason WA 2 1,464

1088 Shelton Mason WA 16 14,115

1089 Skokomish CDP / Indian Reservation Mason WA 1 618

1090 Sun Beach Mason WA 2 2,748

1091 Sunset Beach Mason WA 1 827

1092 Tahuya Mason WA 2 628

1093 Union Mason WA 1 517

1094 Walkers Landing - Grant Mason WA 2 1,389

1095 Brewster Okanogan WA 2 2,175

1096 Brewster city (part) - Paradise Hill Okanogan WA 1 481

1097 Carlton - Methow Okanogan WA 1 310

1098 Cheesaw - Havillah - Bodie Okanogan WA 1 599

1099 Conconully Okanogan WA 1 263

1100 Cordell - Ellsford Okanogan WA 1 1,004
46

Table 2—Block group aggregations in the Northwest Forest Plan region (continued)

Identifying Number Population,

number Block group aggregation namea County State of BGsb 1990

1101 Coulee Dam - Elmer City - (Colville Indian

Reservation) Okanogan WA 2 1,290

1102 Loomis - Enterprise (part) Okanogan WA 1 922

1103 Malott Okanogan WA 1 519

1104 Nespelem town - Nespelem Community

CDP - (Colville Indian Reservation) Okanogan WA 2 1,401

1105 Nighthawk - Chopaka Okanogan WA 2 1,392

1106 Okanogan Okanogan WA 4 3,211

1107 Okanogan (part) - Chillowist - (Colville Indian

Reservation) Okanogan WA 1 723

1108 Old Toroda - Wauconda - Aeneas - Syrnarep Okanogan WA 1 707

1109 Olema - Wakefield Okanogan WA 1 506

1110 Omak Okanogan WA 6 5,265

1111 Omak city (part) - North Omak CDP - (Colville

Indian Res) Okanogan WA 2 2,068

1112 Oroville Okanogan WA 3 2,024

1113 Pateros Okanogan WA 1 711

1114 Riverside Okanogan WA 2 1,013

1115 Ruby - Brown Lake Okanogan WA 1 595

1116 Starr Okanogan WA 1 328

1117 Tonasket Okanogan WA 1 1,065

1118 Tonasket town (part) - Janis - Barker Okanogan WA 1 1,145

1119 Twisp Okanogan WA 4 2,445

1120 Winthrop Okanogan WA 4 1,188

1121 Bruceport - Bay Center - Nemah Junction Pacific WA 2 717

1122 Frankfort - Naselle - Nemah Pacific WA 1 1,092

1123 Hilda - Pluvia - Willapa Pacific WA 2 1,559

1124 Ilwaco Pacific WA 2 1,087

1125 Ilwaco city (part) - Chinook - Knappton Pacific WA 1 1,008

1126 Long Beach Pacific WA 5 2,329

1127 Loomis - Oceanside Pacific WA 3 1,240

1128 North Cove - Dexter by the Sea - Tokeland -

Heather Pacific WA 3 753

1129 Ocean Park CDP Pacific WA 8 2,522

1130 Raymond Pacific WA 5 3,638

1131 Raymond city (part) - Brooklyn Pacific WA 1 839

1132 Shoalwater Indian Reservation Pacific WA 1 129

1133 South Bend Pacific WA 3 1,969

1134 (McNeil Island: Federal Penitentiary) Pierce WA 1 1,188

1135 Buckley - Wilkenson (part) Pierce WA 6 7,708

1136 Croker Pierce WA 1 1,362

1137 DuPont city Pierce WA 1 625

1138 Eatonville Pierce WA 5 3,902

1139 Fort Lewis CDP / Fort Lewis Military

Reservation Pierce WA 2 22,224

1140 Fox Island CDP Pierce WA 2 1,984

1141 Graham - Thrift Pierce WA 3 3,988

1142 Herron - Home Pierce WA 1 1,275

1143 Jims Corner Pierce WA 1 811

1144 Johnsons Corner Pierce WA 4 5,759

1145 Kapowsin - Tanwax - Electron - Ohop Pierce WA 1 1,172
47

Table 2—Block group aggregations in the Northwest Forest Plan region (continued)

Identifying Number Population,

number Block group aggregation namea County State of BGsb 1990

1146 Longbranch - Lakebay Pierce WA 2 1,803

1147 Maplewood - Purdy Pierce WA 4 5,670

1148 McChord AFB CDP Pierce WA 1 4,543

1149 McKenna Pierce WA 4 4,894

1150 Minter - Wauna Pierce WA 2 3,419

1151 Orting Pierce WA 2 2,787

1152 Prairie Ridge CDP Pierce WA 7 9,767

1153 Roy Pierce WA 1 507

1154 South Prairie - Carbonado - Wilkeson (part) Pierce WA 1 1,573

1155 Sunrise Beach - Glencove Pierce WA 2 825

1156 Swede Hill Pierce WA 2 2,559

1157 Vaughn - Sunshine Beach Pierce WA 3 3,294

1158 Wilkeson (part) - Fairfax - Upper Fairfax -

Greenwater Pierce WA 2 685

1159 Yoman - Johnson Landing Pierce WA 1 562

1160 (Lopez Island) San Juan WA 3 1,518

1161 (Orcas Island) - (Waldron Island) San Juan WA 5 3,199

1162 (Shaw Island) - (Blakely Island) - (Decatur

Island) San Juan WA 1 269

1163 Friday Harbor - (San Juan Island) - (Stuart

Island) San Juan WA 8 5,049

1164 (Guemes Island) - (Sinclair Island) - (Cypress

Island) Skagit WA 1 557

1165 Alger Skagit WA 1 839

1166 Anacortes Skagit WA 13 12,989

1167 Bay View Skagit WA 1 848

1168 Belfast Skagit WA 1 944

1169 Blanchard - Edison - Allen - Samish Island Skagit WA 3 2,798

1170 Burlington Skagit WA 8 9,674

1171 Cedardale Skagit WA 1 859

1172 Clear Lake Skagit WA 2 1,477

1173 Concrete Skagit WA 3 1,355

1174 Fredonia - Rextown - Avon Skagit WA 1 1,644

1175 Hamilton Skagit WA 1 988

1176 La Conner Skagit WA 2 1,261

1177 Lyman Skagit WA 1 897

1178 Mansford - Van Horn Skagit WA 1 1,287

1179 McMurray Skagit WA 1 931

1180 Montborne - Big Lake - Baker Heights -

Day Creek Skagit WA 2 1,578

1181 Mount Vernon Skagit WA 19 21,069

1182 Sedro-Woolley Skagit WA 11 12,072

1183 Skagit City - Conway - Milltown Skagit WA 1 962

1184 Swinomish Indian Res - Shelter Bay CDP -

Snee Oosh CDP - Swinomish Village CDP Skagit WA 2 2,285

1185 Whitmarsh Junction - Gibraltar - Dewey Skagit WA 2 1,523

1186 Carson River Valley CDP Skamania WA 2 2,111

1187 Carson River Valley CDP - Stabler - (Wind

River) Skamania WA 1 409

1188 Hood - Underwood - Willard - Mill A Skamania WA 1 1,205

1189 North Bonneville Skamania WA 1 901
48

Table 2—Block group aggregations in the Northwest Forest Plan region (continued)

Identifying Number Population,

number Block group aggregation namea County State of BGsb 1990

1190 Northwoods Skamania WA 2 75

1191 Prindle Skamania WA 2 1,858

1192 Stevenson Skamania WA 2 1,730

1193 Arlington Snohomish WA 5 5,810

1194 Arlington Heights Snohomish WA 2 1,494

1195 Cicero - Oso - Halterman - Rowan Snohomish WA 1 1,072

1196 Darrington Snohomish WA 2 1,840

1197 Florence - Silvana Terrace Snohomish WA 1 1,294

1198 Forest Glade Snohomish WA 1 1,174

1199 Gold Bar Snohomish WA 1 2,063

1200 Granite Falls Snohomish WA 1 1,137

1201 Granite Falls town (part) - Hyland - Lochsloy Snohomish WA 4 4,676

1202 Granite Falls town (part) - Robe - Verlot -

Silverton Snohomish WA 1 1,233

1203 High Rock - (State Reformatory Farm No. 2) Snohomish WA 1 1,308

1204 Index Snohomish WA 1 599

1205 Jamieson Corner - (Three Lakes) Snohomish WA 2 1,376

1206 Jordan - Riverside Snohomish WA 2 2,721

1207 Lake Goodwin CDP Snohomish WA 2 2,539

1208 Lake Stevens city - West Lake Stevens CDP Snohomish WA 13 17,761

1209 Machias Snohomish WA 2 2,416

1210 Maltby - Turner Corner - Clearview - Cathcart Snohomish WA 7 10,436

1211 McKees Beach Snohomish WA 1 1,133

1212 Monroe city Snohomish WA 12 15,219

1213 Pilchuck - Bryant Snohomish WA 3 3,670

1214 Smokey Point CDP Snohomish WA 4 5,120

1215 Snohomish Snohomish WA 11 14,560

1216 Stanwood Snohomish WA 4 5,434

1217 Stanwood city (part) - Norman - Silvana Snohomish WA 1 1,044

1218 Stimson Crossing CDP - Tulalip Indian Res -

Military Res Snohomish WA 2 1,362

1219 Sultan town (part) Snohomish WA 4 3,665

1220 Sultan town (part) - Startup Snohomish WA 1 1,286

1221 Trafton Snohomish WA 1 1,249

1222 Tulalip - Tulalip Indian Reservation Snohomish WA 7 5,741

1223 Warm Beach Snohomish WA 1 1,510

1224 White Horse - Forston - Swede Heaven - Hazel Snohomish WA 1 571

1225 Bordeaux - Mima Thurston WA 1 333

1226 Bucoda Thurston WA 1 837

1227 Delphi Thurston WA 3 4,189

1228 East Olympia Thurston WA 1 1,173

1229 Fort Lewis Military Reservation (part) Thurston WA 4 2,914

1230 Four Corners Thurston WA 3 3,447

1231 Grand Mound CDP Thurston WA 3 3,719

1232 Helsing Junction - Michigan Hill -

Independence Thurston WA 1 914

1233 Kellys Corner Thurston WA 1 2,299

1234 Maytown - Littlerock - South Union Thurston WA 3 3,182

1235 Nisqually Indian Res - Fort Lewis Military

Res (part) Thurston WA 1 774
49

Table 2—Block group aggregations in the Northwest Forest Plan region (continued)

Identifying Number Population,

number Block group aggregation namea County State of BGsb 1990

1236 Olympia - Tumwater - Lacey - TanglewildeThompson CDP Thurston WA 105 114,806

1237 Plumb - Offutt Lake Thurston WA 1 1,469

1238 Rainier town Thurston WA 1 924

1239 Ranier (part) - Skoomkumchuck - Western

Junction Thurston WA 1 1,066

1240 Ranier (part) - Vail Thurston WA 1 753

1241 Rochester CDP Thurston WA 3 2,796

1242 Saint Clair Thurston WA 1 1,110

1243 Schneiders Prairie - Elizan Beach - (Summit

Lake) Thurston WA 3 2,502

1244 Sunnydale Thurston WA 2 1,805

1245 Sunrise Beach - Gravelly Beach - Edgewater

Beach Thurston WA 2 2,343

1246 Tenino Thurston WA 2 2,530

1247 Yelm - North Yelm CDP Thurston WA 4 5,269

1248 Brookfield - Grays River - Oneida Wahkiakum WA 1 831

1249 Cathlamet Wahkiakum WA 4 2,141

1250 Skamokawa - Sleepy Hollow Wahkiakum WA 2 355

1251 Ash - Port Kelley - Walulla Walla Walla WA 2 967

1252 Burbank CDP Walla Walla WA 2 2,099

1253 Gardena - Reese - Touchet Walla Walla WA 1 759

1254 Hadley - Rulo - Sapolil Walla Walla WA 1 540

1255 Lowden - Mojonier Walla Walla WA 1 761

1256 Prescott - (Eureka Flat) - (Snake River) Walla Walla WA 1 668

1257 Waitsburg city Walla Walla WA 1 1,133

1258 Waitsburg city (part) - Dixie - Kooskooskie Walla Walla WA 1 821

1259 Walla Walla - College Place - Walla Walla

East CDP - Garrett CDP Walla Walla WA 38 40,691

1260 Acme - Comar - Clipper - Van Zandt Whatcom WA 1 1,173

1261 Bellingham Whatcom WA 32 63,557

1262 Blaine city - Birch Bay CDP Whatcom WA 12 9,186

1263 Cedarville - Goshen - Wahl Whatcom WA 1 1,469

1264 Custer Whatcom WA 1 1,504

1265 Delta Whatcom WA 1 1,879

1266 Deming - (Sumas Mountain) Whatcom WA 1 1,152

1267 Everson city (part) - Greenwood Whatcom WA 1 1,916

1268 Ferndale Whatcom WA 8 9,999

1269 Glacier - Kendall - Kulshan - Columbia Whatcom WA 3 1,279

1270 Laurel - Victor Whatcom WA 4 5,094

1271 Lummi Indian Reservation Whatcom WA 3 3,164

1272 Lummi Island Whatcom WA 1 610

1273 Lynden Whatcom WA 5 7,655

1274 Lynden (part) - Northwood - Clearbrook Whatcom WA 2 1,992

1275 Marietta-Alderwood CDP - Ferndale city (part) Whatcom WA 1 2,654

1276 Nooksack - Everson Whatcom WA 4 4,937

1277 Noon - Van Wyck Whatcom WA 2 2,283

1278 Point Roberts - (U.S. Customs) Whatcom WA 4 916

1279 Saxon - Doran - Wickersham Whatcom WA 2 488

1280 Sudden Valley CDP Whatcom WA 1 2,414
50

Table 2—Block group aggregations in the Northwest Forest Plan region (continued)

Identifying Number Population,

number Block group aggregation namea County State of BGsb 1990

1281 Sudden Valley CDP (part) - Sunnyside -

Blue Canyon - (South Lake Whatcom) Whatcom WA 1 1,005

1282 Sumas Whatcom WA 1 1,305

1283 Concrete town (part) - (North Cascades) Whatcom -

Skagit WA 2 867

1284 American River - Cougar Valley - Nile Yakima WA 1 531

1285 Brace - Fruitvale CDP (part) - Selah (part) Yakima WA 1 1,791

1286 Buena Yakima WA 3 1,451

1287 Cowiche Yakima WA 1 314

1288 Donald Yakima WA 1 528

1289 Emerald - Nass Yakima WA 2 1,630

1290 Eschbach - Gleed Yakima WA 2 2,136

1291 Flint - Sawyer Yakima WA 1 707

1292 Grandview city Yakima WA 8 10,250

1293 Granger Yakima WA 3 2,991

1294 Gromore Yakima WA 3 2,556

1295 Holtzinger Yakima WA 1 637

1296 Liberty Yakima WA 1 1,526

1297 Mabton city - Byron Yakima WA 2 2,457

1298 Moxee City Yakima WA 4 3,622

1299 Naches Yakima WA 2 1,117

1300 Outlook Yakima WA 1 385

1301 Pinecliff - Wenas Yakima WA 1 601

1302 Rimrock - Tampico Yakima WA 1 606

1303 Selah Yakima WA 8 12,568

1304 Sunnyside Yakima WA 13 15,708

1305 Tasker - Weikel - (Naches Heights) Yakima WA 3 2,153

1306 Terrace Heights CDP - Fairview-Sumach CDP

(part) - Yakima city (part) Yakima WA 6 6,537

1307 Tieton Yakima WA 3 1,804

1308 Toppenish - Yakima Indian Reservation Yakima WA 4 7,529

1309 Toppenish (part) - Yethonat - Yakima Indian

Reservation Yakima WA 3 1,653

1310 Wapato - Yakima Indian Reservation Yakima WA 4 5,147

1311 Wiley City Yakima WA 1 1,717

1312 Yakima - Union Gap - Fruitvale CDP - West

Valley CDP Yakima WA 67 81,555

1313 Yakima Indian Res - Harrah town - White

Swan CDP - Satus CDP Yakima WA 20 12,622

1314 Zillah Yakima WA 5 3,577

Metropolitan block group aggregationsc

1 San Francisco Marin CA 148 217,915

2 Santa Rosa Sonoma CA 158 212,694

3 West Sacramento Yolo CA 20 28,739

4 Portland-Vancouver Washington,

Clackamas,

Multnomah,

Clark OR, WA 912 1,162,738

5 Eugene – Springfield Lane OR 180 193,004
51

Table 2—Block group aggregations in the Northwest Forest Plan region (continued)

Identifying Number Population,

number Block group aggregation namea County State of BGsb 1990

6 Salem – Keizer Polk OR 94 158,537

7 Richland – Kennewick – Pasco Benton,

Franklin WA 128 116,167

8 Seattle Snohomish,

King WA 1,549 1,749,913

9 Bremerton Kitsap WA 80 112,524

10 Tacoma Pierce WA 443 486,713

a

 Block group aggregation (BGA) names are composites of names of incorporated places, census-designated places (CDPs), geographic

names information system localities, and geographic features. A composite name may not identify all localities within a BGA, but may represent

the geographic extent of populated places or the larger populated places. Names in ( ) indicate that the place is a geographic feature and not

necessarily a populated place. The notation (part) indicates that the aggregation contains only part of the census place, Indian reservation, or

military reservation that is listed.

b

 BGs (block groups) indicates the number of block groups within each BGA. Census 1990 block group numbers associated with BGAs are

available from the author.

c

 Some metropolitan areas extend beyond that region that was examined in this project. This is reflected in the names given to the metropolitan

areas, as well as the associated counties and population size listed. For instance, the metropolitan area called West Sacramento does not

include the metropolitan area of Sacramento that is part of Sacramento County.
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The Forest Service of the U.S. Department of Agriculture is dedicated to the principle of

multiple use management of the Nation’s forest resources for sustained yields of wood,

water, forage, wildlife, and recreation. Through forestry research, cooperation with the

States and private forest owners, and management of the National Forests and National

Grasslands, it strives—as directed by Congress—to provide increasingly greater service

to a growing Nation.

The U.S. Department of Agriculture (USDA) prohibits discrimination in all its programs

and activities on the basis of race, color, national origin, gender, religion, age, disability,

political beliefs, sexual orientation, or marital or family status. (Not all prohibited bases

apply to all programs.) Persons with disabilities who require alternative means for communication of program information (Braille, large print, audiotape, etc.) should contact

USDA’s TARGET Center at (202) 720-2600 (voice and TDD).

To file a complaint of discrimination, write USDA, Director, Office of Civil Rights, Room

326-W, Whitten Building, 14th and Independence Avenue SW, Washington, DC 20250-

9410 or call (202) 720-5964 (voice and TDD). USDA is an equal opportunity provider and

employer.

Pacific Northwest Research Station

Web site http://www.fs.fed.us/pnw

Telephone (503) 808-2592

Publication requests (503) 808-2138

FAX (503) 808-2130

E-mail pnw_pnwpubs@fs.fed.us

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P.O. Box 3890

Portland, OR 97208-3890
U.S. Department of Agriculture

Pacific Northwest Research Station

333 S.W. First Avenue

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