United States

Department

of Agriculture

Forest Service

Rocky Mountain

Research Station

General Technical

Report RMRS-GTR111WWW

August 2003

United States State-Level

Population Estimates:

Colonization to 1999

David P. Coulson

Linda Joyce
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Coulson, David P.; Joyce, Linda. 2003. United States state-level population estimates:

Colonization to 1999. Gen. Tech. Rep. RMRS-GTR-111WWW. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 55 p.

Abstract: The U.S. landscape has undergone substantial changes since Europeans first

arrived. Many land use changes are attributable to human activity. Historical data concerning these changes are frequently limited and often difficult to develop. Modeling historical

land use changes may be neccessary. We develop annual population series from first European settlement to 1999 for all 50 states and Washington D.C. for use in modeling land

use trends. Extensive research went into developing the historical data. Linear interpolation was used to complete the series after critically evaluating the appropriateness of linear

interpolation versus exponential interpolation.

Authors

David Coulson, MATCOM, Fort Collins, CO.

Linda Joyce, Rocky Mountain Research Station, Fort Collins, CO.

Acknowledgments

RPA, Forest Service, United States Department of Agriculture funded this work.
Contents

Introduction ...................................................................................................................... 1

Background ................................................................................................................... 1

Availability of historical information on United States populations ............................... 1

Objective ....................................................................................................................... 2

Methodology .................................................................................................................... 3

Series development ...................................................................................................... 3

Data sources ................................................................................................................. 3

Historical data series .................................................................................................... 4

Evaluation of interpolation methodologies ................................................................... 6

Test 1 - State and national level census data, 1790 to 1990 .................................. 7

Test 2 - Census annual estimates interpolation between 1900 and 1990 .............. 7

Test 3 - Census annual estimates interpolation between censuses ....................... 8

When might exponential interpolation be better? .................................................... 8

Results ............................................................................................................................ 12

Interpolation ................................................................................................................ 12

The data ...................................................................................................................... 12

Conclusion .................................................................................................................. 17

References ..................................................................................................................... 18

Book ............................................................................................................................ 18

Government documents ............................................................................................. 19

Journal articles ........................................................................................................... 19

Electronic media ......................................................................................................... 20

Census ................................................................................................................... 20

General................................................................................................................... 21

States ..................................................................................................................... 21

Appendices

A Development of difference measure between exponential and

linear interpolation ............................................................................................... 24

B Proof linear interpolation is always greater than or equal to exponential

interpolation under strictly increasing conditions ................................................ 28

C State level series development .............................................................................. 30

Introduction ............................................................................................................ 30

Alabama ................................................................................................................. 31

Alaska..................................................................................................................... 31

Arizona ................................................................................................................... 32

Arkansas ................................................................................................................ 33

California ................................................................................................................ 33

Colorado ................................................................................................................. 34

Connecticut ............................................................................................................ 35

Delaware ................................................................................................................ 35

Florida .................................................................................................................... 35

Georgia................................................................................................................... 36

Hawaii ..................................................................................................................... 36

Idaho ...................................................................................................................... 36

Illinois ..................................................................................................................... 37

Indiana.................................................................................................................... 37

Iowa ........................................................................................................................ 37

Kansas ................................................................................................................... 37

Kentucky ................................................................................................................. 37

Louisiana ................................................................................................................ 38

Maine...................................................................................................................... 38

Maryland ................................................................................................................ 38

Massachusetts ....................................................................................................... 38

Michigan ................................................................................................................. 38

Minnesota ............................................................................................................... 39

Mississippi .............................................................................................................. 39

Missouri .................................................................................................................. 39

Montana ................................................................................................................. 40

Nebraska ................................................................................................................ 40

Nevada ................................................................................................................... 40
New Hampshire...................................................................................................... 41

New Jersey ............................................................................................................. 41

New Mexico ............................................................................................................ 41

New York................................................................................................................. 42

North Carolina ........................................................................................................ 42

North Dakota .......................................................................................................... 42

Ohio ........................................................................................................................ 42

Oklahoma ............................................................................................................... 42

Oregon ................................................................................................................... 43

Pennsylvania .......................................................................................................... 43

Rhode Island .......................................................................................................... 43

South Carolina ....................................................................................................... 43

South Dakota ......................................................................................................... 43

Tennessee .............................................................................................................. 44

Texas ...................................................................................................................... 44

Utah ........................................................................................................................ 45

Vermont .................................................................................................................. 45

Virginia ................................................................................................................... 45

Washington ............................................................................................................ 45

West Virginia .......................................................................................................... 45

Wisconsin ............................................................................................................... 46

Wyoming ................................................................................................................ 46

Population Data Set

ASCII download available at: http://www.fs.fed.us/rm/pubs/rmrs_gtr111/us_population_est.txt

Excel download available at: http://www.fs.fed.us/rm/pubs/rmrs_gtr111/us_population_est.xls
USDA Forest Service RMRS-GTR-111WWW 1

United States State-Level Population Estimates:

Colonization to 1999

David P. Coulson

Linda Joyce

Introduction

Background

The United States landscape has undergone substantial changes since the

first European settlements. Ecological models used to examine the potential

impact of climate change suggest the likelihood of substantial future changes on

the United States landscape (Joyce and Birdsey 2000, McGuire and others

2001). The role that historical land management has had on changes in the

United States landscape has not been considered in these ecological models.

Casperson and others (2000) suggest that historical land management may

have masked any impact that recent climate changes may have caused.

Historical data series reflecting these landscape changes are limited and often

difficult to develop, in part, due to the lack of historical records. The lack of

historical land use information, particularly at levels below the national level, has

made it difficult to test this idea using ecological models examining the impact of

climate change. Ramankutty and Foley (1999) developed historical information

on the area of cropland converted from forestland and the type of crops planted

annually. Unfortunately, recording forest harvest area was not a concern of the

early settlers facing a seemingly endless forest. The few early forest harvest

records that exist are primarily product oriented, such as barrels of pitch or

number of ship masts. Houghton and others (1987) used aggregations of this

information to determine the area disturbed through harvest at large spatial

scales. However, at finer spatial scales, these records are frequently plagued

with missing values, inconsistencies, unknown collection methodologies,

measurement errors, varying standards of measure, and in some cases, even

fraudulent reporting. Thus, the paucity of information at finer spatial scales leads

us to model estimates of resource use using human population level as one of

our data sources.

Human population data is used in ecological and land-use models. Some

examples are: Berry and others 1996; Brown 2001; Campbell 2001; Irwin and

Geoghegan 2001; Jenerette and Wu 2001; Reynolds and Pierson 1942;

Sandewall and others 2001; Schumacher 2001; Serneels and Lambin 2001;

Stéphenne and Lambin 2001; and Veldkamp 1997. Further, Reynolds and

Pierson (1942) use population levels to estimate fuel wood consumption from

1630 to 1930. This work implies that detailed spatial and temporal population

series could be used to estimate resource use on an annual basis from 1600 to

1999. We presume that the magnitudes of these landscape changes are related

to the nonindigenous population levels.

Availability of Historical Information on U.S. Populations

While detailed U.S. population series exist for recent years (1900 to present),

data becomes increasingly scarce for earlier periods, especially before 1790.

Further, the population estimates frequently used are those of the American

colonies, which exclude French and Spanish colonies. For example, the 1630
2 USDA Forest Service RMRS-GTR-111WWW

population estimate of the American Colonies (United States Bureau of Census

1975) is 4,646. This estimate excludes Florida and New Mexico, which we

estimate had a population of 2,032 at the time. The 1780 population estimate of

the American Colonies (United States Bureau of Census 1975) is 2,780,369 and

excludes the population of other areas of what would become the United States

(16 other states with settlements at the time), which we estimate to have been

some 445,985 persons, or 13.8 percent of the total U.S. population. The

estimates are for the contiguous states and only those indigenous peoples

accounted for by the colonists. Hawaiian, Alaskan, and those Native Americans

of the contiguous states are excluded and have conservative estimates of

300,000 in 1777 (Castle 1917), 72,600 in 1740 (Denevan 1976), and 879,400 in

1600 (Denevan 1976) respectively. Detailed temporal and spatial population

series for the entire present day United States from first European settlement to

present are rare.

Prior to 1900, many annual population values are missing. As a result, annual

state level population series development requires estimation of population

numbers for intervening years, generally through interpolation. Linear

interpolation is a commonly used method to estimate missing values. Human

population growth is typically considered an exponential process; however, as

the United States was settled and population grew, factors other then natural

birth and death rates influenced state level population changes. For example,

immigration and emigration strongly impacted population levels in parts of the

United States, such as when easterners pushed westward to seek their financial

futures and during the California gold rush. We explore the possible use of

exponential interpolation, before opting to use linear interpolation. We recognize

that other mathematical processes might fit the data better, but exploring those

options is beyond the scope of this work.

Objective

Our objective was to develop an annual population data series from the first

nonindigenous settlements to 1999 for each present day state. These series can

then be used to model landscape change presumed to be a direct result of

activities associated with and subsequent to the settlement of nonindigenous

people. Aboriginal peoples were utilizing resources at the time of European

discovery and likely modified the landscape, such as clearing land for

agriculture, setting fires, and so forth. We are presuming that this influence on

the vegetation cover of the American landscape differed from the settlers who

came to the continent in the 1600s. And we presume that the magnitudes of

landscape changes after the settlements of the 1600s to present day are related

to those nonindigenous population levels. Aboriginal populations prior to, at the

time of, and subsequent to first European settlement were not uniformly

included in the earlier population data. Our assumption is that when the

aboriginals were counted and recorded by the settlers in the historical data,

these individuals were an integral part of life and land use of the settlement.

Slaves, both indigenous and nonindigenous, appear to have been fully recorded

and are included in the series. Thus, we assume that all persons counted by the

settlers were a part of the settlement and, as such, represented the total

population that was changing the surrounding land cover and land use. Thus,

the population values for early years of the series developed here may not fully

represent all people living in the state at that time. As time progresses,

increasing numbers of aboriginals are counted until at some unknown point all

peoples are fully counted and presumably having a similar impact on the land.

We provide annual U.S. state-level population estimates from the first

European settlement (Fort Caroline, Florida, 1564) to 1999. These data are

downloadable either as an Excel or an ASCII comma delimited text file. We

caution the user to understand the caveats and methodologies associated with
USDA Forest Service RMRS-GTR-111WWW 3

this data before downloading. The values presented are estimates, representing

the magnitude and distribution of nonindigenous settlers during the early years

and, as time progresses, all peoples in the United States. Developed to help

quantify historical land use changes, these estimates represent general trends,

and are not, and should not be considered “exact” head counts. It is

recommended that the user read and understand the methodologies used in

developing these estimates before using them for any purpose. While

considerable care was given to the development of this series, the user is fully

responsible for any issues that arise from the use of these data. The authors

make no claims or warranties as to the suitability of these estimates for any

purpose. There are no copyright restrictions, and we ask only that appropriate

credit be given. While extensive research went into the development of this

series, it is by no means exhaustive. We consider this series a “work in

progress.” It is subject to revision as new information is brought to light. To that

end, we welcome input that improves the accuracy of these estimates.

Methodology

Series Development

Our objective was to construct an annual time series of state-level population

estimates from the first European settlement in the area now known as the

United States to 1999. To do this, we first established the temporal and spatial

availability of federal census. Second, we included population values from other

historical data, and lastly, interpolated missing values between years. The

federal censuses and other censuses form a population series for only the

census years. Using other historical information, we established a time series of

population values from 1564 (first settlement) to 1999 with intermittent years

missing. Two different interpolation methodologies were explored as to which

method resulted in the best fit for the missing years. A detailed procedural

description follows.

Data Sources

The following general sources were used in the development of the

population series. They are listed in descending order of preference. A full listing

of sources is provided in the references.

United States Federal censuses began in 1790. Census values are used over

all other sources. Table 1 shows the decade when the first federal census was

taken for a state. Additionally, we use Census Bureau annual population

estimates for all states from 1900 to 1999 (Alaska and Hawaii from 1950). Prior

to 1790 we use the United States Bureau of Census estimates where available.

Greene and Harrington’s (1932) work proved extremely valuable and was

generally given preference over other sources. Their work is a collection of

population estimates, census values, and other population related data, such as

polls, tax rolls, or military rolls, and is fully referenced. Wilson (1998) was used

as the primary source for date of first settlement. Further, many texts on state

histories were reviewed. In addition to hardcopy references, we made extensive

use of internet sources, primarily historical narratives. From these narratives we

obtained not only numbers, but also information on significant events such as

gold rushes, massacres, settlement dates, land rushes, wars, and other

significant historical events that impacted population levels. We used this

knowledge as a means to estimate the timing and magnitude of shifts in

population, primarily for times prior to 1790 and occasionally times between

censuses.
4 USDA Forest Service RMRS-GTR-111WWW

Historical Data Series

Starting with United States Bureau of Census data and estimates, we fill in as

many years as possible with data from 1564 to 1999. This includes decadal

estimates prior to 1790. Additional values are then added on a state-by-state

basis using the following general procedures. These values and their sources

are presented in Appendix C.

We establish date of first settlement for each state and the initial settlement

size. The population prior to first settlement is assumed to be zero. First

Table 1—Year of first European settlement, first federal census, and statehood.

First First U.S.

State settlement census Statehood

Alabama 1702 1800 1819

Alaska 1784 1880 1959

Arizona 1687 1870 1912

Arkansas 1686 1810 1836

California 1769 1850 1850

Colorado 1825 1860 1876

Connecticut 1634 1790 1788

Delaware 1631 1790 1787

Florida 1564 1830 1845

Georgia 1733 1790 1788

Hawaii 1778 1900 1959

Idaho 1809 1870 1890

Illinois 1675 1810 1818

Iowa 1833 1840 1846

Kansas 1821 1860 1861

Kentucky 1763 1790 1792

Louisiana 1714 1810 1812

Maine 1604 1790 1820

Maryland 1634 1790 1788

Massachusetts 1620 1790 1788

Michigan 1669 1810 1837

Minnesota 1689 1850 1858

Mississippi 1699 1800 1817

Missouri 1735 1810 1821

Montana 1828 1870 1889

Nebraska 1822 1860 1867

Nevada 1849 1860 1864

New Hampshire 1623 1790 1788

New Jersey 1633 1790 1787

New Mexico 1598 1850 1912

New York 1624 1790 1788

North Carolina 1650 1790 1789

North Dakota 1801 1850 1889

Ohio 1788 1800 1803

Oklahoma 1889 1890 1907

Oregon 1805 1850 1859

Pennsylvania 1643 1790 1787

Rhode Island 1636 1790 1790

South Carolina 1670 1790 1788

South Dakota 1817 1870 1889

Tennessee 1768 1790 1796

Texas 1682 1850 1845

Utah 1828 1850 1896

Vermont 1724 1790 1791

Virginia 1607 1790 1788

Washington 1845 1850 1863

West Virginia 1726 1790 1889

Wisconsin 1665 1840 1848

Wyoming 1834 1870 1890
USDA Forest Service RMRS-GTR-111WWW 5

settlement is defined as: the first permanent European presence in a state

(present day political boundaries). While simple in definition, the date of first

settlement is not always clear, as the distinction among explorers, traders,

trappers, missionaries, and settlers and their activities is often blurred. As

modern boundaries were not established, settlement locations were sometimes

obscure. While initial settlement size was occasionally found, it was frequently

necessary to estimate the size of the initial settlement. While somewhat

subjective, these estimates were made after reading historical accounts of the

event and considering the initial size of other settlements, population levels after

initial settlement, size and numbers of ships, and other accounts.

Consider for example, the following historical account of New Mexico’s first

settlement from the New Mexico fact book online at http://www.edd.state.nm.us/

FACTBOOK/PDF/hist.pdf.

“The man chosen to establish the first settlement in New Mexico

was Don Juan de Onate, who set out for New Mexico in 1598 with

400 men (some 130 brought wives and children), 10 Franciscan

friars, 7,000 head of livestock and 83 carts. They moved north along

the Rio Grande to San Juan. He established the first settlement there

on July 11, 1598.”

From this account we assume there were 130 families of size 4.5. Thus, the

initial settlement is calculated to be 865: 270 men (400 less 130) plus 10 friars

plus 715 in families (130 times 4.5). We use 4.5 in this instance, rather then 5.5

family size suggested by Felt (referenced in Greene and Harrington 1932) under

the assumption family size would be smaller at the time of settlement versus an

established settlement. Lower and upper bounds for this estimate are as follows.

The minimum would be 400 men plus 10 friars plus 130 (women and children,

family size of 2) or 540. This estimate seems unrealistically low, due to the small

family size assumption. The upper bound could be any value if we assumed

ridiculously high family sizes. However, if we assume a realistic family size, say

6, and interpret “some” to mean at least 130 women, then we would estimate an

initial population of 1,114. Further, we note that this account does not state

whether or not Native Americans were included in this initial settlement, a

common practice in early Spanish settlements, and likely in this case given the

friars’ presence. Additionally, many early explorers/traders/trappers/settlers were

known to take native wives. Thus, while the actual settlement size is not known,

we do have a sense of magnitude and are able to make an estimate.

After establishment of first settlement date and size, further research was

conducted to fill in the missing years. As with the initial settlement, some

subjectivity was required in sifting through the various sources. For consistency,

Coulson made all “subjective” determinations. The following general approach

was taken. Values from nonfederal censuses, head counts, rosters, rolls,

houses, and similar records were generally accepted “as is” unless strong

evidence suggested something was awry. Greene and Harrington (1932)

provided many such counts and estimates, counts generally being preferred

over estimates. In cases of non-census counts, a conversion factor was applied

to the count to obtain an estimate of the population at the time. For example,

Felt estimates that each house counted was equivalent to 7.15 persons. Table 2

provides examples of the conversion factors given in Greene and Harrington

(1932). There were cases where we had a time series, a tax roll for example,

that overlapped census values or defensible population estimates. We then

“linked” the two sources and used the trend of the count data to obtain

population estimates over that period, effectively calculating a series specific

conversion factor.

When count data were unavailable, we then considered population estimates,

ignoring any estimates in which we lacked confidence in their validity. For

example, Sheridan (1995) estimated the population of Texas to be 10,000 in

1830, up from 4,155 in 1809 (non-federal census). This is a reasonable estimate
6 USDA Forest Service RMRS-GTR-111WWW

in that from 1823 to 1830 the Mexican government permitted extensive

American settlement. All counts and estimates found were checked for

reasonableness. The assumption is that interim population values (between

census years for example) are between the endpoints in magnitude, unless

there was strong evidence to the contrary. For example, New York has United

States Bureau of Census estimates of 1,930 and 4,116 for years 1640 and 1650

respectively. If a source had an estimate of 6,000 in 1641, we would be

suspicious of its validity unless there was collaborating evidence to support such

a sudden shift in population, such as the documented arrival of large numbers of

colonists. We would also want to document the losses from 1641 to 1650.

The data reflect all peoples the settlers considered a part of their colony,

including slaves, who were always counted, and some aboriginal peoples. We

assume that if the aboriginals were counted and recorded by European settlers,

then they were an integral part of the European settlement and subsequently

were changing the landscape in a manner similar to the European settlers.

Therefore they are included in the data. However, aboriginal populations prior to

first settlement are not included in this data, nor are aboriginal population

estimates made specifically of aboriginals living separately and independently of

European settlers. We justify this approach in that these data were developed

for the express purpose of modeling land use change, presumed to be a result

of European settlement.

Evaluation of Interpolation Methodologies

Developing a database of annual state population estimates for each state

(and DC) from its initial European settlement to 1999 requires 14,080 values.

The Bureau of Census provides all values from 1900 to 1999, except for Alaska

and Hawaii. We developed 1,647 additional values based on available reliable

sources for the period from first settlement to 1900 (out of 9,041 possible), or 18

percent. All remaining values were filled in using linear interpolation.

Historical human population change plotted over time is generally an

“exponential” growth curve. This questions the appropriateness of linear

interpolation. Would exponential interpolation be a better approach? To answer

this question we conducted three empirical tests on the two interpolation

methods (linear and exponential), using the two existing data series from the

United States Bureau of Census: the state-level decadal census data 1790 to

1990 and the annual state-level census estimates from 1900 to 1990. In all three

tests we interpolate linearly and exponentially between the series starting and

ending values for each state. The sum of squared differences are calculated for

each method and compared. The premise is that the smaller sum of squares

represents the better fit to the data and thus is the better interpolation method

had it been necessary to interpolate the “known” data.

Table 2—Conversion factors of counts.a

Militia Polls, tax lists Familiesb Houses

All Regions 5:1 6:1 7:1

North 4:1

South 3:1

Feltc 5.33:1 4:1 5.5:1 7.15:1

aSource: Greene and Harrington (1932).

b1790 Census average family was 5.7.

c

Felt’s work (a historian) was our primary choice for conversion factors.
USDA Forest Service RMRS-GTR-111WWW 7

Test 1 - Census, interpolate 1790 to 1990 and match decades

(census values)

We interpolate between the initial census value and the 1990 census value

for each state and the national total. Figure 1 compares the two methods to the

actual data for national totals. The actual data falls between the two interpolation

methods. Exponential interpolation provided the “best” fit in the case of national

totals. However, examination of the sum of squared differences for each method

at the state level showed that linear interpolation fit the actual decadal census

data better for 61 percent of the states. See table 3.

Table 3—Interpolation comparison resultsa for the 50 states and Washington

DC.

Census Interpolate Census Estimates Census Estimates

1790 to 1990 Interpolate 1900 to 1990 Interpolate by Decade

Match Decades Match Annually Match Annually

Best fitb Percentc Best fit Percent Best fit Percent

Linear 31 61 29 57 33 65

Exponential 20 39 22 43 18 35

aIncludes Washington DC.

bSmallest sum of squared differences between data and interpolation method.

c

Percent of Cases method fits best, out of a possible 51.

0

50

100

150

200

250

1790 1810 1830 1850 1870 1890 1910 1930 1950 1970 1990

Year

Census Linear Exponential

Figure 1—Interpolation between the 1790 and 1990 United States censuses by decade

and actual census data.

Test 2 - Census annual estimates interpolate between 1900 and

1990 matching annually

We interpolate linearly and exponentially between the population values in

1900 and 1990 for all states, Washington DC (1950 to 1990 for Alaska and

Hawaii), and national totals. As previously, the actual values for the national
8 USDA Forest Service RMRS-GTR-111WWW

totals generally fall between the two interpolation methods and exponential fits

best. See figure 2. Examination of the state level interpolations shows that linear

interpolation fit the census estimates better for 57 percent of the states. See

table 3.

Test 3 - Census annual estimates interpolating between censuses

The decadal census values are known values, so a more realistic comparison

is interpolation between the decadal census values compared to census

estimates. Figure 3 illustrates that when short periods are used, both methods

produce similar results. In this comparison, linear interpolation produces a better

fit for 65 percent of the states over the entire period, table 3. When we look at

each individual decade (449 decadal intervals) we find, individually, that 55

percent fit better using linear interpolation.

Linear interpolation “fits” the known data more frequently then exponential,

suggesting that the use of linear interpolation is generally more appropriate.

Exponential interpolation’s fit is “better” frequently enough to raise the question, “Is it

possible to determine when exponential interpolation would provide a better fit?”

When might exponential interpolation be better?

We know that short line segments can approximate any complex curve and

that increasing the number of intervals provides a better approximation. The

above work indicates that using linear interpolation for missing data for intervals

of 10 years or less is reasonable. However, in the development of “actual” data

series, intervals exceeding 10 years exist. Should exponential interpolation be

used in these cases? At what point is the difference between the two methods

“substantially” different to justify exponential over linear interpolation?

To answer these questions, we assume that the long-term human population

growth curves are exponential. We further assume that all populations are

increasing over time (mostly true for the states). Under this assumption, linear

interpolation will always be larger then exponential interpolation values at the

same point in time (see Appendix B for proof). We now seek to know when the

maximum difference between the two methods occurs and the magnitude of that

0

50

100

150

200

250

1900 1910 1920 1930 1940 1950 1960 1970 1980 1990

Year

Census Linear Exponential

Figure 2—Interpolation between the 1900 and 1990 United States censuses by year and

annual Bureau of Census population estimates.
USDA Forest Service RMRS-GTR-111WWW 9

difference. The idea is to use the time interval and magnitude of population shift

to determine when to use one interpolation method over the other.

We demonstrate that the maximum difference between linear and exponential

interpolation is strictly dependent on the ratio of T1/Tn, which we refer to as a

difference ratio and define the ratio as y = T1/Tn , where T1 is the initial population

and Tn is the ending population. See Appendix A for the derivation. Using

( ) 1 100% 1

1 x

y

y a y DP a 



 ̄



Á

Á

Ë

Ê - + - = - ,

where ‘a’ is a function of ‘y’ and DP is the difference percentage, we find that

even when a population has doubled the maximum percent difference between

linear and exponential interpolation is 6 percent. This relationship between the

difference ratio and the maximum percent difference is shown in table 4 and

graphically in figure 4. Thus, we see that changes in population estimates need

to nearly double before a significant error (over 5 percent) is introduced using

linear interpolation. Our empirical tests indicate that linear interpolation was

“better” for short intervals (10 year period, table 3). This suggests the following

decision rule: For intervals over 10 years, select exponential interpolation over

linear interpolation when T1/Tn, the difference ratio, is less then some value

based an acceptable level of error. For example, using T1/Tn = 0.53 would limit

the difference percentage to under 5 percent, under the assumption that the

growth is exponential.

We empirically test this decision rule using a 10 percent level of error. Our

decision rule becomes: For periods over 10 years, use exponential interpolation

for difference ratios (T1

/Tn) less than or equal to 0.407 and linear interpolation for

ratios greater than 0.407. Applying this rule to the previous empirical work, we

“predict” the best interpolation method to use. We then compare the predicted

interpolation method to the interpolation method that actually gave the best fit to

the data. Using this decision rule we were able to select the “correct”

0

50

100

150

200

250

1900 1910 1920 1930 1940 1950 1960 1970 1980 1990

Year

Census Linear Exponential

Figure 3—Annual interpolation between United States census from 1900 and 1990 for

both interpolation methods and annual Bureau of Census population estimates.
10 USDA Forest Service RMRS-GTR-111WWW

interpolation method 66.7 percent of the time when we interpolated from 1790 to

1990 by decade. We got slightly better results (70.6 percent) when we varied T1/

Tn until we maximized the number of matches. When we interpolated between

1900 and 1990 and matched to the United States Bureau of Census estimates,

we correctly selected the interpolation method 56.1 percent of the time.

Interpolating between decades was worse; only 39.2 percent of the time was the

“correct” method selected. Seeking the difference ratio that maximized the

correct method improved our selection percentage only slightly. Table 5

summarizes the results of this empirical test.

This empirical test suggests that the decision rule is not particularly effective

in determining which of the two interpolation methods to use for the “best” fit.

The reason is likely that the assumption of exponential growth is not valid for

these population data. Factors other then births and deaths influence population

growth, such as immigration, emigration, and counting previously uncounted

aboriginals. In the long run nationally (1790 to 1990), the United States

Table 4—Relationship of difference ratio to

recent difference between linear and

exponential interpolation using equation

A.13.

T1/Tn Percent

difference

0.754 1.0

0.75 1.0

0.53 5.0

0.5 6.0

0.407 10.0

0.3333 14.8

0.331 15.0

0.278 20.0

0.25 23.4

0.238 25.0

0.207 30.0

0.2 31.3

0%

5%

10%

15%

20%

25%

30%

35%

0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

Difference Ratio - T1/Tn 

Figure 4—Relationship of difference ratio to percent error.
USDA Forest Service RMRS-GTR-111WWW 11

population growth fits an exponential model more closely than a linear model

(figure 1). At the state level this is not generally the case. Thus, it is possible that

the effects of immigration and emigration mask “natural” growth and,

subsequently, invalidate the exponential assumption at a finer spatial and

temporal scale.

Even though empirically linear interpolation appears to fit more frequently,

and there is no selection criterion to “predict” when one interpolation method is

better then the other, we have shown (Appendix B) that using exponential

interpolation provides lower population estimates under an increasing population

scenario. Thus, it might be prudent to err on the side of conservatism when the

intervals between data points are large (over 10 years) and there are large

differences between the starting and ending population level for that interval.

Table 6 provides a list of such intervals for our data set. When the missing

population values are estimated using exponential interpolation for these

intervals only, we get differences in our estimates of national population (linear

interpolation) ranging from less than 0.01 percent to a maximum of 5.9 percent

(1618, 143 fewer individuals). The differences in population estimates between

linear and exponential for the intervals listed in table 6 vary from a low of 17 to

29,558.

Table 5—Results of predicting “Best” interpolation method for each of the three

tests.

Census Estimates Census Estimates

Interpolate Decades Interpolate 1900 Census Estimates

1790 to 1990 to 1990 Interpolate by Decade

Match Decades Match Annually Match Annually

T1/Tn Matched T1/Tn Matched T1/Tn Matched

10 percent 0.407 66.7% 0.407 56.1% 0.407 39.2%

difference

Best Prediction 0.180 70.6% 0.450 56.1% 0.15 41.2%

Ratio

Note: The difference ratios of 0.18, 0.45, and 0.15 result in percent differences between linear and

exponential interpolation of 42.9 percent, 35.3 percent, and 7.9 percent respectively.

Table 6—Intervals to consider using exponential interpolation over linear

interpolation.

State T1/Tn Starting year Ending year

Alaska 0.160 1799 1833

California 0.162 1781 1822

Illinois 0.123 1682 1723

Illinois 0.197 1787 1810

Maine 0.050 1650 1760

Missouri 0.114 1735 1763

Missouri 0.097 1770 1804

New Jersey 0.066 1633 1665

New Mexico 0.154 1692 1776

New Mexico 0.167 1776 1800

Vermont 0.151 1724 1763

West Virginia 0.004 1732 1790

Wisconsin 0.137 1800 1820
12 USDA Forest Service RMRS-GTR-111WWW

Results

Interpolation

We opted to use linear interpolation to fill in missing population values

throughout the data set, recognizing that there are possibly cases where

exponential interpolation might be better. This decision is based, first, on the

empirical evidence, which indicates linear interpolation fits the known population

data more frequently than does exponential interpolation. Second, we were

unable to develop a criterion allowing us to predict when to use one method

over the other. Third, assuming conservative estimates might be better, we

examined the impact that specific intervals with large differences between

starting and ending populations would have on our estimates. The differences

were minor in terms of the overall estimates. Further, linear interpolation also

has the additional advantages of being easily applied, easily explained, easily

understood, and accepted as a valid methodology.

The Data

The United States population estimates cover the 50 states and Washington

DC from first European settlement to 1999. These estimates represent the new

settlers whom are presumed responsible for changing the landscape from an

earlier state. Thus, these estimates do not include aboriginals unless they were

counted as part of the settlements. There are estimates of aboriginal

populations at the time of European settlement and prior to 1564, although they

may not be complete. Figure 5 shows the U.S. total population estimates from

1564 to 1999. It would appear that little population growth occurred prior to

1790. However, figure 6 and figure 7 demonstrate that early growth in the plot is

masked by the magnitude of recent population levels.

Figure 8 further demonstrates the varying rates of growth over time. Here we

treat each century, seventeenth through the twentieth, as a separate population

and standardize each to a range between zero and one by dividing though the

hundredth year (1699, 1799, 1899, and 1999 respectively).

0

50

100

150

200

250

300

1564 1651 1738 1825 1912 1999

Year

Figure 5—United States population estimates from first European settlement to 1999.
USDA Forest Service RMRS-GTR-111WWW 13

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

1564 1592 1620 1648 1676 1704 1732 1760 1788

Year

Figure 6—United States population estimates 1564 to 1789.

0

50

100

150

200

250

300

1790 1818 1846 1874 1902 1930 1958 1986

Year

Figure 7—United States population estimates 1790 to 1999.

In 1790 only 31 of the 51 present day states and Washington DC had

population estimates over 1,000, pointing out the need for spatial distributions

finer then the national level. While the overall national population is relatively

small in the early years (prior to 1790) when compared to today, there are states

with early population levels high enough to have caused substantial land use

early in the time series. Figures 9 through 13 show the population estimates for

Arizona, Maine, California, North Dakota, and South Carolina, respectively.

Figure 14 illustrates the variation in population growth across states through time.

We standardized the individual growth curves between zero and one for Arizona,

California, Maine, North Dakota, South Carolina, and the United States by dividing

each population value by the maximum population value for the series from 1790 to

1999.
14 USDA Forest Service RMRS-GTR-111WWW

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

1 12 23 34 45 56 67 78 89 100

Period (year)

17th Century 18th Century 19th Century 20th Century

Figure 8—Standardized population growth curves by century.

0

1

2

3

4

5

6

1687 1726 1765 1804 1843 1882 1921 1960 1999

Year

Figure 9—Arizona population estimates 1687 to 1999.
USDA Forest Service RMRS-GTR-111WWW 15

0

5

10

15

20

25

30

35

1769 1815 1861 1907 1953 1999

Year

Figure 10—California population estimates 1769 to 1999.

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1604 1683 1762 1841 1920 1999

Year

Figure 11—Maine population estimates 1604 to 1999.
16 USDA Forest Service RMRS-GTR-111WWW

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

1801 1823 1845 1867 1889 1911 1933 1955 1977 1999

Year

Figure 12—North Dakota population estimates 1801 to 1999.

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

1670 1702 1734 1766 1798 1830 1862 1894 1926 1958 1990

Year

Figure 13—South Carolina population estimates 1670 to 1999.
USDA Forest Service RMRS-GTR-111WWW 17

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

1790 1809 1828 1847 1866 1885 1904 1923 1942 1961 1980 1999

Year

Arizona

California

Maine

North Dakota

South Carolina

United States

Figure 14—Standardized population growth curves for the United States and selected

states (figures 9 to 13).

Conclusion

We present United States population series from first European settlement to

1999 for all states and Washington DC. These series were developed to assist

in modeling historical trends in land use, but may have other applications. As

historical land use changes are frequently viewed as having their beginnings

with the arrival of European settlers, the data do not account for the aboriginal

peoples during early settlement. However, aboriginals were not excluded as

time passed and they were subsequently counted. Thus, this series is meant to

represent the magnitudes and trends of the American population that was

impacting/causing changes in land use from European settlement.

There was a substantial human population in North America prior to the

arrival of Europeans. There is little doubt that the aboriginal peoples impacted

the land, although to what extent is not readily quantifiable. With the arrival of

Europeans and the introduction of disease and other factors, there was a large

loss of human life, primarily the aboriginal population (Mann 2002). This raises

the possibility that the anthropogenic disturbances may have been actually

reduced, temporarily, with the onset of European settlement. There may be merit

in the development of spatial and temporal population data to account for all

peoples prior to and subsequent to European settlement for use in modeling

historical land use.

While extensive research went into the development of this series and an

extensive number of sources were consulted, it is by no means exhaustive. As

“new” historical information comes to light, the authors may revise the series as

appropriate. Further, it should be noted that data were not available for every

year from first settlement to 1999; in fact even when values are available for

specific years (other than censuses), they are generally estimates.

In addition to the data series, a critical look was taken on the use of linear

interpolation when working with human population series. Ask someone to draw

a growth curve for human population and you will likely get something in the

form of an exponential curve. While this seems intuitive, we find that at the

state-level, forces other than natural reproduction and death, such as

immigration and emigration, appear to drive population change. Thus, the
18 USDA Forest Service RMRS-GTR-111WWW

empirical findings of this work suggest that linear interpolation is a better

interpolation method than exponential. We further point out those states and

times where linear interpolation could potentially overestimate the population

and show that the overall estimation error is likely small. Given the lack of clear

evidence on which interpolation methods to use, further work on data

assimilation and population may be warranted.

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http://www.happyones.com. St-Croix: 1604–2004; Il faut se souvenir de ces 400 ans!

Available: http://www.happyones.com/franco-american/st-croix/

Maine 2 — Dunnack, Henry E. 1920. The Maine Book (Augusta, ME: 1920): 80–84, 110–

113. [Online]. History & government of the colonial period (1600–1820) Available:

http://www.waterboro.lib.me.us/histme.htm#colhist

Michigan 1 - Stocking, William. 1908. The Book of Detroiters, a biographical dictionary of

leading living men of the city of Detroit. Marquis, Albert Nelson, ed. Chicago: A. N.

Marquis & Company. [Online]. Available: http://www.usgennet.org/usa/mi/county/

tuscola/det/dethistorya.htm

Michigan 2 — City Beautiful Design. 2001 [Online] web page. http://

www.citybeautifuldesign.com. History Detroit 1701–2001. Available: http://

www.historydetroit.com/places/fort_british.asp

Minnesota — Minnesota Secretary of State. March 2002 [last visit]. [Online] home page.

http://www.sos.state.mn.us. Minnesota Chronicle. Available: http://

www.sos.state.mn.us/student/mnchron.html

Mississippi — Natchez-Adants County Chamber of Commerce. Natchez, Mississippi,

history of Natchez. [Online]. Available: http://www.natchezpd.com/history.html

Missouri — Wayman, Norbury. March 2002 [last update]. City of St. Louis. [Online] home

page. http://stlous.Missouri.org. Physical Growth of the City of Saint Louis. Available:

http://stlouis.missouri.org/heritage/History69/

Nebraska — Kearny High School. February 21, 2003 [last visit]. [Online] home page.

http://kearnykomets.sdcs.k12.ca.us. The history of Fort Kearny. Available: http://

www2.sandi.net/kearny/history/swk/fk.html

Nevada — Wischmann, Lesley. 1996–2001. [Online] home page. http://octa-trails.org.

Mormon station. Available: http://calcite.rocky.edu/octa/morsta.htm

New Jersey — Grundy, J. Owen; Carosell, Louis P. 1970. History of forms of government

from early Dutch days to the present time. Jersey City Online Top Stories. [Online]

home page. Available: http://www.jerseycityonline.com/jc_history.htm

New Mexico — New Mexico Economic Development Department. March 2002 [last visit].

Factbook. [Online]. http://www.edd.state.nm.us/FACTBOOK/. New Mexico’s colorful

history and cultural diversity. Available: http://www.edd.state.nm.us/FACTBOOK/PDF/

hist.pdf.

New York — Gore, Robert H., Jr. December 7, 1997. The coins of colonial and early

America. [Online] home page. http://www.coins.nd.edu/ColCoin. A brief outline of

Dutch history and the Province of New Netherland. Available: http://

www.coins.nd.edu/ColCoin/ColCoinIntros/Netherlands.html

North Carolina — State Library of North Carolina, North Carolina Encyclopedia. [Online]

home page. May 5, 1998 [last update]. Historical highlights of North Carolina.

Available: http://statelibrary.dcr.state.nc.us/nc/history/history.htm

North Dakota 1 — Time Passages, Genealogy of the Dakotas. April 1, 2002 [last update].

[Online] home page. http://www.time-passages.com. Available: http://www.timepassages.com/1850_census.html

North Dakota 2 — Time Passages, Genealogy of the Dakotas. April 1, 2002 [last update].

[Online] home page. http://www.time-passages.com. Available: http://www.timepassages.com/1860_census.html

Ohio — Marietta Ohio’s Hometown Website. April 1, 2002 [last visit]. [Online] home page.

http://mariettaohio.info. Early history of Marietta. Available: http://www.mariettaohio.com/about/history_earlyhistory.htm

Oregon — Green, Abernethy. March 2002 [last visit]. The American Local History

Network. [Online]. http://www.alhn.org. Clakamas County early records. Available:

http://www.usgennet.org/alhnorus/ahorclak/census.html

Rhode Island — Office of Secretary of State, Rhode Island. March 2002 [last visit].

[Online] home page. http://www.state.ri.us. RI early history, Indians and explorers.

Available: http://www.state.ri.us/rihist/earlyh.htm

South Carolina —The University of South Carolina-Aiken. November 17, 1997 [last

update]. Time-line. [Online]. Available: http://www.usca.sc.edu/aasc/timeline.htm

South Dakota 1 - Encyclopedia.com. 2002. Tucows Inc. [Online]. http://

www.encyclopedia.com. Available: http://www.encyclopedia.com/html/section/

sthdak_history.asp
USDA Forest Service RMRS-GTR-111WWW 23

Texas 1 — Hendricks, Rick. July 23, 2001 [last update]. The Texas State Historical

Association. [Online]. http://www.tsha.utexas.edu. The handbook of Texas Online,

Corpus Christi De La Isleta Mission. Available: http://www.tsha.utexas.edu/handbook/

online/articles/view/CC/uqc3.html

Texas 2 — Fehrenbach, T. R. July 23, 2001 [last update]. The Texas State Historical

Association. [Online]. http://www.tsha.utexas.edu. The handbook of Texas Online,

San Antonio, Texas. Available: http://www.tsha.utexas.edu/handbook/online/articles/

view/SS/hds2.html

Utah 1 — Barton, John D. 1996. Buckskin Entrepreneur, Antoine Robidoux and the Fur

Trade of the Uinta Basin 1824–1844. [Online]. Fort Robidoux/Reed Trading Post.

Available: http://www.lofthouse.com/USA/Utah/uintah/towns/reed.html

Utah 2 — Salt Lake Convention & Visitors Bureau. Copyright 2001, 2002. [Online] home

page. The official travel site of Utah. http://www.utah.com. Salt Lake City-history.

Available: http://www.utah.com/cities/slc_history.htm

Utah 3 — Sadler, Richard W. 1978. Utah history encyclopedia. [Online]. http://

www.media.utah.edu/uhe. Miles Goodyear. Available: http://www.media.utah.edu/

UHE/g/GOODYEAR%2CMILES.html

Vermont 1 — State of Vermont, Department of Forests Parks & Recreation. 2001.

[Online] homepage. http://www.vtstateparks.com. Fort Drummer State Park. Available:

http://www.vtstateparks.com/dummer/

Vermont 2 — Encyclopedia.com. 2002. Tucows Inc. [Online]. http://

www.encyclopedia.com. Available: http://www.encyclopedia.com/html/section/

vermont_history.asp

Washington 1 — Flora, Stephenie. March 2002 [last visit]. The Oregon Territory and It’s

Pioneers. [Online] homepage. http://www.oregonpioneers.com/ortrail.htm. Pioneers of

1844. Available: http://www.oregonpioneers.com/1844.htm

Washington 2 — City of Tumwater. February 21, 2003. [last update]. [Online] homepage.

http://www.ci.tumwater.wa.us. Tumwater pioneers- Why did they choose to settle in

Tumwater? Available: http://www.ci.tumwater.wa.us/ResearchCenter/Pioneerspage%202.htm

West Virginia — Dilger, Robert Jay; White, Joseph M. August 1, 2000 [last update].

Berkeley County history. Available: http://www.polsci.wvu.edu/wv/Berkeley/

berhistory.html

Wisconsin 1 — Carpenter, Paul D. The Catholic Encyclopedia, volume XV. Online Edition

Copyright © 1999 by Kevin Knight Wisconsin. New Advent Website. [Online]. http://

www.newadvent.org. Available: http://www.newadvent.org/cathen/15661b.htm

Wisconsin 2 — Wisconsin Blue Book 2001–2002. [Online]. http://www.legis.state.wi.us/

lrb/bb. Wisconsin History: 682–685. Available: http://www.legis.state.wi.us/lrb/bb/

ch8i.pdf

Wyoming — Fort Laramie Park. [Online] homepage. http://fortlaramie.areaparks.com.

Available: http://fortlaramie.areaparks.com/parkinfo.html
24 USDA Forest Service RMRS-GTR-111WWW

Appendix A—Development of Difference Measure

between Exponential and Linear Interpolation

Linear interpolation is defined as

( )1 Ti = T1 + D i - A.1

and exponential interpolation is defined as

m ( )1

1

- = r i

i T T e . A.2

Where Ti = period population, i = 1 to n, n is the number of equal time

intervals, and note that

1

1

-

- = nT T

D n A.3

and

1

ln

1

-





 ̄



Á

Á

Ë

Ê

= n

T

T

r

n

. A.4

We write the difference function as

(difference) ( ) () ( )1 ( ) exp( ) 1 f = T1 + D i - - T1 r i - . A.5

Taking the derivative, setting to zero and solving for i gives

= D - rT1 exp( ) r( ) i -1 = 0

di

df

( ) () ( ) 1

ln ln ln 1 + - - = rD r T

i .

Substituting in A.3 and A.4 gives

( )

1

1

ln

ln

1

ln

ln

1

ln

1

1

1 1

+

-





 ̄



Á

Á

Ë

Ê

-











 ̄



Á

Á

Á

Á

Á

Ë

Ê

-





 ̄



Á

Á

Ë

Ê

 -

 ̄

 Á

Ë

Ê

-

-

=

n

T

T

T

n

T

T

n

T T

i

n

n

n

( )( ) ( ) ()

( )1 1

ln

ln ln 1 ln ln ln 1 ln

1

1

1

1

- +





 ̄



Á

Á

Ë

Ê





 ̄



Á

Á

Ë

Ê

+ - - 



 ̄



Á

Á

Ë

Ê





 ̄



Á

Á

Ë

Ê - - - -

= n

T

T

n T

T

T

T T n

i

n

n

n
USDA Forest Service RMRS-GTR-111WWW 25

( ) ( )

( )1 1

ln

ln ln ln ln

1

1

1

1

- +





 ̄



Á

Á

Ë

Ê





 ̄



Á

Á

Ë

Ê -



 ̄



Á

Á

Ë

Ê





 ̄



Á

Á

Ë

Ê - -

= n

T

T

T

T

T

T T

i

n

n

n

. A.6

This represents the time i that maximizes the difference between linear and

exponential interpolation. If we let





 ̄



Á

Á

Ë

Ê





 ̄



Á

Á

Ë

Ê





 ̄



Á

Á

Ë

Ê -



 ̄



Á

Á

Ë

Ê -

=

1

1 1

1

ln

ln ln ln

T

T

T

T

T

T T

a

n

n n

A.7

our equation reduces to

i = a( ) n -1 +1. A.8

We note that A.7 is independent of i, time.

We now demonstrate that the maximum difference is independent of time by

substituting A.3, A.4, and A.8 into our difference equation A.5 to obtain.

( ) ( ) ( )











 ̄



Á

Á

Á

Á

Á

Ë

Ê











 ̄



Á

Á

Á

Á

Á

Ë

Ê

- + - -





 ̄



Á

Á

Ë

Ê

-



 ̄



Á

Á

Ë

Ê  - + -  ̄

 Á

Ë

Ê

-

- = + ( 1) 1 1

1

ln

1 1 1 exp 1 (difference) 1

1

1 a n

n

T

T

a n T

n

T T f T

n

n

i

( ) ( ) 



 ̄



Á

Á

Ë

Ê





 ̄



Á

Á

Ë

Ê = + - -

a

n

i n T

T f T T T a T

1

1 1 (difference) A.9

Neither i nor n remain in the equation, thus demonstrating that the

maximization of the difference between linear and exponential interpolation is

independent of the time interval.

We further demonstrate that the percent difference between the two methods,

defined as

100%

exponential

linear exponential % difference x - =

is independent of the actual magnitude or difference between the starting and

ending populations T1 and Tn respectively and is dependent solely on the

relative magnitude of T1 and Tn, expressed as a ratio, T1/Tn . Thus, the maximum

percent difference between the two interpolation methods can be calculated with

a single value y = T1/Tn.

We define the difference proportion as

exponential

linear - exponential DP =
26 USDA Forest Service RMRS-GTR-111WWW

( ) ( )





 ̄



Á

Á

Ë

Ê





 ̄



Á

Á

Ë

Ê





 ̄



Á

Á

Ë

Ê





 ̄



Á

Á

Ë

Ê + - -

= a

n

a

n

i n

T

T

T

T

T

T T T a T

DP

1

1

1

1 1

( ) ( ) 1

1

1

1 -





 ̄



Á

Á

Ë

Ê





 ̄



Á

Á

Ë

Ê

+ - = a

n

i n

T

T

T

T T T a

DP

. A.10

Define the magnitude ratio as

Tn

T

y 1 = . A.11

Substitute A.11 in to A.7





 ̄



Á

Á

Ë

Ê





 ̄



Á

Á

Ë

Ê





 ̄



Á

Á

Ë

Ê -



 ̄



Á

Á

Ë

Ê -

=

y

y y

a

1 ln

1 1 ln ln 1 ln

( ) () ( )

() ( )y

y

y

y

a

ln 1 ln

ln ln 1 ln 1 ln

-

- - 



 ̄



Á

Á

Ë

Ê -

=

( ) ( )

( )y

y

y

y

a

ln

ln ln 1 ln - - 



 ̄



Á

Á

Ë

Ê -

= - . A.12

Further substitute A.11 into A.10

( ) ( ) -1





 ̄



Á

Á

Ë

Ê





 ̄



Á

Á

Ë

Ê

+ - = a

n

n

n

n n n

yT

T

yT

yT T yT a

DP

( ) T ( ) y a ay

y

DP yT n

a

n = + - 



 ̄



Á

Á

Ë

Ê





 ̄



Á

Á

Ë

Ê +

1 1

( ) () DP y y a y a + = + - - 1 1 1

( ) 1 1

1 - + - = -a y

y a y DP . A.13
USDA Forest Service RMRS-GTR-111WWW 27

We note that a is a function dependent only on y. Therefore, so is the

maximum percent difference between the two interpolation methods. This

means that the maximum difference between the two methods, under the

assumption that exponential interpolation is correct, is calculable using the ratio

of starting population to ending population values.
28 USDA Forest Service RMRS-GTR-111WWW

Appendix B—Proof linear interpolation is always

greater than or equal to exponential interpolation

under strictly increasing conditions

We assume £ T1 £ Td 1 and that both are integer valued. The difference

equation from A.5 is

(difference) ( ) () ( )1 ( ) exp( ) 1 f = T1 + D i - - T1 r i - .

We assume our difference equation is greater than or equal to zero and

substituting in A.3 and A.4 respectively we obtain

( ) 0

1

1

exp ln

1

1

1

1 1 1 ≥



 ̄



Á

Á

Ë

Ê 

 ̄

 Á

Ë

Ê

-

-





 ̄



Á

Á

Ë

Ê  -

 ̄

 Á

Ë

Ê

-

- + - ni

T

T

T

n

i T T T n

n . B.1

Rearranging terms produces

( ) 0

1

1 1

1

1

1 1 1 ≥ 



 ̄



Á

Á

Ë

Ê  -

 ̄

 Á

Ë

Ê

-

- + -



 ̄

 Á

Ë

Ê

-

-

n

i

n

n T

T

T

n

i T T T

which we divide through by T1 giving

0

1

1

1

1 1

1

1

1 1

≥ 



 ̄



Á

Á

Ë

Ê

- -

-  -

 ̄

 Á

Ë

Ê

-

- +



 ̄

 Á

Ë

Ê

-

-

n

i

n n

T

T

n

i

n

i

T

T .

Rearrange terms and multiply through by T1/Tn gives

0

1

1

1

1 1

1 1

1

1 1 ≥ 



 ̄



Á

Á

Ë

Ê  -

 ̄

 Á

Ë

Ê

-

- + --





 ̄



Á

Á

Ë

Ê

-



 ̄

 Á

Ë

Ê

-

- - ni

n

n n T

T

n

i

n

i

T

T

T

T .

Rearrange and combine terms to get

1 0

1

1 1

1 1

1 1 1 ≥ 



 ̄



Á

Á

Ë

Ê + - 



 ̄



Á

Á

Ë

Ê

 -  ̄

 Á

Ë

Ê

-

- 

 ̄

 Á

Ë

Ê

-

- - ni

n n Tn

T

T

T

T

T

n

i

. B.2

We note that





 ̄



Á

Á

Ë

Ê

 -  ̄

 Á

Ë

Ê

-

-

Tn

T

n

i 1 1

1

1

B.3

is always greater then one because 

 ̄

 Á

Ë

Ê

-

-

1

1

n

i

 is constrained between 0 and 1 as

i = 1 to n. Likewise, 



 ̄



Á

Á

Ë

Ê -

Tn

T1 1 is constrained between 0 and 1 as T1

 is greater

than or equal to one and Tn is greater than or equal to T1. Multiplying two

positive numbers between 0 and 1 result in a value between 0 and 1. Therefore

this part is always equal to or greater than zero.
USDA Forest Service RMRS-GTR-111WWW 29

Turning our attention to



 ̄

 Á

Ë

Ê

-

- -





 ̄



Á

Á

Ë

Ê

- 1

1 1

1 1 n

i

n Tn

T

T

T

B.4

we note the power term of the second radical is constrained to be between 0

and 1 by the previous argument and will always be positive. Also the ratios, by

the previous arguments, are constrained between 0 and 1. Ratios between 0 to

1 taken to a power between 0 and 1 will always be less than the ratio. Thus, this

component is obviously greater than or equal to one. The sum of two values

greater than or equal to zero will be greater than or equal to zero.

QED

We note that under strictly decreasing situations a similar proof can be made

to show exponential interpolation will always be larger than linear interpolation.
30 USDA Forest Service RMRS-GTR-111WWW

Appendix C—State level series development

Introduction

All Internet references that follow are given as state and number, labeled in

the reference section, under States (Electronic media). All missing years are

filled in via linear interpolation unless otherwise noted. In cases where the initial

settlement size was not found, an estimate was made based on the general size

of other settlements in the region during a comparable time. For example, early

French posts (1600s) were generally a handful of trappers, rarely exceeding 10.

Historical accountings of these trading posts indicate that they remained small,

rarely exceeding 40 to 50 inhabitants. English settlements, on the other hand,

were generally 100 to 200, while the Spanish settlements were frequently larger.

We note that 10 to 25 people permanently staffed fur-trading forts during the

1820s to 1840s in the Western United States, but they often saw their ranks

swollen to as many as 250. Further, the 10 to 25 staff do not account for the

wives and children frequently present. Thus we assume trading forts/posts

during this period represent a “resident” population of 100, accounting for

travelers, traders, trappers, miners, soldiers, and miscellaneous settlers present

in the region but not well accounted. The interested reader might read the

account of Bent’s Old Fort (State Historical Society of Colorado 1979) for more

information on the historical activities of a western trading post.

An interesting situation exists when attempting to estimate settlement size.

Frequently the records will list the number of men present but not wives and

children. In the case of trappers, particularly the early French, they frequently

took native wives, especially with the establishment of forts and trading posts. In

the case of the Spanish, most soldiers were soldier/settlers and many, if not

most, had their wives and children with them. Another characterization of the

Spanish was their mission system. Missions were nearly always established

with a military presence. In fact this was such a hand--in-glove situation that the

Spanish government limited expansion of the mission system in America due to

the lack of resources to provide adequate soldiers to protect the missions. The

implications of this are simply that records listing the numbers of soldiers,

missionaries, and traders generally understate the true numbers of people

present.

The following is a synopsis of the research by state. The population estimates

found and their references are provided. The following are the definitions for the

sources given in the data tables developed from Greene and Harrington (1932)

and United States Bureau of Census (1975). The conversion factors in table 2

were used to convert the data to the population estimates reported in the data

tables, barring an overriding reason to use a different factor. In the cases where

a different conversion factor was used, it is so noted in the state-level accounts.

Census A census conducted by someone other than the United States federal

government.

Estimate Population estimated prior to 1790 made by the United States Bureau

of Census.

Family Count of families in the region excludes soldiers and individuals.

Assumed to be six individuals.

House Count of habitable structures. Assumed to be seven people per

house, as homes generally had extras above and beyond the family

unit.

Men A count of men able to bear arms. Assumed to be equivalent to four

individuals.

Militia Those registered to be called to fight. Assume to be equivalent to

5.33 people per militia.
USDA Forest Service RMRS-GTR-111WWW 31

Poll A list of eligible voters; the relation to population is assumed to be

similar to that of “men,” equivalent to four individuals.

Taxable Those individuals eligible for taxation. The list may include slaves. It

is assumed that there are four individuals for every person on the tax

rolls.

Tithable Count of those obligated to pay tithes to churches. It is assumed to

be equivalent to four individuals.

Value Population estimate made at the time. These estimates come from a

wide variety of sources, such as newspapers, letters, visitors, local

leaders, and so forth.

The following state level accounts show the development of the historical

population series prior to the first federal census. Unless stated otherwise, we

linearly interpolate between all data values in the final series development. The

last population value given here for each state is also linearly interpolated to the

first federal census value that is not generally provided in the following accounts.

Alabama - 01

Pickett (1851) provides the following account.

1702 Fort Louis, the first permanent settlement, was established by d’Iberville

with 202 colonists.

1704 Fort Louis was reported to have 180 men, two French families (with 10

children), six Indian slaves, and officers (est. 218). Later that year 23

women arrived from France along with 75 soldiers of whom 30 died

shortly after arrival. We estimate the population to be 286.

1706 Fifty Canadians from the upper Mississippi joined the colony. We estimate the population to be 330.

1708 There were 279 persons reported, plus an additional 60 Canadians for a

total of 339.

1712 There were 28 families reported, plus 20 Negroes, 75 Canadians, and

two companies of 50 each for a total of 324.

1717 There were an estimated 400 inhabitants.

1721 There were 5,420 plus some 600 Negroes in the French Colonies (includes all of the Mississippi and Gulf region). That year two ships of

slaves (240) and three ships of immigrants (806) were unloaded at Mobile. We estimate Alabama’s population at 1,500 in 1721 (240 + 806 +

400, rounded up).

1722 The Royal Bank of France failed, subsequently the colonies’ needs were

neglected and many settlers began abandoning the settlement, which

we assume to be approximately 1,500.

1723 We estimate a one-third population loss, reducing it to 1,000.

1724 We estimate another 500 abandoned the settlement, reducing the population to 500, and assume it remains constant population until 1763.

1763 The British take over. Mobile has a population of 350 at the time

(Rogers, 1994). We assume the existence of another 150 in the region.

We interpolate from 500 to the 1800 census.

Alaska - 02

1741 The Russians first sighted Alaska in (Alaska 1).

1784 The first permanent settlement was established at Three Saints Harbor

on Kodiak Island (Hardwick 1993) with over 200 men. There were over

6,500 Sugpiaq Eskimos living in the area at the time (Alaska 3). We

assume that Kodiak was settled with half those on the initial expedition

(three ships, one lost), or 100.

1787 Fort St. George and St. Nicholas Redoubt were established on the

Kenai (Hardwick 1993). We assume 100 each for the two settlements on

Kenai in 1787, bringing the non-native population to 300.
32 USDA Forest Service RMRS-GTR-111WWW

1791 Kenai has an estimated population of 300 (Alaska 2) and Kodiak has a

population of 110 Russians and 900 natives (Alaska 4). The Russian

population is estimated at 1,310 (300 + 110 + 900) this year and we

assume no further growth in 1792.

1793 St. Constantine Redoubt established (Hardwick 1993) with an assumed

100 and we estimate Alaska’s population to be 1,410 and assume no

further growth until the next settlement.

1795 Slavorossiya (Yakutat) established (Hardwick 1993) with an assumed

100. We estimate Alaska’s population to be 1,510 and assume no further growth until the next settlement.

1799 New Archangel (Sitka) established (Hardwick 1993) with an assumed

initial 100 and we estimate Alaska’s population to be 1,610.

1817 New Archangel had a population of 620 (190 Russians, 182 Creoles,

248 Aleuts) (Hardwick 1993).

1820s The region was divided into four districts (Hardwick 1993).

1833 New Archangel - Russians 379, Creoles 307, natives 136, total 822 (882

in text).

Kodiak - Russians 103, Creoles 239, natives 6,607, total 6,949.

Unalaska - Russians 30, Creoles 186, natives 1,282, total 1,498.

Atka - Russians 41, Creoles 146, natives 593, total 780.

The total is 10,049 (Hardwick 1993).

1840 There were 10,313 Orthodox in Alaska - 706 Russian, 1,295 Creole and

8,312 natives (Hardwick 1993). We estimate 11,000 under the assumption that nearly all members of the Russian-American Company were

Orthodox.

1867 The Russian-American Company (trading company) was Alaska from

1791 until the United States purchase in 1867. As the fur trade was on

the decline from 1840 to 1867 we assume a constant population during

this period.

1897 The famous gold rush this year suggests a sudden influx of people. So

we assume 35,000 in 1896, rather than a straight interpolation from

the1890 census to the 1900 census.

Arizona - 04

The following accounts are taken from Peck (1962), Sheridan (1995), and Wagoner (1975).

1687 Kino and a few colleagues established the first “settlement,” the mission

Tumacacori. We assume a low initial population of 10 Europeans and

interpolate to 1732, noting that the missions were not well maintained.

1732 San Xavier de Bac and Guevavi were established, bringing in a trickle of

colonists. We estimate a population of 100 and note that there was renewed interest in the region by the Catholic Church.

1736 Silver was discovered, attracting miners and traders. We estimate a

population of 200.

1741 The Mexican government shuts down the silver trade, but many remained in the region. As no new towns were established we assume the

population grew to 1,000.

1744 San Xavier had a population of over 400 families, primarily native (Arizona 2).

1751 The Pima uprising resulted in the death of over 100 settlers; many more

escaped. We assume a constant population of 1,000 (non-native) from

1741-50. Then we estimate a population of 100, assuming the majority

of 1,000 were forced out of the state.

1752 The Spanish responded by establishing a Presidio at Tubac, the first

permanent non-native town in Arizona with a garrison of 50 and their

families. We estimate a population of 300 (100 remaining + 50 soldiers

times 4).
USDA Forest Service RMRS-GTR-111WWW 33

1757 Tubac had over 400 residents. We estimate 500 for the state.

1768-72 San Xavier (near Tucson) had a population of nearly 300. We estimate 800 in 1768 and assume a constant population through 1778.

1779 A garrison was established at Tucson with 80 soldiers (and presumably

families). We assume a population of 1,120 (700 plus 80 times 4).

1780 Yuma was established with 40 families and 42 soldiers (30 with their

wives and children). A short-lived settlement, as the Yuma killed all but

seven men. Northern settlement did not occur again until 1870-80 when

the Indians were brought under control by the American military.

1790 to 1820 There was general peace in the region and the population was

steady at 300 to 500 in Tucson, 300 to 400 in Tubac and 100 in

Tumacacori. Tucson had a population of 395 in 1820 (Arizona 1). Therefore we assume a constant population from 1779 to 1820 (1,120).

1820-30 Hundreds of trappers arrived in the region. With the influx of trappers,

we estimate the population rises to 2,000 by 1830.

1830-59 The Apache Indians halted any further settlement and effectively limited non-native populations to Tubac, Yuma, and Tucson, so we assume

a constant population of 2,000 during this period.

1860 A territorial census shows Arizona to have 2,421 whites, 4,040 Indians,

and 21 Negroes, totaling 6,482. We interpolate from 1850 to 1860.

Arkansas - 05

1686 DeTonti established the Arkansas Post, Arkansas’ first settlement, with a

party of six (Arkansas Secretary of State, 2000). There is no evidence to

suggest that the settlement grew beyond a small trading post until 1720.

1720 Some 100 settlers came to the area (Arnold 1991).

1722 Forty-four settlers remain; the rest resettled outside present day New

Orleans.

1723 A visiting priest indicated that there were only 20 living in the area

(Arnold 1991).

1727 Approximately 30 French were living in the area (Ashmore 1978).

1731 The Fort was reestablished with 12 soldiers (Arnold 1991). Thus, we

assume a population of 42 at that time (30 from 1727 plus 12 soldiers).

1770 Pittman (Ashmore 1978) found 32 soldiers and eight families. Assuming

six to a family, we estimate a population of 80.

1779 Thirty dwellings were noted (Arnold 1991). Assuming seven per dwelling, we estimate a population of 210.

1793 The area was reported have 220 free and slave (Arnold 1991).

1799 The white population was estimated to be 386, with a total population

likely around 400 (Arnold 1991).

California - 06

1769 Franciscan Father Juan Crespi with three ships and two land parties set

out from the Baja to establish a mission at present day San Diego, with

maybe half the initial 300 plus surviving the journey (Bean 1968).

1770 A Presidio was established at Monterey with a population of 47. Five

died before year-end, 20 more joined in 1771, and by 1772 nearly 50

remained at Monterey (California 3).

1776 San Francisco is established with 30 soldiers and families plus four civilian families.

Bean (1968) provides the following timeline for mission establishment in table

B1 from 1769-80. The state population estimates are of the authors, based on

the above information and the assumption that each mission established after

San Francisco had an initial population of 50.

1781 The population of Alta California was approximately 600 (202 men in

garrisons) (California 2).
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1822 The population of Alta California was approximately 3,700 (California 2).

1845 Bean (1968) estimates the non-native population was approximately

7,000.

1848 The discovery of gold brought the gold rush and about 6,000 miners that

year Bean (1968). We extend the interpolation trend line from 1822 to

1845 (estimated 7,000) to 1847 (estimate 7,287) and then add 6,000 to

estimate a population of 13,000.

1849 There were 40,000 miners, so we estimate a population of 50,000 that

year.

Colorado - 08

Hafen (1933) provides us with the following account, except as noted. There

were lesser posts, explorers, and visitors in the region from 1820 through 1850

that are not specifically accounted for here. We assume each trading post in

operation through 1850 represents 100 residents. Population estimates given

are for Colorado as a whole.

1825 Robidoux established the first permanent trading post (Colorado 1).

Population estimated at 100.

1828 Fort Bent established on the Arkansas. Population estimated at 200.

1830 Marurice LeDoux established near Florence, on the South Platte River.

Population estimated at 300.

1836 Fort Lupton established. Population estimated at 400.

1837 Fort Velasquez established. Population estimated at 500.

1838 Fort Jackson and Fort St. Vrain. Population estimated at 700

1839 Browns Hole established. Population estimated at 800.

1842 A settlement was attempted and failed at Pueblo.

1842 Fort Pueblo established. Population estimated at 900.

1843-44 Fifteen to 20 families settled at Hardscrabble creek south of Trinidad.

We estimate a population of 1,000 in 1843.

1846 Two hundred and seventy-five Mormons settle south of Pueblo. We estimate a population of 1,300.

In addition to the settlements during the 1840s there were numerous ranches in

the region. Starting in 1851, we estimate that each permanent settlement adds 200 to the population and that Fort Massachusetts adds 100

(two companies).

1851 San Luis is established at Conejos in San Luis Valley (Colorado 1). We

estimate a population of 1,500.

1852 San Pedro and Fort Massachusetts are established. We estimate a

population of 1,800

1853 San Acacio is established. We estimate a population of 2,000.

1854 Galadalpe is established. We estimate a population of 2,200.

1858 Fort Garland replaced Fort Massachusetts and had two companies of

soldiers and officers (100 plus). Gold was discovered at Dry Creek near

Englewood resulting in sudden changes. Auraria, near present downtown Denver, was founded with a meeting of 200 men (Colorado 2). We

estimate a population of 2,500 in 1858 with the establishment of Auraria

(Denver).

1859 An estimated 100,000 set out for Colorado from Missouri; 50,000

reached the mountains, and of those, half returned home after reaching

Cherry Creek. We estimate a population of 27,500 (25,000 + 2,500).

1860 The population is 34,277 according to the United States Bureau of Census estimates (CPH-2-1, table 16). A territorial census in 1861 puts the

population of the territory at 25,331 (Hafen 1933). Given that the gold

boom turned to bust, the population dropped as fast as it started.

There is a real lack of “hard” numbers for early Colorado, so the values we

present from 1825 though 1858 are estimates. In 1858, we know that there were

at least four communities and one fort (with over 100 men), and that the
USDA Forest Service RMRS-GTR-111WWW 35

founding meeting for Denver drew over 200 men. Assuming four people for each

man at the meeting, that accounts for 800. Further, assuming 200 per

community (family size of 4) and adding another 100 for the fort, we are sure

Colorado’s population was over 1,700 people at the time. This does not account

for ranchers, explorers, miners, natives, trappers and miscellaneous settlers. So

we suspect our estimate of 2,500 for 1858 is low.

Connecticut - 09

We use the founding of Wethersfield, Windsor, 1634, as the initial settlement

date (Wilson 1998). From Greene and Harrington we find the population was

800 in both 1636 and 1637, so we use this as our starting population. Table B2

of population estimates was developed from Greene and Harrington (1932) and

Census Bureau estimates (estimate).

Delaware - 10

In 1631 Dutch establish Zwaanendael, the first settlement (Wilson 1998). No

information was found on the initial size of the settlement, but it was set up as a

whaling colony and everyone was killed the first year. The colony was

reestablished in 1632. We assume 25, although that is likely conservative. The

subsequent years to 1790 were developed from Greene and Harrington (1932)

and Census Bureau (1975) estimates (estimate) as shown in table B3.

Florida - 12

Milanich (1995) reported that the French built Fort Caroline in 1564 with 300.

Some men stole a ship and headed home, another 60 deserted. A month or two

later the Spanish established St. Augustine with 600 and cleared out the French,

killing 132 Frenchmen and capturing 50 plus women and children. The

shipwrecked French fleet arrived and the Spanish killed the first wave (111),

sparing a dozen Catholics. The second group arriving two weeks later was all

killed. Other forts and settlements occurred after 1564, but all were abandoned

by 1587 and St. Augustine was the sole remaining settlement in Florida until

1598 when Pensacola was established.

1564 Deagan (1991) reported that while a large force built St. Augustine, the

residual force left was 70 men and an unknown number of women and

children. We estimate Florida’s population at 82, assuming 15 percent

women and children.

1569 Eighty men and 14 women were added to the fort. We assume no

growth prior to this year and estimate a population of 176.

1577 The fort reported 100 men and officers and a more “normal” ratio of men

and women (we assume normal to mean 50/50, and use 60/40 men/

women as approaching normal). We estimate the population to be 167.

1578 186 men were reported (27 being seamen). We assume the same ratio

applied to the 186 less the 27 sailors. Thus we estimate a population of

292.

1580 150 men were reported. We estimate the population to be 250 (150/0.6).

From 1596 to 1761, Deagan (1991) provides population estimates for St.

Augustine (table B4). TePaske (1975) estimated St. Augustine’s population in

1746 to be 1,509 (403 blacks). When the Spanish evacuated St. Augustine the

population was 3,104. We linearly interpolate between these values and add

them to the Pensacola population estimates obtaining an estimate for Florida.

Pensacola, the only other Florida settlement through 1763, was established in

1698 with 100 soldiers. In 1699 another 357 soldiers were added. In 1763 at the

time of evacuations there were 981 residents (Bense 1999). Assuming 15

percent women and children we estimate the population to be 118 and 538 for

1698 and 1699 respectively. We linearly interpolate to estimate the missing

values.
36 USDA Forest Service RMRS-GTR-111WWW

Numbers for the British era from 1763 to 1783 are scarce. While efforts were

made to colonize the region, they appear to have been relatively unsuccessful.

Tanner (Proctor 1975) estimated the population at the time of the American

Revolution (1776) to be approximately 1,000 whites and 3,000 blacks.

Therefore, we assume the British simply replaced the Spanish with an

equivalent number of settlers and soldiers (4,085). During the Second Spanish

era, West Florida’s population was 3,190 in 1787 and approximately 900 in East

Florida in 1791 (Tebeau 1971). We thus estimate a total Florida population of

4,090 for 1789. This suggests and therefore we assume there was no population

change from 1763 through 1789.

1795 Florida’s population was 8,363 (Bense 1999).

1825 A census put Florida’s population at 13,544 (Tebeau 1971).

Georgia - 13

Early in 1733, Oglethorpe led 116 carefully selected colonists to present day

Charleston, SC, and on Feb. 12, 1733, he founded Savannah (Georgia). Table

B5 provides the rest of the pre-census values found in Greene and Harrington

(1932) and Census Bureau (1975) estimates (estimate).

Hawaii - 15

Hawaii is an unusual state, in that it was first settled in the thirteenth century

(Castle 1917). Castle (1917) provides the insight into the Hawaiian Islands

history. The islands consisted of many warring factions up to and subsequent to

their discovery by Cook in 1777, although historical records indicate the Spanish

were aware of the Islands prior to 1777. King Kamehameha I consolidated the

islands over the next 30 years. While there were many subsequent visits by ship

after Cook’s landing, the visitors primarily engaged in commerce. Peoples of

European descent did not start settling in force until 1820 with the arrival of

Protestant American missionaries, as well as the whaling ships. Further, Hawaii

was always an independent country until its annexation to the United States in

1898. While we add the population in from 1777, when Hawaii was “discovered,”

it could easily be argued that its population should not be included prior to its

becoming a territory.

Given Hawaii was not colonized like the rest of the United States, we treat it

differently. We start with its estimated population of 300,000 (Hawaiian) at its

discovery, accounting for the entire “aboriginal” population from the onset.

Several non-federal censuses were conducted and those values are presented

in the table B6 (Hawaii 2). The “gift” of disease from visiting ships resulted in a

huge loss of life. By 1853 the native population had “dwindled” to 70,036 (Hawaii

1) versus the census value of 73,148, the difference between these two values

suggests non-native population of 3,112 at the time.

Idaho - 16

The following accounts are from Arrington (1994) except as otherwise noted.

1809 Daniel Thompson and associates (46 mule train), employed by the British Northwest Co., built the first trading structure (Wilson 1998). We

assume a party of nine (one per five mules). Thompson occupied this

structure for four years. There was a steady flow of trappers in the region

and Arrington (1994) provides detailed accounts of various trappers

(crew size rarely given) through the 1850s.

1818 Fort Nez Perce was established in 1818 with 56 trappers. We estimate a

population of 100 to account for others in the area.

1820-55 Based on the level of trapping activity we estimate a constant population of 300 during this period.

1856 The first “settlement” occurred with 79 people. Interestingly, while many

immigrants passed through from 1840-60, there is no evidence of prior

settlement. We estimate a population 400.
USDA Forest Service RMRS-GTR-111WWW 37

1859 We estimate the population to be 600.

1860 The discovery of gold brought an influx of miners to the area.

Table B7 shows the major mining areas and their approximate populations

(Arrington 1995). We assume these values represent the peak populations

occurring in 1863 and declining thereafter. We estimate Idaho’s population to be

1,000 in 1860, 1,600 in 1861, and 24,200 in 1863.

Illinois - 17

Father Marquette established a mission in 1675 (Illinois 2). We assume a

starting population of six and a constant population until Fort Creve Coeur was

built and abandoned (approx. 35) in 1680 (Illinois 1). Fort St. Louis was

completed in 1682 so we estimate a population of 41 from 1680 to1682. Greene

and Harrington (1933) was the source of the population values in table B8.

Indiana - 18

Fort Ouiatenon was established in 1717, then Fort Miami in 1721, followed by

Fort Vincennes in 1832 (Indiana). Clarksville was established in 1783 with a

population of 100. Table B9 shows the populations of the three forts from

Greene and Harrington (1933).

We assume a starting population of 56 in 1717. We develop population

estimates for Indiana by assuming constant population values for Ft. Miami

(1721 to 1783) and Ft. Ouiatanon (1717 to 1783, 56 through 1765, 48

thereafter) and add these values to the interpolated values for Vincennes. For

1783 we add 100 to the estimate for Clarksville and estimate a population of

1,404.

Iowa - 19

In 1788 DuBuque opened a lead mine (Wilson 1998) and upon his death the

Indians continued operation and kept settlers out. In 1833, with the ending of the

Black Hawk war and the removal of military protection (of the Indians from the

settlers), there was a rush of settlers into the area, first by the hundreds, then by

the thousands (Sage 1975). We use 1833 as the date of first settlement and

estimate a population of 500. A sheriff’s census in 1836 showed a population of

10,531, illustrating the magnitude of the rush.

Kansas - 20

With the pioneering of the Santa Fe Trail in 1821, Kansas experienced an

influx of immigrants through its boundaries. In 1827 Fort Leavenworth was

established with 14 officers and 174 men (Kansas) to protect the wagon trains.

Despite the heavy traffic, there was little if any settlement in the region until

Kansas became a territory in 1854, after which the population boomed to

107,206 in 1860 (census). We therefore use 1821 as the period of “first”

settlement and assume that there were at least 100 buffalo hunters and trappers

working the area. Then with the establishment Fort Leavenworth we estimate a

population of 300 in 1827, and then estimate a population of 500 in 1853.

Kentucky - 21

We use 1763 as the time of first settlement, the end of the French and Indian

War. The initial population is estimated to be 100. Although considering the War,

the numbers were likely higher. It is noted that parts of Kentucky were explored

from 1748 on and that Europeans were obviously “present” in parts of Kentucky

from 1748 forward (Kentucky). However, early settlers faced frequent Indian

attacks keeping early settlement to a minimum.
38 USDA Forest Service RMRS-GTR-111WWW

Louisiana - 22

Population data are sparse for Louisiana. Natchitoches was the first

permanent settlement, established in 1714 (Wilson 1998) with 27 (Davis,1975).

Davis (1975) provides the following information. In 1717 it is estimated that less

that 1,000 occupied the region and in 1731 the population was an estimated

7,500. A census in 1744 showed over 3,000 whites, 800 soldiers, and over

2,000 slaves (total estimate 5,900). In 1757 the colony had a population of

approximately 7,500. A 1780 census showed approximately 29,000. In 1803 the

population was estimated to be approximately 50,000.

Maine - 23

First settlement occurred at St. Croix in 1604 with 80 (Maine 1). By 1611,

there were Jesuit colonists on the Penobscot and at Mount Desert. English

fishermen and traders also visited the coast from year to year (Maine 2). In 1623

a permanent settlement was made at Saco. Other settlements around this time

included Sheepscot, Damariscotta, Pemaquid, Monhegan, and a few other

points (Maine 2).

Based on this information we estimate 400 in 1623 under the assumption of a

constant population through 1630. The following estimates are from Greene and

Harrington (1932) and United States Bureau of Census (1975): 900 in 1640,

1,000 in 1650, 20,000 in 1760, 21,587 in 1765, 31,257 in 1770, 47,767 in 1776,

49,133 in 1780, and 50,493 in 1784.

Maryland - 24

First settlement was by Leonard Calvert, with 200 settlers in 1634 (Wilson

1998). Table B10 provides the rest of the pre-census values found in Greene

and Harrington (1932) and United States Bureau of Census (1975).

Massachusetts - 25

First settlement was Plymouth in 1620 with 102, of which only 50 were left

after the first winter. Plymouth and Massachusetts were separate entities

through around 1690. Thus, we develop separate data sets through 1690 and

sum to obtain the population of Massachusetts. The table B11 provides the rest

of the pre-census values found in Greene and Harrington (1932) and United

States Bureau of Census (1975) for Plymouth and table B12 similarly for

Massachusetts. We assume a starting population of 100 in 1625 for

Massachusetts. Maine, from 1660 to 1750, was part of Massachusetts. Maine’s

population estimates were subtracted from Massachusetts’s estimates for this

period.

Michigan - 26

Dunbar (1970) provides the following information, unless otherwise noted. We

assume that slaves represent 15 percent of population, that houses represent

six people, and that men are 60 percent of the population for the remote

garrisons (all but Detroit).

1668 Marquette establishes Sault Ste. Marie with eight.

1671 The settlement moves to St. Ignance with 21 and Fort de Buade is established. We estimate a population of 51.

1683 St. Ignance has 30 soldiers. We estimate a population of 100 (50 per

fort).

1686 Fort De Buade has 400 (Greene and Harrington 1932). We estimate 450

total.

1696 The garrisons are ordered closed. We estimate that 100 people remain

in the region.
USDA Forest Service RMRS-GTR-111WWW 39

1701 Detroit was founded by Antoine de la Mothe Cadillac, with about 100

followers. We assume a constant population through 1700 and add that

to the new for an estimate of 200.

1715 Fort Michilimackinac is established.

1755 Fort St. Joseph is established.

1760 Detroit had 80 houses and a population of approximately 500 (Michigan

2). We estimate the region population to be 600, Detroit plus Fort

Michilimackinac and Fort St. Joseph.

1763 St. Joseph had 14 men and Fort Michilimackinac had 32 men. We estimate the population to be 577 (500 plus 46 men divided by 0.6).

1767 St. Joseph had 40 men. We estimate the population to be 577 (500 plus

72 men divided by 0.6).

1779 Detroit recorded 138 slaves. We estimate a population of 1,040 (Detroit

920 plus 120 for the other two forts).

1780 Detroit recorded 175 slaves. We estimate a population of 1,290 (Detroit

1,170 plus 120).

1781 Fort Michilimackinac has 100 men.

1782 Detroit recorded 179 slaves. We estimate a population of 1,400 (Detroit

1,170 plus 230).

1796 Detroit recorded 300 houses and 53 men in the garrison. We estimate a

population of 2,100.

Minnesota - 27

The first fort was Saint Antoine in 1689 (Minnesota 1). The French developed

the following forts and settlements in Minnesota: Isle Pelee in 1695, Fort L.

Huillier in 1700, Fort Beauharnois in 1727, Fort St. Pierre and Fort St. Charles in

1731, Fort Lullier in 1750, and Fort La Sueur 1755. The French ceded these

lands in 1763. From 1784 to 1803 the Northwest Trading Company (British)

operated over the Grand Portage with approximately 500 people (Blegen 1975).

There was little activity in the region until the treaty of 1837 when the Natives

ceded the lands, opening the region for European settlement. An 1840 census

showed 341 and an 1849 census put the population at 4,852 (Blegen 1975).

We note that forts were established in years 1695, 1700, 1727, and 1731 (two

forts). We assume each fort represented approximately 50 people and estimate

the population as 50 in 1689, 100 in 1695, 150 in 1700, 200 in 1727, 300 in

1731, 350 in 1750, and 400 in 1759. We further assume constant population

values between the years through 1783. From 1784 through 1803 we assume a

constant population of 500.

Mississippi - 28

In 1699 d’Iberville established the first settlement near present-day Biloxi with

80 men (Hamilton 1976). Natchez was founded in 1716 (Mississippi 1).

McLemore (1973) provides the following information. In 1704 Biloxi had 243

residents. In 1729, 246 of the 733 residents of Natchez were killed. In 1785 the

Natchez district (encompassing most of present day Mississippi) had

approximately 1,100 whites and 900 blacks. A 1793 census put the district at

4,346 residents.

We assume that Natchez was founded with 200 in 1716 and that Biloxi had

grown, estimating the population to be 500 in 1716. In 1729 we assume that

Biloxi was as large as Natchez and estimate a population of 1,500.

Missouri - 29

Foley (1971) provides the following information. St. Genevieve was the first

permanent settlement in 1735 although there is evidence of mining prior to this

time. In 1800, the original town site had 50 houses. Other forts and settlements

are Fort La Huillier (1740), Fort Orleans (1755), St. Louis (1764), and Cape
40 USDA Forest Service RMRS-GTR-111WWW

Gerareau (1793). In 1804, the population was 10,350 of which 15 percent were

slaves.

The City of St. Louis (Missouri) provides the following population estimates

for St. Louis: founded 1764 with 40 settlers, 300 in 1766, 500 in 1770, 925 in

1798, 1,100 in 1806, and 1,200 in 1811. In 1804 there were 180 houses;

assuming six per house, we estimate a population of 1,080.

We assume that St. Genevieve had a starting population of 50, which would

be typical for early French settlements. As it only had 50 houses by 1800 we

assume it reached this maximum population early (a mining community) by 1764

(300). We also assume 50 for the other two forts at the time of 1764 and add the

40 for St. Louis. Thus, we estimate the population for Missouri to be 440 in

1764. We then assume that St. Louis represents 50 percent of the population for

Missouri in 1766 and 1770 for populations of 600 and 1,000 respectively.

Montana - 30

Abbott (1964) provides the following accounting unless otherwise noted.

Manuel Lisa established the first trading post in 1807 with 40 and the trading fort

lasted through the War of 1812 when the Blackfoot attacked the fort. No other

permanent forts were established until 1828, when Fort Union with

approximately 100 was built. It is noted that the Indians (Blackfoot), in general,

did not permit whites (including fur trappers) on their lands. A small pox infection

in the early 1860s paved the way for European settlement.

1828 We use the establishment of Fort Union as the first settlement and estimate a population of 100.

1831 Fort Piegan was built. Population is estimated to be 200.

1832 Fort Cass was built and abandoned in 1835. Fort McKenzie was built

and abandoned in 1843. Population is estimated to be 400.

1836 Population is estimated to be 300.

1843 Fort Chardon built in 1843 and moved in 1844 to Fort Van Buren (Miles

city). 1845 Fort Benton was built. Population is estimated to be 400.

1853 Fort Owen built with a capacity for 150 men. Population is estimated to

be 500.

Most of the posts and fur trading forts were gone by 1860. The Federal

Government bought Fort Benton in 1868. Some missions occurred from 1840-

80. Pioneer city was started in 1862 with the discovery of gold. Then in 1863 the

gold rush gained full steam with the discovery at Alders Gulch drawing

thousands from California, Colorado, and Idaho. We assume a constant

population between years through 1861 (500). With the discovery of gold in

1862 we estimate 1,000, with 5,000 in 1863, and 10,000 in 1864.

Nebraska - 31

Olson (1966) provides the following information except as noted. Bellevue, a

trading post, was established in 1822 by the American Fur Company and was

the only settlement until 1847 when Fort Kearny was built in 1847 with 175

(Nebraska). In 1854, Bellevue was estimated to have a population of maybe 50.

It is noted that the treaties of 1833 made it illegal to occupy Indian territories

without specific permission of the Federal Government. In 1854 the Indians

ceded most of these lands, opening them to settlement. Censuses taken during

this period yielded the following counts: 2,732 in 1854, 4,495 in 1855, 10,716

and in 1856. In 1867 the population was estimated to be 50,000.

We estimate a population of 100 from 1822 through 1846 and estimate the

population to be 275 in 1847.

Nevada - 32

The Spanish entered southern Nevada as early as 1776, but no further

interest was taken in the region until 1826 when Jedediah Smith explored and
USDA Forest Service RMRS-GTR-111WWW 41

trapped parts of the Great Basin. Several other trappers worked the state

occasionally as late as 1843, as fur possibilities in Nevada were very limited and

no trading posts were established. A few emigrant parties passed through the

region from 1841 to 1845. The Donner party misfortune ended any further travel

through the area until 1848, when the discovery of gold in California prompted

others to cross once again (Elliot 1987).

Mormon Station or Genoa was the first “permanent” establishment in 1850

(Wilson 1998) with seven people (Nevada). In 1851 over 100 settlers met at

Reese’s station to establish a framework of control (Elliot 1987). In 1857, 450

Mormon settlers were recalled to Salt Lake. From 1850 to 1859, 100 to 180

miners worked the Gold Canyon, peaking in 1855.

Based on this information we estimate 1850 population to be 107. We

assume the settlers who met in 1851 to be adult males with families. Erring on

the side of caution we assume a family size of four and estimate the population

at 400 settlers and 100 miners or 500. In 1861, a census commissioned by

Governor Nye had the population at 16,374. Elliot (1987) suggested this count

included approximately 1,000 in California, so we reduce the count by that much

and show the 1861 population as 15,374.

New Hampshire - 33

David Thompson established Little Harbor in 1623 as a fishing colony (Wilson

1998). We estimate a starting population of 100. Table B13 provides the rest of the

pre-census values found in Greene and Harrington (1932) and United States

Bureau of Census (1975).

New Jersey - 34

The date of first settlement is not clear. However, in 1630, Michael Pauw

received the first Dutch land grant on the west bank of the Hudson River, which

is the current site of Jersey City (New Jersey). The first houses were built in

1633, the date we use as first settlement. We estimate 50 as the starting

population, as this was the minimum settlement size required by the charter.

Table B13 provides the rest of the pre-census values found in Greene and

Harrington (1932) and United States Bureau of Census (1975).

New Mexico - 35

Unless otherwise noted Reeve and Cleaveland (1969) are the source for this

information.

1598 Juan de Onate founded San Gabriel (Wilson 1998) with 400 men (some

130 brought wives and children) and 10 Franciscan friars. Assuming a

family size of 4.5 suggests a starting population of 865 people (New

Mexico).

1610 Santa Fe was founded. We estimate the population to be 1,000 (San

Gabriel estimated at 900 plus 100 for Santa Fe).

1638 Santa Fe had 50 houses and about 200 residents. We estimate the

population to be 1,200.

1680 An estimated 2,500 Spanish lived in New Mexico when the Indian uprising resulted in the death of 421. The rest were forced leave New Mexico,

leaving the region “unpopulated.”

1692 De Vargas reestablished Mexican control over the region with 200 soldiers. He then left and returned with 100 additional soldiers, 70 families,

some singles, and servants, for a total of over 800 people.

1696 Taos and San Cruz were founded.

1706 Albuquerque was founded with 252.

1754 Abiquiu was founded.

1765 Taos had a population of 160.
42 USDA Forest Service RMRS-GTR-111WWW

1776 The population of New Mexico was 5,201 in the following communities:

Santa Fe area - 2,014 (1337 in Santa Fe proper), Taos - 67 families or

306 residents, Santa Cruz - 680, Chiayo - 367, Quemando - 200,

Truchas - 122, Trampas - 278, Bernalillo - 81, Albuquerque - 763, and

Abiquiu - 254 plus 136 natives.

Given the number of small communities and uncertainty of their initial

establishment size, we estimate the population between 1692 and 1776 through

linear interpolation. The total population was estimated at 30,000 by the end of

the 18th century, including the Pueblos (natives).

New York - 36

Fort Orange was originally established in 1615 as a trading post but

abandoned in 1617, so we do not consider New York as having a population

until 1624 when 30 Flemish families were brought to the area (New York). Table

B15 provides the rest of the pre-census values found in Greene and Harrington

(1932) and United States Bureau of Census (1975)

North Carolina - 37

Wilson (1995) shows the first Colony being established in 1585. However, all

110 settlers vanished without a trace by 1590 and no further settlement occurred

before 1650. At that time there was an overflow of settlers from Virginia into the

Albemarle area of northeast North Carolina (North Carolina 1). We use 1650 as

the date of first settlement and estimate 100. Table B16 provides the rest of the

pre-census values found in Greene and Harrington (1932) and United States

Bureau of Census (1975).

North Dakota - 38

Robinson (1966) provides the following accounting. Alexander Henry, Jr.,

established a trading post at Pembina in 1801. In 1823, Pembina had a

population of approximately 350 and 637 in 1849. Further, in 1829, Fort Union

was established, and then Fort Clark in 1831. The official 1850 census

enumerated 1,134 persons, but the true total was actually 1,116 persons, as

three families were counted twice (North Dakota 1). Based on the actual

numbers from the Dakota Territory Census of 1860, we calculate the population

to be 3,899 (North Dakota 2) out of the 4,837 reported by the United States

Census for South Dakota in 1860.

We estimate a population of 100 in 1801. For the years from 1823 to 1849 we

linearly interpolate the Pembina estimates and add 100 for the years 1829 and

1830 (Fort Union), 200 for years 1831 to 1844, and 300 for years 1845 to 1849.

Ohio - 39

Marietta, founded in 1788, was the first permanent American settlement in

Ohio, founded by Rufus Putnam and Manasseh Cutler. By the end of 1788, 137

people populated the area (Ohio). Roseboom (1988) shows that in 1790

Columbia (Cincinnati) and Gallipolis were founded, Gallipolis with 600 French.

We estimate the population to be 300 in 1789, assuming it more than doubled

from the previous year. In 1790 we add 600 for Gallipolis and 100 for Columbia,

estimating a population of 1,000.

Okalahoma - 40

While there is little doubt that Europeans were present in the area prior to

1889, the lands were Indian Territory and not open for settlement until the land

rush in April 1889 (Wilson 1998). The population went from essentially zero to

258,657 in 1890.
USDA Forest Service RMRS-GTR-111WWW 43

Oregon - 41

We set the first date of “settlement” as 1792 based on the “roll call” of settlers

to Oregon from 1792 to 1842. We counted heads for each year of arrival and

kept a running total (Oregon); the results are presented in table B17.

Good records were kept of the wagon trains crossing to Oregon on the

Oregon Trail. Arrington (1994) provides the following values: 1,000 in 1843,

1,000 in 1844, 2,500 in 1845, 1,200 in 1846, 4,000 in 1847, and 1,300 in 1848.

Adding these values annually provides population estimates for each year. This

seems a reasonable approach, as our estimate for 1848 is 10,743 and the

United States Census Bureau 1850 value is 12,093. Additional growth of 1,350

(the difference) seems very reasonable as the 1848 California gold rush

undoubtedly attracted the majority of the westward bound travelers.

Pennsylvania - 42

The Governor of New Sweden, John Printz, built the first settlement on

Tinicum Island in 1643. In 1647 there were reported 183 under John Printz’s

command, then in 1654 that declined to 100. An influx of settlers in 1655

brought the settlement to 420 and in 1664 it was reported to be 650 (Dunaway

1948). We assume no growth from 1643 to 1647. We also note that the great

influx of settlers to the state occurred with William Penn in 1682, so we assume

a population of 680 in 1681. Table B18 provides the rest of the pre-census

values found in Greene and Harrington (1932) and United States Bureau of

Census (1975).

Rhode Island - 44

Roger Williams founded Providence in 1636. While the initial starting

population was not located, it was stated he had a small band of followers,

which we assume to be 50 (Rhode Island). Table B19 provides the rest of the

pre-census values found in Greene and Harrington (1932) and United States

Bureau of Census (1975).

South Carolina - 45

While there was an initial settlement in 1526 by Vasquez, it failed and there

was no other recorded settlement until 1670, when a group of about 100 settled

at Albemarle Point near current day Charleston (South Carolina). Table B20

provides the rest of the pre-census values found in Greene and Harrington

(1932) and United States Bureau of Census (1975).

TePaske (1964) provides the following estimates: 4,220 whites and 3,250

blacks in 1703, 4,100 blacks and 4,080 whites in 1708, 10,500 blacks and 6,250

whites in 1715, and 11,800 blacks and 7,800 whites in 1721.

South Dakota - 46

Wilson (1998) suggests that Pierre Dorian settled in the area as early as

1780. While this may be so, European presence in South Dakota was likely

limited to explorers and an occasional trapper until 1817 with the establishment

of Fort Pierre, a trading post and the first continuous European presence. (South

Dakota 1). The only other trading post noted was Fort Lookout built in 1822. The

European presence was minimal until the late 1850s with the establishment of

land companies. In 1860 the territorial census indicates a population of 914, with

the following populations: 38 in Sioux Falls established 1856: Vermillion, 228,

established 1859: and Yankton, 458, established 1859. The rest were dispersed

between various trading post and abandoned forts (North Dakota 2).

We assume a starting population of 100 in 1817 and assume the population

remains constant until 1822 when we estimate the population to be 200. Again

we assume a constant population until 1856 when we estimate 250 for that year,
44 USDA Forest Service RMRS-GTR-111WWW

1857 and 1858. Then in 1859 we estimate the population to be 850 (250 plus

600 for Vermillion and Yankton).

Tennessee - 47

William Bean established the first permanent settlement on the Watauga

River in 1768 with 10 families (Abernethy 1967). There was exploration of

Tennessee prior to 1768, but due to Indians and land grant issues settlers were

effectively kept out. In 1768 the Indians ceded their claims to the British. We

assume a family size of six and estimate the population to be 60 in 1768.

Texas - 48

Anderson and others (1988) provide the following accounting, except as

noted.

1682 Corpus Christi de la Isleta was the first mission and pueblo (called

Ysleta del Sur) in Texas, established by Antonio de Otermín and Fray

Francisco de Ayeta (Texas 1). The early settlement had 21 families plus

three friars. We estimate the population to be 129 (21 times 6 plus 3).

From the 1682 through the early 1700’s many missions were attempted

and failed.

1716 With 25 soldiers, nine priests, and 30 families Captain Domingo Ramon

established five missions: Mission San Francisco de los Tejas, Nuestra

Senora de la Purisima Concepcion, Nuestra Senora de Guadalupe de

los Nacogdoches, San Jose de los Nazonis, and Nuestra

Senora de los Dolores. We assume minimal growth through 1715 to 150

and add 214 (25 plus 9 plus 30 time 6) estimating a population of 364.

1718 San Antonio was founded.

1721 Aguayo set out for Texas with 500 men founding La Bahia and Los

Adaes (capital 1722 to 1773 and was always a small struggling community) with 100 men and left behind 269 men at San Antonio.We assume

no growth through 1720 and add 615 (369 divided by 0.6) for a population of 1,000.

1735 An additional 55 soldiers were sent to San Antonio. We assume no

growth until 1735 and estimate 1,100 with the addition of the soldiers.

1749 Escandon entered the Louisiana region with 3,000 settlers and soldiers.

1755 Escandon had placed 6,000 in 23 settlements, two of which were

Dolores and Laredo (about 250 per settlement) in the present day

boundaries of Texas. Again, we assume no further growth occurred until

1755 when we assume the two new settlements brought an additional

500 to the state and we estimate the population to be 1,600.

1778 The population of San Antonio was estimated to be 2,060 (Texas 2). In

1778 we estimate the population to be approximately 3000.

1782 Golid (La Bahia) was 512.

1790 Nacogdoches was 480.

1803 There were three communities in Texas: San Antonio population 2,500,

Golid population 1,200, and Nacogdoches population 500, for at total of

4,200.

1809 The population was estimated at 4,155.

1820 Austin (Anderson and others 1988) received a contract to bring 300

families in by 1823. From 1809 to 1819 we assume a constant population, then we add 100 families (600 people) a year through 1823, for

population estimates of 4,800, 5,400 and 6,000, respectively.

1830 The population was estimated to be 7,000 Anglos and 3,000 Mexicans

1834 The population was estimated at 24,70l.

1836 The ratio of Anglos to Mexicans was assumed to be 10 to 1 with no

change in the number of Mexicans from 1830. Thus we estimate 33,000

(Sheriden 1995).
USDA Forest Service RMRS-GTR-111WWW 45

1850 The census (212,592) is estimated to be a 50 percent increase over

1847 numbers.

Utah - 49

Utah had “settlers” long before the arrival of the Mormons in 1847, although

they were minimal in number.

1828 William Reed established a trading post in Utah. We assume a population of 100.

1838 Antoine Rabidoux bought Reed’s post and ran the business as Fort

Uinta, along with Fort Uncompahgre (Colorado) until 1844 when the

Utes burned both down (Utah 1). We assume a population of 100.

1845 Miles Goodyear built Fort Buena Ventura near present day Ogden. He

lived there with his wife, two children, Indian helpers, and other trappers.

So we estimate a population of 100.

1847 Mormons settled in the Salt Lake Valley with an initial population of 148

(Utah 2). We estimate Utah’s population at 248 (100 plus 148).

1848 Brigham Young led some 2,500 emigrants to Utah (Olson). We estimate

a population of 3,000.

Vermont - 50

Although the French established a fort on Isle La Motte in 1666 and manned

it with over 600 troops for 20 years, no efforts were made to settle the region.

The troops were part of a contingent sent to Quebec, so those that did settle the

region most likely settled around Quebec (Vermont 2). Therefore, we show the

date of first settlement to be Fort Dummer, established by the English in 1724

with 43 soldiers and 12 Mohawks (Vermont 1). Table B21 provides the rest of

the pre-census values found in Greene and Harrington (1932) and United States

Bureau of Census (1975).

Virginia - 51

Virginia began in 1607 with the settlement of Jamestown (Wilson 1998). Table

B22 provides the rest of the pre-census values found in Greene and Harrington

(1932) and United States Bureau of Census (1975).

Washington - 53

While there may have been some trading with the Indians prior to 1845, when

Tumwater was established, it was likely limited as Pacific coast Indians were

very protective of their lands and discouraged early settlement. The first settlers

came via wagon train that was led by Simmons bound for Oregon. One of the

party, George Bush, was a mulatto. Oregon law at the time forbade land

ownership by people of color. The wagon train then turned north into

Washington where such laws did not exist where they founded “New Market” or

present day Tumwater (Washington 2). The initial wagon train started out with

323 (Washington 1), which we will assume to be the initial population.

West Virginia - 54

The first “official” settlement recorded appears to be Morgan Morgan in 1726.

Indications are he was the only settler that year, possibly with his family of eight

(West Virginia 1). Lewis (1904) provides the following account. In 1727 a few

German families trickled in and founded New Meckenberg. We assume a few to

mean fewer then 10, so we estimate the population to be 50 in 1727. The next

settlement occurred in 1732 when Joist Hite settled in the region with 16

families. We assume that New Meckenberg had grown to 100 and add 100 for

Joist Hite’s group (200 total).
46 USDA Forest Service RMRS-GTR-111WWW

Wisconsin - 55

The first explorers of Wisconsin arrived in 1634, but we select 1665 as the

date of first settlement with the establishment of the first permanent missions by

Father Claude Allouez (Wilson 1998). From 1685 to 1687 three French trading

posts were established: Trempealeace, Fort St. Antoine, and Fort St. Nicolas

(Thompson 1973). In 1716 La Porte arrived at Green Bay with 800 men to

conduct a campaign against the Indians (Wisconsin 1) and built a fort at present

day Green Bay. In 1781 the only other “settlement” prior to 1800 was

established, Paire du Chiem. Around 1800 the population of Wisconsin

(European) was

estimated to be around 200 (Writers 1941). In 1820 the population was 1,455

and in 1830 approximately 3,000 (Thompson 1973). 1825 to 1835 saw a rush to

the lead mines in southwest Wisconsin. By 1836, half the 11,683 people were

estimated to be associated with the mining (Wisconsin 2). In 1847 the

population was estimated to be 210,546 (Wisconsin 2).

We assume a small presence in Wisconsin of 10 in 1665 and estimate that it

was 100 by 1685 with the establishment of the trading posts. From 1685 until

1715 we assume a constant population. In 1716 we estimate 800 for that year

only and estimate it dropped to 150 in 1717 and remained constant through

1780. In 1781, with the establishment of Praire du Chiem, we estimate the

population to be 200. Again we assume a constant population until 1800 were

we then interpolate to 1,455 in 1820.

Wyoming - 56

The first permanent settlement was Fort Laramie in 1834 (Wilson 1998), a

trading post then called Fort William. The Army purchased Fort John (Fort

Laramie) in 1849 for $4,000. The first garrison was comprised of two companies

of Mounted Riflemen and one company of the 6th Infantry. In 1850, the high tide

of emigration passes Fort Laramie; nearly 50,000 people flowed through the

area (Wyoming).

In 1842 Fort Bridger, a trading post, was built and sold in 1853 to Robinson

for use as a Mormon community. In 1868 the building of the railroad brought

large numbers into the state. The crew was approximately 10,000 strong and

when they left Cheyenne approximately 1,500 remained in the area (Writer’s

Project, Wyoming 1941).

Based on the information found, we estimate a constant population of 100

from 1834 to 1841. With the establishment of Fort Bridger in 1842, we estimate

a population of 200, which we assume remains constant through 1848. Then in

1849 we estimate 500, based on Fort Laramie’s three companies, around 200

plus the high traffic flow. We assume moderate growth until the railroad in 1868.

We estimate a population of 2,000 in 1867, which jumps to an estimated 12,000

in 1868.

Table C1—Timeline of California mission establishment.

Estimated

Year Mission population

1769 San Diego de Alcala 150

1770 San Carlos Borromeo 192

1771 San Antonio de Padua andSan Gabriel Arcangel 250

1772 San Luis Obispo De Tolosa 300

1776 San Francisco de Asis 500

1776 San Juan Capistrano 525

1777 Santa Clara de Asis 550

1780 La Purisima Concepcion (Arizona) 550

1780 San Pedro and San Pablo (Both destroyed by Yumas) 550
USDA Forest Service RMRS-GTR-111WWW 47

Table C2—Connecticut population estimates.

Year Pop. Source Year Pop. Source

1636 800 Value 1697 24,284 Taxable

1637 800 Value 1698 25,433 Taxable

1640 1,472 Estimate 1699 26,528 Taxable

1642 2,000 Value 1700 25,963 Taxable

1643 3,000 Value 1701 26,604 Taxable

1650 4,139 Estimate 1702 28,166 Taxable

1654 3,186 Value 1703 29,160 Taxable

1655 3,011 Taxable 1704 28,958 Taxable

1660 7,980 Estimate 1705 28,145 Taxable

1665 9,350 Families 1706 29,837 Taxable

1669 10,822 Freemen 1707 32,256 Taxable

1670 12,603 Estimate 1708 33,610 Taxable

1671 12,300 Men 1710 39,450 Value

1674 12,420 Men 1714 46,750 Value

1676 16,121 Houses 1715 47,500 Value

1677 12,991 Families 1720 58,830 Estimate

1678 13,695 Families 1730 75,530 Estimate

1679 13,871 Families 1740 89,580 Estimate

1680 17,246 Houses 1742 100,000 Value

1681 17,714 Taxable 1746 100,000 Value

1682 17,600 Taxable 1750 111,280 Estimate

1683 18,407 Taxable 1754 130,000 Value

1684 17,194 Taxable 1756 130,612 Census

1685 19,953 Taxable 1760 142,470 Estimate

1686 19,266 Taxable 1762 146,490 Value

1687 20,669 Taxable 1765 180,000 Value

1689 20,173 Taxable 1770 183,881 Estimate

1690 21,658 Taxable 1774 197,842 Census

1691 21,266 Taxable 1775 200,000 Value

1692 21,115 Taxable 1780 206,701 Estimate

1693 21,397 Taxable 1782 209,177 Census

1694 22,536 Taxable 1783 206,000 Value

1695 23,247 Taxable 1786 192,000 Value

1696 23,725 Taxable 1787 202,000 Value

Table C3—Delaware population estimates.

Year Pop. Source

1644 210 Men

1648 166 Men

1650 185 Estimate

1653 200 Value

1655 440 Men

1660 540 Estimate

1670 700 Estimate

1677 886 Tithable

1680 1,146 Families

1687 1,256 Taxable

1690 1,482 Estimate

1700 2,470 Estimate

1710 3,645 Estimate

1720 5,385 Estimate

1730 9,170 Estimate

1740 19,870 Estimate

1750 28,704 Estimate

1760 33,250 Estimate

1770 35,496 Estimate

1780 45,385 Estimate

1786 50,000 Value

Table C4—TePaske’s population

estimates of St. Augustine.

Year Population

1596 175

1601 275

1611 450

1621 450

1631 538

1641 575

1651 588

1661 725

1671 725

1681 988

1691 1,175

1701 912

1711 800

1721 925

1731 1,350

1741 1,325

1751 1,700

1761 2,750
48 USDA Forest Service RMRS-GTR-111WWW

Table C5—Georgia population estimates.

Year Pop. Source

1734 437 Value

1736 2,300 Value

1740 2,021 Estimate

1750 5,200 Estimate

1755 6,500 Value

1760 9,578 Value

1761 9,700 Value

1765 13,300 Value

1766 17,700 Value

1770 23,375 Estimate

1773 33,000 Value

1780 56,071 Estimate

Table C6—Hawaii census values.

Year Population

1832 130,313

1836 108,579

1850 84,165

1853 73,138

1860 69,800

1866 62,959

1872 56,897

1878 57,985

1884 80,578

1890 89,990

1896 109,020

Table C7—Early Idaho mining communities

and their peak populations.

Community Period Population

Clearwater 1860-66 1,000

Florence 1861-66 600

Boise Basin 1863-66 16,000

Idaho City 1863-66 6,000

Owyhee 1863-66 500

Table C8—Illinois population estimates.

Year Pop. Source

1723 334 Value

1726 700 Value

1732 699 Value

1750 1,460 Value

1764 1,400 Value

1766 1,488 Families

1767 1,449 Families

1770 2,000 Value

1772 1,500 Value

1787 2,424 Males
USDA Forest Service RMRS-GTR-111WWW 49 Table C9—Population estimates of Illinois

forts.

Year Vincennes Ft. Miami Ft. Ouiatanon

1733 40

1758 70

1763 280

1765 320 40 56

1767 232

1769 250 40 48

1775 240 48

1778 621

1787 1,692

1788 1,710 Table C10—Maryland population estimates. Year Pop. Source

1634 200 Wilson

1640 583 Estimate

1642 828 Tithable

1650 4,504 Estimate

1660 8,426 Estimate

1670 13,226 Estimate

1675 16,525 Tithable

1680 17,904 Estimate

1690 24,024 Estimate

1694 24,368 Taxable

1695 25,976 Taxable

1696 25,953 Taxable

1697 27,575 Taxable

1700 29,604 Estimate

1701 32,258 Value

1704 34,192 Value

1707 33,833 Value

1710 42,741 Value

1712 46,151 Value

1715 50,270 Value

1720 66,133 Estimate

1728 80,000 Value

1730 91,113 Estimate

1732 96,000 Value

1740 116,093 Estimate

1743 125,000 Taxable

1748 130,000 Value

1750 141,073 Estimate

1754 148,000 Value

1755 153,505 Census

1756 170,688 Value

1762 182,007 Value

1770 202,599 Estimate

1775 223,050 Taxable

1780 245,474 Estimate

1782 254,050 Census
50 USDA Forest Service RMRS-GTR-111WWW

Table C11—Plymouth population estimates.

Year Pop. Source

1620 102 Value

1621 50 Value

1624 180 Value

1629 300 Value

1630 390 Estimate

1633 324 Poll

1634 324 Poll

1637 732 Freemen

1640 1,020 Estimate

1643 1,167 Men

1650 1,566 Estimate

1660 1,980 Estimate

1670 5,333 Estimate

1671 5,330 Militia

1678 6,396 Freemen

1680 6,400 Estimate

1690 7,424 Estimate

Table C12—Massachusetts population estimates.

Year Pop. Source Year Pop. Source

1630 506 Value

1631 426 Value

1632 2,000 Value

1633 4,000 Value

1634 4,000 Value

1637 7,912 Value

1638 8,592 Value

1640 8,932 Estimate

1643 15,000 Value

1650 14,037 Estimate

1660 20,082 Estimate

1665 23,467 Value

1667 30,000 Value

1670 30,000 Estimate

1675 40,612 House

1678 40,000 Militia

1680 39,752 Estimate

1688 44,000 Value

1690 49,504 Estimate

1700 55,941 Estimate

1709 56,000 Value

1712 75,102 Value

1715 96,000 Value

1718 94,000 Value

1720 91,008 Estimate

1721 94,000 Value

1726 99,000 Poll

1727 106,600 Militia

1730 114,116 Estimate

1731 120,000 Value

1733 120,000 Value

1735 144,308 Value

1736 138,000 Poll

1737 138,212 Militia

1740 151,613 Estimate

1742 164,000 Value

1747 180,000 Militia

1750 188,000 Estimate

1754 200,000 Value

1758 199,587 Men

1760 202,600 Estimate

1761 228,800 House

1763 241,024 Value

1765 223,841 Census

1770 266,565 Estimate

1771 292,000 Poll

1772 293,912 Poll

1775 291,039 Value

1776 290,900 Census

1779 305,780 Poll

1780 317,760 Estimate

1781 318,580 Poll

1784 307,018 Census

1788 356,542 Value

1789 360,000 Value
USDA Forest Service RMRS-GTR-111WWW 51

Table C13—New Hampshire population

estimates.

Year Population Source

1630 500 Estimate

1639 1,000 Value

1640 1,055 Estimate

1650 1,305 Estimate

1660 1,555 Estimate

1670 1,850 Estimate

1671 1,800 Value

1680 2,047 Estimate

1682 2,399 Militia

1684 4,000 Value

1690 4,164 Estimate

1700 4,958 Estimate

1708 5,000 Men

1709 5,150 Value

1710 5,681 Estimate

1712 6,642 Value

1715 9,650 Value

1716 9,000 Value

1720 9,375 Estimate

1721 9,500 Value

1730 10,755 Estimate

1732 11,784 Poll

1737 13,100 Value

1740 23,256 Estimate

1742 24,500 Poll

1745 28,000 Poll

1750 27,505 Estimate

1753 25,568 Poll

1755 30,000 Value

1760 39,093 Estimate

1761 36,584 Poll

1767 52,720 Census

1770 62,396 Estimate

1773 73,097 Census

1774 80,000 Value

1775 81,300 Census

1780 87,802 Estimate

1786 95,849 Census

1787 102,000 Value

Table C14—New Jersey population

estimates.

Year Population Source

1665 754 Men

1670 1,000 Value

1673 2,580 Men

1676 3,500 Value

1680 3,400 Estimate

1682 3,450 Value

1690 8,000 Estimate

1698 12,000 Value

1699 13,005 Freemen

1700 14,010 Estimate

1701 15,000 Value

1708 20,000 Value

1710 19,872 Estimate

1715 22,500 Value

1720 29,818 Estimate

1726 32,422 Census

1730 37,510 Estimate

1738 46,676 Census

1740 51,373 Estimate

1745 61,403 Census

1747 70,000 Value

1750 71,393 Estimate

1752 79,000 Value

1754 81,500 Value

1755 81,800 Value

1760 93,813 Estimate

1765 100,000 Value

1770 122,806 Estimate

1772 121,008 Census

1774 130,000 Value

1775 130,000 Value

1780 139,627 Estimate

1784 149,435 Census
52 USDA Forest Service RMRS-GTR-111WWW

Table C15—New York population

estimates.

Year Population Source

1624 165 Family

1625 200 Estimate

1628 270 Estimate

1630 350 Estimate

1640 1,930 Estimate

1650 4,116 Estimate

1660 4,936 Estimate

1667 8,000 Estimate

1671 8,250 Men

1672 11,000 Militia

1673 12,000 Estimate

1674 11,000 Militia

1690 13,909 Estimate

1693 16,126 Militia

1695 16,500 Family

1698 18,067 Census

1700 19,107 Estimate

1703 20,665 Census

1708 22,000 Militia

1710 21,625 Estimate

1712 22,608 Census

1715 26,650 Militia

1716 26,970 Militia

1718 30,301 Militia

1721 31,980 Militia

1723 40,564 Census

1730 48,594 Estimate

1731 50,286 Census

1737 60,437 Census

1740 63,665 Estimate

1746 61,589 Census

1749 73,348 Census

1750 76,696 Estimate

1754 96,000 Estimate

1756 96,790 Census

1760 117,138 Estimate

1770 162,920 Estimate

1771 163,348 Census

1774 182,251 Estimate

1776 191,741 Estimate

1780 210,541 Estimate

1786 238,897 Census

1787 280,000 Estimate

Table C16—North Carolina population

estimates.

Year Population Source

1660 1,000 Estimate

1663 1,800 Family

1670 3,850 Estimate

1677 4,200 Tithable

1680 5,430 Estimate

1690 7,600 Estimate

1700 10,720 Estimate

1710 15,120 Estimate

1720 21,270 Estimate

1730 30,000 Estimate

1732 42,000 Value

1735 46,000 Value

1740 51,760 Estimate

1750 72,984 Estimate

1751 74,750 Taxable

1753 76,857 Taxable

1754 83,164 Taxable

1755 88,281 Taxable

1756 91,487 Taxable

1757 92,120 Taxable

1758 92,942 Taxable

1759 103,309 Taxable

1760 110,442 Taxable

1761 123,145 Taxable

1762 123,835 Taxable

1763 123,995 Taxable

1764 137,958 Taxable

1765 139,621 Taxable

1766 148,458 Taxable

1767 158,532 Taxable

1768 158,783 Taxable

1769 174,950 Taxable

1770 197,200 Taxable

1771 204,000 Taxable

1774 217,600 Taxable

1780 270,133 Estimate

1786 300,000 Value
USDA Forest Service RMRS-GTR-111WWW 53

Table C17—Oregon population estimates

and settlers arriving 1792 to 1842.

Year Settlers Population

1792 4 4

1793 6 10

1794 0 10

1795 0 10

1796 0 10

1797 0 10

1798 0 10

1799 0 10

1800 1 11

1801 0 11

1802 0 11

1803 0 11

1804 34 45

1805 0 45

1806 1 46

1807 5 51

1808 4 55

1809 3 58

1810 5 63

1811 25 88

1812 30 118

1813 14 132

1814 7 139

1815 1 140

1816 1 141

1817 2 143

1818 9 152

1819 4 156

1820 3 159

1821 2 161

1822 1 162

1823 3 165

1824 7 172

1825 10 182

1826 3 185

1827 2 187

1828 11 198

1829 3 201

1830 10 211

1831 5 216

1832 21 237

1833 15 252

1834 34 286

1835 11 297

1836 25 322

1837 20 342

1838 48 390

1839 56 446

1840 446

1841 446

1842 197 643

Table C18—Pennsylvania population

estimates.

Year Population Source

1680 680 Estimate

1682 3,000 Value

1683 4,000 Value

1685 8,200 Value

1688 12,000 Value

1689 12,000 Value

1690 11,450 Estimate

1693 10,660 Militia

1700 17,950 Estimate

1708 20,000 Men

1710 24,450 Estimate

1720 30,962 Estimate

1722 40,000 Value

1730 51,707 Estimate

1733 80,000 Value

1740 85,637 Estimate

1747 120,000 Value

1750 119,666 Estimate

1752 116,600 Taxable

1760 183,703 Estimate

1769 230,000 Value

1770 240,057 Estimate

1774 300,000 Value

1775 302,000 Value

1779 311,693 Taxable

1780 327,305 Estimate

1786 368,088 Taxable
54 USDA Forest Service RMRS-GTR-111WWW

Table C19—Rhode Island population

estimates.

Year Population Source

1640 300 Estimate

1650 785 Estimate

1655 1,200 Value

1658 1,200 Family

1660 1,539 Estimate

1670 2,155 Estimate

1675 2,850 House

1678 3,000 Men

1680 3,017 Estimate

1690 4,221 Estimate

1693 4,800 Men

1700 5,894 Estimate

1702 6,000 Men

1704 6,600 Men

1708 7,181 Census

1710 7,573 Estimate

1714 8,550 Value

1715 9,000 Value

1720 11,680 Estimate

1730 16,950 Estimate

1731 16,950 Value

1740 25,255 Estimate

1748 34,128 Census

1749 35,000 Value

1755 40,636 Census

1760 45,471 Estimate

1770 58,196 Estimate

1774 59,607 Census

1775 58,000 Value

1776 54,715 Value

1780 52,946 Estimate

1783 51,887 Census

1786 59,670 Value

1787 58,000 Value

Table C20—South Carolina population

estimates.

Year Population Source

1670 200 Estimate

1671 200 Value

1672 406 Value

1680 1,200 Value

1682 2,500 Value

1690 3,900 Estimate

1700 5,704 Estimate

1701 7,000 Value

1702 7,150 Value

1710 10,883 Estimate

1715 16,750 Value

1720 17,048 Estimate

1730 30,000 Estimate

1737 32,000 Men

1740 45,000 Estimate

1745 50,000 Value

1747 65,000 Value

1749 64,000 Value

1750 64,000 Estimate

1751 65,000 Value

1752 65,000 Value

1753 70,000 Value

1754 80,000 Value

1760 94,074 Estimate

1763 110,000 Value

1765 120,000 Value

1769 125,000 Value

1770 124,244 Estimate

1773 175,000 Value

1774 180,000 Value

1780 180,000 Estimate

1786 225,000 Value

Table C21—Vermont population estimates.

Year Population Source

1763 385 Family

1767 1,375 Family

1768 3,999 Family

1770 10,000 Estimate

1780 47,620 Estimate
USDA Forest Service RMRS-GTR-111WWW 55

Table C22—Virginia population estimates.

Year Population Source Year Population Source

1607 104 Value

1608 200 Value

1609 240 Value

1610 350 Value

1611 400 Men

1612 700 Value

1613 300 Value

1614 400 Value

1616 351 Value

1617 400 Value

1618 400 Value

1619 2,400 Value

1620 2,200 Value

1621 4,000 Value

1623 2,500 Value

1624 1,275 Value

1625 1,227 Census

1628 3,000 Value

1630 2,500 Value

1634 4,909 Census

1635 5,119 Value

1640 10,442 Estimate

1648 15,300 Value

1650 18,731 Estimate

1653 20,610 Tithable

1660 27,020 Estimate

1665 30,000 Men

1670 35,309 Estimate

1671 40,000 Value

1680 43,596 Estimate

1682 45,486 Tithable

1688 50,000 Value

1690 53,046 Estimate

1696 52,437 Tithable

1697 53,600 Tithable

1698 55,002 Tithable

1699 58,040 Census

1700 58,560 Estimate

1701 57,596 Census

1702 60,606 Value

1703 71,746 Tithable

1704 72,167 Tithable

1705 72,502 Tithable

1708 80,400 Tithable

1710 78,281 Value

1714 84,527 Tithable

1715 84,843 Tithable

1721 84,000 Value

1722 84,560 Tithable

1723 89,065 Tithable

1724 98,284 Tithable

1726 102,720 Tithable

1729 107,959 Tithable

1730 114,000 Value

1740 180,440 Estimate

1750 231,033 Estimate

1755 231,632 Tithable

1756 293,472 Value

1759 314,445 Tithable

1760 339,726 Estimate

1761 339,861 Tithable

1762 363,066 Tithable

1763 368,826 Value

1766 409,480 Tithable

1769 409,480 Tithable

1770 447,016 Value

1772 522,087 Tithable

1773 529,861 Tithable

1774 560,000 Value

1780 538,004 Estimate

1782 567,614 Value

1786 650,000 Value

1787 700,000 Value

1788 821,385 Value
The Rocky Mountain Research Station develops scientific

information and technology to improve management, protection, and use of the forests and rangelands. Research is designed to meet the needs of National Forest managers, Federal

and State agencies, public and private organizations, academic

institutions, industry, and individuals.

Studies accelerate solutions to problems involving ecosystems, range, forests, water, recreation, fire, resource inventory,

land reclamation, community sustainability, forest engineering

technology, multiple use economics, wildlife and fish habitat,

and forest insects and diseases. Studies are conducted cooperatively, and applications may be found worldwide.

Research Locations

Flagstaff, Arizona Reno, Nevada

Fort Collins, Colorado* Albuquerque, New Mexico

Boise, Idaho Rapid City, South Dakota

Moscow, Idaho Logan, Utah

Bozeman, Montana Ogden, Utah

Missoula, Montana Provo, Utah

Lincoln, Nebraska Laramie, Wyoming

*Station Headquarters, Natural Resources Research Center, 2150 Centre Avenue, Building A, Fort Collins, CO 80526

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