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
Author
Ellen M. Donoghue is a research social scientist, Forestry Sciences Laboratory,
P.O. Box 3890, Portland, OR 97208-3890.
Abstract
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.
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Introduction
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
1
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).
Assessments and
Monitoring
2
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.
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
3
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 Northwest Forest
Plan Region
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
4
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.
Defining Community
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).
The Influence of
Secondary Data on
Community Research
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,
5
Table 1—Three forms of community as defined by authors
Hillery (1955)
Wilkinson (1979)
Wilkinson (1991)
Luloff (1998)
Area
Territorial unit or
place
Locality
Locality or
geographic area
Common ties
System of norms
and institutions
Local society
Human-life dimension
or social organization
to satisfy human needs
Social interaction
Interconnections and
action
Community
action
Processes for localityoriented social actions
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
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.
6
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.
The Utility of Census
Block Groups
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.
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).
7
United States
Region
Division
State
County
Tract
Place
Block group
Block
Figure 1—Hierarchy of census geographic areas.
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.
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).
8
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.
Aggregating Census
Block Groups
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
4
Doak and Kusel (1997) used a similar method for their
assessment of communities in the region surrounding
the Klamath National Forest in California.
9
Figure 2—Block group aggregation process. GIS = geographic information system.
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
10
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.6 Metropolitan 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.
11
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
12
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.
Block Group
Aggregations for
the Northwest
Forest Plan Region
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.
13
Figure 3—Block group aggregations in the Northwest Forest Plan region.
14
Figure 4—Block group aggregation points and Northwest Forest Plan (NWFP) counties.
15
Figure 5—Census places in the Northwest Forest Plan (NWFP) region.
16
Conclusion
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.
17
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.
Acknowledgments
Thanks to Anne Schneider, USDA Forest Service, and Gosia Bryja, Pacific Meridian
Resource Inc./Space Imaging, for data compilation and consultation.
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22
Appendix
Table 2—Block group aggregations in the Northwest Forest Plan region
Identifying
number
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
State
Number
of BGsb
Population,
1990
Colusa
Colusa
Colusa
Colusa
Colusa
Colusa
Colusa
Colusa
Del Norte
Del Norte
Del Norte
Del Norte
Del Norte
Del Norte
Glenn
Glenn
Glenn
Glenn
Glenn
Glenn
Glenn
Glenn
Glenn
Humboldt
Humboldt
Humboldt
Humboldt
Humboldt
Humboldt
Humboldt
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
1
1
7
1
1
1
1
3
10
1
1
1
1
2
1
1
2
2
1
1
8
8
2
17
1
1
1
1
2
1
2,435
815
6,753
657
1,395
494
551
3,175
17,382
1,244
660
743
1,382
2,049
535
658
595
3,299
512
958
8,674
7,901
1,666
19,160
983
320
899
509
1,655
746
Humboldt
Humboldt
CA
CA
1
1
816
883
Humboldt
CA
46
44,066
Humboldt
Humboldt
Humboldt
Humboldt
Humboldt
Humboldt
Humboldt
Humboldt
Humboldt
Humboldt
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
3
1
13
2
1
1
3
1
1
1
2,865
943
10,123
1,992
900
672
2,624
1,370
519
917
Block group aggregation namea
County
Arbuckle
College City - Harrington
Colusa
Grimes - Graino - Millers Landing
Maxwell - Delevan - Cortena
Stegeman - Princeton
Stonyford - Lodoga - Sites
Williams city
Crescent City - Crescent City North CDP
Fort Dick - Tyron Corner
Gasquet - Patrick Creek - Idlewild
Hiouchi - Douglas Park
Klamath CDP
Smith River
Butte City - Afton
Elk City - Dogtown
Fruto - Copper City - Newville
Hamilton City CDP - Mills Orchard
Norman - Logandale - Glenn
Ordbend - Bayliss
Orland
Willows
Wyo
Arcata
Arcata (part) - Korblex - Maple Creek
Beatrice
Benbow - Cooks Valley - Whitethorn
Berry Glenn - Orick
Blue Lake
Bridgeville - Dinsmore
Bull Creek - Honeydew - Ettersburg Thorn Junction
Carlotta - Riverside Park
Eureka - Myrtletown CDP - Cutten CDP Bayview CDP - Pine Hills CDP Humboldt Hill CDP
Ferndale city - Port Kenyon - Waddinton Capetown
Fieldbrook
Fortuna
Freshwater
Garberville
Glendale
Hoopa Valley Indian Reservation
Hydesville CDP
Korbel - Fernwood
Larabee - Fort Seward - Alderpoint
23
Table 2—Block group aggregations in the Northwest Forest Plan region (continued)
Identifying
number
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
24
State
Number
of BGsb
Population,
1990
Humboldt
Humboldt
Humboldt
Humboldt
Humboldt
Humboldt
Humboldt
Humboldt
Humboldt
Humboldt
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
1
11
1
1
1
1
1
4
1
1
1,194
10,936
686
443
434
1,184
1,221
4,302
393
1,093
Humboldt
Humboldt
Lake
Lake
Lake
Lake
CA
CA
CA
CA
CA
CA
3
2
1
20
4
2
2,695
1,575
302
12,443
2,347
2,015
Lake
Lake
Lake
CA
CA
CA
2
1
1
560
425
1,027
Lake
Lake
Lake
Lake
Lake
Lake
Lake
Lake
Lake
Lake
Lassen
Lassen
Lassen
Lassen
Lassen
Lassen
Lassen
Lassen
Lassen
Lassen
Lassen
Lassen
Lassen
Lassen
Lassen
Lassen
Marin
Marin
Marin
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
1
1
13
13
3
8
8
4
1
5
2
1
1
1
1
1
1
1
1
1
1
2
1
1
7
2
1
3
1
1,050
370
8,700
8,478
1,503
3,238
4,522
1,367
661
1,623
418
761
969
406
1,028
511
364
1,529
1,873
318
406
1,421
280
762
10,075
2,279
957
1,665
308
Block group aggregation namea
County
Lolita - Table Bluff - Hookton
McKinleyville CDP
Orleans, CA
Pepperwood - Shively - Holmes
Petrolia
Phillipsville - Briceland
Redway CDP
Rio Dell
Shelter Cove
Weott - Myers Flat - Miranda
Westhaven-Moon CDP - Trinidad Trinidad Rancheria
Willow Creek CDP
Castle Rock Springs
Clearlake
Clearlake Oaks CDP
Cobb CDP
Enterprise - Parramore Springs Saratoga Springs
Glenhaven
Hidden Valley Lake CDP
Hidden Valley Lake CDP (part) Military Reservation (part)
Hough Springs - Barkerville
Kelseyville CDP
Lakeport
Loch Lomond - Seigler Springs
Lower Lake CDP
Lucerne CDP - Nice CDP
Middletown
Pepperwood Grove
Upper Lake
Belfast - Litchfield - Crest
Bieber - Nubieber - Pumpkin Center
Buntingville
Coppervale - Lasco - Westwood Junction
Doyle - Scotts - Plumas
Halls Flat - Jelico - Little Valley
Hot Springs - Leonard - Hayden Hill
Janesville
Johnstonville
Madeline - Termo - Ravendale
Milford
Sierra Army Depot - Wendel - Herlong
Spalding - (Eagle Lake)
Standish
Susanville
Westwood CDP
Bivalve - Marconi - Ocean Roar
Bolinas CDP - (Bolinas Point)
Dillon Beach
Table 2—Block group aggregations in the Northwest Forest Plan region (continued)
Identifying
number
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
State
Number
of BGsb
Population,
1990
Marin
Marin
Marin
Marin
Marin
Marin
Marin
Marin
Mendocino
Mendocino
Mendocino
Mendocino
Mendocino
Mendocino
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
2
2
1
1
3
1
1
3
1
1
2
2
1
1
1,392
1,449
510
815
1,062
628
627
1,937
656
857
609
2,925
588
1,032
Mendocino
Mendocino
Mendocino
CA
CA
CA
1
10
1
2,018
8,639
1,742
Mendocino
Mendocino
CA
CA
2
1
1,745
1,908
Mendocino
Mendocino
Mendocino
Mendocino
Mendocino
Mendocino
Mendocino
Mendocino
Mendocino
Mendocino
Mendocino
Mendocino
Mendocino
Mendocino
Mendocino
Mendocino
Mendocino
Mendocino
Mendocino
Mendocino
Mendocino
Mendocino
Modoc
Modoc
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
1
1
2
1
1
1
1
1
1
1
3
1
3
1
1
1
1
2
20
2
1
7
1
1
1,122
1,745
3,175
506
887
863
522
812
773
1,140
2,456
1,501
5,154
1,899
515
1,048
887
2,381
20,789
1,484
711
7,256
829
4,276
Modoc
Modoc
Modoc
Modoc
CA
CA
CA
CA
1
1
1
1
660
976
434
892
Block group aggregation namea
County
Inverness CDP
Lagunitas-Forest Knoll CDP
Nicasio
Point Reyes Station
Stinson Beach - (Mount Tamalpais)
Tocaloma - Olema - Sacramento Landing
Tomales - Fallon
Woodacre CDP
Andersonia - Leggett - Cummings
Boonville
Calpella
Caspar
Cleone
Comptche - Navarro - Cape Horn
Covelo CDP - Round Valley Indian
Reservation
Fort Bragg
Gualala - Anchor Bay - Fish Rock
Hopland - Nacomis Indian Rancheria The Oaks
Inglebrook - Redwood Lodge - Northspur
Laytonville CDP / Laytonville Indian
Reservation
Little River - Albion - Elk
Longvale - Hearst - Crowley
Manchester
Mendocino
Nashmead - Dos Rios - Farley
Orrs Springs
Philo
Pine Grove, CA
Point Arena
Potter Valley
Presswood
Redwood Valley - Laughlin
Ridge
Rockport - Westport - Kibesillah
Talmage
Tan Oak Park - Branscomb
The Forks
Ukiah
Vichy Springs
Whiskey Springs - Melbourne
Willits
Adin - Day - White Horse
Alturas
Canby - Ambrose Station - (Warm Springs
Valley)
Cedarville - Eagleville - (Surprise Valley)
Fort Bidwell - Lake City
McArthur - Likely
25
Table 2—Block group aggregations in the Northwest Forest Plan region (continued)
Identifying
number
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
26
Block group aggregation namea
County
State
Number
of BGsb
Population,
1990
New Pine Creek - Willow Ranch - Davis Creek
Newell - Homestead - Hackamore
Aetna Springs
American Canyon CDP
Angwin CDP
Atlas - [Moskowite Corners]
Calistoga
Cuttings Wharf
Deer Park CDP
Knoxville - (Lake Berryessa) - (Pope Valley)
Napa
Napa Soda Springs
Oakville - Rutherford - Zinfandel
Spanish Flat
St. Helena
Yountville
Anderson city
Bella Vista
Big Bend - Hillcrest - Roaring Creek Indian
Rancheria
Burney CDP
Cassel - Old Station - Doyles Corner
Castle Crag - Fisher - Delta
Centerville
Central Valley CDP
Cloverdale - Olinda
Cottonwood CDP
Fall River Mills - Glenburn
Fern - Whitmore
French Gulch - Minnesota - Matheson
Ingot - Oak Run
Johnson Park
Lakehead - Sugarloaf - O’Brien
McArthur - Pittville - Spalding Corner
Millville - Redwoods - Inwood
Montgomery Creek - Montgomery Creek
Indian Rancheria - Round Mountain
Mountain Gate
Obie - Cayton - Four Corners
Ono - Gas Point - Knob
Palo Cedro
Redding
Redding (part) - Buckeye
Redding (part) - Keswick
Redding (part) - Loomis Corners
Redding (part) - Pine Grove
Redding (part) - Silverthorn
Shasta - Whiskeytown - Iron Mountain - Kett
Shasta (part) - Igo
Shingletown
Viola - Summertown - Manzanita Lake
Modoc
Modoc
Napa
Napa
Napa
Napa
Napa
Napa
Napa
Napa
Napa
Napa
Napa
Napa
Napa
Napa
Shasta
Shasta
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
1
1
1
5
4
1
5
1
2
1
67
4
2
3
7
5
15
3
429
1,182
708
7,893
4,648
1,624
5,189
949
1,758
343
71,752
1,881
1,864
1,130
5,538
5,488
16,384
3,400
Shasta
Shasta
Shasta
Shasta
Shasta
Shasta
Shasta
Shasta
Shasta
Shasta
Shasta
Shasta
Shasta
Shasta
Shasta
Shasta
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
1
3
1
1
1
7
3
4
1
1
1
2
1
2
1
1
513
3,431
915
631
1,077
8,967
3,709
4,855
936
477
512
2,803
872
1,139
1,168
1,497
Shasta
Shasta
Shasta
Shasta
Shasta
Shasta
Shasta
Shasta
Shasta
Shasta
Shasta
Shasta
Shasta
Shasta
Shasta
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
1
2
1
1
2
52
2
2
2
1
1
1
1
1
2
1,027
1,893
834
903
1,756
72,440
2,315
1,380
2,442
1,528
1,598
883
1,361
1,799
1,591
Table 2—Block group aggregations in the Northwest Forest Plan region (continued)
Identifying
number
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
Block group aggregation namea
County
State
Number
of BGsb
Population,
1990
Big Springs - Bolam
Clear Creek - Somes Bar - Hamburg
Deetz - Upton
Dorris
Dunsmuir
Etna
Etna (part) - Callahan - Sumerville
Etna (part) - Greenview - Cheeseville
Fort Jones
Grenada - Gazelle
Happy Camp
Hilt - Gottsville - Hornbrook
McCloud CDP
Montague
Montague (part) - Little Shasta - Grass Lake
Mount Shasta
Seiad Valley - Horse Creek - Klamath River
Tulelake
Weed
Yreka
Annapolis - Los Lomas
Black Oaks - Mercuryville
Bloomfield - Valley Ford
Bodega Bay CDP - Bridgehaven Salmon Creek
Cadwell - Cunningham
Chianti
Cloverdale city
Duncan Mills
Forestville CDP
Fort Ross - Walsh Landing - Jenner
Geyserville - Cozzens Corner - Jimtown
Glen Ellen CDP
Hacienda - Hollydale - Summerhome Park
Healdsburg
Hessel
Kellogg
Knowles Corner
Lytton
Mark West Spring
Monte Rio CDP
Monte Rio CDP (part) - Montesano - Cazadero
Occidental CDP
Petaluma
Petaluma (part) - McNear - Lakeville
Roblar - Turner
Sears Point - Wingo - Shellville (Naval Reservation)
Sebastopol
Siskiyou
Siskiyou
Siskiyou
Siskiyou
Siskiyou
Siskiyou
Siskiyou
Siskiyou
Siskiyou
Siskiyou
Siskiyou
Siskiyou
Siskiyou
Siskiyou
Siskiyou
Siskiyou
Siskiyou
Siskiyou
Siskiyou
Siskiyou
Sonoma
Sonoma
Sonoma
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
1
1
1
2
3
1
1
1
1
1
1
1
2
2
1
4
1
1
4
8
1
1
1
1,817
669
1,188
2,020
2,706
600
1,066
1,800
1,634
848
1,000
802
1,728
2,681
953
5,519
1,117
1,467
3,998
9,918
569
1,027
1,641
Sonoma
Sonoma
Sonoma
Sonoma
Sonoma
Sonoma
Sonoma
Sonoma
Sonoma
Sonoma
Sonoma
Sonoma
Sonoma
Sonoma
Sonoma
Sonoma
Sonoma
Sonoma
Sonoma
Sonoma
Sonoma
Sonoma
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
3
3
1
6
1
4
1
2
3
3
11
1
1
1
1
2
2
2
2
44
1
1
2,554
2,281
863
6,593
280
5,190
1,278
2,447
3,531
2,089
16,402
1,602
582
1,131
1,117
2,448
1,852
1,741
2,068
52,019
2,808
843
Sonoma
Sonoma
CA
CA
1
17
863
16,122
27
Table 2—Block group aggregations in the Northwest Forest Plan region (continued)
Identifying
number
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
28
Block group aggregation namea
Sonoma city - Eldridge CDP - Fetters Hot
Springs-A - Boyes Hot Springs CDP El Verano CDP - Temelec CDP
Stewarts Point - Sea Ranch
Temelec CDP (part) - Big Bend
Two Rock - Two Rock Ranch Station
Military Reservation
Abbott - Tudor - Wilson
Live Oak
Marchant - Cunard - Karnak
Meridian - Tarke - Tisdale
Nicholaus -East Nicholaus - Trowbridge
Pennington - Encinal - Sanders
Pleasant Grove - Riego - Counsman
Rio Oso
Robbins - Kirkville - Cranmore
Sutter CDP
Sutter CDP (part) - West Butte
Verona - Joes Landing
Yuba City - Tierra Buena CDP - South
Yuba City CDP
Bend
Corning
Dairyville
Dales - Manton - Campbellville
Henleyville - Paskenta - Sunnyside
Hooker
Kirkwood
Las Flores-Gerber CDP
Los Molinos
Proberta
Rawson
Red Bank
Red Bluff
Red Bluff (part) - Blunt
Richfield - El Camino
Rosewood - Cold Fork
Squaw Hill
Tehama
Vina
Big Bar - Del Loma
Burnt Ranch
Carrville - Trinity Center - Trinity Alps
Douglas City
Hayfork CDP
Helena - Junction City
Hyampom
Lewiston CDP
Ruth - Zenia - Kekawaka
Salyer - Trinity Village - Denny
Weaverville CDP
County
State
Number
of BGsb
Population,
1990
Sonoma
Sonoma
Sonoma
CA
CA
CA
26
1
1
31,136
594
781
Sonoma
Sutter
Sutter
Sutter
Sutter
Sutter
Sutter
Sutter
Sutter
Sutter
Sutter
Sutter
Sutter
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
1
1
4
1
2
1
1
1
1
2
1
1
1
1,869
1,068
5,946
410
794
802
806
850
969
538
1,205
1,983
340
Sutter
Tehama
Tehama
Tehama
Tehama
Tehama
Tehama
Tehama
Tehama
Tehama
Tehama
Tehama
Tehama
Tehama
Tehama
Tehama
Tehama
Tehama
Tehama
Tehama
Trinity
Trinity
Trinity
Trinity
Trinity
Trinity
Trinity
Trinity
Trinity
Trinity
Trinity
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
38
1
9
2
3
1
2
1
1
3
1
1
1
16
2
1
2
1
1
1
1
1
2
2
5
1
1
1
4
2
4
48,704
957
8,637
2,214
1,376
1,697
3,011
508
1,193
2,261
744
1,042
1,155
17,545
2,232
961
1,149
2,028
451
464
301
287
812
997
2,549
675
301
1,352
840
965
3,695
Table 2—Block group aggregations in the Northwest Forest Plan region (continued)
Identifying
number
Block group aggregation namea
County
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
Wildwood - Forest Glen - Peanut
Capay - Guinda - Rumsey
Clarksburg - Arcade - Central
Davis
Davis (part) - El Macero
Davis (part) - Merritt - Webster
El Rio Villa
Esparto CDP
Greendale - Sorroca - Valdez
Hershey - Dunnigan
Jacobs Corner
Knights Landing
Madison - Citrona - Arroz
Plainfield
West Sacramento (part) - Beatrice - Kiesel
Winters
Woodland
Woodland city (part) - Sugarfield - Conaway
Yolo - Dufour
Zamora - Tyndall Landing
Adair Village
Alsea
Corvallis
Corvallis (part) - Lewisburg
Dawson - Glenbrook - Alpine - Bellfountain
Fern Road
Kings Valley - Blodgett - Harris
Monroe
North Albany CDP
Palestine
Philomath
Wren
Alder Creek - Cherryville
Anderson
Barlow
Boring
Bull Run - Marmot
Canby
Canby (part) - O’Neil Corners
Carus
Carver
Cedardale - Dickey Prairie - Fernwood
Cedarhurst Park - Logan
Central Point
Colton - Clarkes - Timber Grove
Cottrell - Kelso
Currinsville
Damascus - Wetzels Corner - Wilson Corner
Dodge - Springwater
Douglass Ridge
Eagle Creek - Barton
Trinity
Yolo
Yolo
Yolo
Yolo
Yolo
Yolo
Yolo
Yolo
Yolo
Yolo
Yolo
Yolo
Yolo
Yolo
Yolo
Yolo
Yolo
Yolo
Yolo
Benton
Benton
Benton
Benton
Benton
Benton
Benton
Benton
Benton
Benton
Benton
Benton
Clackamas
Clackamas
Clackamas
Clackamas
Clackamas
Clackamas
Clackamas
Clackamas
Clackamas
Clackamas
Clackamas
Clackamas
Clackamas
Clackamas
Clackamas
Clackamas
Clackamas
Clackamas
Clackamas
State
Number
of BGsb
Population,
1990
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
3
2
1
17
2
1
1
3
1
1
1
1
1
1
1
4
23
1
2
2
1
3
35
3
1
1
1
2
4
1
3
2
2
1
2
1
1
8
1
2
1
1
1
1
1
2
1
5
1
1
2
289
947
653
49,489
2,604
1,400
898
1,836
952
774
1,554
567
755
808
391
5,495
40,844
550
1,404
432
1,502
2,060
48,328
3,053
744
1,243
1,083
1,954
4,394
1,369
3,108
1,973
2,633
1,505
625
1,483
947
9,614
1,453
3,642
1,342
1,632
1,288
429
1,617
3,335
773
6,986
1,166
1,821
2,457
29
Table 2—Block group aggregations in the Northwest Forest Plan region (continued)
Identifying
number
State
Number
of BGsb
Population,
1990
Clackamas
Clackamas
Clackamas
Clackamas
Clackamas
Clackamas
Clackamas
Clackamas
Clackamas
Clackamas
Clackamas
Clackamas
Clackamas
Clackamas
Clackamas
Clackamas
Clackamas
Clackamas
Clackamas
Clackamas
Clackamas
Clackamas
Clackamas
Clackamas
Clackamas
Clackamas
Clatsop
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
3
1
1
1
1
1
1
3
1
1
1
1
2
1
4
3
2
1
1
2
2
6
2
1
1
5
9
3,091
750
1,299
2,960
1,248
505
537
3,480
1,746
503
824
1,052
2,160
1,693
5,321
2,445
1,865
1,337
863
4,219
3,831
6,553
1,938
1,643
1,090
8,659
10,671
Clatsop
Clatsop
Clatsop
Clatsop
Clatsop
Clatsop
Clatsop
Clatsop
Clatsop
Clatsop
Clatsop
Clatsop
Clatsop
Clatsop Clackamas
Columbia
Columbia
Columbia
Columbia
Columbia
Columbia
Columbia
Columbia
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
1
5
1
3
1
2
1
1
1
10
1
3
3
976
1,230
1,436
1,595
682
927
1,050
506
955
5,728
674
2,432
2,467
OR
OR
OR
OR
OR
OR
OR
OR
OR
2
1
1
1
8
1
1
1
1
1,964
825
1,159
1,226
9,329
1,116
1,067
939
1,007
Block group aggregation namea
County
363
364
365
366
367
368
369
370
371
372
373
374
375
Estacada
Faraday
Firwood - Dover
Fishers Corner - Beaver Creek - Echo Dell
Garfield - Tracy - Whitewater
George - Bissell
Government Camp - Timberline Lodge
Highland - Upper Highland - Viola
Hillsview
Hoodview - Mulloy
Kokel Corner
Ladd Hill
Lone Elder - Macksburg - Dryland
Marquam - Wilhoit
Molalla
Mount Hood Village CDP
Mulino
Old Colton - Elwood
Paradise Park
Redland - Fishers Mill
Rural Dell - Yoder - Ninety-One - Needy
Sandy
Stafford
Union Mills
Whiskey Hill
Wilsonville
Astoria
Brownsmead - Westport - (Tenasilahe Island
and others)
Cannon Beach
Fern Hill
Gearhart
Hammond - Warrenton (part)
Jewell - Elsie - Hamlet
Knappa - Knappa Junction - (Karlson Island)
Necanicum
Olney
Seaside
Svensen - (Russian Island)
Warrenton
Warrenton (part) -Miles Crossing
Glenwood - Sunset Beach - Westlake
376
377
378
379
380
381
382
383
Beaver Homes - Goble
Clatskanie
Clatskanie (part) - Swedetown - Apiary
Columbia City - St. Helens
Deer Island - Reuben
Delena - Downing
Inglis - Quincy
Kerry - Marshland
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
30
Table 2—Block group aggregations in the Northwest Forest Plan region (continued)
Identifying
number
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
State
Number
of BGsb
Population,
1990
Columbia
Columbia
Columbia
Columbia
Columbia
Columbia
Columbia
Columbia
Columbia
Columbia
Coos
Coos
Coos
Coos
Coos
Coos
Coos
Coos
Coos
Coos
Coos
Coos
Coos
Coos
Coos
Coos
Coos
Coos
Coos
Coos
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
1
2
2
1
6
2
2
2
3
1
1
3
2
1
1
1
20
1
1
5
1
1
1
2
1
1
1
2
1
1
559
1,723
1,767
829
6,161
2,205
1,805
1,755
3,136
949
1,086
2,577
1,560
1,572
594
839
18,250
789
715
4,958
995
1,603
1,053
1,414
377
1,263
1,113
1,949
873
880
Coos
Coos
Coos
Coos
Coos
Coos
Coos
Coos
Crook
Crook
Crook
Crook
Curry
Curry
Curry
Curry
Curry
Curry
Curry
Curry
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
1
10
1
1
2
1
1
1
2
1
12
2
1
6
3
5
2
3
2
2
842
9,636
1,200
966
807
627
1,033
702
1,515
1,290
10,946
360
122
7,086
2,583
4,426
217
669
1,800
959
Block group aggregation namea
County
Locoda - Woodson - (Wallace Island)
Prescott - Ranier (part)
Rainier city
Rainier city (part) - Alston - Mayger
Scappoose - (N. Sauvie Island)
Spatenberg
St. Helens city (part) - McNutty
Trenholm - Waterview- Yankton
Vernonia
Warren
Allegany - Dellwood - Fairview
Bandon
Bandon (part) - Twomile - Fourmile
Barview CDP - Crown Point
Bullards - Randolph
Cheney - Bridge - Remote
Coos Bay city - Bunker Hill CDP
Coos Head Naval Facility - Charleston
Cooston
Coquille
Coquille (part) - Leneve - Coaledo
Cordes - Hauser - (Saunders Lake)
Glasgow
Lakeside
Lakeside (part) - Templeton
Libby - Southport
McCormac
Myrtle Point
Myrtle Point (part) - Arago
Myrtle Point (part) - Estabrook - Warner
Myrtle Point (part) - Norway - Sitkum McKinley
North Bend
Overland - Delmar - Green Acres
Powers
Prosper - Parkersburg - Winterville
Riverton
Shorewood
Sumner
Lakin Place - (Ochoco Reservoir)
Powell Butte - O’Neill - Forest Crossing
Prineville
Roberts - Post- Paulina - Suplee
Agness - Illahe - Marial
Brookings
Gold Beach
Harbor CDP
Ophir
Pistol River - Carpenterville
Port Orford
Sixes - Denmark - Langlois
31
Table 2—Block group aggregations in the Northwest Forest Plan region (continued)
Identifying
number
Block group aggregation namea
County
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
Wedderburn - Nesika Beach
Alfalfa
Bend city
Cloverdale - Plainview
Deschutes - Deschutes Junction
Deschutes River Woods
Elk Lake - Lava Lake Resort
Hampton - Brothers - Millican - Paulina Lake
La Pine
Prinveville Junction
Redmond
Sisters
Sunriver
Terrebonne
Three Rivers CDP
Tumalo
Anlauf - Curtin
Ash
Azalea - Galesville - Fortune Branch
Camas Valley - Reston - Olalla - Tenmile
Canyonville
Cleveland - Elgarose - Callahan
Days Creek
Dillard - Carnes
Dixonville
Dole
Drain
Drain (part) - Skelley
Elkton
Gardiner - Kroll - Sulphur Springs
Glendale city - Fernvale
Glide - Idlewild
Green CDP
Hawthorne - Nonpareil
Kellogg - Tyee
Lookinglass
Melrose
Milo - Tiller - Drew
Myrtle Creek
Oaks - Glengary - Round Prairie
Peel - Steamboat
Quines Creek
Reedsport
Reedsport (part) - Winchester Bay
Rice Hill - Isadore
Riddle
Roseburg - Roseburg North CDP
Roseburg (part) - Riversdale
Scottsburg
Stephens - Akin
Surprise Valley
Curry
Deschutes
Deschutes
Deschutes
Deschutes
Deschutes
Deschutes
Deschutes
Deschutes
Deschutes
Deschutes
Deschutes
Deschutes
Deschutes
Deschutes
Deschutes
Douglas
Douglas
Douglas
Douglas
Douglas
Douglas
Douglas
Douglas
Douglas
Douglas
Douglas
Douglas
Douglas
Douglas
Douglas
Douglas
Douglas
Douglas
Douglas
Douglas
Douglas
Douglas
Douglas
Douglas
Douglas
Douglas
Douglas
Douglas
Douglas
Douglas
Douglas
Douglas
Douglas
Douglas
Douglas
32
State
Number
of BGsb
Population,
1990
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
1
1
39
3
1
3
2
4
9
1
13
5
2
3
5
2
1
1
1
3
1
1
1
1
1
1
1
1
2
6
2
3
3
1
1
2
1
1
5
1
1
1
5
1
1
2
26
2
1
1
1
1,465
959
36,756
2,386
2,056
3,205
645
1,150
4,779
771
11,450
2,340
1,121
3,010
1,689
2,641
1,081
406
684
2,529
1,410
1,553
959
532
1,013
1,009
1,098
519
646
592
1,421
2,539
5,076
702
764
2,166
1,110
739
4,562
647
1,083
617
3,918
1,736
686
2,140
24,668
3,951
427
675
1,120
Table 2—Block group aggregations in the Northwest Forest Plan region (continued)
Identifying
number
Block group aggregation namea
County
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
Sutherlin - Oakland
Tokatee Falls - Clearwater - Diamond Lake
Tri City CDP
Umpqua - Millwood - Green Peak
Wilbur - Redbell
Winston
Yoncalla
Yoncalla (part) - Elkhead
Cascade Locks
Dee - Winans - Summit
Hood River
Mount Hood - Parkdale - Trout Creek
Oak Grove - Rockford
Odell - Lenz
Pine Grove
Windmaster Corner
Applegate
Ashland
Buncom
Butte Falls
Central Point city
Colestin
Eagle Point
Foots Creek
Gold Hill
Jacksonville
Lakecreek - Brownsboro
LIncoln - Climax - Steinman
Medford
Medford (part) - White City CDP (part)
Phoenix
Prospect - Cascade Gorge - McLeod
Rogue River
Ruch - McKee Bridge - (Applegate Lake)
Shady Cove
Shady Cove (part) - Rogue Elk
Spikenard - Trail
Starvation Heights
Table Rock - Beagle
Talent
Tolo
Voorhies
White City CDP
Wimer - Bybee Springs
Camp Sherman
Culver city - Opal Springs - Opal City
Gateway - Grizzly - Donnybrook
Grandview
Madras
Madras Station
Mecca - Paxton
Douglas
Douglas
Douglas
Douglas
Douglas
Douglas
Douglas
Douglas
Hood River
Hood River
Hood River
Hood River
Hood River
Hood River
Hood River
Hood River
Jackson
Jackson
Jackson
Jackson
Jackson
Jackson
Jackson
Jackson
Jackson
Jackson
Jackson
Jackson
Jackson
Jackson
Jackson
Jackson
Jackson
Jackson
Jackson
Jackson
Jackson
Jackson
Jackson
Jackson
Jackson
Jackson
Jackson
Jackson
Jefferson
Jefferson
Jefferson
Jefferson
Jefferson
Jefferson
Jefferson
State
Number
of BGsb
Population,
1990
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
6
1
3
1
2
3
1
1
2
2
9
3
2
1
3
2
1
18
1
1
7
2
2
3
2
4
1
2
25
2
4
1
3
2
1
1
1
1
4
3
4
2
1
2
1
1
1
2
6
2
1
8,838
263
3,880
416
802
4,090
1,004
578
948
1,487
6,126
2,265
2,229
1,057
1,912
879
1,212
18,384
649
454
10,964
620
5,008
3,704
3,130
5,704
811
1,453
49,990
2,046
10,135
1,080
2,984
1,688
1,552
1,314
472
944
3,260
5,185
3,917
1,497
6,065
2,167
251
1,368
307
938
5,125
1,281
742
33
Table 2—Block group aggregations in the Northwest Forest Plan region (continued)
Identifying
number
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
34
State
Number
of BGsb
Population,
1990
Jefferson
Josephine
Josephine
Josephine
Josephine
OR
OR
OR
OR
OR
2
1
4
1
2
1,274
918
2,915
1,058
902
Josephine
Josephine
Josephine
Josephine
Josephine
Josephine
Josephine
Josephine
Josephine
Josephine
Josephine
Josephine
Josephine
Josephine
Josephine
Klamath
Klamath
Klamath
Klamath
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
28
3
3
2
1
1
2
1
2
1
1
2
2
2
1
1
2
2
1
34,144
2,930
3,099
2,731
1,697
610
2,377
1,093
1,430
686
716
2,052
1,626
1,242
423
740
988
1,521
1,159
Klamath
Klamath
Klamath
Klamath
Klamath
Klamath
Klamath
Klamath
Klamath
OR
OR
OR
OR
OR
OR
OR
OR
OR
1
2
1
1
1
2
1
3
49
330
2,351
574
339
384
407
1,179
2,196
39,750
Klamath
Klamath
Klamath
Klamath
Klamath
Lane
Lane
Lane
Lane
Lane
Lane
Lane
Lane
Lane
Lane
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
1
1
3
1
2
1
2
2
1
1
2
11
7
1
1
1,391
1,155
2,306
573
359
377
2,246
2,127
911
989
2,050
10,818
6,924
943
979
Block group aggregation namea
County
Metolius
Bridgeview - Holland
Cave Junction
Cave Junction (part) - Dryden
Galice - Rand
Grants Pass city - Harbeck-Fruitdale CDP Redwood CDP
Jerome Prairie
Merlin
Murphy
New Hope
O’Brien
Pleasant Valley - Three Pines - Hugo
Provolt
Selma
Sunny Valley - Placer - Golden - Speaker
Takilma
Wilderville - Wonder
Williams
Winona
Wolf Creek - Leland
Algoma - Shady Pine
Beatty - Sprague River
Bonanza (east) - Bly - Langell Valley
Bonanza (west) - Hildebrand - Yonna
Chemult - Beaver Marsh - Diamond Lake
Junction
Chiloquin
Crescent - Rosedale
Crescent Lake Junction - Mowich
Falcon Heights
Fort Klamath - Sand Creek - Yamsay
Gilchrist - Little River
Keno - Worden
Klamath Falls - Altamont CDP
Klamath Falls-Altamont (part) - Pine Grove Olene
Malin
Merrill
Midland
Rocky Point - Lake of the Woods
Ada - Siltcoos - Canary
Alvadore
Bear Creek - Cheshire - Franklin - Goldson
Blue River - Finn Rock - Nimrod
Cloverdale
Coburg
Cottage Grove
Creswell
Crow
Deadwood - Triangle Lake - Blachly
Table 2—Block group aggregations in the Northwest Forest Plan region (continued)
Identifying
number
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
State
Number
of BGsb
Population,
1990
Lane
Lane
Lane
Lane
Lane
Lane
Lane
Lane
Lane
Lane
Lane
Lane
Lane
Lane
Lane
Lane
Lane
Lane
Lane
Lane
Lane
Lane
Lane
Lane
Lane
Lane
Lane
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
1
1
2
3
1
1
12
2
1
2
1
1
8
1
1
1
1
1
1
1
1
2
1
1
4
3
1
1,123
955
1,061
3,759
964
600
7,809
1,618
969
1,854
1,039
976
6,145
1,011
1,417
521
803
776
731
733
894
1,644
632
1,528
3,424
2,507
707
Lane
Lane
Lane
Lane
Lane
Lane
Lane
Lane
Lane
Lane
Lane
Lincoln
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
1
1
1
1
3
3
1
1
2
1
1
2
642
629
1,032
439
3,138
3,762
970
1,652
1,667
966
447
919
Lincoln
Lincoln
Lincoln
Lincoln
Lincoln
Lincoln
Lincoln
Lincoln
Lincoln
Lincoln
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
1
1
17
5
15
1
3
1
1
2
1,016
485
7,620
2,171
10,269
450
2,156
305
391
2,371
Block group aggregation namea
County
Dexter
Dorena - Culp Creek - Disston
Dunes City
Eugene (part) - (Bailey Hill) - (Spencer Creek)
Fall Creek - Unity
Firo - Swisshome - (Deadwood Creek West)
Florence
Gap
Glenada - Westlake
Goshen
Horton
Jasper - Trent
Junction City
Lancaster
Leaburg - Deerhorn
London - (Black Butte)
Lorane
Lowell
Lowell (part) - Minnow - Crale - Winberry
Mabel - Wendling
Mapleton - Tiernan - Nekoma
Marcola
Maywood
Mohawk
Oakridge
Pleasant Hill, OR
Pryor - Kitson Hot Springs - Frazier
Rainbow - McKenzie Bridge - Belknap Springs Foley Springs
Richardson - Alma - Wolf Creek
Sailor - Elrus - Long Tom - Vaughn
Searose Beach - Minerva
Veneta
Veneta (part) - Elmira
Vida
Walker - Saginaw - Royal
Walterville
Walton - Noti - Penn
Westfir
Depoe Bay
Elk City - Burnt Woods - Harlan - Siletz
Indian Reservation (part)
Fruitvale
Lincoln City
Lincoln Beach CDP
Newport
Otter Rock - Beverly Beach
Rose Lodge CDP
San Marine
Seal Rock - Ona
Siletz - Siletz Indian Reservation
35
Table 2—Block group aggregations in the Northwest Forest Plan region (continued)
Identifying
number
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
36
Block group aggregation namea
County
State
Number
of BGsb
Population,
1990
Tidewater
Toledo
Waldport
Yachats
Albany
Berlin - (McDowell Creek)
Brewster - Griggs
Brownsville
Cartney - Miller - Rowland
Cascadia - Santiam Junction - Marion
Forks (part)
Crabtree
Crawfordsville - Union Point
Fawn - Jordan - Fox Valley
Greenville - Narrows - Santiam Terrace
Halsey
Harrisburg
Holley - Calapooia - Dollar
Idanha (part) - Gates (part)
LaComb - Marion Forks (part)
Lebanon city - South Lebanon CDP
Lyons
Mill City
Millersburg
Orleans, OR
Pirtle - Riverside
Scio
Shelburn - Kingston
Sodaville
Spicer - Tallman - Irvinville
Sweet Home
Tangent
Waterloo
Aumsville
Aurora
Broadacres
Brooks - Waconda - Lakebrook
Champoeg - Fairfield
Detroit
Donald city
Fargo - Butteville - Curtis
Fruitland - Geer
Gates
Gervais
Hazel Green - Labish Village
Hubbard
Idanha
Jefferson
Marion
Mill City (part) - Mehama
Mount Angel
Lincoln
Lincoln
Lincoln
Lincoln
Linn
Linn
Linn
Linn
Linn
OR
OR
OR
OR
OR
OR
OR
OR
OR
1
5
6
2
27
1
1
2
1
423
4,879
4,147
1,287
32,288
654
1,306
2,565
1,150
Linn
Linn
Linn
Linn
Linn
Linn
Linn
Linn
Linn
Linn
Linn
Linn
Linn
Linn
Linn
Linn
Linn
Linn
Linn
Linn
Linn
Linn
Linn
Marion
Marion
Marion
Marion
Marion
Marion
Marion
Marion
Marion
Marion
Marion
Marion
Marion
Marion
Marion
Marion
Marion
Marion
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
2
4
1
1
1
2
2
1
1
2
17
1
2
3
1
1
2
1
1
1
10
2
1
1
2
1
2
1
1
1
1
1
1
1
1
3
1
3
3
1
4
333
1,244
1,203
1,130
1,268
1,773
2,048
925
726
1,855
16,557
1,069
1,468
2,017
739
835
1,895
1,598
1,245
941
9,169
1,889
1,337
1,741
2,865
707
2,468
920
383
1,032
1,208
907
645
1,205
2,395
2,582
248
3,047
1,824
1,298
4,518
Table 2—Block group aggregations in the Northwest Forest Plan region (continued)
Identifying
number
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
State
Number
of BGsb
Population,
1990
Marion
Marion
Marion
Marion
Marion
Marion
Marion
Marion
Marion
Marion
Marion
Marion
Marion
Marion
Marion
Multnomah
Multnomah
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
1
1
1
2
1
2
6
1
9
2
1
3
3
12
1
2
2
1,124
1,828
1,279
1,657
1,203
2,680
7,778
752
6,694
2,904
1,179
1,048
5,711
15,721
860
2,097
770
Multnomah
OR
1
478
Multnomah
OR
3
2,996
Multnomah
Polk
Polk
Polk
Polk
Polk
Polk
Polk
Polk
Polk
Polk
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
3
1
1
6
2
1
1
2
8
1
1
4,242
1,313
1,382
7,518
4,033
1,389
1,398
1,642
11,308
939
926
Polk
Polk
Polk
Sherman
Sherman
Sherman
Tillamook
Tillamook
Tillamook
Tillamook
Tillamook
Tillamook
Tillamook
Tillamook
Tillamook
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
1
1
1
1
1
1
4
1
2
2
3
3
1
1
3
3,949
347
932
873
459
586
1,927
902
963
1,316
1,082
1,383
499
311
1,378
Block group aggregation namea
County
Pratum - North Howell
Salem (part) - Rosedale
Scotts Mills
Shaff - West Stayton - North Santiam
Shaw - Macleay
Silver Falls City - Drake Crossing
Silverton
St. Paul
Stayton
Sublimity
Sunnyside - Orville
Talbot - Sidney
Turner
Woodburn
Woodburn (part) - Saint Louis
Holbrook - (Sauvie Island)
Latourell - Warrendale - Bonneville
Portland-Vancouver (part) - Burlington Folkenberg
Portland-Vancouver (part) - Corbett Springdale
Portland-Vancouver (part) - Orient Pleasant Home
Ballston - McCoy - Walkers Corner
Boyer - Grand Ronde - Gold Creek
Dallas
Dallas (part) - Ellendale
Dallas (part) - Rickreal - Orr Corner
Falls City
Fern Corner - Bridgeport - Airlie
Independence - Monmouth
Oak Grove - Bethel - Bethel Heights
Parker - Buena Vista - Hopville - Modeville
Salem-Keizer (part) - Eagle Crest Corner Zena - Lincoln
Valsetz
Willamina (part) - Buell - Fort Hill
Grass Valley - Moro
Rufus
Wasco
Bay City
Beaver - Hemlock - Sand Lake
Cloverdale - Hebo - Dolph - Winema Beach
Fairview
Garibaldi
Manzanita - Nehalem (part)
Nehalem (part) - Salmonberry
Neskowin
Netarts - (Netarts Bay)
37
Table 2—Block group aggregations in the Northwest Forest Plan region (continued)
Identifying
number
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
38
Block group aggregation namea
County
Oceanside - Cape Meares - Bayocean
Pacific City - Woods
Pleasant Valley - Blaine
Rockaway Beach
South Prairie
Tierra del Mar
Tillamook
Tillamook city (part) - Jordan Creek
Wheeler
Antelope - Shaniko
Celilo - Petersburg- Boyd
Chenoweth CDP - Rowena
City of the Dalles
Dufur
Maupin
Mosier
Ryan Corner
Tygh Valley - Pine Grove - Dant
Warm Springs CDP - Warm Springs Indian
Reservation
Banks
Chehalem - Middleton
Cherry Grove - (South Henry Hagg Lake)
Christie - Greenville - Starkey Corner
Cochran - Glenwood - Timber
Cornelius - Forest Grove
Farmington - Hazeldale - Jacktown
Gales Creek - Kansas City - Thatcher
Gaston
Laurel
Manning - Scofield - Tophill
Meacham Corner
Midway - Scholls
Mountaindale
North Plains
Sherwood
Stimson Mill
Wilsonville (part) - Tonquin
Amity
Bellevue
Briedwell - Winch
Carlton
Carlton (part) - Yamhill (part)
Dayton
Dewey - (Chehalem Mountain)
Dundee
Eola Crest - Hopewell - Yampo
Fairdale - Pike
Grand Ronde Agency - Midway
Lafayette
Lunnville - Cove Orchard - Dellwood - Wapato
Tillamook
Tillamook
Tillamook
Tillamook
Tillamook
Tillamook
Tillamook
Tillamook
Tillamook
Wasco
Wasco
Wasco
Wasco
Wasco
Wasco
Wasco
Wasco
Wasco
Wasco Jefferson
Washington
Washington
Washington
Washington
Washington
Washington
Washington
Washington
Washington
Washington
Washington
Washington
Washington
Washington
Washington
Washington
Washington
Washington
Yamhill
Yamhill
Yamhill
Yamhill
Yamhill
Yamhill
Yamhill
Yamhill
Yamhill
Yamhill
Yamhill
Yamhill
Yamhill
State
Number
of BGsb
Population,
1990
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
2
3
1
3
1
2
7
1
2
1
1
5
15
2
1
1
2
2
489
816
558
1,102
1,018
487
5,580
830
929
217
381
4,252
11,538
1,192
553
676
859
1,262
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
3
1
2
1
3
1
9
3
2
2
1
1
1
1
1
2
2
1
1
1
1
1
1
1
1
1
1
1
1
2
2
1
3,143
1,834
1,719
745
2,645
760
23,585
3,877
1,580
3,466
868
1,357
618
1,241
894
3,428
3,434
992
823
1,193
1,247
520
1,632
977
1,850
1,609
2,195
1,535
754
957
2,156
2,163
Table 2—Block group aggregations in the Northwest Forest Plan region (continued)
Identifying
number
Block group aggregation namea
County
State
Number
of BGsb
Population,
1990
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
McMinnville
McMinnville (part) - Orchard View
Newberg
Pleasantdale
Rex - (Parrett Mountain)
Sheridan
Sunnycrest
Unionvale - Wheatland
Willamina (part)
Yamhill
Hatton town
Keystone - Palm Lake - Rockwell - Tokio
Koren - Simensen - Bruce - Shano
Lind town
Moody - Marcellus - Paha
Othello
Ritzville
Washtucna town
Apricot
Badger - Kiona
Benton City
Benton City (part) - Gibbon
Finley CDP - Yellepit - Barian
North Prosser - Whistran - Chaffee
Prosser
West Richland
Whitcomb - Patterson - Plymouth
Holden - Lucerne - Sunnybank - (Lake Chelan)
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
13
1
10
1
1
4
1
1
1
1
1
1
1
2
1
8
3
1
2
1
4
1
6
1
5
2
1
18,975
1,429
14,517
678
1,850
5,139
1,181
807
1,209
978
515
333
585
713
467
8,730
1,773
487
2,187
1,727
4,148
480
5,467
1,814
5,270
3,371
539
806
807
808
809
810
811
812
813
814
815
816
817
818
Ardenvoir - Winesap
Cashmere
Chelan
Chelan (part) - Azwell
Coles Corner - Chiwaukum - Chumstick
Dryden
Entiat city
Greens Landing - Manson
Leavenworth
Malaga
Monitor
Peshastin
South Wenatchee CDP (part) - Wenatchee
Heights
Sunnyslope CDP - Wagnersville
Wenatchee - West Wenatchee CDP South Wenatchee CDP - Sunnyslope CDP
(part)
Winton - Nason Creek - Berne - Trinity
Agnew
Blyn
Carlsborg
Yamhill
Yamhill
Yamhill
Yamhill
Yamhill
Yamhill
Yamhill
Yamhill
Yamhill
Yamhill
Adams
Adams
Adams
Adams
Adams
Adams
Adams
Adams
Benton
Benton
Benton
Benton
Benton
Benton
Benton
Benton
Benton
Benton Chelan
Chelan
Chelan
Chelan
Chelan
Chelan
Chelan
Chelan
Chelan
Chelan
Chelan
Chelan
Chelan
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
2
1
6
6
1
1
1
1
3
4
1
1
1
401
638
6,045
4,161
645
761
652
910
2,173
3,864
1,031
581
790
Chelan
Chelan
WA
WA
1
1
1,562
1,220
Chelan
Chelan
Clallam
Clallam
Clallam
WA
WA
WA
WA
WA
30
6
1
2
4
26,268
548
1,128
1,566
3,906
819
820
821
822
823
824
39
Table 2—Block group aggregations in the Northwest Forest Plan region (continued)
Identifying
number
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
40
Block group aggregation namea
County
State
Number
of BGsb
Population,
1990
Crane
Dungeness
Elwha - Snug Harbor - Olympic Hot Springs (South Lake Crescent)
Forks
Jamestown
La Push - Mora
Neah Bay CDP - Makah Indian Reservation
Old Town
Ozette - Clallam Bay - Twin
Port Angeles city - Port Angeles East CDP
Quilayute - Shuwah - Sappho
R Corner - Little Oklahoma - King Hill
Sequim
Sequim city (part) - Port Williams - Washington
Harbor
Shadow - Coville - Fairholm - (North Lake
Crescent)
Alpine - Venersborg
Battle Ground
Blurock Landing - (Vancouver Lake)
Brush Prairie CDP
Camas
Camp Bonneville Military Reservation
Charter Oak
Creswell Heights - Ireland
Dole - Lucia
Etna - Fargher Lake - Highland
Good Hope
Hockinson
La Center
Little Elkhorn
Meadow Glade CDP
Pioneer
Portland-Vancouver UA (part) - Proebstal
Portland-Vancouver UA (part) - Salmon Creek
(part) - Knapp
Ridgefield
Sara
Washougal
Yacolt
Arial
Bunker Hill - Stella
Carrolls - Rose Valley - Vision Acres
Castle Rock
Coal Creek - Longview city (part)
Cougar - Woodland Park - Yale
Eufaula - Eufaula Heights - Longview (part)
Headquarters
Kalama
Kelso
Clallam
Clallam
WA
WA
1
1
1,132
1,494
Clallam
Clallam
Clallam
Clallam
Clallam
Clallam
Clallam
Clallam
Clallam
Clallam
Clallam
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
1
5
1
1
2
1
2
28
3
1
8
790
4,647
1,266
566
1,238
1,276
1,662
23,822
1,699
1,805
6,390
Clallam
WA
1
360
Clallam
Clark
Clark
Clark
Clark
Clark
Clark
Clark
Clark
Clark
Clark
Clark
Clark
Clark
Clark
Clark
Clark
Clark
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
2
1
5
2
5
15
1
1
1
1
1
2
2
2
1
1
1
1
1,717
1,767
9,316
642
5,719
12,259
1,308
2,054
1,851
1,139
2,085
3,099
1,598
3,830
1,890
2,122
1,609
1,553
Clark
Clark
Clark
Clark
Clark
Cowlitz
Cowlitz
Cowlitz
Cowlitz
Cowlitz
Cowlitz
Cowlitz
Cowlitz
Cowlitz
Cowlitz
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
1
3
1
7
3
1
1
3
4
1
1
1
1
4
19
4,916
3,647
1,481
7,651
4,630
1,135
471
2,476
3,407
1,352
618
1,179
709
3,312
15,055
Table 2—Block group aggregations in the Northwest Forest Plan region (continued)
Identifying
number
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
Block group aggregation namea
Kid Valley - Harrington Place Pigeon Springs- Toutle
Longview city - West Longview CDP LongviewHeights CDP West Side Highway CDP
Oak Point
Olequa
Pleasant Hill
Ryderwood
Sandy Bend
Silver Lake
Woodland city
Baird - McCarteney - Sims Corner
Bridgeport
Bridgeport town (part) - Brandts Landing Dyer - Beebe
Downing - Rocky Butte
East Wenatcheeá- East Wenatchee Bench
Leahy - Niles Corner - Osborne Corner
Mansfield
Orondo
Palisades - Appledale - Bonspur - Voltage
Rock Island
Waterville
Burr - Redd - Sagemoor
Glade - Eltopia
Kahlotus
Mathews Corner
Mesa (part) - Basin City - Edwards
Mesa (part) - Connell
Beverly - Schwana - Wanapum Village
Coulee City - Hartline
Ephrata
George
Gloyd - Mitchell
Grand Coulee - Electric City
Lakeview Park
Mae
Mattawa
Moses Lake - Moses Lake North CDP Cascade Valley CDP
Moses Lake city (part) - McDonald - Sieler
Naylor
Quincy
Quincy city (part) - Trinidad - Crater
Royal City
Soap Lake
Warden
Warden town (part) - Ritell - Tiflis - Barham
Wilson Creek - Krupp (aka Marlin)
Winchester
County
State
Number
of BGsb
Population,
1990
Cowlitz
WA
2
1,317
Cowlitz
Cowlitz
Cowlitz
Cowlitz
Cowlitz
Cowlitz
Cowlitz
Cowlitz
Douglas
Douglas
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
50
1
1
1
1
2
2
5
1
2
42,094
344
1,387
588
308
1,305
1,363
3,699
159
1,516
Douglas
Douglas
Douglas
Douglas
Douglas
Douglas
Douglas
Douglas
Douglas
Franklin
Franklin
Franklin
Franklin
Franklin
Franklin
Grant
Grant
Grant
Grant
Grant
Grant
Grant
Grant
Grant
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
1
1
18
1
1
1
1
2
3
1
1
1
1
2
3
1
2
6
1
1
3
1
1
1
523
787
17,468
361
442
767
349
1,744
2,089
653
675
381
2,012
2,586
2,556
704
1,292
5,728
1,226
626
2,252
1,263
1,219
2,323
Grant
Grant
Grant
Grant
Grant
Grant
Grant
Grant
Grant
Grant
Grant
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
17
1
1
3
1
2
3
1
1
1
1
21,581
805
1,346
3,894
1,217
3,074
1,579
1,669
1,009
813
1,138
41
Table 2—Block group aggregations in the Northwest Forest Plan region (continued)
Identifying
number
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
42
State
Number
of BGsb
Population,
1990
Grays Harbor
Grays Harbor
Grays Harbor
Grays Harbor
Grays Harbor
Grays Harbor
Grays Harbor
Grays Harbor
Grays Harbor
Grays Harbor
Grays Harbor
Grays Harbor
Grays Harbor
Grays Harbor
Grays Harbor
Grays Harbor
Grays Harbor
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
20
1
1
2
2
1
2
1
4
1
1
1
8
1
1
1
1
17,004
925
299
2,703
1,982
419
1,992
263
5,301
663
1,339
407
8,719
1,293
1,042
729
1,172
Grays Harbor
Grays Harbor
WA
WA
1
4
566
3,728
Grays Harbor
Grays Harbor
Grays Harbor
Grays Harbor
Grays Harbor
Grays Harbor
Grays Harbor
Grays Harbor
WA
WA
WA
WA
WA
WA
WA
WA
1
1
1
3
1
1
1
3
2,519
1,550
800
2,280
705
303
645
1,842
Grays Harbor Thurston
WA
2
1,721
Island
Island
Island
Island
Island
Island
WA
WA
WA
WA
WA
WA
5
1
5
2
4
5
2,322
980
4,742
2,321
5,452
3,304
Island
Island
WA
WA
2
1
1,406
424
Island
Island
Island
WA
WA
WA
3
2
1
1,775
744
928
Island
Island
Island
Island
WA
WA
WA
WA
1
2
22
1
776
1,142
32,271
498
Block group aggregation namea
County
Aberdeen
Aberdeen - Hoquiam
Aloha - Ocean Grove - Iron Springs - Carlisle
Central Park CDP
Cohassett - Ocosta - Grayland
Copalis Beach
Cosmopolis
Cosmopolis (part) - Junction City
Elma
Elma (part) - Satsop
Fuller - South Elma - Porter - Lankner
Gray’s Harbor
Hoquiam
Humptulips - Newton - Tulips - Gray Gables
McCleary
McCleary (part) - Hillgrove - Sine
McCleary (part) - Rayville - Garden City
Moclips - Sunset Beach - Highland Heights Pacific Beach
Montesano
Montesano (part) - Aberdeen (part) Brady - Grisdale
New London - Nisson - Greenwood - Wishkah
Ocean City - Sampson - Copalis Crossing
Ocean Shores
Quinalt - Neilton - Weatherwax
South Arbor - Markham
South Montesano - Arctic - Vesta - Weikswood
Westport
Oakville city - Chehalis Village CDP Chehalis Indian Res (part)
Bretland - Indian Beach (South Camano Island)
Camano
Clinton CDP
Cornet
Coupeville - (Naval Air Station)
Freeland CDP
Freeland CDP (part) - Baby Island Heights Saratoga
Greenbank
Juniper Beach - Sunrise Point
(aka Lona Beach) - (Livingston Bay)
Keystone
Langley
Langley city (part) - Freeland CDP (part) Bayview
Madrona Beach
Oak Harbor city - Ault Field CDP
Sunlight Beach
Table 2—Block group aggregations in the Northwest Forest Plan region (continued)
Identifying
number
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
1001
1002
1003
State
Number
of BGsb
Population,
1990
Island
WA
2
1,110
Jefferson
Jefferson
Jefferson
Jefferson
WA
WA
WA
WA
3
1
1
1
2,145
346
1,285
500
Jefferson
WA
1
392
Jefferson
WA
1
740
Jefferson
Jefferson
WA
WA
1
3
512
2,266
Jefferson
Jefferson
Jefferson
Jefferson
Jefferson
Jefferson
Jefferson
Jefferson Grays Harbor
King
King
King
King
King
King
King
King
King
King
King
King
King
King
King
King
King
King
King
King
WA
WA
WA
WA
WA
WA
WA
1
1
1
2
7
1
2
1,914
116
748
393
7,155
478
962
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
4
1
7
2
5
6
2
3
1
10
1
1
1
2
1
1
6
2
2
10
2
1,542
1,764
7,545
546
4,266
5,605
2,869
5,748
911
11,018
1,588
860
1,974
1,591
1,602
1,310
5,967
2,606
2,967
11,909
2,057
King
King
King
King
King
King
WA
WA
WA
WA
WA
WA
1
1
1
1
1
1
1,654
561
1,491
406
641
1,660
Block group aggregation namea
County
Utsalady - English Boom - Terrys Corner
Beaver Valley - Port Ludlow - Mats Mats Chimwaucan
Brinnon
Cape George Military Reservation
Duckabush
East Quilcene - Dabob - Camp Discovery Coyle
Fort Flagler - Nordland - (Marrowstone Island) (Indian Island)
Gardiner - Port Discovery - Uncas Discovery Junction
Hadlock-Irondale CDP
Hadlock-Irondale CDP (part) - Glen Cove Adelma Beach - Eaglemount
Hoh Indian Reservation
Leland
Oil City - Hoh - Clearwater
Port Townsend
Quilcene
Shine-Gri-La (aka Stine)
Taholah CDP - Quinault Indian Reservation
(Maury Island)
(Vashon Island)
Bagley Junction - Edgewick - Denny Creek
Bayne - Cumberland - (Green River)
Black Diamond
Carnation
Duvall
Ellisville - Ernies Grove
Enumclaw
Fall City CDP
Fall City CDP (part) - Pleasant Hill
Green River
Hobart - Atkinson
Issaquah city (part) - Fall City (part)
Issaquah city (part) - High Point
Maple Valley CDP
Mirrormount CDP
Newaukun
North Bend - Snoqualmie
Novelty - Stuart - Stillwater
Selleck - Kangley - Kanasket - Landsburg Trude
Skykomish
Spring Glen - Preston
Upper Preston - Kerriston
Wabash
Wilderness
43
Table 2—Block group aggregations in the Northwest Forest Plan region (continued)
Identifying
number
1004
1005
1006
1007
1008
1009
1010
1011
1012
1013
1014
1015
1016
1017
1018
1019
1020
1021
1022
1023
1024
1025
1026
1027
1028
1029
1030
1031
1032
1033
1034
1035
1036
1037
1038
1039
1040
1041
1042
1043
1044
1045
1046
1047
1048
1049
1050
44
Block group aggregation namea
County
Bangor - Olympic View
Kitsap
Bangor Trident Base C CDP
Kitsap
Burley
Kitsap
Fort Ward - South Beach
Kitsap
Holly - Hintzville - Crosby - Hite Center
Kitsap
Indianola CDP - Port Madison Indian
Reservation
Kitsap
Kingston CDP
Kitsap
Lofall
Kitsap
Olalla
Kitsap
Port Gamble - Four Corners - Breidsblick
Kitsap
Port Gamble Indian Reservation
Kitsap
Poulsbo
Kitsap
Poulsbo city (part) - Vinland
Kitsap
Scanda - Pearson - Virginia
Kitsap
South Colby - Southworth - Banner - Fragaria Kitsap
Streibel’s Corner
Kitsap
Suquamish CDP - Port Madison Indian
Reservation
Kitsap
Twin Spits - Hansville
Kitsap
Warrenville - Seabeck - Camp Wesley Harris
Naval Reservation
Kitsap
Wildcat Lake - Naval Depot Junction
Kitsap
Wildwood - Glenwood
Kitsap
Winslow city - (Bainbridge Island)
Kitsap
Cle Elum - South Cle Elum
Kittitas
Ellensburg
Kittitas
Horlick - Thorp
Kittitas
Kittitas city (part) - Regal
Kittitas
Kittitas city (part) - Renslow - Vantage
Kittitas
Levering - Yakima Firing Center
Kittitas
Martin - Easton - Lavender - Nelson
Kittitas
Roslyn
Kittitas
Roza - Umtanum
Kittitas
Thrall - East Kittitas - Beverly Junction - Hillside Kittitas
Appleton - Pitt
Klickitat
Bickleton - Sundale - Roosevelt - McCredie
Klickitat
BZ Corner - Husum - Panakanic - Snowden
Klickitat
Centerville - Swale
Klickitat
Dallesport - Murdock - Smithville - Warwick
Klickitat
Glenwood - Yakima Indian Reservation
Klickitat
Goldendale
Klickitat
Klickitat
Klickitat
Lyle - Klickitat Springs
Klickitat
Maryhill - Towal - Goodnoe Hills - Pleasant
Valley
Klickitat
Trout Lake
Klickitat
Wahkiacus - Blockhouse - Firwood
Klickitat
White Salmon - Bingen
Klickitat
Wishram - Wishram Heights
Klickitat
Adna - Claquato - Littell
Lewis
State
Number
of BGsb
Population,
1990
WA
WA
WA
WA
WA
1
1
3
1
1
1,753
4,426
5,711
592
1,472
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
2
5
2
2
1
1
7
1
2
2
1
1,733
3,495
2,360
3,110
1,025
555
7,889
1,080
3,277
5,569
1,353
WA
WA
3
1
3,105
1,256
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
3
1
3
11
4
18
1
1
3
3
1
4
1
1
1
1
1
1
1
1
4
1
1
4,461
1,655
3,344
15,254
2,476
17,587
733
800
1,124
417
582
1,888
389
1,146
548
505
763
361
1,001
517
3,659
722
665
WA
WA
WA
WA
WA
WA
1
1
2
5
1
2
965
973
1,156
4,378
403
1,874
Table 2—Block group aggregations in the Northwest Forest Plan region (continued)
Identifying
number
1051
1052
1053
1054
1055
1056
1057
1058
1059
1060
1061
1062
1063
1064
1065
1066
1067
1068
1069
1070
1071
1072
1073
1074
1075
1076
1077
1078
1079
1080
1081
1082
1083
1084
1085
1086
1087
1088
1089
1090
1091
1092
1093
1094
1095
1096
1097
1098
1099
1100
Block group aggregation namea
County
State
Number
of BGsb
Population,
1990
Alpha - Cinebar - Silver Creek
Bunker - Ceres - Dryden
Carlson - Mineral
Centralia city - Fords Prairie CDP
Chehalis
Cispus - Glenoma
Curtis
Doty - Klaber - Boistfort - McCormick
Evaline - Saint Urban
Klaus - Marys Corner - Salkum
Kopiah - Nulls Crossing
Lacamas
Morton
Mossyrock
Mossyrock city (part) - Bremer - Harmony
Napavine
Newaukum
Onalaska - Phillips
Packwood
Pe Ell
Randle - Silver Brook
Toledo city
Vader
Winlock
Agate - Graham Point
Allyn-Grapeview
Arcadia
Belfair
Dewatto
Forbes - Marmac - Stimson - (Kamilche Valley)
Forest Beach
Hartstene - Ballow - (Hartstene Is) (Squaxin Is) - (Hope Is)
Kamiliche - New Kamilche
Little Hoquiam - (Mason Lake)
Matlock - Dayton - Deckerville - Frisken Wye
Mohrweiss
Potlatch - Hoodsport - Eldon - Triton
Shelton
Skokomish CDP / Indian Reservation
Sun Beach
Sunset Beach
Tahuya
Union
Walkers Landing - Grant
Brewster
Brewster city (part) - Paradise Hill
Carlton - Methow
Cheesaw - Havillah - Bodie
Conconully
Cordell - Ellsford
Lewis
Lewis
Lewis
Lewis
Lewis
Lewis
Lewis
Lewis
Lewis
Lewis
Lewis
Lewis
Lewis
Lewis
Lewis
Lewis
Lewis
Lewis
Lewis
Lewis
Lewis
Lewis
Lewis
Lewis
Mason
Mason
Mason
Mason
Mason
Mason
Mason
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
1
1
1
19
12
1
1
1
1
3
1
1
3
2
1
1
1
1
3
1
2
2
2
2
4
4
1
2
2
1
1
635
979
625
17,695
9,211
1,132
1,568
890
907
3,680
883
1,686
2,013
1,347
698
1,294
1,246
968
1,351
779
1,806
2,186
2,020
1,885
2,214
2,519
476
1,968
418
749
765
Mason
Mason
Mason
Mason
Mason
Mason
Mason
Mason
Mason
Mason
Mason
Mason
Mason
Okanogan
Okanogan
Okanogan
Okanogan
Okanogan
Okanogan
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
1
1
3
2
1
2
16
1
2
1
2
1
2
2
1
1
1
1
1
598
1,475
684
3,348
821
1,464
14,115
618
2,748
827
628
517
1,389
2,175
481
310
599
263
1,004
45
Table 2—Block group aggregations in the Northwest Forest Plan region (continued)
Identifying
number
1101
1102
1103
1104
1105
1106
1107
1108
1109
1110
1111
1112
1113
1114
1115
1116
1117
1118
1119
1120
1121
1122
1123
1124
1125
1126
1127
1128
1129
1130
1131
1132
1133
1134
1135
1136
1137
1138
1139
1140
1141
1142
1143
1144
1145
46
Block group aggregation namea
Coulee Dam - Elmer City - (Colville Indian
Reservation)
Loomis - Enterprise (part)
Malott
Nespelem town - Nespelem Community
CDP - (Colville Indian Reservation)
Nighthawk - Chopaka
Okanogan
Okanogan (part) - Chillowist - (Colville Indian
Reservation)
Old Toroda - Wauconda - Aeneas - Syrnarep
Olema - Wakefield
Omak
Omak city (part) - North Omak CDP - (Colville
Indian Res)
Oroville
Pateros
Riverside
Ruby - Brown Lake
Starr
Tonasket
Tonasket town (part) - Janis - Barker
Twisp
Winthrop
Bruceport - Bay Center - Nemah Junction
Frankfort - Naselle - Nemah
Hilda - Pluvia - Willapa
Ilwaco
Ilwaco city (part) - Chinook - Knappton
Long Beach
Loomis - Oceanside
North Cove - Dexter by the Sea - Tokeland Heather
Ocean Park CDP
Raymond
Raymond city (part) - Brooklyn
Shoalwater Indian Reservation
South Bend
(McNeil Island: Federal Penitentiary)
Buckley - Wilkenson (part)
Croker
DuPont city
Eatonville
Fort Lewis CDP / Fort Lewis Military
Reservation
Fox Island CDP
Graham - Thrift
Herron - Home
Jims Corner
Johnsons Corner
Kapowsin - Tanwax - Electron - Ohop
State
Number
of BGsb
Population,
1990
Okanogan
Okanogan
Okanogan
WA
WA
WA
2
1
1
1,290
922
519
Okanogan
Okanogan
Okanogan
WA
WA
WA
2
2
4
1,401
1,392
3,211
Okanogan
Okanogan
Okanogan
Okanogan
WA
WA
WA
WA
1
1
1
6
723
707
506
5,265
Okanogan
Okanogan
Okanogan
Okanogan
Okanogan
Okanogan
Okanogan
Okanogan
Okanogan
Okanogan
Pacific
Pacific
Pacific
Pacific
Pacific
Pacific
Pacific
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
2
3
1
2
1
1
1
1
4
4
2
1
2
2
1
5
3
2,068
2,024
711
1,013
595
328
1,065
1,145
2,445
1,188
717
1,092
1,559
1,087
1,008
2,329
1,240
Pacific
Pacific
Pacific
Pacific
Pacific
Pacific
Pierce
Pierce
Pierce
Pierce
Pierce
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
3
8
5
1
1
3
1
6
1
1
5
753
2,522
3,638
839
129
1,969
1,188
7,708
1,362
625
3,902
Pierce
Pierce
Pierce
Pierce
Pierce
Pierce
Pierce
WA
WA
WA
WA
WA
WA
WA
2
2
3
1
1
4
1
22,224
1,984
3,988
1,275
811
5,759
1,172
County
Table 2—Block group aggregations in the Northwest Forest Plan region (continued)
Identifying
number
1146
1147
1148
1149
1150
1151
1152
1153
1154
1155
1156
1157
1158
1159
1160
1161
1162
1163
1164
1165
1166
1167
1168
1169
1170
1171
1172
1173
1174
1175
1176
1177
1178
1179
1180
1181
1182
1183
1184
1185
1186
1187
1188
1189
Block group aggregation namea
County
State
Number
of BGsb
Population,
1990
Longbranch - Lakebay
Maplewood - Purdy
McChord AFB CDP
McKenna
Minter - Wauna
Orting
Prairie Ridge CDP
Roy
South Prairie - Carbonado - Wilkeson (part)
Sunrise Beach - Glencove
Swede Hill
Vaughn - Sunshine Beach
Wilkeson (part) - Fairfax - Upper Fairfax Greenwater
Yoman - Johnson Landing
(Lopez Island)
(Orcas Island) - (Waldron Island)
(Shaw Island) - (Blakely Island) - (Decatur
Island)
Friday Harbor - (San Juan Island) - (Stuart
Island)
(Guemes Island) - (Sinclair Island) - (Cypress
Island)
Alger
Anacortes
Bay View
Belfast
Blanchard - Edison - Allen - Samish Island
Burlington
Cedardale
Clear Lake
Concrete
Fredonia - Rextown - Avon
Hamilton
La Conner
Lyman
Mansford - Van Horn
McMurray
Montborne - Big Lake - Baker Heights Day Creek
Mount Vernon
Sedro-Woolley
Skagit City - Conway - Milltown
Swinomish Indian Res - Shelter Bay CDP Snee Oosh CDP - Swinomish Village CDP
Whitmarsh Junction - Gibraltar - Dewey
Carson River Valley CDP
Carson River Valley CDP - Stabler - (Wind
River)
Hood - Underwood - Willard - Mill A
North Bonneville
Pierce
Pierce
Pierce
Pierce
Pierce
Pierce
Pierce
Pierce
Pierce
Pierce
Pierce
Pierce
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
2
4
1
4
2
2
7
1
1
2
2
3
1,803
5,670
4,543
4,894
3,419
2,787
9,767
507
1,573
825
2,559
3,294
Pierce
Pierce
San Juan
San Juan
WA
WA
WA
WA
2
1
3
5
685
562
1,518
3,199
San Juan
WA
1
269
San Juan
WA
8
5,049
Skagit
Skagit
Skagit
Skagit
Skagit
Skagit
Skagit
Skagit
Skagit
Skagit
Skagit
Skagit
Skagit
Skagit
Skagit
Skagit
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
1
1
13
1
1
3
8
1
2
3
1
1
2
1
1
1
557
839
12,989
848
944
2,798
9,674
859
1,477
1,355
1,644
988
1,261
897
1,287
931
Skagit
Skagit
Skagit
Skagit
WA
WA
WA
WA
2
19
11
1
1,578
21,069
12,072
962
Skagit
Skagit
Skamania
WA
WA
WA
2
2
2
2,285
1,523
2,111
Skamania
Skamania
Skamania
WA
WA
WA
1
1
1
409
1,205
901
47
Table 2—Block group aggregations in the Northwest Forest Plan region (continued)
Identifying
number
1190
1191
1192
1193
1194
1195
1196
1197
1198
1199
1200
1201
1202
1203
1204
1205
1206
1207
1208
1209
1210
1211
1212
1213
1214
1215
1216
1217
1218
1219
1220
1221
1222
1223
1224
1225
1226
1227
1228
1229
1230
1231
1232
1233
1234
1235
48
State
Number
of BGsb
Population,
1990
Skamania
Skamania
Skamania
Snohomish
Snohomish
Snohomish
Snohomish
Snohomish
Snohomish
Snohomish
Snohomish
Snohomish
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
2
2
2
5
2
1
2
1
1
1
1
4
75
1,858
1,730
5,810
1,494
1,072
1,840
1,294
1,174
2,063
1,137
4,676
Snohomish
Snohomish
Snohomish
Snohomish
Snohomish
Snohomish
Snohomish
Snohomish
Snohomish
Snohomish
Snohomish
Snohomish
Snohomish
Snohomish
Snohomish
Snohomish
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
1
1
1
2
2
2
13
2
7
1
12
3
4
11
4
1
1,233
1,308
599
1,376
2,721
2,539
17,761
2,416
10,436
1,133
15,219
3,670
5,120
14,560
5,434
1,044
Snohomish
Snohomish
Snohomish
Snohomish
Snohomish
Snohomish
Snohomish
Thurston
Thurston
Thurston
Thurston
Thurston
Thurston
Thurston
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
2
4
1
1
7
1
1
1
1
3
1
4
3
3
1,362
3,665
1,286
1,249
5,741
1,510
571
333
837
4,189
1,173
2,914
3,447
3,719
Thurston
Thurston
Thurston
WA
WA
WA
1
1
3
914
2,299
3,182
Thurston
WA
1
774
Block group aggregation namea
County
Northwoods
Prindle
Stevenson
Arlington
Arlington Heights
Cicero - Oso - Halterman - Rowan
Darrington
Florence - Silvana Terrace
Forest Glade
Gold Bar
Granite Falls
Granite Falls town (part) - Hyland - Lochsloy
Granite Falls town (part) - Robe - Verlot Silverton
High Rock - (State Reformatory Farm No. 2)
Index
Jamieson Corner - (Three Lakes)
Jordan - Riverside
Lake Goodwin CDP
Lake Stevens city - West Lake Stevens CDP
Machias
Maltby - Turner Corner - Clearview - Cathcart
McKees Beach
Monroe city
Pilchuck - Bryant
Smokey Point CDP
Snohomish
Stanwood
Stanwood city (part) - Norman - Silvana
Stimson Crossing CDP - Tulalip Indian Res Military Res
Sultan town (part)
Sultan town (part) - Startup
Trafton
Tulalip - Tulalip Indian Reservation
Warm Beach
White Horse - Forston - Swede Heaven - Hazel
Bordeaux - Mima
Bucoda
Delphi
East Olympia
Fort Lewis Military Reservation (part)
Four Corners
Grand Mound CDP
Helsing Junction - Michigan Hill Independence
Kellys Corner
Maytown - Littlerock - South Union
Nisqually Indian Res - Fort Lewis Military
Res (part)
Table 2—Block group aggregations in the Northwest Forest Plan region (continued)
Identifying
number
1236
1237
1238
1239
1240
1241
1242
1243
1244
1245
1246
1247
1248
1249
1250
1251
1252
1253
1254
1255
1256
1257
1258
1259
1260
1261
1262
1263
1264
1265
1266
1267
1268
1269
1270
1271
1272
1273
1274
1275
1276
1277
1278
1279
1280
Block group aggregation namea
Olympia - Tumwater - Lacey - TanglewildeThompson CDP
Plumb - Offutt Lake
Rainier town
Ranier (part) - Skoomkumchuck - Western
Junction
Ranier (part) - Vail
Rochester CDP
Saint Clair
Schneiders Prairie - Elizan Beach - (Summit
Lake)
Sunnydale
Sunrise Beach - Gravelly Beach - Edgewater
Beach
Tenino
Yelm - North Yelm CDP
Brookfield - Grays River - Oneida
Cathlamet
Skamokawa - Sleepy Hollow
Ash - Port Kelley - Walulla
Burbank CDP
Gardena - Reese - Touchet
Hadley - Rulo - Sapolil
Lowden - Mojonier
Prescott - (Eureka Flat) - (Snake River)
Waitsburg city
Waitsburg city (part) - Dixie - Kooskooskie
Walla Walla - College Place - Walla Walla
East CDP - Garrett CDP
Acme - Comar - Clipper - Van Zandt
Bellingham
Blaine city - Birch Bay CDP
Cedarville - Goshen - Wahl
Custer
Delta
Deming - (Sumas Mountain)
Everson city (part) - Greenwood
Ferndale
Glacier - Kendall - Kulshan - Columbia
Laurel - Victor
Lummi Indian Reservation
Lummi Island
Lynden
Lynden (part) - Northwood - Clearbrook
Marietta-Alderwood CDP - Ferndale city (part)
Nooksack - Everson
Noon - Van Wyck
Point Roberts - (U.S. Customs)
Saxon - Doran - Wickersham
Sudden Valley CDP
Number
of BGsb
Population,
1990
County
State
Thurston
Thurston
Thurston
WA
WA
WA
105
1
1
114,806
1,469
924
Thurston
Thurston
Thurston
Thurston
WA
WA
WA
WA
1
1
3
1
1,066
753
2,796
1,110
Thurston
Thurston
WA
WA
3
2
2,502
1,805
Thurston
Thurston
Thurston
Wahkiakum
Wahkiakum
Wahkiakum
Walla Walla
Walla Walla
Walla Walla
Walla Walla
Walla Walla
Walla Walla
Walla Walla
Walla Walla
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
2
2
4
1
4
2
2
2
1
1
1
1
1
1
2,343
2,530
5,269
831
2,141
355
967
2,099
759
540
761
668
1,133
821
Walla Walla
Whatcom
Whatcom
Whatcom
Whatcom
Whatcom
Whatcom
Whatcom
Whatcom
Whatcom
Whatcom
Whatcom
Whatcom
Whatcom
Whatcom
Whatcom
Whatcom
Whatcom
Whatcom
Whatcom
Whatcom
Whatcom
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
38
1
32
12
1
1
1
1
1
8
3
4
3
1
5
2
1
4
2
4
2
1
40,691
1,173
63,557
9,186
1,469
1,504
1,879
1,152
1,916
9,999
1,279
5,094
3,164
610
7,655
1,992
2,654
4,937
2,283
916
488
2,414
49
Table 2—Block group aggregations in the Northwest Forest Plan region (continued)
Identifying
number
State
Number
of BGsb
Population,
1990
Whatcom
Whatcom
WA
WA
1
1
1,005
1,305
Whatcom Skagit
Yakima
Yakima
Yakima
Yakima
Yakima
Yakima
Yakima
Yakima
Yakima
Yakima
Yakima
Yakima
Yakima
Yakima
Yakima
Yakima
Yakima
Yakima
Yakima
Yakima
Yakima
Yakima
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
2
1
1
3
1
1
2
2
1
8
3
3
1
1
2
4
2
1
1
1
8
13
3
867
531
1,791
1,451
314
528
1,630
2,136
707
10,250
2,991
2,556
637
1,526
2,457
3,622
1,117
385
601
606
12,568
15,708
2,153
Yakima
Yakima
Yakima
WA
WA
WA
6
3
4
6,537
1,804
7,529
Yakima
Yakima
Yakima
WA
WA
WA
3
4
1
1,653
5,147
1,717
Yakima
WA
67
81,555
Yakima
Yakima
WA
WA
20
5
12,622
3,577
148
158
20
217,915
212,694
28,739
912
180
1,162,738
193,004
Block group aggregation namea
County
1282
Sudden Valley CDP (part) - Sunnyside Blue Canyon - (South Lake Whatcom)
Sumas
1283
Concrete town (part) - (North Cascades)
1284
1285
1286
1287
1288
1289
1290
1291
1292
1293
1294
1295
1296
1297
1298
1299
1300
1301
1302
1303
1304
1305
1306
American River - Cougar Valley - Nile
Brace - Fruitvale CDP (part) - Selah (part)
Buena
Cowiche
Donald
Emerald - Nass
Eschbach - Gleed
Flint - Sawyer
Grandview city
Granger
Gromore
Holtzinger
Liberty
Mabton city - Byron
Moxee City
Naches
Outlook
Pinecliff - Wenas
Rimrock - Tampico
Selah
Sunnyside
Tasker - Weikel - (Naches Heights)
Terrace Heights CDP - Fairview-Sumach CDP
(part) - Yakima city (part)
Tieton
Toppenish - Yakima Indian Reservation
Toppenish (part) - Yethonat - Yakima Indian
Reservation
Wapato - Yakima Indian Reservation
Wiley City
Yakima - Union Gap - Fruitvale CDP - West
Valley CDP
Yakima Indian Res - Harrah town - White
Swan CDP - Satus CDP
Zillah
1281
1307
1308
1309
1310
1311
1312
1313
1314
Metropolitan block group aggregationsc
1
San Francisco
2
Santa Rosa
3
West Sacramento
4
Portland-Vancouver
5
50
Eugene – Springfield
Marin
CA
Sonoma
CA
Yolo
CA
Washington,
Clackamas,
Multnomah,
Clark
OR, WA
Lane
OR
Table 2—Block group aggregations in the Northwest Forest Plan region (continued)
Identifying
number
Block group aggregation namea
County
6
7
Salem – Keizer
Richland – Kennewick – Pasco
8
Seattle
9
10
Bremerton
Tacoma
Polk
Benton,
Franklin
Snohomish,
King
Kitsap
Pierce
State
Number
of BGsb
Population,
1990
OR
94
158,537
WA
128
116,167
WA
WA
WA
1,549
80
443
1,749,913
112,524
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.
51
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