Geochemical 

Survey of Missouri 

Geography of Soil Geochemistry of 

Missouri Agricultural Soils 

By RONALD R. TIDBALL 

Geochemical Classification by Factor Analysis~ of 

Missouri Agricultural Soils 

By RONALD R. TIDBALL 

G E 0 L 0 G I CAL SURVEY P R 0 FE S S I 0 N A L PAPER 9 54 -H, I 

UNITED STATES GOVERNMENT PRINTING O:FFICE, WASHINGTON 1984 
UNITED STATES DEPARTMENT OF THE INTERIOR 

WILLIAM P. CLARK, Secretary 

GEOLOGICAL SURVEY 

Dallas L. Peck, Director 

Library of Congress Cataloging in Publication Data 

Tidball, Ronald R. 

Geography of soil geochemistry of Missouri agricultural soils. 

(Geochemical survey of Missouri) (Geological Survey professional paper ; 954 H-1) 

Includes bibliographies 

Supt. of Docs. no.: I 19.16:954-H 

1. Soils-Missouri-Composition. 2. Soils-Missouri-Classification-Statistical methods. 3. Geochemistry-Missouri. 4. Factor analysis. 

I. Tidball, Ronald R. Geochemical classification by factor analysis of Missouri agricultural soils. 1983. II. 

Title. III. Series. IV. Series: Geological Survey professional paper; 954 H-I. 

S599.M52T524 1983 631.4'9778 82-600306 

For sale by the Branch of Distribution 

U.S. Geological Survey 

604 South Pickett Street 

Alexandria, VA 22304 
CONTENTS 

[The letters in parenthe~es preceding the titles are those used to designate the chapters) 

(H) Geography of soil geochemistry of Missouri agricultural soils . . . . . . . 

(I) Geochemical classification by factor analysis of Missouri agricultural soils 

Page 

Hl 

I1 
• 
Geography of Soil Geochemistry of 

Missouri Agricultural Soils 

By RONALD R. TIDBALL 

GEOCHEMICAL SURVEY OF MISSOURI 

G E 0 L 0 G I CAL SURVEY P R 0 FE S S I 0 N A L PAPER 9 54 -H 

A study of the distribution of 4 3 elements 

in agricultural soils at 1,140 locations 

in Missouri 

Abstract ........ . 

Introduction . . . . . . . 

Review of literature 

Acknowledgments 

Soil parent materials 

Methods ...... . 

Field methods . . 

Laboratory methods 

Data analysis 

Results ..... 

Discussion . . . 

References cited 

CONTENTS 

ILLUSTRATIONS 

FIGURE 1. Map showing soil- forming parent materials of Missouri ... 2--44. Element distribution in selected agricultural soils of Missouri 

2. Aluminum. 

3. Arsenic 

4. Barium 

5. Beryllium 

6. Boron .. 

7. Cadmium 

8. Calcium 

9. Carbon 

10. Cerium 

11. Chromium 

12. Cobalt .. 

13. Copper 

14. Fluorine . 

15. Gallium 

16. Iodine .. 

17. Iron ... 

18. Lanthanum 

19. Lead . .. 20. Lithium .. 

21. Magnesium 

22. Manganese 

23. Mercury .. 

24. Molybdenum 

25. Neodymium. 

26. Nickel ... 

27. Niobium .. 

28. Phosphorus 

29. Potassium. 

30. Scandium 

31. Selenium 

32. Silicon . 

33. Silver .. 

34. Sodium 

35. Strontium . 

36. Thorium .. 

III 

Page 

H1 

1 

1 

1 

2 

2 

2 

2 

4 

6 

7 

10 

Page 

H3 

12 

13 

14 

15 

16 

17 

18 

19 

20 

21 

22 

23 

24 

25 

26 

27 

28 

29 

30 

31 

32 

33 

34 

35 

36 

37 

38 

39 

40 

41 

42 

43 

44 

45 

46 
IV CONTENTS 

Page 

F'IGURES 37-44. Element distribution in selected agricultural soils of Missouri-Continued 

37. Tin . . . H47 

38. Titanium 48 

39. Uranium 49 

40. Vanadium 50 

41. Ytterbium 51 

42. Yttrium . 52 

43. Zinc . . . 53 

44. Zirconium 54 

TABLES 

Page 

TABLE 1. List of elements looked for, methods of analysis and lower limits of 

determination . . . . . . . . . . . . . . . . . . . . . . . . . . . 

2. Average total concentrations of elements in Missouri soils . . . . . . . . . . 

H4 

6 

3. Comparison of mean concentrations in Missouri agricultural soils determined in 

this study with a previous study by Erdman and others (1976b) and with 

the mean concentrations in parts of the eastern U.S. . . . . . . . . 

4. Variance components of soil elements . . . . . . . . . . . . . . . . . . . 

5. Variance mean ratios for soil elements within areas of decreasing size 

7 

8 

9 
GEOCHEMICAL SURVEY OF MISSOURI 

GEOGRAPHY OF SOIL GEOCHEMISTRY OF MISSOURI 

AGRICULTURAL SOil.S 

By RONALD R. TIDBALL 

ABSTRACT 

Samples of 1,140 agricultural soils from throughout the State of 

Missouri were analyzed for total concentrations of 43 elements. The 

results are shown on gray-level symbol maps. Soils developed on 

young parent materials, such as glacial till, loess, and alluvium, tend 

to have large concentrations of numerous elements, notably calcium, 

potassium, magnesium, and sodium. Soils developed on deeply weathered residuum from carbonate rocks have large amounts of silicon 

(exceeding 40 percent in some cases), titanium, and zirconium and 

have very small amounts of most other elements. 

INTRODUCTION 

The amounts of various elements in surficial geologic 

material differ from one location to another. This condition has resulted from geologic and soil-forming processes that have concentrated certain elements more in 

some environments than in others. More recent processes, including the activities of man, have tended to 

redistribute the elements in still more diverse patterns. 

The character of these patterns may be estimated by 

reconnaissance geochemical survey techniques such as 

those being developed by the U.S. Geological Survey 

(Miesch, 1976). 

The geochemical survey of the agricultural soils of 

Missouri was undertaken (1) to determine typical natural concentrations of the elements in soils as expressed 

by total analyses, and (2) to describe the geographic 

patterns of compositional variation. Both univariate and 

multivariate interpretations of the data will be given, 

but the multivariate treatment appears separately in 

a companion report, Chapter I. Typical concentrations 

of elements are given by the grand mean and deviation, 

by histograms, and by the 95 percent expected range. 

The geographic distributions are illustrated by graylevel symbol maps. 

The geochemical survey was conducted primarily to 

assist epidemiologists at the University of Missouri in 

their studies of the possible relation between health 

(animal and human) and trace substances in the environment. In addition, the survey is part of the continuing development of reconnaissance sampling techniques 

for large areas: Missouri contains about 180,000 square 

kilometers. 

RI~VIEW OF LITERATURE 

There are very few previous reports of total chemical 

analyses of soils in Missouri. Several important soil 

series were analyzed for both major and minor elements 

by Pickett and Dinius (1954). Johnson (1950) studied 

the cobalt and copper concentrations in 26 different 

soils. The arsenic, copper, and lead concentrations of 

both contaminated orchard soils and selected natural 

soils were repo1rted by Hess and Blanchar (1977). Missouri was included in extensive geochemical maps of 

the conterminous U.S. that showed the distribution of 

over 30 elements in soils and other surficial materials 

(Shacklette and others, 1971a, b; 1973; 197 4). 

Plants and associated soils were collected from within 

major native-vegetation-type areas in Missouri in two 

different studies. In the first one, Erdman Shacklette, 

and Keith (1976a) collected native plants and the B horizon of uncultivated soils at 60 sites from throughout 

the State. In the second study (Erdman and others, 

1976b), crop plants and the plow zone of cultivated soils 

were collected from 40 sites. 

ACKNOWLEDGMENTS 

Sample collection was guided by the Statewide staff 

of the Extension Division of the University of Missouri 

under the supervision of Dr. Walter F. Heidlage, Program Coordinator, Extension Environmental Health. 

Chemical analyses of all samples were made in the laboratories of the U.S. Geological Survey in Denver, Colorado and Reston, Virginia by: L. A. Bradley, 

semiquantitative spectrograph and J. S. Wahlberg, M. 

W. Solt, and Mike Brown, X-ray fluorescence. Additional analyses for selected elements were done by 

Johnnie GardnE!r and Violet Merritt, magnesium and 

Hl 
H2 GEOCHEMICAL SURVEY OF MISSOURI 

sodium; I. C. Frost, G. T. Burrow, and G. D. Shipley, 

carbon; J. P. Cahill, cadmium; J. A. Thomas, lithium 

and zinc; R. L. Turner, mercury; F. W. Brown, Joseph 

Budinsky, B. A. McCall, Leung Mei, and Roosevelt 

Moore, arsenic and fluorine; A. J. Bartel, iodine; A. 

J. Bartel, E. L. Brandt, J. P. Hemming, R. J. Knight, 

H. T. Millard, R. J. Vinnola, R. J. White, uranium 

and thorium. Computer programs for mechanical plotting were written by M. R. Mall. The special assistance 

of J. G. Boerngen in automatic data processing is gratefully acknowledged. 

SOIL PARENT MATERIALS 

The distribution of bedrock in Missouri was compiled 

by McCracken (1961) and the geology of Missouri was 

summarized by Vineyard and others (1967, p. 13-31). 

The distribution of soil parent materials in Missouri is 

shown in figure 1; the bedrock in more than half of 

the State is covered by an overburden of glacial materials that includes till, loess, and outwash. These glacial 

materials are geologically younger, and therefore less 

weathered than the residual type of parent materials 

in the southern half of the State. The southern limit 

of glaciation across central Missouri defines the approximate limit of glacial till. However, loess extends as 

far south as the 38th parallel. Loess also occurs in a 

narrow band along the Mississippi River valley in 

southeast Missouri. Much of the original loess cover has · 

been completely eroded away, especially on the steeper 

slopes, but some deposits remain on the broad interstream divides. Loess deposits of maximum thickness 

(more than 10 meters) occur on the bluffs along both 

the Missouri and Mississippi Rivers. The thickest loess 

deposits occur in northwest Missouri along the Missouri 

River; they diminish in thickness and extent toward 

the east where recognizable deposits occur only on the 

broad interstream divides. 

Glacial till is widely exposed in northern Missouri 

where the loess cover is absent. A typical exposure is 

on the side slopes of the rolling terrain between the 

loess cover of the interstream divide that tapers from 

above and the mixed alluvium of the valley bottom that 

tapers from below. Most of northern Missouri is, therefore, a mosaic of loess and glacial till with scattered 

exposures of bedrock in the lower portions of the valley 

sides. 

A limited exposure of granites and felsites of Precambrian age occurs in southeast Missouri in Iron, Madison, and St. Francois Counties, with an outlier in Shannon County. These exposures are surrounded by outcrops of cherty dolomite of Cambrian age. The bulk 

of the Ozark Plateaus province is covered by a thick, 

brick-red, cherty, and highly weathered residuum from 

carbonate rocks-dolomite of Ordovician age and limestone of Mississippian age. Sandstones, shales, and 

limestones of Pennsylvanian age are exposed in westcentral Missouri. The bedrock in areas near the southern limit of glaciation is covered to various degrees by 

loess, which ranges in thickness from a few centimeters 

to several meters. 

The valleys of the Missouri and Mississippi Rivers 

are flat plains composed of fine-grained alluvial sediments of recent age. The Mississippi Alluvial Plain 

(Fenneman, 1946) of southeast Missouri contains 

sedimets from both the Mississippi and Ohio Rivers as 

well as local streams. A central ridge on the Plain is 

composed of materials of Tertiary and Cretaceous ages. 

METHODS 

The methods of sampling, laboratory analysis, and 

statistical reduction of data that are used in this study 

were described by Miesch (1976). The following sections 

under the headings of field methods, laboratory 

methods, and data management discuss the application 

to this study. 

FIELD METHODS 

The soil samples represent the population of soils defined as the surface soil horizon (plow zone, 0-15 em 

depth) of agricultural fields throughout Missouri. The 

samples were collected by individual landowners from 

selected fields for fertilizer recommendation under the 

program of the University of Missouri Extension Division. Each sample is a composite of several vertical 

channel subsamples collected haphazardly within a 

field. Each local county Extension Agent selected 10 

of the composite samples that were thought to be representative of some of the principal soils that occur in 

the county. About 10 percent of the samples had to 

be recollected by the author because the original samples were insufficient in amount. A total of 1140 samples (10 each from 114 counties) were collected. The 

sampling localities are scattered throughout most of the 

counties. 

lo 

LABORATORY METHODS 

A random selection of 60 samples were each split into 

two parts in order to estimate analytical reproducibility. The entire suite of samples including the 60 duplicates were arranged in a randomized sequence. Both 

sample preparation and analysis were performed in that 

sequence to avoid confounding any inherent geographic 

variation with a possible systematic analytical error. 

Randomization does not eliminate a systematic error, 

but the error is effectively transformed into one that 
GEOGRAPHY OF SOIL GEOCHEMISTRY 

1. Loess or glacial till 

2. Shales and limestones of Pennsylvanian age 

3. Shales and sandstones of Pennsylvanian age 

4. Cherty limestone of Mississippian age 

5. Cherty dolomite of Ordovician age 

6. Granite and cherty dolomite of Cambrian and 

Precambrian age 

7. Recent Mississippi and Ohio Rivers alluvium and a 

central ridge of Tertiary and Cretaceous ages 

..--:--:-• Approximate forest-prairie boundary; forest south and 

· · · east, prairie north and west of boundary 

FIGURE 1.-Map showing soil-forming parent materials of Missouri. (Adapted from Scrivner and others, 1966; physical regions after 

Fenneman, 1946). 

H3 

is random with respect to geographic location. Each 

sample was air dried, gently disaggregated, sieved 

through a 2-mm stainless steel screen, ground in a 

ceramic mill to -100 mesh, and then thoroughly mixed 

to ensure homogeneity. 

The samples were analyzed for 70 elements. The total 

concentrations were determined chiefly by emission 

spectrographic analysis. The concentrations of some 

elements, however, were outside of the optimum range 

of the spectrographic method. For those elements of 
H4 GEOCHEMICAL SURVEY OF MISSOURI 

special interest, therefore, other analytical methods, 

such as atomic absorption, neutron activation, and Xray fluorescence, were substituted for the spectrographic method. It was impractical to anal~e all 1200 

samples for iodine, thorium, and uranium because of 

the expense of the neutron activation procedure. Therefore, only one randomly selected sample from each 

county was analyzed for iodine, and two randomly 

selected samples from each county were analyzed for 

thorium and uranium. 

The elements looked for, the methods of analysis, and 

the lower limits of determination are summarized in 

table 1. Elements that were looked for in all samples 

but were never found above the lower limits of determination are as follows: antimony, bismuth, germanium, gold, hafnium, indium, palladium, platinum, 

rhenium, tantalum, tellurium, thallium, tin, and 

tungsten. If cerium and lanthanum were found, then 

other elements were looked for as follows: europium, 

neodymium, praseodymium, and samarium. If yttrium 

was found in concentrations greater than 50 parts per 

million, which was rare, then the following elements 

were looked for: dysprosium, erbium, gadolinium, holmiun, lutetium, terbium, and thulium. If lead or 

platinum were found, then the following elements were 

looked for: iridium, osmium, rhodium, and ruthenium. 

Detailed descriptions of the analytical procedures are 

given for semiquantitative emission spectrography 

(Neiman, 1976), X-ray fluorescence (Wahlberg, 1976), 

atomic absorption and other related chemical methods 

(Huffman and Dinnin, 1976), radioisotope dilution-neutron activation for iodine (Bartel and Millard, 1976), and 

delayed neutron counting for uranium and thorium (Millard, 1976). The method of reporting semiquantitative 

spectrographic analyses has been described by Miesch 

(1976). The concentrations of elements in soils are expressed as either parts per million or percentages of 

air-dry weight of the less-than-2 mm soil material. 

DATA ANALYSIS 

Most tests of statistical significance require normal 

distributions in the populations from which the data are 

drawn. Tests for this condition show that the distributions of most elements are much closer to being lognormal than normal. Consequently, the data for all elements except aluminum, iodine, iron, potassium, sodium, and silicon were transformed to logarithms prior 

to statistical analysis. 

The average concentrations for those elements 

thought to be lognormally distributed are estimated by 

the geometric mean (GM), which is the antilogarithm 

of the mean of the logarithmic values (table 2). The 

deviation about the mean is estimated by the geometric 

TABLE 1.-List of elements looked for, methods of analysis, and 

lower limits of determination 

[*, element has been looked for but the range of concentrations in most common soils 

is below the lower limit of determination for the method and no data are available; 

or element has not been looked for because associated elements were not detected] 

Element 

Ag-----------

Al---------

As-----------

Au*---------

B------------ Ba-----------

Be-----------

Bi *----------

C (total)----

C (inorganic) 

C (organic)--

Ca-----------

Cd---------

Ce-----------

Co----------- Cr----------

Cu----------

Dy*---------

Er*----------

Eu *----------

F------------

Fe-----------

Ga-----------

Gd*----------

Ge*--------

Hf*----------

Hg---------

Ho*----------

I----------

In*----------

Ir*----------

K-----------

La----------

Li-----------

Lu*----------

Mg----------

Mn----------

Mo-----------

Na----------

Nb-----------

Nd---------

Ni ---------

Os*------- P----------- Pb-----------

Pd*----------

Pr*----------

Pt*-------

Re*----------

Rh*----------

Ru*----------

Sb*---------

Se-----------

Se-----------

Si ----------

Sm*----------

Sn---------

Sr----------

Ta*--------

Tb*--------

Te*---------

Th----------

Ti -----------

Tl*-------

Tm*----------

u--------

v-----------

W*------

y ------------ Yb-----------

Zn---------- Zr----------

Analytical method Lower limit of determination 

(parts per million) 

Spe ct rogr ap hie----------------

X-ray fluorescence------------

Spe ct rop ho tome t ric-----------

Spe ct rogr aphi c----------------

---<1 o------------------------- ---d o-------------------------

---do-------------------------

---do------------------------

Induct ion Furnace-------------

Gasomet ric--------------------

Difference between total and 

inorganic. 

X-ray fluorescence------------

Atomic absorption------------

Spectrographic---------------

---do-------------------------

---do-------------------------

---do-----------------------

---do-------------------------

---do-----------------------

---do-----------------------

Selective ion electrode-----

X-ray fluorescence------------

Spectrographic-------------

---do-----------------------

---do------------------------

---do-------------------

Instrumental atomic absorption 

Spectrographic-------------

Neutron activation-----------

Spe ct rogr ap hie---------------

---do----------------------

X-ray fluorescence-----------

Spectrographic---------------

Atomic absorption-------------

Spe ct rographi c--------------

Atomic absorption-------------

Spe ct rogr aphi c--------------

---do------------------------

Atomic absorption-------------

Spectrographic--------------

---do-----------------------

---do-------------------

---do----------------------

X-ray fluorescence----------

Spectrographic----------------

Spectrographic---------------

---do--------------------

---do-----------------------

---do------------------------

---do------------------------

---do----------------------

---do---------------------

---do-------------------

X-ray fluorescence------------

X-ray fluorescence-------

Spe ct rogr ap hie---------------

---do------------------

---do----------------

---do---------------------

---do---------------------

---do----------------------

Neutron activation--------

Spectrographic---------------

---do--------------------

---do----------------------

Neutron activation------------

Spectrographic---------------

---do-----------------------

---do------------------------

---do------------------------

Atomic absorption--------

Spe ct rogr ap hie---------------

0.5 

10,000 

1 

20 

20 

2 

1 

10 

500 

100 

1,000 

150 

1 

150 

3 

1 

1 

50 

50 

100 

40 

150 

5 

50 

10 

100 

.01 

20 

.05 

10 

50 

200 

30 

5 

30 

200 

1 

3 

80 

10 

70 

5 

50 

500 

10 

2 

100 

50 

50 

2 

10 

200 

5 

1,000 

100 

10 

5 

500 

300 

.1 

2,000 

1.2 

2 

50 

20 

.I 

7 

100 

10 

1 

10 

10 
GEOGRAPHY OF SOIL GEOCHEMISTRY H5 

deviation (GD), which is the antilogarithm of the standard deviation of the logarithmic values. The error variance for logarithmic values is estimated by the geometric error (GE), which is the antilogarithm of the square 

root of the logarithmic analytical error variance. The 

arithmetic mean (AM), the standard deviation (SD), 

and the standard error (SE) are given for the other 

elements. 

The GD describes the dispersion about the GM so 

that the expected range of 68 percent of the population 

is within the bounds of GM -:-GD to GMxGD. The expected range of 95 percent of the population is from 

GM -:-GD2 to GMxGD2 • The expected range of 68 percent of the population on an arithmetic scale lies within 

the bounds of AM±SD; the 95 percent expected range 

lies within the bounds of AM±2SD. GE and SE express 

the reproducibility of the laboratory procedures for this 

sample set, but more particularly they provide an estimate of that portion of the total variation that is attributed to analytical imprecision. The remainder of the 

total variation is attributed to sampling and geographic 

variability. 

The lower limits of determination by certain methods 

are above some of the smaller concentrations that are 

typical for some elements; some of the frequency distributions, therefore, are truncated on the left side or leftcensored. The means and deviations for such elements 

were estimated by the method of Cohen (1959), described by Miesch (1976). However, some of the frequency distributions are so severely censored that it 

was possible to report only that the mean is less than 

the lower limit of determination. 

The frequency distribution of data for each element 

was divided into 3 or 5 classes; the classes are of unequal width and were defined so that each contains 

about the same number of samples. Gray-level symbol 

maps (figs. 2-44) illustrate the distribution of samples 

that have concentrations within each class. 

The total variation for each element is comprised of 

the analytical-error variance and the geographic variance. Excessive error variance can easily obscure the 

geographic variation, but there is no way of subtracting 

the effects of such error from each sample. Because 

all the samples were analyzed in a randomized sequence, however, it is unlikely that any resulting map 

patterns reflect a systematic error generated in the laboratory. In general, the smaller the proportion of 

analytical-error variance, the greater is the confidence 

that a given map symbol reflects the actual sample 

composition. Even under conditions of perfect analysis, 

however, local variation in soil compositions can 

obscure regional geographic patterns. Soils tend to be 

naturally heterogeneous in composition and a sample 

collected at a given point may differ markedly from 

another one collected only a few meters away. Although a map symbol may truly reflect the composition 

of the sample, it may also misrepresent the composition 

of the general area from which the sample was collected. Chance fluctuations due to small-scale compositional diversity, therefore, may cause small-scale patterns that are not reproducible. 

If the actual geographic variance of an element is 

small, even small analytical errors or small local fluctuations can cause a regional geochemical map to be unstable. An unstable geochemical map is one whose pattern would be nonreproducible if the sampling and 

laboratory analysis were to be repeated. Thus, the critical measure of the stability or reproducibility of a 

geochemical map is the ratio of the total variance across 

the map, or some part of it, to the local variance which 

is due in varying part to analytical variation. If this 

ratio is large, the analytical variation and the local fluctuations are unlikely to obscure the regional geochemical pattern, and it is likely that the same regional pattern would emerge if the sampling and laboratory analysis were repeated. If this ratio is small, however, the 

pattern displayed by the map may be completely unreliable. The ratio suggested by Miesch (1976), referred 

to as Vm, is the variance among the sampling locality 

means over the error variances of the means. The sampling localities may be defined in various ways to 

examine map stability at different scales. 

The Vm ratio was calculated using variance components that were derived from a 4-level nested analysis 

of variance (table 4) and that represented sources of 

variation within areas of diminishing size as follows: between groups of six contiguous counties, between pairs 

of counties within groups, between counties within 

county pairs, and between samples within each county. 

The equation for Vm was modified along the lines of 

the general equation of Cochran (1963, p. 286) to incorporate finite population correction factors. The general 

equation for the Vm of groups is 

where the s2 terms are the variance components at the 

group (g), county pair (p), county (c), and sample (s) 

levels, the n's are the number of items selected from 

a population of N items, and f terms are the ratios 

of n/N for each of the above levels, respectively. The 

88

2 term ~ontains variance due to both sampling error 

and laboratory error. Because the entire population of 

N items was selected for p and c levels and because 

the (1-j)-terms are nearly zero, the first two terms in 
H6 GEOCHEMICAL SURVEY OF MISSOURI 

the denominator drop out and the general equation (1) 

reduces to 

s 2 

Vm(g) =_!!_X 60 

s 2 

8 

for groups of size counties, 

s 2 

vm(P) = _!!_ x 20 for county pairs, and 

Ss2 

s 2 

Vm(c) = _.!!.___ x 10 for counties. 

Ss2 

(2) 

(3) 

(4) 

The Vm ratio may be viewed as a relative index of reproducibility of the map pattern at the scale for which 

the ratio was computed. By a Monte Carlo simulation 

technique, it was found that the general configuration 

of a map pattern is almost totally unreproducible if the 

computed ratio is less than 1 (Tidball, 1972, p. 20-21). 

Reproducibility increases as the ratio increases over 1, 

and good reproducibility is generally present if the ratio 

is about 3 or more. 

RESULTS 

Total element concentrations in the surface horizon 

of Missouri agricultural soils are summarized in table 

2. The grand means, deviations, ranges, and measures 

of the analytical precision are shown for all elements 

except for those with severely censored distributions. 

The detection ratios for severely censored distributions 

(as for cadmium, molybdenum, silver, and tin) show 

that only a few of the 1140 samples analyzed contained 

detectable quantities of the element. For moderately 

censored distributions (for example, beryllium with a 

detection ratio of 520:1140) the mean and deviation are 

estimated by methods of Cohen (1959), described in 

Miesch (1976). Carbon is reported in three forms as 

carbonate, organic, and total, but nearly all of the carbon occurs in the organic form. 

The grand means for Missouri agricultural soils are 

compared in table 3 with grand means that were calculated from the area means reported by Erdman, 

Shacklette, and Keith (1976b). The means for soils of 

the United States collected east of the 97th meridian 

(Shacklette and others, 1971a, b; 1973; 197 4) are also 

included for comparison to show the relative position 

of Missouri soils. 

The ave:;_·,~g-e concentrations of elements in cultivated 

soils reported in tables 2 and 3 are nearly the same 

as the averages given by Erdman, Shacklette, and 

Keith (1976b, tables 8, 9, 10, 11). Although the estimates of this report are considered to be more precise 

TABLE 2.-Average total concentrations of elements in Missouri soils 

[Detection ratio is number of samples with detectable concentration to total number 

analyzed. Geometric mean, geometric deviation, and geometric error given except a..~ 

noted by a..~terisk (*) where arithmetic mean, standard deviation, and standard error 

are given. Mean values and ranges are in prrts per million except as noted in percent. 

Leadered entries(--) mean insufficient data] 

Element Detection Geometric Geometric Geometric 

ratio deviation Observed range 

Ag------------------- 4:1140 (0. 7 <O. 7 - 3 

Al, pet-------------- 1140:1140 4.1* 1.19* 1.1 - 7. 9 o. 34* 

As------------------- 1140:1140 R. 7 1.46 2.5 - 72 1.16 

B-------------------- 1113:1140 31 1. 34 (20 - 700 1.40 

Ba------------------- 1140:1140 SRO 1.46 100 - 1500 1.2?. 

Be------------------- 520: 1!40 0.8 1.43 <I - 2 1.1fi 

c (as total), pet---- 1140:1140 1.30 1.50 0.24 - s. 2 1.07 

c (as carbonate) pet- 946:1140 0.02R 2.R 5 (0.01 - 2.9 2.31 

c (as organic) pet--- 1140:1140 1.25 1.53 0.08 - s. 2 1.11 

Ca, pet-------------- 1114:1140 0.33 2.03 (0.07 - 5.6 1.12 

Cd------------------- 12:1140 0 <1 - 11 

Ce------------------- 435:1140 115 1.27 <ISO - 300 

Co------------------- 1139:1140 10 1.50 <3 - 30 1.27 

Cr------------------- 1140:1140 54 1.44 10 - 150 1. 27 

Cu------------------- 1140:1140 13 1.55 5 - 150 1.28 

F-------------------- 1140:1140 270 2.22 10 - 6400 1.86 

Fe, p c t -------------- 1140:1140 2.11* 0.64* 0.49 - 5.4 0.12* 

Ga------------------- 1111: 1!40 11 1.49 <S - 30 1.22 

Hg------------------- 1124:1140 0.039 1.80 <.01 - 0.8 1. 53 

I-------------------- 114: 1!4 4.4* l.fi5* 1.2 - 11.7 0.65* 

K, p c t --------------- 1140:1140 1.4* 0.40* 0.33 - 3. 7 0.07* 

La------------------- lJ 36: 1140 41 1. 39 <30 - !50 1.2fi 

Li ------------------- 1140:1140 22 1. 28 7 - 47 1.05 

Mg, pc t -------------- 1140:1140 0.26 1.65 0.05 - 2.8 1.10 

Mn------------------- 1140:1140 740 1.83 15 - 3000 1.30 

Mo------------------- 16:1140 <3 (3 - 15 

Na, pet-------------- 1140:1140 0.53* 0.23* 0.07 - 1.2 0.03* 

Nh------------------- 375:1140 7. 2 I. 38 <10 - 15 1.11 

Nd------------------- 739:1140 63 1.17 <70 - 150 

Ni ------------------- 1131:1140 14 1.59 <S - 70 1.24 

P, pc t --------------- !130: 1140 0.059 l.fi1 <.01 - 0.61 1.30 

Pb------------------- 1140:1140 20 1.55 10 - 7000 1.22 

Sc------------------- 1092:1140 7 ·" 1. 34 (5 - 15 1.16 

Se------------------- 925: 1!40 n. 2R 2.54 <0.1 - 2. 7 1.6 7 

Si, pc t-------------- 1140:1140 35* 2. 77* 23 - 43 1.32* 

Sn------------------- 9:1140 <15 <15 - 50 

Sr------------------- 1140:1140 110 1.60 20 - 500 1.25 

Th------------------- 199:22R 9.6* 2.4 7* 3. 2 - 21 2.29* 

Ti ------------------- 1140:1140 3300 1.31 1500 - 7000 1.20 

u-------------------- 22R: 22R 3.R 1.34 1.1 - 15 1.26 

v-------------------- 1140:1140 69 1.50 15 - 150 1.25 

Y-------------------- 113R: 1140 32 1.35 on - 70 1.25 

Yh------------------- 1138:1140 3.2 1. 31 <1 - 7 1.25 

Zn------------------- 1140:1140 49 1.55 1R - 640 1.08 

Z r------------------- 1140:1140 310 I. 53 70 - 700 1.35 

because they are based on 1140 samples, it is remarkable that the estimates by Erdman, Shacklette, and 

Keith that are based on only 40 samples are so similar. 

Q.ompared with the soils of the eastern U.S., the soils 

of Missouri tend to have slightly larger amounts of 

barium, chromium, florine, lead, manganese, strontium, 

vanadium, and zinc. 

The geochemical patterns of the elements across the 

State are shown in figures 2 to 44 as gray-level symbol 

maps. Actual measured values rather than symbols are 

given for those elements where frequency distributions 

are severely censored and where histograms are not 

shown. Means, deviations, and measures of analytical 

precision from table 2 are repeated on the maps for 

the convenience of the reader. What confidence do we 

have that the map is faithfully portraying the true distribution of an element? 
GEOGRAPHY OF SOIL GEOCHEMISTRY H7 

TABLE 3.--Comparison of mean concentrations of elenwnts in Missouri agricultural soils determined in this study with a previous 

study by Erdtnan, Shacklette, and Keith (1976b) and with the mean 

concentrations in parts of the eastern U.S. 

[Concentrations in parts per million, except where noted to be in percent. Geometric mean 

given, except where noted to be arithmetic means. Leadered entries(--), no data] 

Element 

Al, pet 

4

---------

As----------------

B-----------------

Ba----------------

Be----------------

C, carbonate, petC, organic, pct---

Ca, pet-----------

Cd----------------

Co----------------

Cr----------------

Cu----------------

F-----------------

Fe, pct-----------

Ga----------------

Hg----------------

K, pct------------

La----------------

Li----------------

Mg, pct-----------

Mn----------------

Na, pet-----------

Nb----------------

Ni----------------

P, pet------------

Pb----------------

Se----------------

Se----------------

Si, pct-----------

Sn----------------

Sr----------------

Ti, pet-----------

v-----------------

Y-----------------

Yb----------------

Zn----------------

Zr----------------

Missouri soils Eastern 

This study 1 Other analyses 2 United States3 

4.1 

8.7 

31 

580 

• 8 

.03 

1.25 

.33 

<1 

10 

54 

13 

270 

2.1 

11 

.039 

1.4 

41 

22 

.26 

740 

.53 

7.2 

14 

.059 

20 

7.6 

.28 

35 

<IS 

110 

.33 

69 

32 

3.2 

49 

310 

4.2 

9.0 

30 

680 

1.0 

<.01 

1.5 

.49 

<1 

8.4 

64 

17 

260 

2.2 

12 

.046 

1.6 

43 

20 

550 

9 

12 

.28 

.62 

.054 

24 

6.7 

.44 

37 

<10 

130 

.31 

70 

25 

3.0 

52 

250 

5.2 

5s.4 

32 

300 

.6 

.32 

<1 

36 

14 

5120 

2.5 

10 

6.096 

1.6 

33 

4,722 

.23 

290 

• 71 

13 

13 

.018 

14 

5 .39 

51 

.30 

46 

23 

3.0 

36 

250 

1Based on 1140 samples. 

2Erdman, Shacklette, and Keith (1976b), based on 40 samples. 

3shacklette, Hamilton, Boerngen, and Bowles (197lh), unless 

otherwise noted. 

The variance-mean ratios, Vm, as calculated from the 

variance components in table 4, are given in table 5; 

the ratios serve as indices of confidence so that the 

general character and the major features of the map 

patterns could be reproduced by a repetition of the sampling and laboratory analysis. In general, features of 

the maps that extend over about six counties or more 

are probably reproducible; the values of vm(g) are high 

for most elements. Less extensive features of the maps, 

those that extend over only one or two counties are 

generally nonreproducible, or at least unlikely to be reproducible; the values of Vm(P) and Vm(c) are generally 

small and many are less than 1 . 

The reason that the larger areas are more often reproducible is that they are represented by larger numbers of samples; this causes the variance of the area 

means to be small and, therefore, the values of vm(g) 

to be high. Variance-mean ratios were not calculated 

for iodine, thorium, and uranium because not all samples were analyzed for these elements nor for beryllium, cerium, molybdenum, niobium, neodymium, silver, 

and tin because these elements were not detected in 

many of the samples. 

The analytical precisions (reproducibility) of the 

analyses for fluorine, mercury, ytterbium, and yttrium 

are poor (analytical error variance is greater than 50 

percent of the total variance, see table 4). Except for 

mercury, the poor precision still does not completely 

diminish the reproducibility of the maps for these elements at the county-group level because the values of 

Vm(g) are moderately high. 

DISCUSSION 

The regional distribution patterns for some elements 

are quite distinct, but other elements exhibit high degrees of local variation and no apparent regional variation. The regional patterns are of two contrasting types: 

sodium (fig. 34), a relatively mobile element, represents 

the first type and is more abundant in soils developed 

on geologically young materials; it is more depleted in 

soils on older land surfaces. Silicon (fig. 32), represents 

the second type and is a resistate element which appears to be enriched in soils after the more mobile elements have moved out during prolonged weathering. 

4Arithmetic mean. 

Sshacklette, Boerngen, and Keith (1974). Based on 420 

samples. 

6Shacklette, Boerngen, and Turner (197la). Based on 420 

samples. 

7Shacklette, Boerngen, Cahill, and Rahill (1973). Based on 

420 samples. 
H8 GEOCHEMICAL SURVEY OF MISSOURI 

TABLE 4.-Variance components of soil elements 

[Variance based on log10 concentrations, except where noted. Asterisk(*), components are significantly greater than zero at 0.05 

probability level] 

Variance Components 

Between groups of Between pairs of Between counties - 2 

Between samples 

Element counties, :x,_2 counties, :_p__2 within pairs, s 2 within 2 __.£ county,~ 

s 2 

e s 2 a 

Al 1 0.63265* 0.07235* 0.08203* 0.56121 0.11498 

As .00434* .00056 .00162* .01677 .00413 

B .00047* .00035 .00056* 0 .01127 

Ba .00697* 0 .00138* .00792 .01138 

C (tot.) .00679* .00089 .00160* .02127 .00079 

Ca .03572* .00536* .00747* .04643 .00244 

Co .00089* .00055 .00271* .01642 .01097 

Cr .00429* .00064 .00132* .00881 .01047 

Cu .00232* .00158* .00069 .02090 .o 1128 

F .00684* 0 .00627* .03532 .07321 

Fe 1 .07339* .02511* .01771* .28223 .01484 

Ga .01086* .00200* .00035 .01140 .00732 

Hg 0 .00205* .00086 .03090 .03370 

Kl .05043* .01898* .01010* .07525 .00546 

La .00110* 0 .00135* .00201 .00985 

Li .00204* 0 .00129* .00764 .00039 

Mg .02110* .00195* .00259* .02134 .00160 

Mn .00690* .00092 .00650* .04275 .01265 

Na1 .03458* .00461* .00231* .01323 .00083 

Ni .00870* .00279* .00171* .01950 .00884 

p .00472* .00038 .00284* .02325 .01269 

Pb .00212* .00136 .00350* .002248 .00745 

Sc .00325* .00008 .00110* .00943 .00435 

Se .01624* .00473 .00465* .07154 .04970 

Si 1 2.3282* 0.22463 0.28905* 3.141 1.730 

Sr .02353* .00229* .00085* .00743 .00907 

Ti .00138* .00068* .00020 .00549 .00633 

v .00791* .00024 .00225* .01139 .00922 

y .00158* .00085* .00031 .00514 .00950 

Yb .00153* .00044* .00034 .00217 .00955 

Zn .00509* .00101 .00310* .02563 .00123 

Zr .00481* .00205* .00152* .00905 .01678 

1variance based on nontransformed data. 

2

ss 2 = 2 + , where 2 = total between-sample variance, 

se =sampling error, sa2 =analytical error 
GEOGRAPHY OF SOIL GEOCHEMISTRY H9 

TABLE 5.-Variance mean ratios for soil elements within areas of 

decreasing size 

Cvm(g), ratio for groups of six counties. vm(p), ratio for county pairs. Vm(c), ratio for counties] 

Element vm(~) vm(.£) vm(.s_) Element vm(g) vm(.£.) vm(.s_) 

Al----- 56 2.1 1.2 Mg----- 55 1.7 1.1 

As----- 12 .54 • 77 Mn----- 7.4 .38 1.2 

B------ 2.5 .63 .so Na----- 150 6.6 1.6 

Ba----- 22 0 • 72 Ni----- 18 2.0 .60 

c (tot) 18 .80 • 73 P------ 12 .21 .79 

Ca----- 44 2.2 1.5 Pb----- 4.2 .91 1. 2 

Co----- 1.9 .40 .99 Sc----- 14 .12 .80 

Cr----- 13 .67 .69 Se----- 8.0 .78 .38 

Cu----- 4.3 .98 .21 Si----- 29 .92 .59 

F------ 3.8 0 .58 Sr----- 86 2.8 .52 

Fe----- 15 1. 7 .60 Ti----- 7 .o 1.2 .17 

Ga----- 35 2.1 .19 v------ 23 .23 1.1 

Hg----- 0 .64 .13 Y------ 6.5 1.2 .21 

K------ 37 4.7 1.3 Yb----- 7.8 • 76 • 29 

La----- 3.5 0 .73 Zn----- 11 • 75 1.2 

Li----- 15 0 1.6 Zr----- 11 1.6 .59 

The bimodal frequency distribution of sodium (fig. 34) 

is unusual among the elements studied. The samples 

represented by each peak of the histogram occur within 

separate and distinct areas of the State: the higher concentrations occur in the northern part and the lower 

concentrations occur in the southern part. The eastern 

part of the Ozark Plateaus exhibits exceptionally low 

concentrations of sodium. The sharp boundary between 

the two populations coincides approximately with the 

1¥2-meter-depth isopach for loess deposits that parallels 

both the southern limit of glaciation and the Mississippi 

River valley (Scrivner and others, 1966, p. 7). 

The elements aluminum, calcium, magnesium, potassium, strontium and to a lesser extent lithium and 

nickel have distributions similar to that of sodium. Although other factors may have affected the general distribution of these elements, the principal factor appears 

to have been the distributions of at least three of the 

major types of underlying geologic materials: (1) glacial 

materials comprised of till, loess, and alluvium, (2) 

rocks of Precambrian, Mississippian, and Pennsylvanian 

ages, and (3) residuum from carbonate rocks of Cambrian and Ordovician ages. 

Above-average concentrations of silicon occur in the 

southern part of the State, and below-average values 

occur in the northern part (fig. 32). The boundary between the two areas is less abrupt than that for sodium. Manganese, niobium, and zirconium exhibit distribution patterns similar to that of silicon. 

Between the two extreme patterns represented by 

sodium and silicon, there are numerous elements (arsenic, barium, beryllium, boron, cerium, gallium, iron, 

lanthanum, neodymium, scandium, selenium, titanium 

and vanadium that- exhibit large local variations and no 

distinct regional pattern. 

Carbon (fig. 9) is another element with high local variation: carbon reflects in a general way the contrasting 

vegetation types of forest and grass under which the 

soils have developed. Grass vegetation results in moderately higher concentrations of carbon in the soils; 

whereas, forests promote lower concentrations. The approximate boundary between the original prairie and 

forest communities is irregular and trends diagonally 

northeast-southwest across the middle of the State (fig. 

1) with the prairie to the northwest and the forests 

to the southeast (U.S. Geological Survey, 1970, sheet 

no. 90). The effect of climate tends to reinforce the effects of vegetation. Both precipitation and temperature, at least by present-day records, increase from 

north west to southeast (Scrivner and others, 1966), 

which provides increasingly favorable conditions for the 

oxidation of carbon toward the southeast. 

Some elements may become concentrated either by 

natural processes of mineralization or by man-induced 

processes. Phosphorus, for example, occurs in rather 

uniform concentrations over large areas of the State 

(fig. 28), which suggests the likelihood of widespread 

application of P-containing fertilizer. Lead (fig. 19) is 

an element that may have been redistributed by both 

natural and man-induced processes. Concentrations are 

particularly high near the southeast Missouri lead district (Washington, St. Francois, and Jefferson Counties) where near-surface mineral deposits have been 

worked since the early 1700's (Kiilsgaard and others, 

1967). Samples with the highest concentrations of lead 

were obtained from the flood plains of streams that flow 

through the district. The distribution pattern of lead 

was reconfirmed by subsequent sampling and analysis 

of alluvial soils along Big River and Mineral Fork in 

Iron, St. Francois, Washington, and Jefferson Counties 

(Tidball, 1973). These samples also contained high concentrations of barium that reflect the extensive mining 

of barite from surface deposits. Lead-mine tailings have 

been used as agricultural lime in some areas near the 

mining districts (W. F. Heidlage, written commun., 

1971), a practice that introduces unusually large 

amounts of lead to agricultural soils. The distributions 
HlO GEOCHEMICAL SURVEY OF MISSOURI 

of copper and zinc (figs. 13, 43) are associated largely 

with the occurrence of significant loess deposits. 

In summary the more mobile elements, such as calcium, magnesium, potassium, and sodium are more 

highly concentrated in areas with geologically young 

glacial till and loess. Less mobile elements, like silicon 

and zirconium, are enriched in soils on very old, nonglaciated, and deeply weathered geologic materials. The 

regional variation in the carbon content of the soils reflects the climatic and vegetation differences across the 

State, and locally high concentrations of lead and a few 

other metals appear to be related to mining activities. 

Many of the elements have predominantly local variation and fail to display regional patterns of variations 

. across the State. The large number of samples collected 

in this study and their extensive distribution illustrate 

spatial patterns, but if the objective had been simply 

to estimate means then fewer samples would have been 

required: remarkably, Erdman, Shacklette, and Keith 

(1976b) reported similar means with only 40 samples. 

REFERENCES CITED 

Bartel, A. J. and Millard, H. T., Jr., 1976, Analysis of rocks and 

soils for iodine by radioisotope dilution-neutron activation, in A. 

T. Miesch, Geochemical survey of Missouri-methods of sampling, laboratory analysis, and statistical reduction of data, with 

sections on Laboratory methods by 11 others: U.S. Geological 

Survey Professional Paper 954-A, p. 15--17. 

Cochran, W. G., 1963, Sampling techniques [2nd ed.]: New York, 

John Wiley, 413 p. 

Cohen, A. C., Jr., 1959, Simplified estimators for the normal distribution when samples are singly censored or truncated: Technometrics, v. 1, no. 3, p. 217-237. 

Erdman, J. A., Shacklette, H. T., and Keith, J. R., 1976a, Elemental 

composition of selected native plants and associated soils from 

major vegetation-type areas in Missouri: U.S. Geological Survey 

Professional Paper 954-C, 87 p. 

--1976b, Elemental composition of corn grains, soybean seeds, 

pasture grasses, and associated soils from selected areas in Missouri: U.S. Geological Survey Professional Paper 954-D, 23 p. 

Fenneman, N. M., 1946, Physical divisions of the United States: U.S. 

Geological Survey map, 1 sheet. 

Hess, R. E. and Blanchar, R. W., 1977, Arsenic determination and 

arsenic, lead, and copper content of Missouri soils: Missouri University Agricultural Experiment Station Research Bulletin 1020, 

46p. 

Huffman, Claude, Jr. and Dinnin, J. I., 1976, Analysis of rocks and 

soils by atomic absorption spectrometry and other methods, in 

A. T. Miesch, Geochemical survey of Missouri-methods of sampling, laboratory analysis, and statistical reduction of data, with 

sections on Laboratory methods by 11 others: U.S. Geological 

Survey Professional Paper 954-A, p. 12-15. 

Johnson, F. E., 1950, A survey of the trace elements of Missouri 

soils: Missouri University Master's thesis, 39 p. 

Kiilsgaard, T. H., Hayes, W. C., and Heyl, A. V., 1967, Metallic 

mineral resources: lead and zinc, in Mineral and water resources 

of Missouri: U.S. Congress, 90th, 1st session, Senate Document 

No. 19, Washington, D.C., U.S. Government Printing Office, p. 

41-63. 

McCracken, Mary H., 1961, Geologic map of Missouri: Missouri Division of Geological Survey and Water Resources, Map, scale 

1:500,000, 1 sheet. 

Miesch, A. T., 1976, Geochemical survey of Missouri-methods of 

sampling, laboratory analysis, and statistical reduction of data, 

with sections on Laboratory methods by 11 others: U.S. Geological Survey Professional Paper 954-A, 39 p. 

Millard, H. T., Jr., 1976, Determination of uranium and thorium in 

USGS standard rocks by delayed neutron technique, in F. J. 

Flanagan, ed., Description and analyses of eight new USGS rock 

standards: U.S. Geological Survey Professional Paper 840, p. 61-

65 . 

Neiman, H. G., 1976, Analysis of rocks, soils, and plant ashes by 

emission spectroscopy, in A. T. Miesch, Geochemical survey of 

Missouri-methods of sampling, laboratory analysis, and statistical reduction of data, with sections on Laboratory methods by 

11 others: U.S. Geological Survey Professional Paper 954-A, p. 

14-15. 

Pickett, E. E. and Dinius, R. H., 1954, Trace elements in Missouri 

soils: Missouri University Agricultural Experiment Station Research Bulletin 553, 20 p. 

Scrivner, C. L., Baker, J. C., and Miller, B. J., 1966, Soils of Missouri: Missouri University Extension Division Circular No. 823, 

47p. 

Shacklette, H. T., Boerngen, J. G., Cahill, J. P., and Rahill, R. L., 

1973, Lithium in surficial materials of the conterminous United 

States and partial data on cadmium: U.S. Geological Survey Circular 673, 7 p. 

Shacklette, H. T., Boerngen, J. G., and Keith, J. R., 1974, Selenium, 

fluorine, and arsenic in surficial materials of the conterminous 

United States: U.S. Geological Survey Circular 692, 14 p. 

Shacklette, H. T., Boerngen, J. G., and Turner, R. L., 1971a, Mercury in the environment--surficial materials of the conterminous 

United States: U.S. Geological Survey Circular 644, 5 p. 

Shacklette, H. T., Hamilton, J. C., Boerngen, J. G., and Bowles, 

J. M., 1971b, Elemental composition of the surficial materials 

in the conterminous United States: U.S. Geological Survey Professional Paper 574-D, 71 p. 

Tidball, R. R., 1972, Geochemical survey of soils, in U.S. Geological 

Survey, Geochemical survey of Missouri, plans and progress for 

third six-month period (July-December, 1970): U.S. Geological 

Survey Open-file Report, p. 1&-23. 

--1973, Geochemical survey of soils, in U.S. Geological Survey, 

Geochemical survey of Missouri, plans and progress for seventh 

six-month period (June-December, 1972): U.S. Geological Survey 

Open-file Report, p. 1&-25. 

U.S. Geological Survey, 1970, National atlas of the United States 

of America: Washington, D.C., 417 p. 

Vineyard, J. D. and others, 1967, Geology, in Mineral and water 

resources of Missouri: U.S. Congress, 90th, 1st session, Senate 

Document No. 19, Washington, D.C., U.S. Government Printing 

Office, p. 13--31. 

Wahlberg, J. S., 1976, Analysis of rocks and soils by X-ray fluorescence, in A. T. Miesch, Geochemical survey of Missourimethods of sampling, laboratory analysis, and statistical reduction of data, with sections on Laboratory methods by 11 others: 

U.S. Geological Survey Professional Paper 954-A, p. 11-12. 
FIGURES 2-44. 

Element distributions in selected agricultural soils of Missouri 
H12 GEOCHEMICAL SURVEY OF MISSOURI 

,- r- -,:t- rtr-

} + ~ :.;t + :r- -;'r- ; T - ; : - ~ ~-~ !!: ~ - r:r-;- l £ ~ T:r--:r-"-

~ z 

w 

:::> 

d 

w 

a: 

LL. 

" .,.. 'IF , ~ :t: :t: ~ \ :t: + + :t: :t: :t: :t: I +:if ~:t= :t: I + :t: ' 

: :J:t !I,' :j: J,-~----ty :j::J:t I :j:+ :r-L _____ ; :j: ''>:j: :j: ~ + #+ ~:J:t+ :j: +' ..... 

~ :J:t ... I lt:r- ,:t: +f ! + :t: :r-1 r-j~f:Lt_~ __ +j :r- :t: I 

~ -:-;J;t :J:t +j.._ i ! :J:t 1,--=.--i-;,•1 1 :t + 1':t + + i :t :t ~--~--=!=/ 

250 

+ , I :t: + ++ ::t: :t ;t, :t: ' + r----,..--i :t: ~---~-1 :t :t:· ++ :t, I I ~ ' 

\ :~:t·w :J:t }-----i+:r- :t, - .::: +I+ .::: :i =t-\, =t :r- ~· -t:t + 1 

... :J:t .::::# :t:t:' .::: I + :J:t~----T'-,-+-----1+ +I I + .:!=\ '"Vtt\ :~:t! .:::+ ,-i----i + + ~ :r- +-.~-J-·--,-----~ "'----~1':j: .::: :t:l + + I :t + + I + I f + :t \ ,..J :j: :j: '----------' :t # I :j: .::: I •+ + I ::t: 

,. tl!:t :-4---: +:t: .:::.::: 1 ;ll + + + 1.::: :t:l + +i :r-+"! +' ~ # '; :j: +J .:::+:j: i:t:.::: + +:-;;;----:t·-~ .::: :j: t 1 _ __2: ___ ~,.------~--+'\_ 

L""'_ __ _A:-_fl :t:r- i :t:# \----#~ :t: :J:t >;r-+--!F"· .::: + I +.::: -· Vt :j: I :t:# ,--:1=---- .::: + fit :J:t I I +I :t ' # .::: / ' 

i.::= 1----,~---1 + 1:, I + I + 1+ / -tl , :j: i :j: ' .::: ' I + :J:t ~# I+ + I I :j: ' I .:!1 + ' 

:j:o:J:t:j: :j: ! 1 .:!=,_t +\ ___ :J:t ' ' + + 0 ::_ _ ___:: ___ ___) +\ :j: :j: ' ~ I :J:t .::::t:_:t1 :t: :t :t:#=t :J:t •'- ; + -,,:J:t,f ~---------- :- + :t: '---, + :t :t+' .... ..; "_/, -th __ :t: .~ 1=------· __,- -------1 +=~-"-- '-)'.::: +rt:+~-~- 1 :t :t I -------\ 

r--J.::= .:1= ,------ '/ .::= ~ :t , #/ :tt :t + •;t_ + I+ 

I :t: :t:I:J:t :t: =t 1 :t: < + , + ::to + r+-' _;_if-++ + 1 

+ i + + :J:t ' +) :t I + .-L ~---- - ' + I :::0 I 

1 :t:,:J:t :t: I++.::: 1(+'-----~:t.' :t j:t= ! :-+--++~ l :j: .::: :j: f-----_J---+.:::-~----; :j:~ + \ + ' :j: + I 't. I ~+ :~t_ ~*\ I ~ ... 

-------,; :J:t .::: I :j: I + +If\ .:::I ' ... _ _j I 4='--~ 1:- + _, li·"'~~' 

I :t: "1'1 :r- + + 1

, :J:t+ .::: , + 1

.::r-t -f; ;' + :t: I -+--;---- + · 1· -t- r' + :!::{ # :t ,· I + I ' -+-1 i:t :::0 I I ' ' 

+ ' I + ~-4=------4 ')_ ( + /~+-!:-----'---;.:+-" .::=:t' + ---1-+ I I + L:j: :j: +I + 1++[.::: 4- '-,, .:::;y:J:t i+ +i , __ I /+ +:t:, I 

I+ :t :t: ~~-::14----':t: # -- ~ '# :::0 I'+- "-, __ / + , + + ' '-:__i('! + \t -----~-:f!.! .:1= ~-----=!--' + --* '\1 +_I++ :t,~ + !+ ~ I I +~-F-r~ I I + + + t :t -t:t I I + :J:t ~-=-~1 .:::-):_ ---:t: :J:t I . + I , + -Y 

:j: +' + I + 1 I+ ,J++ __ _:t-•f':j: + I + ~ + ~i I 

l:t -1 I :t 1 L 1 1 1L-----------j , 1 r- r +' :;t +- , ', , r , ' , .+ :\ # r+---+r-z, + ~(·'---·-----'-:., +I +11+·--~---;---~__:- I " 

f 

' ' -!'- + I , + ·+ ++ :J:t r- --1+ I 1, 1 + .,__ \_+ --J>,. - ----1---- ----±-_ _ J + + f------- -+ ~ 1 \_ I + 1 I ' + ' 'I-- :t r' , 

+ '-:i, ', I + 'I --,, I -._±- + ___:___ ++ r---__::--+ :t:l i + ~------< -it' I + I I I I I I - I+ I :';'- '-fj' -; -1 ¢ ++ : +ty~ +:t +t~ 

1 1 + r' .::: + 1 ;L-·- _____:±-_ .---- _, 1 I · ( , ,I - I + ' +t ' ::t:-:t: "n ' 

I

+ I+' ! I L--,-;± ___ J_~ I + ' I "'JI' I I I I' ' I I I I '+ I / _,_ \ + 1 + ' ,1 +r I + 1

' ~---~--, I+ + :t' ++ f-- '::t:-+; :f ... _::t:-

-+--------- + + 1

1+ : r+ 1) J - _ :___ ! :tl I - I L__:-::___----+:-t {·''/ , 1-:t ~ \ 

I --j :t - ' I + :t ----, I ' I I '1------- ' ::t:- 1 + I_ '-f-""'F ____ J! + I+ I +, ~i - - ,_: _____ _j_ll r-r'----r-, +! + + ~-;;----.~----i!O---.____-( 

J 

_ 1

11 _ ! _ + I + ; ____ 1_ 1 

_ _1 ! 1, r ·.=---, !++1+.:::.:::1+,1 ~ + :t' 

___ I 1, I i+-----__!__~L! _ r;-- +--~ l_-:;- _____ __;__- - , 1 , i , • 

1 

I ::t:-1- ::t:- + , 

I - ,---. + ' I + ' I ' I '+ -+I ' +' ::t:- ~ 1 1 ~-L ____ t 1 + 1, 1 1 ++ r 1 L - 1 r.-----' 1 1 + +-_/. .. I I+ + 'I ' + I +I ' 1 ' T-- ' I ;+- + i -+--...-' t 

1 

I I + I r 1'r 1 I I• , ~ + · ' I 1 1 , __,_, +t I I, +I + ' ---+ ---1 lr I .____ I I _- - - I , -++ -,__,, I 1- : : ,_ r -"'f-,-':t + ~ ---~---! 11 ---·-· 1 

1 , , ::t:- -----rt ,._ + ' "" <: I I· I 1 ' I I ;t------------,------1 + 1 ----'---;, ,~-~ 'I· I > "' 1 1 1 11 !

1

·-=------=t;l ,I Jr- ': -, 'I \ -- !" + t_i+ .J£+r I I ,~--------l---, I 11_1 ' ' - - - ! I I I 1- I --1 _____ _-f + ( : . -~ # / 

1-- 1 - I'll I I' + I -- I ,-,-----' I ~· -f. ,~,_~ +t I ~ I '---------·--- ' IJ - L--,-----~- _I_ ' '- I '' :_L--~---:---1 I' I +-I I_, ---~----:· ' i +• \.+ +t + "·:t ::t:"J I I - + I I I I I ' I ' + ' + ' ~~- r I ill rl , - I I , ! I, :- \II +I \l+t+t, 

L • · ! 1- - + 1 : 1 - I 1 1 I + + 7-~-,----·+ r v 

L I # f __j I __j_ + , , I , _ _ I , + : • + , I ! + tt '., - - - - - _, - - - - - ·- _:t- - .L..L - - _I - - --=- -L - --= - .J _I ;>j-- t+- +t +t "rt I 

l.. I ~---;'-:,_';..) \1 ,· +t +' 

0 50 100 200 KILOMETERS ,..+ '! 1 +t ::t:- \. ~ r +I ! +t +t--ro.... I j _,_ / 

50 100 MILES '-~ .:_ _~ t 

SYMBOL AND PERCENTAGE OF TOTAL SAMPLES 

17 26 19 28 10 

I I+ + # 

Ln 

a:i 

ALUMINUM, IN PERCENT 

c co ,...: ,...: N 

cO 

Arithmetic mean 4.1 

Standard deviation 1 . 19 

Analytical error variance 

(percent of total variance) 8 

Number of analyses 1140 

FIGURE 2.-Aluminum distribution in selected agricultural 

soils of Missouri. Map symbols correspond to frequency 

classes as shown in the histogram. 
ELEMENT DISTRIBUTIONS, AGRICULTURAL SOILS H13 

I- + + i::- r..,- - -~ -- - "TT" - - --,- - ~ ---.--:!: 5 -s:-- - r+- l ~- - T "l:t '\. 

\ J; I + +t r· ,. , + 1

· 1 :j::.., :j:( •

1 i-t +l:t _Jl: ~ ~-- , , 

>- u 

z 

w 

+ * =If , + __,__ + Jl + , .., + <t , ~ +I tt I ' L'-l:.:J._ ' :f:i: I '+ ' I + +t • +' t::l __,__ __,__ ~ : ! \ 

• :;: I I -If, i*f :;: I ' --t· >--------,:rl ;-> ~ ' .1:: .. -+- __,__ ,-1 "'\ 

L.::.... + · I ~- ,+ ~ · :t: ·I r---~-t ·n ' +r tt ) ,--~- +t ' "1+ I '+ ~~-~-...:., I I +:;: + . -----< --~-- I 

v- , * ~ =~=I + . tt I·~ ~ ... 1 __ ... : o:tt l:t: + :t: I =I 0 --- '+ k :;: I ++ ~ -+- ~-- i(:j: :f:i:o j:l: 1 ---JtT +--i :;: . :;:

1

--r-1 +:~: 1

1

'·7 1 tt tt I+ :;: I '*' . 1 

' ~ + -Pi -----J.I+ + I:;: :t:l: :j:: • J :t:l: :j:: ' :t:l: :f:i: ' +:1: +I ... ::t :j:: [:::::~ :;:+' +' L_L_.J!:~----T,--1----~:;:. :I +:1: :f:i: +\ ... ' :)1: +I *'! +! ++ I u I+ + #; I +-.-~--:::·~-----~ 

"L- ---t-1

' 1 + ul + _ ! :;: I + 1 I 1 I f : : , \ I .,.,. '------- +:1: u I + + I !:+: u ' - .... + I ,-..J +----+-"----1 I + :j:: l :j:: l - ' I I +I : :t:l: I +...,. + ,. +i *! I , :t:+ I :t: *, -,-.!....._"'F.t..~l f +:~: . n~_,; __ .,x 4 + ::t: ::t: -! :t:* ~~----~' * ±. +:1:- ~------'---*, +' ~----*-i-1 ::t: u L ::t- +t ~ + :t:l u + >:t:- i--r-· ::t- ::t- I ++t ,'' ~ I +:~:+ . ~----~ ' + q; * I + +:~:r * , + * / I +::t: +:1: 1----~--l + +:1: ~- I :tt I I I# /' - , - +'+ I *' I :j:::j:: ~- I I u I u ' i:tl :j:: ' 

:j::!:j::+ + ! 1 :j:: ,.r'~t- # • ,I + + ~-!_ _ _2 __ -~..Jt!-=. _ _:._1 + 1:1: ~ ~ I ++±.1 :j:: +*II I •'- ; 1+/: ...... ___ ' + :j:: \ I I + ' "-+-.... :t: "_./:;:.-.._n >P\::p--·__,·----._.A~ 1 ,

1

_;; _;:-~---, ::t: u \ -------\ 

"",..--J + +.I ' y I * ' 'tl I+ :j:: :It # ....l. # 1::~: 

I 1 +!; + * + 4 u < + ' 1 E :t: nr~~;¢~tt :;: , .f:t + j + + :j:: I'+ + ~) '-., :j:: #,/ .f:t :j:: I .#----- i .f:t I * I 

I !:t: + .f:t -( + ---~-..... f-t:t I .f:t .f:t ~ - \ ....._ 1 ::t" ::t" ::t" f--- __ _.J- --"""~ ---:j:----;1 ::t"+* I ~ + 1' .f:t + I \ ! - -f' .f:t __ .J·r\ _., 1 I -tl'' -------. * * + + +.,...\ * , r--J -it-w .f:t - -*' +~' 

I + ::..:1 :j:: I * ,· -t:t+ + ' + ~+ -~ ; + .f:t I +I· + ~ I ( I -t:t( ::t: ::t: ,· I .f:t I ) * +' 1+1 I 'I I -/ ;' I .f:t '--*- ~ ( :f:i: ,-'- ,±.,·-'---!-..... -4 I 0 ,-·++ I + 'L+ :j:: -t:tl I II -t#-"'l:t t' -,_, -t:t~**'ll Ill , __ I I/ I +.f:t I I 

-+- .f:t I ... ' .... - '- ./ + I ....... --'I I \ 1... :j:: '*' ~---f"'''*---·a:t; ... ~ # ++ ,- '-- ' .f:t I '~ i ' I 

------ ::t...l * -t:t ~-'l'l-_r·;~ )t,1 1 f- :t:1: -!}- I +I- * ~-r-...:-"o/ I + - ' :t I + ~ ::_ I =~:r· :t: ,I , - -, I 

+ :j:: ! :j:: + + I .f:t I I I .f:t * ;:;:. 'I] ::t:,!-4t+ + I # + -I 

II -=~: I ... :j:: i I_ I i - ---~L~--=----~ :j:: i + -j+· ~ + ' ... ' I' ' ' I ·+ + I + +y--t:t---r-r"'!, + ~ (,1. __ ,-'--:, - - I - -' 1 ·--~---;-----', '-. 

I , .f:t I , ~ I • + •I =1:- 1:;:. ~ ·1-t:t +: -::.1 _ + \+ ~ 

----+--,-,) ::t: :ttl r----t--~ I - \.....t. ::t:! ++ ,__,. . .JL.~ ~~ - :;:. ' "\r+~--~r I'' + =1: ' + :;:. -• _ 1 ri--..J...._, - =1: , I +::t: 1L1" :t: "> +_ ....._ I + I * I I + I _l:l 'II I I -l_ - :j:: I y' + !-:» 1 * "---. + r' -t:t 1 _±_I_-#-., __ , _ I · '*' , - I 1 • 1 , + 1 ~ ' 

1 -:;:. I ~,-J! ___ J.. ;_ :t: _ '.,.J' - _ 1- - + I • I + ).,_ , / _ \ l :t: ::t: :t: , -1:t: 1 l+1 ..., ~---~--~ I'=~: -t:t' +I ,,..+11 + + ' I l ++ • - ' - I ' L ------ ~- ~ I '' , :j:: * r.:r------ '+ - I+ I :;:.+ I) I ' , *f I - I I --~· - ~-----1.."'~1 - -t:t + \ I .f:t + 1_ ____ # .# t ' II+ f ",_ __ j __ __j_- -.r----:f;-1 ! I ~ ~-;---,--*--r'-{ 

_ I !-t:t* + --~ I 1 -~-__::!_- _ !- + ! _ [_-, ! -t:t*+i- ::t" ~ i " + +' l --~ 1 1 + ,fr~---=l=-1 -r=---~--~ * u ______ __l_- - * 1, i * 1 +i 1 *I * + ' 

-------·I :t:1; J- I , _ • i ' - ++ I ' =1: ~ 

I I - I I ~-~-------±. I ' ++ I ::t::t:l; + ! + + ' L I I I __ j:,..----(- I! + + ..r', 

I =1:+ .f:t l;::t: I' I l I + 'I l l:l I l' .... Tl - I + * I J ..r- ' 

J + I 'I 1 -t' + =1: ++ - I I ' ' # :t\ + • I • +I' + ·

1 :t: 1 1 + 1 ... :t:l: -,, I 1 1 +: _ r · ;:< ·, 1 - ;:t:/ --=~: 1 r----__ ,t 1- * .... +:J .... _j , <: ---+:;---1, + _ • +I - --).---------~-,----,-1 ~ ~-- l'l---1';jj_ ;~---=t- 1 \;::.+- >..,' I * ! I r.·-.:..---:.J I I jt-- ' t I ,_ ~ -* f ,- _J __ ::r I I I "------,1_ ...j I - I - ! + I I + ,_ :t:l: --------, - (- -!:: I 

J-- t I I 'LI -_II I I I - I + 1-,-----L I .f:t - ~- 1\ .~---1:;, * I - L..------·-- + -j I -,.--·~----#.., + ' I - ..,... ~--~-*1 II I I-+ - # _,-----j=---#-;' ' ' I I I 1...-t::t -, ·~ I ,I 

I + ' - + ' ! - I I + I + I *! I' .f:t I - \ -- - I ' .f:t :j:: I 

I- - - r- - ! I I I I , , I ' - ~---;-----~ + r'\ . .J II - .f:t ' I ' ' - ! I - .f:t ! * I ~ - - I + ! u + + I .f ( = ! - I ,. • I L - - -+- _ ~ -~ _ _j_ ____ ,_ --1:f: __ ;;j;;....,.L _ _ _I __ :....J.... ..J. _ -= _ ~ _r '!t: t- - + 'rt, 

L.- ~---l'::\j t-· + -, 

0 50 100 200 KILOMETERS ,._ -i,_ I 1 \.."" f -_! + II" 

0 50 100 MILES ) ' 

___ - .. ! - + / 

SYMBOL AND PERCENTAGE OF TOTAL SAMPLES 

500 18 21 23 21 17 

Geometric mean 8. 7 

Geometric deviation 1 .46 

Analytical error variance 

(percent of total variance) 1 5 

Number of analyses 1140 

5250 

w 

a: 

u.. 

co 

N :! ~ ~ ~ ~ 

ARSENIC, IN PARTS PER MILLION 

FIGURE 3.-Arsenic distribution in selected agricultural 

soils of Missouri. Map symbols correspond to frequency 

classes as shown in the histogram. 
H14 

SYMBOL AND PERCENTAGE 

OF TOTAL SAMPLES 

>- u 

750 

t5 500 ::::> 

d 

w 

a: 

u... 

250 

3 1201581 7 

1+1~1 ~ 

I I I 

I I I I 

I 

I 

I 

I 

I 

I 

I 

I 

I 

I 

00000000 

o.noooooo 

--NMLnr--.OLn 

GEOCHEMICAL SURVEY OF MISSOURI 

Geometric mean 580 

Geometric deviation 1 .46 

Analytical error variance 

(percent of total variance) 42 

Number of analyses 1140 

BARIUM, IN PARTS PER MILLION 

FIGURE 4.-Barium distribution in selected agricultural 

soils of Missouri. Map symbols coiTespond to frequency 

classes as shown in the histogram. 
ELEMENT DISTRIBUTIONS, AGRICULTURAL SOILS H15 

0 

SYMBOL AND PERCENTAGE 

OF TOTAL SAMPLES 

>- u 

z 

w 

:::> 

0 

w 

a: 

500 

LL 250 

0 

v 

BERYLLIUM, IN PARTS PER MILLION 

50 100 

50 100 MILES 

200 KILOMETERS 

Geometric mean 0.8 

Geometric deviation 1.43 

Analytical error variance 

(percent of total variance) 17 

Number of analyses 1140 

FIGURE 5.-Beryllium distribution in selected agricultural 

soils of Missouri. Map symbols correspond to frequency 

classes as shown in the histogram. 
H16 GEOCHEMICAL SURVEY OF MISSOURI 

,- r-*-+- r+-- - '\ } '+ + + [+-; T- ~ ~- "l- -.,...-! -f" 'f ~ - ~+++ ll"-:;- T*-+' 

\ + + f' + '~+ + ~ \ + I + + + +I ++ -!'- I i + + ' 

~ * +*,i + 1~-__:f---{t ++ I ++ +~-----~~+';-->+I ~ +++it++ + +'...., 1......--+--~, 1 ~ • I +:t: ! 1 + +I r---:.r*-Lt_~ __ +J I + 1 ~ ) + + *+ I ,-----1 + + + , -+ I ~* + + ;l- I+ + ' +* I I ++I + + + i+ !++ + +I' --"'+'{ 

I I _r---~--1 + ~:1-- .. -F-i + + ++ + '+ I +~ + I 

"""'\ +,,++ -L ----!,++ +~+++I' + -j/. +4-•+ + ~· + +I ._ + 1 + ~+-=f. I' + I + * r---- """F ~--I---- -j + + I + + I \ 

._~+'It-++ -tj I+! +* ~--~-----~I + ~ + h~-~--*·~-----~ 

"----ril ++II+!+* +++I + + + r +*, 

,...j +. -+=---4--'---1+++--] + * + I + 'II 'I+ + '+ * -t I 

r++ 11+ , 1+, ++*l .. 1 .. ~----r"-i '+ *I+** J.. + ' + + +j I I I+ +, + l ~ + I 1 _ _2-___ ~-h...--.-+--+~ ~---±_,tl +1 

+ 'I I + -fJ ----++\( + ~ + \.+ + , I .--+----i + + + + 1+-~~-~r+ + + ! ;+ + /-, ~:to + .J-+-+_j--~ + j+- , 1 + , I 1+ / ~ , I + ++I I I + ./''--+' :+- I+ + +I + + I+ it I + ' ~ +• + ' + ' ' '-- + . --* + + ~- .. ..! .. - .. ~ + \ + ) \..+ I + +~;;:~ + + + t -~ ,~; 1 + + ---- ---.,-....:.- + + --- 1 * I + ' .... • !"./ :t' (I ,0.,-J--·--' _ _,\ + '--;·'+ ++ + =F"I + + I ~-------\ "',...-·J+ +' 'Y + I=*' -H-1 -f-1 + ±_+ 

I ++!;+ + i + <' +I+ tl + +r+-+*"1+--:++ 1 

I

' *+ +, +) * I *,+-----' I+ I 

I + +,+ * I+ + * -r(*"---~:· :t:' f+ + +L \ 

l + + + 1---.. ..J---.;;=-t"-"'f-----< +** + \ + + + ~ + I '~I -t ,.-+..r\ I~ -------' + + I + I :t +t\ +1, ~_j+ ~--H-+ + "" .!':--'+~' 

I + '19 I + + ' +* * • + -1-+ t; + + :t:' *'. I ~ .,·. + / ' +( I ' I I + I I ' 1*;:: + I +, ' . ++ I ' + '---~ + ) ~ + -~:,..+-±.--"-;-" ++' * ,- --++ I 

I + L + + +I * 1+ +I+ --'t- / -,,, + y + I+ +' '--, I / * '+ ~ I 

+ * I r--+--1: _ _ * + ' '+ :t:' + 'I- \., / + I - :_ ~---- ! -* V ! ---- + I + + - -~- -+- r- ::;::- · j 'I; 1 + l+ + +~ :t:' b + ~ + + +1 • 5 '-+" TI-.,.,Y 

I + ~--· + + + ''i: *' * *..j:.'-q. ' * ; + -+-

+· + I + + + I + + + I + + ' -::j:'- =~ + Jt-+ * I -11- + + I ' + I + I + ,J* --- '+ + I + + +' I I+ ++ I + I I I + +t_ _______ j I r+ * +' ' ,-, • + , :to I + '+ ' +I I I r+---+-'1, + ~(a __ ,-'-, + I +'+·--~--------, * " 

l ' + + ' + + I :_ + -+ + I + * ~ --h + '\i + + '\* -J\ 

r±·i-<:;.--1 + + ++ r---J-) t \ + *! ++ ""+~ _ _: :; + + '"4~~<- .t-' ... I i + I+ * + i + ++ +-~-..L-~- + +' ++ +++ I + > I ~ 1 +* "---, + r' + + *±_, _ _r_ * I* ! + f + _,.. ! + ,7 ~+ ~, 

'

+++++I+ LI- 1 -C:: ___ ±J*+ ;--;\,_J':to*+ 1+ ++I 1 + i +).._ / + \ . + ' '+ + I I + +, ~- - - ~ -- 1 I + * . ++ " I *+; + + ~ *+ l + ' + -!1- + ' + I + ' * L ------~- ~ I '' • + 1- -$--- •+ + I ' + +l * I + ..__ ' + * + --~· + + +-":/ + + + I ' ----j + + ' + + '1 I ' + '=!----- + -~ .;t ) + I "- ____ II -+'*' t + ' + * ~-----_1- + * '-----+-~ ! + r-----, ---a:-'--1 

* + I+ T -, + I + +I+ 1+ 1 r-=- 1 , + · + · + ~ , 

I +*+t ' + + ! + +II ~----'--.---± .. __ , + ' I + ·-r; I + I ' +! +:t:' +++! '-f-. :to :t:' \ 

I, I r'*-----+- I I + + I * l_------ ...~.. I * I + I + + I + 

,:;:·--1+-;,-j -t~ ~ + + ~ *t I' +:t:' i + + i L + I i++J'--~---' +i:: ~ r' -+ '+ - - -1.. • -t- , + I • + I + I + T - - + t-t- -t--1-. ' -t- J , 

I ++ I. + I' + + l * I 1 I I + l. + I + I ' • * I _._,..'- ' 

J 

* +>+ + , + ~ - -r I . ..J· '*' ~ * ' *+ ' ~ + + -t- * I + 1 + 1 + ' * I + + 1 r · <-t- -. + 7 '\ 

--- -r _ _ +I * f' -- ""~- - ·-.lt: I + , + , + . -- 1"-t+_ + -;. + \ <: * --r. + * ' + * '-----------,------l I I --i';-1 .~--=r~ 'l_t+ I ) '\ 

I * * + 1_-+:_ _ _;;~;_ __ Jj;-*......,* I+ ~~~ + , ! +*, •+ '~ :t:'-t· / ~ l,-1- ;_J+~ -r-- 1 f , + '*4-+ , + * ! + I I+ + + --------, * * l + -'~ +/ I :t * ~*++• + I + * I ~ ,-"9------' + c,+ "' .~+-t; t-+ +' +-f+ L .. _+--+·-------1-------t; iJ +L-.--~--=r.+-_;, -t- \:t .1 1 '>J + ']----~--+ + ' ; 1- ++ + +• :t:' ++ ' : + + i -f- I '. •' + •;t + ) 

'++ + *f+ + I + !+ ! +! +, + +. ++ +~-~ _ _:_ __ I __ L + \+' 

4- ' : I I* ++ I + \ +. I + + I-t -j- ( I. , (-...) L * + 4' * I I + ' ' + ' '*' + + -r ,+ I I' , I ! + * • I 

- - - - - - -~ - --..~. - - - - ·- _+- - it......l. - - _I - - - ....I - - - .J _r,.,.. t + +'rt, 

L...l ~---;'+'J VI· + + ... 

0 50 100 200 KILOMETERS 1'1 !I + I ~ .... f +,! + +" 

SYMBOL AND PERCENTAGE 

OF TOTAL SAMPLES 

> 

u 

750 

~ 500 :::::l 

0 

w 

a: 

LL 

250 

0 

10 76 14 

- I+! ~ 

0 0 0 0 0 NNMLn,..., 

v 

BORON, IN PARTS PER MILLION 

" I + , 50 100 MILES J __ ,_ ..:_ , 

Geometric mean 31 

Geometric deviation 1.34 

Analytical error variance 

(percent of total variance) 100 

Number of analyses 1140 

FIGURE 6.-Boron distribution in selected agricultural soils 

of Missouri. Map symbols correspond to frequency classes 

as shown in the histogram. 
ELEMENT DISTRIBUTIONS, AGRICULTURAL SOILS H17 

I ---- r--

' 1 

-:--:--,----r- l--:-" 

L ~ \ i / i I \ I ' -----~ I r------, ,'> ' I ""' 

L- I , : I r-~----t ____ J 

) ___ :_/ ! ~-----• I' l ~------/ ' ' L I I ' ' ' I ' r------i , -----~ · I 1 

\ . ~-----~ i ______ }-----1-- ----~ : \ '""'....._;, '\ I I I I I .......,-----l.----:----·-) 

----i I ! I I ! 1 ' ,_) '--- --- -j~-----1 l i I i I 

/" ! i i -y--------"--1 i [ _____ :__;------~ \---- ~1 +1 i _______ i------~ >------," ! /"' \ ' + ·~------j (, I I / 

, i i i -;:... ! '3 \ " \ +1 ' +1; ,--.._ ,,. '---~, /--------- r-------..:±; ___ 1 ', 

! "__,,--~( ·" --~_.,-~-1 ~~ '-:;i -------,,1 _ _;_ ___ 1,. r---~--. -~-------\ "'....---J ·r ~ , <" . , I i ! /, I ,.L------; I I 

1 ~---_J----~------f --~-( r ~~ ---~-\ ... ' ._, L ______ ; I I ;\ ,_ J -----1 --"' 

I I ' ' / I I ' ;-( 

I L _____ / /)_ ( ~-+-~-~-..... ' L~--- I ! l I '-.~ // i i ·--"'! ~'I "..,' ! __ -- tl ----l--.r--1 ''\., I l i -~- ~ J'--"'7~~ I ~- i i I ~-__;-~ .:;-· . i , I I L i ---1_ ____ --1 i ~ 

r-------r~ ~~( __ ,_;_'_, ,--~---;---·-\, \. -----~ ,~-/· ~----.-t;" \_ , ·~--,, 1 v- ' " - ' ,._------J :+:.---'--,'> ' 

I

, f , -;---'--~., 1 c ' ""? 

, I , .J / .._' ~----, r ;-----,-----\ J' I I ', I \ L_;·t__ ---- ~ '-" I ' ·, ;' 

' 1 :___ ' I L __ --------~ '-,"-/ I 

r·------~----- __ ; --., _J __ _j_ r _ _[__ ~--~-----\-----.~---'---{ 

I ' I I I I i i ! ' 

,____ i ;----- -~-! ~---- --! l ______ ._"J_ i ! ; 

---~------l I L j-----( I -"""., 

I i i l l, I _r 

J ________ ; r-------L_; ___ ; ______ L_ r----~ ~--~-l ___ !,_ ·~;__ __ -~- r· \><:, 

I ~--- -~ I ' I •, /- \ rJ ' ..- 1 r------, i 1 ! I , --.,-------, '1 - / 

I ! ~ ~------l I ,---- --L_,, -~-----'--, ~-~ ~\ t---------4 I i +TI·----------,, " ' '\ ) 

' I ' ' l, \ I \ I 

~ ___ 1 ____ 1 _ : ____ 

1

_ _ +1 i __ j __ re-·-:·---" \..: .r 0 ~ - - ____.1. - - -' - - - .1 - ( ' l.r 

L_ ~---;'--\j 

0 50 100 200 KILOMETERS (,. I '( 

0 50 100 MILES " I , __ .;__1 

FIGURE 7.-Cadmium concentrations, in parts per million, in selected agricultural soils of Missouri. Only samples with concentrations above 

the lower-limit of determination are shown. Location of sampling site is indicated by plus ( + ). · 
H18 GEOCHEMICAL SURVEY OF MISSOURI 

SYMBOL AND PERCENTAGE OF TOTAL SAMPLES 

500 18 23 27 22 10 

>- u 

z 

w 

:::::> 250 

0 

w 

a: 

u.. 

....... 

c 

c::i 

v 

M 

co 

c ~ c::i c::i 

co cc co cc N M Ll') 

c::i c::i c::i c::i 

CALCIUM. IN 

# 

M 

co ""! CJ:! c::i 

PERCENT 

cc co cc N cwi o.ri 

Geometric mean 0.33 

Geometric deviation 2.03 

Analytical error variance 

(percent of total variance) 3 

Number of analyses 1140 

FIGURE 8.-Calcium distribution in selected agricultural 

soils of Missouri. Map symbols correspond to frequency 

classes as shown in the histogram. 
>- u 

2 

w 

500 

=> 250 

d 

w 

a: 

u.. 

ELEMENT DISTRIBUTIONS, AGRICULTURAL SOILS H19 

SYMBOL AND PERCENTAGE OF TOTAL SAMPLES 

13 22 22 

c cc c-.i N 

TOTAL CARBON, IN PERCENT 

Geometric mean 1.30 

Geometric deviation 1.50 

Analytical error variance 

(percent of total variance) 3 

Number of ana!vses 1140 

FIGURE 9.-Total carbon distribution in Selected agricultural soils in Missouri. Map symbols correspond to frequency classes as shown in histogram. 
H20 GEOCHEMICAL SURVEY OF MISSOURI 

, - r- -,- r +- - -,-- - .,... - - -, - .,.. ~ -F T ~ - r+- l + - r -+ '-

\ + ':+- I I t + + + I t I+ I I + +' I' I I I+ I + ' 

\ I I t 'L4-+ I ..ft \ + I I I I I ' +' +I I I I I I I\ I I ' I, _ _±_~ +, I + I ..------~, + : II ' '+' I ,'' "'' 

.. + ! + I ' , I I ' I + I r---,-+-t I + I t ~t I * ' + I I I I ------. t1 l~~-~~J I '! ~I ! + r-;--~-~~ + I :t ll I +!+I I l+r·--;-1---

r--- -- I I t~ I I' I I I I I I ~ I I I '+' I I ~ -~-~ I I I .I I~' I I I' + +I ' I ) I I I' 1, I+ + I + I I ~ I I ' ... ' I r,-:v--,. + I + + ~-----,-~~--1----: I I I I I I\ ... !!> + -+j '+I I,. ,-+----i I 1 + I h-...--;-•---;------=1\ 

~ I +· + I I I I I I I + 11 1 I I \ ----11 II I I 'I + I ~ 'I + I +. ' + I '------- + I I 'I ' + ~I i"'.J I----+--- -1 I I + 1 +I l + I I l1 I I I 1 I I , I+ 11 + · 1+ , 1 1 11------r·-tJ ;1 1 , ----1---~ ~ + I I I 'I II I.±_ _____ ' I I + I I ~----------1-, I+ + 

L_1 ___ _±_t_l +1 i I I ~ I I\ + + + ~-+--r..: + + ! I I /,' 

\.1 I ~-__! ~ .--+~----j + I ( I I +I, I I+ / 1\ 

.J + + ,, + -1 --1 ,I I I I +I I ' I I· I ' , I +I' II I I •"--:+- + ·' ' + + +I I I + + ' + I ,/ I...___ '---4 I I r--------,___ +I' '{ +• + +' I I I + ' I 1 I ' ---- I I I + + 4 I+ I •.-.~ I+..._ J-L---. ..i~· I ~-'+ -~-,_:_T_I I I \ ,-------\ ..,. "" "-" ( I ,'""- -, + ) I,.._/ I I +±_ + + ,rJ+ +',-- :,..-' I ,, ' I ..- I I + I r+- -;r- I I 

I I I If + I I + < I II I ' + + ' I I +; + I I ..... + _____ , I I I 

+ 1 4. I + /'I + I '+"- _ +• I f'l ! + I I L \ ""--

I ' __ I ( + ~-~ I '4, I'~+ + )-r I ,--,' + + I f-----.J---.-T,_ ~ ---; +I + ' + I I 1 ·I • __ _t- 1 1 , 1,,_ , l_- . + + \ + I + +) \ I \ ' ~ -_j I I I . :PI I -

I ~---,1 '+ + , ++ + ' + ' ;''r -f' I ' + ! ''·, ' ' rj I ' '/ +_( + I I' ! I + ) ' + -----1-.-t--.l!-' I I ' I .--{ + I + .._ __ ....__--<+- ' - ' -, I' I' " I / + I I 

I '+ I I I + 'II 'I' I "-· +.Y I' I ·------' ~·I I ' I I+ ,+ L ~-- ~ I + ' + I + 1

1 \.--- / + I ' -~ 1 ' + "' I I+ ..,... ,--'(T_r--1 -~ "'I + i'+ I '/. I I, +1 + + ~r·-"il-; 

1

------ t, ! I • , + +r--; , , I , + "F 

I -+! +I + + + I+ I I :.:t, +.~+ + I I ~ I I 

+ ' I I + : I ,.J' ---t__' I I ' +I j+- I 

II If ! + ! !-- ! t I' --+----~ ~-~+ ______ __: +' 

I -i +y-+---~j'L, I ~ (,1. __ ,-'-:._ I ~I I +~~-~+ + - I' I ·,+ ~ 

J 

' + I ' ~I I . I I I + I I• ++I I ' I r ' 

--l--. J.v--J + 1----l--~ 11 \_j_ +' I+ ,_,-_!-...,J II I \'Jt.!t_---: ;f" ' + + I 'I ;.. I +' >1':1- ..L__r., I I I ++, I + ' I .,....., II i + ! t I+ I I II' I I + I lr I II ! I ,.!/ ~I "t ' 

·---, ' r + r-•--=t---,--, 1 j 1 1 1 ' ' 1 

) I \ 

I

I I I ! I ILt--,-;± ___ _!_~t + ,· + "·Ji+\ I of ~---:...--, l I + +' II+-,._ I +1/ II +I 

I I 1 +' l + l I! J I :___ I I + J I I + l __ :-·,----'f-·i 'j."/ + +I ,.. \ 

fi------~ I I 1 I' + + +, + I 1 1 I 'o l ' 1 + ! - "f.-~---~-\-----_j----+-'-? 

I I +l[jT----~+ ++ I'+ ,;+ + + ,,-----~-1 1 + r··--· r r++i+~+r i+ ..i I ,, 

I II I I ' I + I + II --- _,_---- _l_- _. 'l I . r; ! I + ' I I +' + i I I \ 

' 1 '+----±•U 11 +I + --:--------'-. 1 11 + 1 '· + _,~ -------·I I +I 'I I ' + , + I '------' I I t r : I +II I +I ~ ll - - - -~ I + + ~~ I II I ~ I I I \ + I \ , + I + j ++ I ~ I I I ! I /-: ~ I + + I I +,~ + I I + I ' I t -,_,, + 1- I I I r - "'t -.-; I ~ 

J + +' ++I '-+--=l--t---L_ 

1 i

1

r ! 1 I ++·1

--=F-il 1 '-;-t..-f \, . ,( ---~---I r + 1-----------.,..-----l ' I --~ ' + ,,, ' 1 .. ' 

I + ~ I I I '-- +I + 'r I ' t I ' •+ \ + + 1- 'I /--' I+ r1 + + + ·----*'--!' +l4,, + ! I ,, ! I • + I I !+ I I -r------t. + + !--'-..-1- I +I I + I q-tl I ' + I I I + ,--,-- -- + : \ 1:;, I + ' 1- I I L.-- -- • I I 'J I L- ,--- ~--.,.. _I_+• \ I I I I -l, I I I 

J--,L--~~--1:~ !+ l IT r,+,-,-~-+--1--~-~-r i i I ~~ +I \II I i I \'+' 

',I ' ' I' ' \ I I, + I ' • ' .\ ,I, ' + I + I ~--;-.----·r r J I ' I I I+ I + I + ,. I I I I , • L -'- !._i_- __ + _!- _j- -'- _: __ +_- w- ' __ i! -'....±... _;,- _, - .J ~ I il I ,T-t,' 

0 

0 

SYMBOL AND PERCENTAGE 

OF TOTAL SAMPLES 

750 

(j 500 

z 

w 

:::> 

d 

w 

ff: 250 

0 

62 38 < 1 I 1+1 =*= 

I I 

I I 

I I 

I 

I 

I 

I 

I 

I 

0 0 00 IDIDOO 

.-- N M 

v 

CERIUM. IN PARTS PER MILLION 

50 100 

50 100 MILES 

t.._l ~----''"f\J \1 ,· I I ' 

r 1 !r 1 ' \. .... 

f 1 1! I ,'" 

' + ! I ,' 

200 KILOMETERS 

, __ - .... 

Geometric mean 115 

Geometric deviation 1.27 

Analytical error variance 

(percent of total variance) 

not determined 

Number of analyses 1140 

FIGURE 10.-Cerium distribution in selected agricultural 

soils of Missouri. Map symbols correspond to frequency 

classes as shown in the histogram. 
ELEMENT DISTRIBUTIONS, AGRICULTURAL SOILS H21 

>-

u 

z 

w 

:::::> 

0 

w 

500 

a: 250 

SYMBOL AND PERCENTAGE 

OF TOTAL SAMPLES 

2 18 25 54 1 

+I~ I ~ 

C) Ln C) C) C) C) C) C::l --N(")Ln,..._~~ 

CHROMIUM,IN PARTS PER MILLION 

Geometric mean 54 

Geometric deviation 1.44 

Analytical error variance 

(percent of total variance) 43 

Number of analyses 1140 

FIGURE H.-Chromium distribution in selected agricultural 

soils of Missouri. Map symbols correspond to frequency 

classes as shown in the histogram. 
H22 GEOCHEMICAL SURVEY OF MISSOURI 

'- ~""-to-:- r-~- - -., - - """+"" - - -r - ~-.- r ~ ~ - r~- l ,- - T 't\.. 

\ I + ;;: I ~ l I I I I I ~~ + 'j ~ I~ -jl+ I ~- I ' 't ' II ~ + ~ \ I ...,. I + I I I I + 

: + J +~- _j_- ..,.~ ~'t" I I+ I ~ _____ ;, :t: ,,'> ~ I +, + ~ +-~~I I I \ "\ 

\.._-=~-'-:._, 1 :~: • , '* :, ~ 11 r---,-r-~-t-~ __ J + ~ ;-/ 

) I I ~ I' ~+ I ,-----· + + I ' --+ ,+ I I j I I ~ ' :t: I + +I I + I i I k,+ I I I - - ' r---r-i + ~"!-~-,-~ :r. +· + 1 + :t: ·~ _ 1 ~. + 1 

' +·)I :t: t.----- J.-+ + I + I I I I :i :t: I ' ~ # ~ ~ +I 

"' .. + '~ + ,I~ I+' + 1 __ _!_ __ :;;~---~,--l----~+ :I ~ + I\ 

~'If- + +j +! I+ I+ I + •I + 1-..-,--,·------~ 

..,___ -- ~i I + +I I + ! + :t: I + I + I I ! I i+- I + \ ' + + '----- :t: I I ' I ~ - ~ I ,.....J 1-----f.--- -j + I :t -1 I l I I I I I I I i ~ I I 

,. I+ '! I I' +~ I + II y,--=-- --;-"Ltl !t + ; +~-~--~ ~+ I + I ! ~I j.±_ _____ • + + :t: :i 1-----'---h + '-

\...:_" _± .L_I :t: + I + ~ 1 + :t:1 + I ~-+--:.-· + I I 4 ,'' ~--- - I I + ,--1------ I + •'t" + I I +I + ' ~ ~ / 

-! :j: I 1---- _j- -I + -ft' I ~ ' - I~ / ,, 

>- u 

z 

w 

::::> 

0 

w 

, I -f.,,~ I :t:' I '+ ~+ ,, + +I :t '- '*' I ' 

+' + + ~ I I + ,./ :t ''-- :t . '- + I ' :.._- ____.!- -- _:!::! I \ I ~ ' \ 1 +++i :t: 1+~ 1 •'-: 1.+/~- ........ : I 1 ---, ++~I' 

500 

1_.. ' I <'./+-(.~ ..h.-:-~"__,----.1+--- I '-)+ :t;:,~-,-, I + I -------\ "'~....--J I I 'r-' '/ I ::p + ' -t+-1 :t:l :t: + +L ~ I, 

I 1 1 '+- + 1 1 '*' < + 1 1 t

1 + r~ ~~-1 ~ ::r • 

k

' I + I I :t: I I ------' I ~ I 

+ + I 'I I " :t:: + I ~ I I I + I :t: I(+·--~-( fl I +:t: + ~ + \ ......___ 

1 I I I f----__J---,1"-"-t----; ,~ + ' + ' ~ :j: I + I,~+ u __ )-r.\ I I:::)_' 

------- ' + :t \ I I ~ It\ ~ I ' ~ -_j ~ ·:t~ + I .., ',j.' I~' 

I :t: I ~ + + :t: i + I ~ ' + I }~ r f ~ + :t ! +' +. I ~ ~ 1 / - +,( I I I ~ L_.:t_ ¢ h ' :t _----+- . .;..-~~ ~, +' I __ JI I I 

I I I L :t. + I I I li I,~--<~:: i -.... ,', - v +I i+ ::r; '-,__ I • / I+,+ I I 

1

:t: + ~ r;t-~----':t ~ ; ~ :t: :t: I \.. _ _/ # , +~ , '.:._j~! I "'' 

___ __ ~ 1 + ~---:t:.r-i'~ ~,' + ~ ~ 1-1, 1 b :tl 1 ~ ~-r,.,-""y 

I I ~--· + I+ ~ .L. :t ~.j:.'l ' ' + I' ::r + ~I +I :t: I ~ I :t I :t: '-~, + ·~ :t: I ~ ~ +I ' I I I I + 'J I --- ,-, I I I ' :t +' I 

I I -.:t. I + I I_ I + + 1_-------1 .... I f \ + .... ' I ' ' I ' I .... ':t ' :t I :t: ... ,'1:---+-'1, :t ~ ~,,_ __ ,-", + I I'+·--~--------, :t: " 

f 

, :t:t + • .:t. I _ ;_ :t •

1

+ I 1 :t: :t: ~ +-1+ :t !._; I - ~ ~ _ = _J_ J :t: :t: 1- --:t: J \_ 1 • :j: 'I •r,...+ r ' 

- :t: --.,-., + :t: 'I- --1' 1 +, ~'¢:":!-~~~+ ,"'"-V_!!_i +! I i :t::;: ~~-i'< :( '.,._ I + I + I - + I l:t: 'I #j I I -1 ¢ :t: I ~- ++, 

I + r---, + ( ## +;t-'-~-,---, I I I'+ fl ,I + I ':t:' + "t ...... 

I I 1.- I - Lr -,-~- - -_I__ ~ I :t ' + \.-J' :t:t I I I ' I I I ~, / I \ I ' - . + , ,cr ' I I ' '· :--- -~ --, I ::r ::r . ~ r, + :;:+; :t: + 

~+ I .:t.+ l :? l :t: if. I ~ ! I + I :t: L__:--,----~J '-.~/ 11 'I"\ 

~~------j I I' :t :t., + ! l:t: :t:t '> I , I I ! ~----/--' __ ~ __ 5_ - I .:t. - •·:;:-----~ :;::t: t .:t. :t: :t: " _____ _j_ I -r---~-, ! # ~ I ' ~'-~ -:.. I II I i :t: I _-::_ I!+ I ! I ' I ! :t. ~ I I :t:ti + # -1'-j i I! + :t' 

1

-1- •+ • :t: :t:l ~----,-----'---- l+ ,-+:;:' • # :t: I :t , - I, :t:,~---~-- I+ # I :t: -----------'-- I+ I :t: i + I I :t -------· :t: ,; t ' :t ' ' ':;: -#1 + :;:' :t ~ 1 1 -- 1 ~-L 4 :t: :r. -tl '*' 1 :t: 1 + 1 1 L ::r 1 j------· 1 + r I 1 1 :t. ' I - - - - ' + l :t: I ' + I l # 1: l :t: ' - - :t: I !I :tl :t i .r'+_ ___,. : 

J 

I :t: :t:t I :t: :;:;+- :t. I :t _::p + I + :t --., :t + _I J :t: I ' !· + )I. 

"7---'l:~- +i +:t:t + £-:t:--.J"" __ t__ ~ f- ! + ! ~#7'--~ I I·---... r-"t-\ I - ., r :t: -,_; :t: I . :t: :t: ;t--- --------,------l + I --~*-- I ;~-~~ ·-.- ,~, 

I + .... I + r.:-+-~:t: :t: r-- I ' i + I 'I ~ :t:t .r' ~.- ,_J+ II :t: - ~----*--,+ ~++ 'I - I + #I II :;:--------, * ! I -- I I + f I :t:ill+:r.• + I I :t: ,· :t: -------· 1:;: L,l I· .~~-t; :t: 

I - ±__ +l 1-1, :t: ~--+--+·---'---1------~ tj - -L-.---~-~-'-i-o + ' ,I - .\:;: I t-l -------1---'F I + .:t., .t I' :t + ' ' + - . + I \1 ' I \. J 

I I I I ' I :t: i ' :t: I :t + I + I ! I *· I + \ -- - I \ + * I 

+ 1 I :t: 1 I 1 1 u :t: _1, % 1 ~-------·; r · L '*', i , I'*' -1 1 ++:t:t r r-i '• v L _I- _t_ - ____l: -' - ~ - _:t:_ - : _ _f•- - :....1, - - _i :: -I...!... ~ - ~ - ~ -'~ - ~ - + +:t 'r(_ I 

l..' ~---;"r':.) \1' I I' 

0 50 100 200 KILOMETERS r, ~ 1 - \.."' f --! :t: ::r'" 

SYMBOL AND PERCENTAGE 

OF TOTAL SAMPLES 

6 33 27 31 3 

+ ::t tt 

" I + , 50 100 MILES 1 __ 1

_ .:., t 

Geometric mean 10 

Geometric deviation 1.50 

Analytical error variance 

(percent of total variance) 35 

Number of analyses 1140 

B: 250 

MMI.n,......;:~ 00 V N M 

COBALT, IN PARTS PER MILLION 

FIGURE 12.-Cobalt distribution in selected agricultural 

soils of Missouri. Map symbols correspond to frequency 

classes as shown in the histogram. 
ELEMENT DISTRIBUTIONS, AGRICULTURAL SOILS H23 

•- ~ "1*"- r +- ::;. -4-- - -., - - --,- - + ---.- ~ '~" r- - r +- l - - T -+ \.. 

\ # + t'* * tt l + + + ' I I # ' + +# I I I+ I 

. II * + ~ \ + - + # + I + -+' +I + ' 

~ + ::t,i * +~-~--;=t #+ I +- +~-----~,*';->I t ~ ++*++-+<#+ + +', 

')-~-"":~, I !:+·+ 1f ''* tl r-.t~--J-:-~---_J:t:+ I 

~+ + + ~r -~- #!+ -; ! *#+ !--;--++! I *+ ;+ + · ~+ + ++r--:;:-"""--+~, -. T =r--1 + f---,.:---:r-1 * +· ++ # + '+ + I + ~ ' *·,:t:* -1!:_ ---.l,l+ +,+ ++1- -tl 1+.+ ~- + +' "' + r, +~ +' :t: I + + r----T ~----- ~ I I I I I I 1 

'"j?# +I i ++! I+ ,-i----~ I :t: ~ + +-.-,--t·~-----~ 

~--~i I + +I I + ! + * I + I # I + 'I_ + * \ ~ I -j.._-4-_-t.._ __ ;-+::;:-+--] * + t' ++I + I +I- +I' # + ~I , ~ -11 I +' +* I + *+ +,----r·.!._t + + + ~ ~ -4 I I + * I ++ 1.2:.. ' I 1 + + i ,---- .:__,_;-- --+" 

L' ..±*I ** . , + ---+~ + ":t:"----r- + I I# ~--- -::t.., +* ~--+---l + + r;t" * # I + + + + + . + + /,' 

t+ +* +~-~-:_...i--..j I ;t- I (, I + +, II + I I+ /' ,, 

, I + * * i I + + ~~ + ! I ' # + i - ~\ I I ' 

~ +-+ # J #...... ·-+ ' + r- * + :t:+ I ++*i * + ~ + ,·,_; -1.#-t -........ _ · ---,--+-'---, + + ' 

... ' :t: "-_.:;e-(_-1!_ ~ t-·_..,---,_.1!#- I '-;·'+ +;:+~-'F-1 I + \ -------\ 

"'....--J+ +' ':/ I I + ' +1-/ -tl + ±_- I I 

I +r; * + '*' # , 1 1 1 + + r ~ + -;f- + +I +' I t .:j:• ,+ i + + J + I I '1------' I I l 

I + *.~ + i I + + -( t\ -~'!!· + !+ ! + +' ~ - I - I 

l :i: I + f----_J---T-+--~----< fji=' + ', - ' I I I \ II---; 't __ ~-r.\ f ~ ... 

----___ · + + ..... I + I + :t:t . + \ · ~ . J r--+1 + + "" . ;:' 1 -' 

I + +1 + + ' ' ++ + ' + -, 'Ft- I I I +' - ' + ( + *( ~ + I I I I I ~ ' + + ' I;;, # 4:j - I . - + I ' + '---~ + !) ~ I ~++-±..-~-, I-' - .--t I I 

I + L # + +I + l+ I I --+ i -..,___, + y'* It -; ·~- I / I + + ' I 

,+ + * ~+-~----4- * - ' * +_ - ~ \., _ _./ + I+ ' ....... .:__+~I + \, ---~-#- #I + ~---t-.J + . .j " + ;- + +( + I +1- I I _-,-.....;. 

---< 1 ~ ' , + +I-'"+ I +r·J+ ~) I + + + I + + I I + I + ~- T'- 'I :.At- I I : ..,. + I + ' y ~' - i + I + 'j+ +, I I ~ - ' + I I '+ -~ ! - ! !-- ! t ---,:---,-----1 + ! * 'r+ "t-' I # I r:---~,r1, + ~ <,1. __ , ...... , * I I *'I·- ~---- ---."# ". 

f , , # - _ "'.. # • I I I I ~ 1 I I 1

11' + , "> -= ..± / ~ .:j: f- I \_ I 1 -, - .. + r , - + -"+-, 1 I , --J-.1; '!t. - 1 + • I I ""'-f_i__T :t:l I 

1

•. il&t _.....· .{ ' I i I I* - - I + +* ~ :-jt--'-Tf' -' -I ¢ I *- I - + -" * ~ # , ___ , I r' #+ ,L,_....tt + I + f ' I ! + ,Y +++ "'+- ' I '- ·- - '- I -..... --. J' * i I +I I I I ' I \ 

'

-+ -# , - I -,-'-- - -- -L ' + "- I +-+ 1, I I + , + r' * I ' - + ' ' It l ~---~--, + ++ f I I + I *+ 1 + \ . - ~ - I I ' - L :------"'-i ' " . I ,.. f -1------ ~ I + I -' + I I ' + I -I '1 i :- - I :t: --1 + '=----- -::-/ + : I \ 

+ +_ l':i"F----~ + +I t I+ -i + I "1_..:- ____ _i_l- :t: f~---~-,1 +! ·- ~-+---.-~-r---1-'-{ 

-t._ = ' I '*' ! I I I i--- '~---- ....::--- -' + ' + + +; - + # ' - I ! +Jf *t + I ";-+ I I \ I 1- 11+-----lL- 1- - I I[_ ______ ......_ I* I I I I ,I + -------. I I I I ' ' ' - #* * I ~ 

I - - - + I - '7 I; ~ + ~ + 1 I' I I I I L * - I J' - - - - --' - + I r . r + 1 1 ____ ._ ' I *.t + I # -· + It- ' -t ...r' .. 

I ++ i +- i I+ L # +I ,, # + 1. I _; # I I I + I I +:"' * ' 

J I ' *I I '....j. __ j "1. - ~-- I__:!-- i +ftt:t: .,,_+ I+ -!' ,-..... -.-:l- - ~ --- l_ - _I I -F I + -- . -- I ' ' # '-- #::,;_ I __, I \ <: + -f; - + ' + ;t-----------,-----l + I --~·it. ,..~-T+ '·--~ - >,' I I I + I - .# li -, ,, + I I I' : I ::: I I I ' I I * # f I_* ~ J I I ~ I #--- --,I -+r,+ I + I I It - I -------- I ( ·- _-- #I 

t-+ ·: T lj_l l,t ~ * I I I - ,--,----=--L # - ~I 1-, ·~~·i:;, :J:.---+-~+ I+ .-::~-,-_-·---------- --, l ·;-~-,""f---t-, + .I I + - '\I I~ I I .... + -· # I ,-1, ' I + ' ' '1. 

I I - ' + I i ' * ! I ·- I _I +. + + ' -- I I ' # # I 

(_- !' - ' ! I+ I# i \ * i * I - I r i•-.:_-,·-·-'l: , r\...J - # t I + ' I - ' + ·- + ' I _, ' - I I * ' L - - - - - _+ -' - __l - - - - ·- _#- - =:.....l - - _I - - ~ ....J. - __::: - ,j _f ,.._ l' + t:l: TL I 

L..- ~-- ;'-.:..';.) 

c 'L * - .... 0 50 100 200 KILOMETERS ,._ · # 1 '!( r --! * :t:· I I + , 50 100 MILES J_·~ _;_ _ 1 

SYMBOL AND PERCENTAGE OF TOTAL SAMPLES 

>- u 

z 

w 

:::> 

d 

w 

500 

~250 

15 25 41 13 6 I + .:t: # 

;=~~~~~§:~ 

COPPER, IN PARTS PER MILLfoNGeometric mean 13 

Geometric deviation 1.55 

Analytical error variance 

(percent of total variance) 32 

Number of analyses 1140 

FIGURE 13.-Copper distribution in selected agricultural 

soils of Missouri. Map symbols correspond to frequency 

classes as shown in the histogram. 
H24 

> u 

z 

w 

500 

5 250 

w 

a: 

u. 

0 

N .... c; c; c c c::) c::) 

GEOCHEMICAL SURVEY OF MISSOURI 

0 50 

0 

SYMBOL AND PERCENTAGE OF TOTAL SAMPLES 

16 17 27 20 2~ 

+ ~ 1:1: 

o.n cg N cg N a o.n .... cg C") C") 

~ Q) 

c c c ~ ~ N C") cg c :!: c:::i c c c c c 1::! 1::! 1::! 1::! '"": C") 

c::) c::) c::) c::) c c c c c c c c::) c::) c::) 

FLUORINE, IN PERCENT 

100 

50 

~ C") 

cg 

c::) c::) 

100 MILES 

' ttr' 

200 KILOMETERS 

\ 

Geometric mean 0.027 

Geometric deviation 2.22 

Analytical error variance 

(percent of total variance) 61 

Number of analyses 1140 

FIGURE 14.-Fluorine distribution in selected agricultural 

soils of Missouri. Map symbols correspond to frequency 

classes as shown in the histogram. 
ELEMENT DISTRIBUTIONS, AGRICULTURAL SOILS 

> 

u 

z 

w 

:::> 

d 

w 

500 

EE 250 

SYMBOL AND PERCENTAGE 

OF TOTAL SAMPLES 

5 21 21 49 4 1 +I~ I il: I I I I 

I 

.n.nr--.c.ncc - - N M v 

GALLIUM, IN PARTS PER MILLION 

Geometric mean 11 

Geometric deviation 1 .49 

Analytical error variance 

(percent of total variance) 25 

Number of analyses 1140 

FIGURE 15.-Gallium distribution in selected agricultural 

soils of Missouri. Map symbols correspond to frequency 

classes as shown in the histogram. 

H25 
H26 GEOCHEMICAL SURVEY OF MISSOURI 

---- ' r--

\ l 

- -r-----,--- -,....----- r- l-- T- '-

l, ~ \ + ! I I I I ' 

J----- ' ' I ''> + I ! I \ +I ' ·r I r------, ' ' I "\ ')-t--:__.

1 

1 , + I 1 r-~----t ____ J :to 1 ,-----· 1 1

1 i r------1 ' I L I I I ' I· ' r--- --~ , ----~ + , I I I I 

, -')+ r-----J, I 1 1 , , , 

>- u 

z 

w 

..... ) , ; 1------{-----~---~--L----~~~------\ 

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J I ! I i l + [_;----"--] f ~-~---;__,.------~ 

\~-----~-----J------ i------~- :to ~----T+ : :t:// ' 

') I I ~ I II ' I ' 

\ 

:t:t• :to ' ,./ \._ ,___;_ :_ _______ ) ___ \, + ~'~ r -1, I --........ ' ~_,....-J_/-~<._ ",-L------1 ._• :to '-;' ----..,/ __ _;_ ___ I I, ~-------\ r~' '/ I <' I I r---~---:-- 1 I ) I ,t ______ , i I 

I , i (' "-_ --~ +' I ; ! L.. 

1 :to 1-, ___ _J----r------, -(,__ 1 + I '~+ -\. 1 ....._ 

-------1 

I I ;\ I , ~-j ~---r--~ ., -~·"'-':___, 

I I

' :to i :to ; 1 I I :to ! ; ' I/ -( I .___ ' {) ,' ~-+ -----~,, ' __ ! I ' I ----:t ' '-' / ' ' '- I 

. Lr--------~ ! I, I \ / !+ I '--"'-.:__~·! \,' !-~-- I :to ~--.r---~~ "', 1 1

• I , 

I - .~. r---:-_ J ~--~ i :t:t I ':--~-1 f-=_ i Y +t I I I ,J -- f I I ' 

! ! !-- ! -~~--_;----1 ' I' 

l ~------'~ ~ (.c __ ,-"-~ I ~-~--~---;----- "- \. 

r---;;-v--1 ~-----~ \ , "" ___ ____; i ·r(___--~<~ ' i :to 1 1 - -;----'---r + I + 1 - "'-:, 

1

"---, r' ---,--, I < 1"'- ' L_:_;__ ____ ~ '\_,./i+ I I I ' :to ' \ 

~+ ~ I i~--~--L __ IJ-----~~ -f '-,~/ t r-------1-------i +t 1 _,:to 1--J __ _j_l ~-~-- :e~ --:-i-+--r---~~, 

J 1 i + /------~-! ~------; l_~ ____ ._"J_ _ I i ! * ~ 

-+- ~------l ! ~ + I L :to l, __ j-----( I r I I i 1, I ' I l. I ..r' -<' ~ 

1--------i r----~--l __ ; ___ i ______ L-.------~ f--:-l ___ !~ # ;~---:-~-(' - \><:, I r--- ~ I 'I ' ~ - I_ J +"' - >-----+=--, i :to I .J 1 r / t I I i ' ' -;,-------~ ~~-1-r: 

~-------~ -1 ~-;----·--,--t: _______ ) L_;-~-----'-, \ ! \, J 

1 , 1

· 1 1 1 t. , 1 , , 

# I :to i I ' ' ' ·-------· r'I.J I ' i ' I I ~ I I + .. L ___ I ____ 1 

_ __.1 ____ : ____ w ___ 1 .:- __ _;, __ 1 _ ..J _ _ r,. 

1 't-{, • 

~ ~---;'--\j 

50 100 

50 100 MILES 

SYMBOL AND PERCENTAGE OF TOTAL SAMPLES 

50 10 25 33 22 10 + tl: 

200 KILOMETERS /' i ~ ... 

r i " , " __ .:__1 i 

Arithmetic mean 4.4 

Standard deviation 1 .65 

Analytical error variance 

::J 25 d 

(percent of total variance) 16 

Number of analyses 114 w 

CI: 

u. 

0 M CO en N Lr> CO 

..; o:i- o.ci a::i cc:i .,.; o N 

IODINE, IN PARTS PER MILLION 

FIGURE 16.-Iodine distribution in selected agricultural 

soils of Missouri. Map symbols correspond to frequency 

classes as shown in the histogram. 
ELEMENT DISTRIBUTIONS, AGRICULTURAL SOILS H27 

>- u 

z 

w 

0 50 

SYMBOL AND PERCENTAGE OF TOTAL SAMPLES 

500 12 20 28 20 20 

+ :t 

6250 

w 

a: 

u.. 

0 ~ ~ M ~ N ~ ~ 

N N N M M ~ ~ ~ ~ 

IRON, IN PERCENT 

100 

50 100 MILES 

200 KILOMETERS 

Arithmetic mean 2.11 

Standard deviation 0.64 

Analytical error variance 

(percent of total variance) 4 

Number of analyses 1140 

FIGURE 17.-Iron distribution in selected agricultural soils 

of Missouri. Map symbols correspond to frequency classes 

as shown in the histogram. 
H28 GEOCHEMICAL SURVEY OF MISSOURI 

,- :r- -+- -r:t:-- ~ 'TI-- ---r- "f- -,...--F T r-- r+- l ,--:- T -+'\. 

} + ~+ IL++ +' I I··++, I r+-, \ I + 'l ' I + I +1 \ + I " I + :t: I I I+ I' I I + ' I I ,L1

_.:=r;_'_.,;. -:t: I II ·,I I I''>+ I +I++ I-+'++ I 1\ • I I + ' I I I I >---------;-, • + I + I I "\ \,.__+ I ' I ' ' + I I ' + I r---,-+-l I + rl ~-+--~- I \I I + I_'_ ____ _!_, I I + '-----. 1-

¥'-:t: + + 11 + 1 1- :t: . :t: 1 :t: :t: 1 1 

, 1 :t: i+ + k+ + 1 r- - - - ' r-·-r-~- 1 ~+~-~-~ + 1 • 1 1 + + ·, + 1 :t:;._ + ' I'')++ ~-----l.l:t: +I :t: + I I I :tl I I I+ I ~· + +I ... + I~ k ,:t: I I' :t: 1 __ ±__ __ -t~----,1--l----~+ :I I I I\ ... -r, \ - -+- -+; :t: I I I I :t: I I + 1-r -,--'F.~------±\ ..J/ + + I ' I I :¢: 'I 

~--~· I + I I I I I I i I -:t: 'I I + \ 

,.._) I 1 I +~--_I_- I + :t: I I + ' 'I + ' I :t: + +--+-----/ + I + 1 :t:+ l + I I I, 'I I +I +:t: I +' , +i II I ' ,+ I I I ,,----;--·-: 'I I ' ---j---~ ~I + ' + I I ! +I ! .±._---- ~' I - 1 :t: + I I"----"---!-, I '\. 

L 1 _;t t 1 =i=+ I I+ +! I I\ :t: :t: '+-,--r-· 1 + I l:t: . ' ~--- - ' I + ,- -j-----i + I 4 :t: I : ' +I + I '+ I :t: / I 

-1+ I ~-----=i----1 I it- -+t, I I I / I 

+ +:t: I +' I :t:+ ~- I +I + 'I -+' I ' 

, I + + I I :t: / 11' :t: ' ' I + _±I I \ + :t: ' 

'{ :t: i I + I I i :t: ~ I ,, + ,, - ;' '--- -,' I / --+----... '- I : --+ -~ 1---I I + I I ' 

>-

u 

z 

w 

:::> 

d 

w 

a: 

'-¢ ..... I ('_/-::,?-(_~' ,"; J--/~ 1:t:- I '-)I I ;:I~T-1 I ~-- --- \ 

,...-·J:t: + .- /" 1 -+' + . i+/ I -1- + r-+L :t: + 

I :t: +~ + ' :t: 1 + <. + 1 1 ;1 - r - 1 ~ :t + + , ·- I +, 'I +; :t: I !;-'--~---- I+ I 

-+- I '1- :t: I + I - -:t:" +' -t I ' + I L_ \ I ' -:t: ·( ------...I -,-- -t-. I I :t: ......__ 

1 .:+: .:+: -1- f-----'---~~ -"'f----• ll:t: -1- ' I 'tj ... '~+ l __ )-r I I.::)_' ------- ' I :j:: :j:: I + +f\ + \, - . J r + -;:1 + + ..., , ;S<' f ~' 

I + i1 ++ + ':t:l ,_ I + ;++i-t- I I_._ I !'- I ,' I ( ++( :t: ' I .. I :t: T) '' ~ 'I I ' -

I ,:t: :t: I, :t: -1- + i + + 'J+-,-;+--~~ ... f.'),_\ +I y_,-,1~-'----- I 11;1-"·-': i I / -/~-:* /I + + L~--:r+---' + I + + -,1 ___ / :t: ' + ' -~-~1 + \., I .:t:- I :t: I f!' r·---J "'0: l I II I I + + I , - ----- :t: --,- I-t'- , I f:t: I I, I +i + f-r'--rt:..J I + ---; :t: j :t: I I+ I 't . .L:'fi + *f-'-=l- + i -t + + I' + I' + :t:' I I :t: :t: I I J+ I I +.i+' I I I +I ,, I + I I I~+ ; +--~1_ ___ _:_ l :t: I +,(!- ~ + ' I I' ' I ' + .+ ' + I :j:: :j::~~---f-r'l., + ~ (.l.._.-'-, + I +'I,--~-------- I ' 

l ' + I I +' I I :. + -+ I+ + + ~ 1:t: + !ri + I \,I ~ r+---:;-v--1 -:t: I ,:t: ~--+--~ ~ \_J_ :t:! I+,___,., . ..± _ ____;:; I :t: I -\1,'_--<- ;+' ... -1- ' I I :t:• I I + Tf-:-J--'---- I + I I I I ++I I 4 :t: " + "- +. I + I + I I I ' I I I I I + I -j;-' + +..., I :t: , ___ , + :· +:t: +;t-• . ..;t_, __ , I ! i+ :I ·' :t: I ' I ' + /"t' 

I '+ ' :, I Lr--,- d: - - -± ~:t: I I I '\,' _/I :t: ~ I +, ~ - ~ - -' ; + + : +." I I ' + I\ + :t ·, ,I lj ~ I : I L ______ "f:t:_i ~ I·, +_I I + .,. ' I I ::t= ++ 1 . '-- ' I I I I I - - I + *'~I + I \ 

f :t:-----. --j I I I I I I ! I+ + I ' + ! - - <:t---- +- ,---:-- j:- ) I ' I , ______ ~ +I I + + _____ _j_' ·r--- r I ! + ; + . ~'-, 

' ' I I ' , + + +I+ I r I ' :t: I ::t= + :t:l + 

I 

I I ! \ ' I :t: ! + I ; . -- -I_- • - - _l I ' I + , r; I I :t: , I . + + I+ I , i -i- I '' 

· 1. +r*-·---+L! 1, 1 + l _______ ~ 1' 1 + 1 i! * '~-~~-+-; '_l:t: ' + + ;I I +i II + + + I I L :t: I I+ I J' ---1

----' + i t ~ l, ---:1 , + +: :;: ,- :t: ~ I · + __,. ~ 

I I + I I' I I' :t: l + 'I + I 1. :t: I + + I I + I +.r'- ' 

I I I :t:t-'1- + I I ' + '-, - + I ---'' * ). + ' :t:,t ' -11 1 'I 1 1 1 1 

1 1 :t+ , :t: 1 I 1 , r- "'t ·, 1 I -., _ r +I + r ~-- ~..,.--.-. 1 1 1 . + . --'f! -, + ~ t \ r -- +--+ + + :t: 'f.--- ______ c.__,. __ ---l I I ""--+:, ,~-~ . Ill I )'-\ 

I + I 1 + k -~~ I :t: i1 I I ' : I , •+ +-~ I :t: / :t: I_ I 1-J I~ II :t: :t: "---*-- 1 + ~ + I I + I I * I I I j I "'------, + ( I - I +/ l:t: f+ :t:+!+l:t:' -1- I I I +I +.--,-----L l:t: I ';• 1\ .~-l-1;, 

J--*---+-=q_ 1-):i:: ~-~~---t-~-1",----j-----t +j I ·;-~~,--t; I \+ I! I '1, I I J 

I I I I :t: :t: ! I I I I + ,+ ! I I! I. I +I ' I I I I I \++I 

,+:t: ' +I' + , I ' ' i , ' \ :t: I + ' I +, ' j·-,- ----~ I r\.J I + + I I ' I I I+ I I :I I ,I I' . II I +''• L - - - L - ___j _, - _j_ - - - - :_ -I - - w - - _I - - + _L .... - _, - _J -', I' I + 'rt, ~I~ __ ;'-f';J \1 1

. I I , 

,.., !, ,,~ 

(II! I + 

' ::t= ! I I, J __ - ... 

0 50 100 200 KILOMETERS 

0 50 100 MILES 

SYMBOL AND PERCENTAGE 

OF TOTAL SAMPLES 

48 36 16 

I+ # I 

I 

I 

500 

Geometric mean 41 

Geometric deviation 1.39 

Analytical error variance 

u. 250 

(percent of total variance) 49 

Number of analyses 1140 

0 C) C) C) C) C) C) 

M M o.n ,.._ 0 Ln 

v - LANTHANUM, IN PARTS PER MILLION 

FIGURE 18.-Lanthanum distribution in selected agricultural soils of Missouri. Map symbols correspond to frequency classes as shown in the histogram. 
ELEMENT DISTRIBUTIONS, AGRICULTURAL SOILS H29 

,- =-:_ --- r--- -, -- 'l1-- ---r- ":f--.-r.;: r.-- r,- l:- T -+\.. 

\ - l''- 1[_- .... - ;_ l .. ':t -; ,,,..1, - '-+, 

>- u 

z 

w 

I '-+- ~ ' - - - .... ' I I -1 I ' L_.J _ _.' + I I + + '>I I I I p++ I _, • I I -, ll + I I + .... -------r· I :t:_' '~ '-1 "\ 

u ... -~~- ! ' ,- ~l 1- I -1 r-.=-----r t------t I + I 

J - I I -1 I- I ~-----· I I I I - ~--1---=f ,- - + r- ,_ I ' _+I I - I I I I - - I' i+-1 I +! + 1 - r----~--i - ~----=--i + -· +- + ·- __ 1 t- ' 

' -··.+ I I' -----1.- -I+ I _I- + -* +-I+ I I I +' .. ' I r ,+ ' I I I - r-----::-'-------1+ ~I + I -\ ~d-~- lj -~~ I 1 1_i-___ l~- ~ !1 + ..:_,..,_--f•-,-----J) 

'L ~-! ' I I I i I - I I I I I I I il - \ \ - 1 ._-:_:::..__• + I + I 'II + '- + - I ,.._, ...... ---~. -l - - + l I l I -- - I_ I - I I + - ,--- -J- ' •' I - I_ -,----=·-- 'I I ' +~-~---~ l...... - I I + : -- l..l.. ____ -:-• I 1 I + ..J. ,-------+, I '\, \..:.:": - -I I~ - + I ll I ,_,_______ I I -+ ,'' ~-----h I I ~-t--·--'i I -I .- - I I 1- +f- I - , - I ,/ _\ ~I I ~----=---1 - I l. I + I I+ / .... I - I' I - ...... I - +I I I .... - ' 

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- '""~7"'" • .....--...1 1._ - '-j- _.:::;_: ..... ·T-1 - I ~-------\ "',.-·J- -\-' Y _ _, I , 1-/ ~ I 1 ~I 1 

I 1 _,_ 1 - 1 + < - , 1 l 1 rr· ji+-~+ 1 , 

~ -i I I - ,_ - ~)' - _/ - I I 1-----; _I I I 

I ,I - I +-(+·-----<.,_ J- I+~~ L.l' - \ ...._ l - - I ,_ ___ _J---=r---=----· _,I I • - I I I I .+ ·--; .., __ ,..-:.~ I +'' 

-------j - \ I - -1-\ +I i ,..... . .J +-~ + + "' .•:._ T~' 

I

I I I, - I I i -I i - fl j- i ... I + ' I' .I - ~ I + / ~,r + I I + .. ~....,_ 'I '~ ( + ..... -+-:::--1.!-\_ +_+I .-J!_- I 

I ' • + - I I - , ' -r ·---if i -..... -z + y·l -~- +i '--...... I - / - +' , ' Jf I +- Lr--r+----~ I ~ • f -,I . __ / f , - f 1 .:._.:._"'! f \., 

----- Ll I I ... ,.r·;-·1 -...,- I r- I -:!,- L ~- + +~·1'-....:--y 

I 1 -- • ..._ f 't: .L: I 1 r·1 • 1 , # 

~ + I +- + I + - I I I - '-+ 1] +~I- + 1 -t + +I I I - I + ,.r- ---,- - I I I I ' ' 

J_ -I ! - ! !-. ! I ,1---_:----~ - ! + -fl +' 1 :t -;-+---f-r'l, f ~ 1. __ ,_.., - I 1 1'_,--~--------, f ' 

~ I - • -i! - ;, I .- -- I I ~ . ~- + -ti - - ~ ~ 

1----+--.,~./ I - +' !---4--~ t \-.1 +! ++ ...,.~...± . ....! :;J I I + -~~ ....... :'I' ... 1 • 1 + + ~rn_....__-4=7, I 1 I * ilfr + " - 'lo.. I I I + I I I+ I I I - L -I ¢ ~ I • 7' . -~-, 

I ·---. - rl #+ _±-~---'*'-.,--, ' I , ' I ' I + , ~. - /..._' - I I ~.-~ - ; I I I -" J' I~ 1- I I . I # ), ' - \ I I + ' - I I - ---.~I I ' I +- ,. :---- ~- -, I I + ~ ' *'+ ~- ~ - 11 - - l I 1 I+ J - ~ - I L ------ "f- ~ ' • I ~ •+ - + ++ ) ' ' I+ - - I --· + f. It'":/ I - I \ p------i I _, + 1, + I _+ + " I ' + I '=f,----.---~ I ) 

1 ·--- .f. +' , 1 ' 1 + ·------L _ 1 -~----r- 1 ) _ -----.~---~''-, 

I + I II- ----~ + 1 I '!- 1- 1 ! _ [ l- 1_i # ~ ..... i- ,I I _, 

I ---- ' I I I I -1 ----------=---' l- -=;- I + ' I + I' 'I I \ - 1 ,

1

+-----=.:..LI 1- , 1 + _______ ...... 1 + 1 1 1 -~ - ~ -- - + I- I + ' ' I - I+ - I 

I I ..:-.:.--,-i l ' I -l ,, II I I I l- I I j------' I I :: ,, ----1: I ' I I+ ' ~ I I + T-- I II -1 ' I -I' .. 

I *+ + i i I 1 I 1 l I 1. - I I -I I I ,...- ' 

J 

- ' I+ ' - ;'- ,+ 'I + I + - I +-=+; .,, I I !' I r -~-.--:.: '- ~ ~ t/ -+ 1 ,_ ___ _,-+ __ )__ 1- , - , + .--~·· '-; - { r --- ---- + • +I '1-----------,..-----, I I '1t---l'-';1 .---:... ·- - >'' I + ) I I r·-r-::...- + ~,,- I : -I ,_ \ I J: 1,,- _1_" ..-

I I +~----'---·'- 11,,- I I J - ! I I + 1- - I-~-----~ I 1- -C. -,1 ,_ + I I +'I'--' + I - I + ,---,-----' I - ~ ' .~'""C;, *- :+l -1, - ~--+---~---~---r-----f i -L,--~--=.--+-, \.- ,I - ":'- _ 1 ::.. ---,.. I I I +- + -~· + -- ' ' I . II - '1. + I I I + + I I - I - *' *+ \ -- - ' +I 

_,- 'r' I I ' I+ . , . ·-, -_1, '•·-------·- -,~.1 ~ I I ' I I -I I - \ - I* .± I - i .. • ~ L _ 1_ !_-t __ __;_! _ _.1 __ 1 _ _ :_ -*- _ .J.....l. _: _j _: _,....±: ..1 _ __-: _ .J _ _ r:._- t -I ++""t,' 

~- ~---;'.:..':.) \' I -

0 50 ~~+ ~ .... 100 200 KILOMETERS "- f --!-

0 50 100 MILES , I ___ - ... ! - - ,' 

SYMBOL AND PERCENTAGE OF TOTAL SAMPLES 

423420 3 1 -I I + ~ # 

I 

500 I 

Geometric mean 20 

Geometric deviation 1 .55 

Analytical error variance 

5 250 

(percent of total variance) 20 

Number of analyses 1140 

w 

cc 

u.. 

0 

LEAD, IN PARTS PER MILLION 

FIGURE 19.-Lead distribution in selected agricultural soils 

of Missouri. Map symbols correspond to frequency classes 

as shown in the histogram. 
H30 GEOCHEMICAL SURVEY OF MISSOURI 

50 

SYMBOL AND PERCENTAGE OF TOTAL SAMPLES 

>- u 

z 

w 

::::> 

d 

w 

500 

ff: 250 

Ln 

,....: cri 

12 32 39 12 5 

- .., 

+ ~ 

ccoq-cnLnN-

-NNNMq-Ln 

LITHIUM, IN PARTS PER MILLION 

100 

50 100 MILES 

-~ \ 

200 KILOMETERS 

Geometric mean 22 

Geometric deviation 1.28 

Analytical error variance 

(percent of total variance) 4 

Number of analyses 1140 

FIGURE 20.-Lithium distribution in selected agricultural 

soils of Missouri. Map symbols correspond to frequency 

classes as shown in the histogram. 
ELEMENT DISTRIBUTIONS, AGRICULTURAL SOILS H31 

,- ~ +t- r-:t:r ; -::t:- - ~ - ---.,- - ~ -.---f'"' :r ~ - r~- ~£ - T , \... } ,_ :t:t :t:t L ~ I + I I ~ ~ ' :t:t~ ~ I++ 

\ :t:t :t:t ~ , !t~ ~ #! \ ~ + -If ~ :t:t ~ I + ~ 1..- ~ ' I ' ~ ~ .... ' ~ I + I ~ ~ '') + ~ ~I ~ ~ ~ + \ .. ~ I :t:t ' ---+i ~ I ~ + .... -----~I ' :t:t ' ~ ~I I ' \........;_::t:.~. I :ft ,:.t:-+! 1+ ~ +I 1-;-'"~---:lf-i_ ____ _, ~ ~ I 

l.._.:t 1. :t:t ~- ~I I ~-----< ~ + , ~ +f 

>- u 

z 

w 

'F ~ :t:t !It !~ ~ · :t:t~ I :t:t + ~~ , ~+ i:t:t ~~ ~ :t:t::::r + -- , :t:t r---~--i ~ ~~--.:r-1 ~ ~· ++ ~ '+ + I ~ ' 

' :t:t·,:.t: :t:t {- ---k ~ '~ ~ ~I' ~ d ~+ '~ ~ ~- ~ + \ 

" :t:t 1 :t:t ~ ~ ~:.t:' :.t: I__±_ __ :;~_;--- -T,--J----~+ :I ~ + :t_\ ... ~. + ~I ++ ':t:t I I -+ + -+-.1--f'"·~-----~ 

~---1=t'+ ~ I+ I~ I +I I + I 't + :t \ 

,....) ~ 1 ~ ~L...... __ :f-__ I ~ :t:t I + ~ I + + I- :t :t: -;...,.::.t: ___ _, + + ~ 1 + l + + + I +I+ +I + +I ,. ~ uj ' ~ ' ~ ~~ - --- .+ ¢ ~ + + ~ .L_. :j:t I+ :t:t +1 +~ ~~ +: ~ ~ --+1 ::t -----.:.........,.----+-·. '\ ~ :t:t I :t:t ~ ' 'i. :t:t -----~ ~ '#"±_ _ _:£_ ~ + I +~ + , 'ft ___ _;t-_~1 ~~~ L----$----:1 + ~~ '*" ~ :.t: I I+ +F+ ~ ' :t:t + / ' 

\t:t:t ~ ~-- . ...;t--1 I it -,:_ I I I + r- / ~ 

, + -h~ I :t:t ' ~:t: ~:t:t ~ + +I + '- ~ + ' ~J:t::t:t ~ I J ~ J ~..._ ___ :t:t ..... + :t:, ~ _ _2-___ ...±) +\ + :t: -~ ~ I ~:t:t:t:ti :t:t ~=II' :t:t •"'- ; l.:t:t.i ----..._ : + * ---, + :t ~' \..t: ... . :t " .. /#-(:t:t ;to.,~.___,......, __ ,pt--- :t '-;·'tt +,;--;+~--F- 1 + :t: I -------\ 

""....-·,...l:t; :t;t:t I y :t: I ~ ' #/ :tl :t ~ +±.. + 4-

1 ~ :rijt :t :t 1 * <. + , r t' ' r-+--' £lF·++ + , ' ~+ :t :t:_;. :t I I ~-----' I :t I :t :t:t I ~ I, + :t 1 • :t "-. :t:t• :t:t d: I + + L 

I :tt :t:t ( . ------- -<.,_ ,- I ± :t ' + I ...___ 

1 ~ ~ ~ f---- . .r---f"-Jt--""f=·---; ;t+- + ' ~ ' I ~ I + 1,-f -i: __ fr,\ I #~' --- - · :t:t ~ I ~ I ~ ::1:'1¢\ ~I • J ++I ~ + "" #' +~' 

I ::t?" - :t:1 ~ :.t: + i ~+ ~ I + j:t: tf ; + ~ I ~~- + I i + / :t: :t ( 

:t:t ~ i I ~ L...:-.:t:.... ¢ !) ~ ~ :t:t --+-~-1.,.~, ~++' : .-7:f~ / 

, + . ~ ~ ~~ + '1+ +c _.,. / -....... ~~/:t:t:t:·~+ :r~1 , __ I / + +*, , + .... + L~--~ I ~ ' :t: I ~ "· ./ ~ + ,_. ~I :t: ' - I ~ .... + -v-~---::.t:_ r---~ + ~ -- + , :t:t ' I ~# ' - '-1 ----- :t:tl ~-""'f-- ++ ~~ r t+ ~~ ~ +1 + ~-~-1---.. 1 I + ~ ~-~i + + + i :t: :t: + I+ I :t ):~~ + :-f;-1 ~ i ~ :t + ++i ~y 'I + I + II :t ' ---~ + I + ' + I ' I 

l:t _ -+ , + ! ,'• '! ~ I ~---,-----1 + !+ f +' 

:t:t +r-:t:---+;-'1, + ~ (.l. __ , ........ , I I I +l+o--<----~----, I " 

l ' I ' I'+ - ...,__ :t:t -+ ++ + ~ .f-1+ I 4-i I + ~ . ~ 

r·-l-·7--,.+,-.j + I ++ ~--+-+~ 4- \_...± +! ++ ,.._., . ..±-~ :t:i I + 'I ')M~--:-' #_'' ' II + ' I + I -...~--'-r,-· -t- ' +I +*r jilt :t: -.., '+- ~ +, I ' 1 I I - ' I I + I I ¢ I :t 7. * + -~ ·---, + r ~ r -~-j-., --, - I 1

• 1 + + , + I r ' , * 1

._ ' 1 I L.... .;± ___ __1__ ; I I ' _ '\_ .. ,.../' I~ I ' I + *· , \ I I 1

1 ~ I +; ir I ! I+ I, ;-----~--, J_+ __ -:__ -f:' :t:r ~- I +~I :t+ :t - :I I _I : r+ _) +r l - ...._ - ! +t I :t: + l __ . - :t .i r-':1 I i :t + \ I +-------j - - ' I I + ...., I ' - - I .. ----:f"""- * I + I ·-"F----l! r+ I I '1, ~ I ·-----_]_1_ r·,...-!----r-1 ! + ~-i"·--.~-""*''--{ -:.. - II + I + I I ,+ - 1- + ' I ,_--, I I '+I I + ~ I +l + +' I - -= i - -r·_, __ , __ ...!...[-::....i _____ r~-----,--1 , l_--:..... _____ ...:...- - ' i, i + , - 1 + ;-* + ' _______ ,- + I- I ' + ' . ' I - ++' - +' * _,} ,--- , , _ ,· , , r1 ,+ 1 r 1 1 L - 1 J------· 1 + r I ,,. ----!L ' I ++ I ' T-- I " I ' + ..r .. 

I I I ,· I I' I l I 'I + I I l. - I I - ' I + I +,.,.. -# ' .._ I ,, ' :t - I . ' J----=-~-- 1 J 1 1 1 _f:=--J ___ 1

1__ -~I-' ! _- _ - ! ~*~ __ ;_:r !- I 1 '-1~- r·~-~~ I ~ I .:.., I I ' I I 1J- ----------,-----l + I "'---l-, ' ~ 'It-- >(\ 1 1 ---- _ _ '_ , I - ""'-- I ,r + \ f " - I e ---=-- lr - =., - I'- I I I ' 'I ~ I s' + 'I "f:.• +# .- I -..J...._,- IL- I - I 1- I -------- I ! I -- #I - T - '~L--:_- I - I - - - i I ~---=----- -=--L. _- + - ~I '\ ,~J--r;, ~:...L--~-'-i r ~-;r--:._·-:...-:...-,--------7 ~ ; ~--=--+• \+ #! ' >l,:r #" I -- I I ! + + + I - I I + - -1-, + I I \ -- I I \ # :t:t I 

,r- I - ! 1 1 :: ' - • 1 1 - 1 + r -t-;.-~-.----* r".J - - :t:t · 1 · , I -:t:t r - ~ - , , -· 1 : _ ' , # , • L ___ i ___ 1 _, _ _J_ ____ : __ # __ J......l. ___ I :: _ --=- ~ _ ~ _ ...1 _ _ r l1 f # # ""t, I "'I ~---;'+'J \' li # + .... 

50 100 200 KILOMETERS "r ·

1 + :t ~ .. ( +,! # #~ 

SYMBOL AND PERCENTAGE OF TOTAL SAMPLES 

500 14 19 28 28 11 

+ :t: 

~ I * , 50 100 MILES ,_-_..:. _, 

Geometric mean 0.26 

Geometric deviation 1.65 

Analytical error variance a 250 (percent of total variance) 4 

w Number of analyses 1140 a: 

LL 

0 

cc M LO co c c c:i c:i 

N co cc co cc M N M LO co c:i c:i c:i c:i c:i c:i 

MAGNESIUM, IN PERCENT 

C'! ~ cc 

c-.i 

FIGURE 21.-Magnesium distribution in selected agricultural soils of Missouri. Map symbols correspond to frequency classes as shown in the histogram. 
H32 GEOCHEMICAL SURVEY OF MISSOURI 

,- # -+- r 1- - I 14" - - --r - '1 --,- r li ::::-- - r+- l I - T. "1; '\. 

} I ++ j!- - + + L' * - ' I * * '; + I ;# i I I + ' \ "1- •- if \- I ~ - + 1:* 1- -1' -/ I 

I ' L-:: :::i-:_ ' +_ ' + I + - .', * + :t=l - I;# I - + \ .. +I '· -t-r I + I..--------=· ' ;L' ++ - I "\ ">~+_,_;___ 1 + . - 'i I-* -I r-~+-+ L ___ ~~ + u 1 

>- u 

z 

w 

500 

:::J 250 

d 

w 

a: 

u... 

, - , + ~ + -I 1t + ! + 1-;--_:: ~ i * - - i+ :t - itt:t - - r- -~ - --:r:~ 

' r------i' ~+~-=f"""-~ tt-1::·+, *'' +I u. * ' ' +·,I + :t.------1.-+ +I* + +I- I .:J l:t I 'l:t -It ~ + *I "' I l + )_+- --' * I__L __ =t r-----=-~-----~# :I l:t .:t I\ 

... .!.!)-... \ 'I I I -:t '.:t ~- I J_ I --+--:v·------~ 

..,_--t 1·- - *I _ * ! + + I *- I ! + l':t- - * \ 

,...) :t - '------ .:t I I .:t ' I' l:t '- l:t tt I 

r--+----:---1 --* 1 tf l * - - I_ - - +I +u + "** ,. '* .fj I ' +* I - I -,--- =·-~1 l:t + ' ~--.r--~ ~ - ' + I '! #- I±_ ____ '!'• + _ U J ~-----~:j!, .:t '\. 

L_+ +I :t + :t , ~ :t >--+-----~- * I ~ , '\+---~-~. I,+ ,__, ____ :J:i +I ,, - + I ++ ttitt -- '- * ./' + ~---~--1 - I + -+t I ' - Ill / 1\ 

~~ I + + - * , *" + + . , ,_:._' L .:t un I # . + ~ .:t . ' 

I + + I I + ,.1 # ·.__ :t . ' - - ' ~- _2-_ -- _#I I I .:t l:t ' 

'l +• I ' + I "'\ I -1 I "-+- r- - '---I +I ' I +--I + + -+ I ' - ' ·* + ......_. ' - .:t l:t \ ... ' + r-_...·-,--(~ .+.,~ • ./---1'~ I '-)'+ _.,;::..::_~-+-, .:t + I ~---------

... ,...-J_ l'r-'~ 1 :i:' .:t • ~1 .U: u .:t +rtt-+,;,__u~_+ 

I I'+ :t I I # <. ' - t - ,j: + 1:* :t:t I 

+ -1:i I+ -+ ':t + ~,)\, -1:: +./ + I, ~-----~ :t=l__ + I 

I .+ --~ I- --* 1

( # ---~-" /

1 I *"#+ I '-.:t + +J I..._ 

l + + I 1----_1 ,-t"\ I --< l.::t+ # , * I + + I .:t ·.:t '-- t:t __ ~ 1\ ., +,--.!_'' -------' + + 1 I -** +I\ "** ' ~-J uil- -~ :~c·-

1 

I :d + # :t I' :t=+ # I + }# -f; ; I :t I *' . - ~ + / - + ( I + ' I + ' I ' ~,_ # I + :tt I- I I * ,_--+-- - .# ' ) - \ # - ~ + ~- ±-. ' . " .:t;; ' I -- -+-+ I I I ' :t * *I + I+ +I* -;:t: 4- '·: # y I I# *I '---..... I / + + ' I •* * # L~-·f"*----~ # ; + # I .t:L , ___ ..... # ' #.:t ' .:.._j~! :t:t \, 

----- *! + * f--~-'·+-1 ~,+ + r+ tt -d.* b .:d t:t u ~-s--,·~y I ~--· ~ -,-1 ~ ' # ±:f'l ' ' :t + * + + # I +- -** I * - + + # I ;.;f :tj .+;':4t- tt I -1t: + + i 

' + I + I # ,...- --- + I I .:t ' l:t *' I 

'+ -+ I :t I L I * .:t-L-------1 .. I r:t \ .. ' ' '' ' + ' .:t .... ·* ' # I i I r*"'--+-r'l, + ~ ((l__,-'-:, # I * +'+·--~---;---_:_-. I ' 

' # + ' , I - * 4: *+ # ~ -~+ # \1 :t ~ ~ l...-1 ... ..:t- / # I _ \ I 1 +• # •1-.. # .r , I - _-._,-. "** tt ; -*-- ii: -~ '*', *+,_...-~--'*I ~~---- .t_ ... I ' -+ I+ + :t + tt T/:t:--..L._+-_ '*' 1:* ' I **+ 1'-'*i # "> # '" I + I I I I + ' I .... I + 1,.. --1:: (:t I 17-- + p 1 + 1

, ___ , + r' 1=*-** *~'-*-4=--.--. * I t:t J,+t _f_ 1 tt I .._ ·-.. tt ;""'-' \ 

1

- I_ ~~-~---=-~+ ' + '-,.JI'"** + I '-r I+- # +' + - + '- + ' I I + ~-- ~--, I # # ~:t:t ~ #I + I 

l ~ l I l:t of- I :.._ I I +' '*' L ------:a i -.... ". + ~ \ ~~-- ''*' + * I # #l * I + ' I #- --1 # _____ £!_"_/ :t + + ----j ":! .it. ' ... ' + * -..., __; + ' --- lt) +t \------3-. ..,._-'-) tt ,___ * .... t .... -** * ~----- - 1 -r-- tt ' :t · 1 - --__ 1-+ ;·--i # I '*' +!* 1- - ! # ~:f' I +"***i * # ;t_ i - tt! -t: #' 

--~- '* ' * + 1 I ________ .Jj ___ , L-** ,- +-**' ':t:t "**· 1:t 11 ' 

- I_ -**I#-----~.- I* # ! * --;-------'-, ~ + :t I ## I -' + ~ -------· 1 ::d ; · u 1 L-** "** 1 "** · · :t 1 "** r ,+--+~--=----i* "**, "** I++"**! , 11 .--J~----I::t .+:~=_,...., I # ,+ ' + l "*** ' l # # l I # ' ..j: :t I _r- • 

+- i '*' I * uit # I ::p - I # . • # - it # I . E· I 

1 # ' '*' # ' - tt_ -+' :1: + I * I t:t F #u ">' -tt I t:t - ' r . -'tt ·, + I 'i\ ---*---+1 "** U: #4:#-*#-- -- 7 ___ 1-=: _____ c_'!' ____ , n ---lf;L-'*'-':-:i +t :=t~--+ \_ _ ><:, + + + * ' # ' ; :t *l * I l:t- +t ,r # \ I# f ' - I * I I tt -#~-** # I''*' :t I .:t ' '# ~ # 1- ,- 1-' :t __ I 

I # * "----#-- 1 tt ~ * I * # ' * # I + lt:t I # --.----** # # l + . - + J "** ~ + ~-+* *~--~- I + + "** I u ·-""f---·-=_-L_ -~~ ~- ~:t ~ ·~~~., r' t_ + J. I+ #: ' # - # •---- - -~ - - - _._ :t:t_i ,- '1'1: :t-, I # -- I ' -- - ) -1 - ---*-"""" # t±... # +' ;t -,- ' ' # ' ' ' \ 

- ' * ' I ""F * I # # I * I * - I • - -+ \ ·-I - I + '+it I 't-:t + +1"** :t 1 i # ~+ · · · I "** #<--------·- I r''v 

L ' i ' I# +-1= I -I ~ # + I# * # ' f : - i + -,.' 

L._ -*- ~ t_ - ~ -~ - _.1 - -*- - : _ __#:- - U - - _I :! --1:: _lL ~ - _I - "j _I 1ft - t - it 'rt, I 

0 50 100 

50 

SYMBOL AND PERCENTAGE OF TOTAL SAMPLES 

c 

Lt) 

16 

c 

,.. 

13 25 23 

I : + l :t 

c c c c c c N M Ln 

I I 

I I 

I I 

MANGANESE, IN PARTS PER MILLION 

23 

.u 

c c :5 :5 N M 

100 MILES 

~ + ~---;'.:...'J \1 ;tj + - ... 

200 KILOMETERS ,.~ ~--~ 

-· + + " I I I , J __ - I 

Geometric mean 740 

Geometric deviation 1.83 

Analytical error variance 

(percent of total variance) 19 

Number of analyses 1140 

FIGURE 22.-Manganese distribution in selected agricultural soils of Missouri. Map symbols coiTespond to frequency classes as shown in the histogram. 
>- u 

z 

w 

500 

a 250 

w 

a: 

u.. 

v 

ELEMENT DISTRIBUTIONS, AGRICULTURAL SOILS 

SYMBOL AND PERCENTAGE OF TOTAL SAMPLES 

19 17 30 21 13 

cc 

N 0 

co 0 

cc 

N 

MERCURY, IN PARTS PER BILLION 

0 

co 

(") 

0 

(") 

co 

Geometric mean 39 

Geometric deviation 1.80 

Analytical error variance 

(percent of total variance) 52 

Number of analyses 1140 

FIGURE 23.-Mercury distribution in selected agricultural 

soils of Missouri. Map symbols correspond to frequency 

classes as shown in the histogram. 

H33 
H34 GEOCHEMICAL SURVEY OF MISSOURI 

.----,.._ __ \ :

1 -. -- r--- -r-- --..--·---- r- l-- T- "\.. 

\ l, ~ ~ ! +3 i 1 I ' 

I i L ' I I ' I I \ ~---!__. ' -----~ r ~------r _ _:')----i i , 

' ~ ' ! 7 ~-----i I ~-----r------1 J t ------ I- + I I ' : ' -----~ '1 1' I 3 I 

' 1 r-----~ i r-----'-------~+ .. J "I i ! ,------~ ! -r- 1;------\ ~---i 31 ! I I ! 1 ,...) ._ __ ±_,._ _____ ] ' i I ' I 

, I , , l_ 1 ____ .__ , I ~ \-------! l !------~ L_ ____ L! _____ :_-;----- " 

' 1------~ ------i l, ! ! i //''' 

, i i .~. I I ' I ' 

\ 

' ' ,.1 '- -....L3 ;_ ______ ~~--~. ' I I ,--.._ r -,_ I •-....__ : ' 

~ "./_,_( " __ ._,---._1 ._. ~> ~~- -~---, ~ ,-------\ ,--J 'r' :,.-' 0 <' I I r---~-;-

1 i ' /\ / f-------; I I 

I ' I ( ·-----<.,_, I I ~ I 1 f-----.r---r------• ' I I ~ ' ~-r\ I -.._' 

---- ' \ I I\ j ---1-- "" •'-, ' I ---; i / I ' ~- ' /~ ~( i ,_ _____ : ,r)_ ~ _--+-----~-'-. ' __ I / 

L~----- ' ! I, I "'\.. __ // ' I '------.L-~·! "'' I ---~ __ _,--.~ " I I I 

r-------; i i \-~-] s--· i ,~-r---;-; 1 I I 1 j -- t t ! 3 ! J,, ! -1----------i J I r+ ---r"l. ~ (.l. __ , ....... , I , ·--'---.-~---__: 

f-------.----/ ~-----1 \ · ~---j-: , "·~L--<)' , ___ , r! -·----.--. ~~--...L __ T : )' ~, 

L--,-~----; "-Ji I I i ·,,, // \ 

' 1 \ ~ :----~--L__~-------~ '."/ 

,-------~-------~ i · -;_ __ j_ _ _;_ r_j __ ----, '--~----\-----.~------{ 

I I 1------~_i ___ ! __ j ______ l :_~----·--=- i ! l \ .-------~------1. i i i I L I j------! i ~ 1 • • 1 , ,-- I · _.... .. 

l ________ f ~-------L-,_ ___ 1 . +15 ! -~-~...L3 (

1 

[_. :-~-(" \ r 

I ; r----~lo+3 ~· ----;-----: ! , --,__ ; ·~ /~'- , ~------, -tt I 1 1 ~ s · r· I ' I ' --------, { - I I · ~ t...._ I I ,-------L ±3. \ .~ ~. t---------i ! i ----·--,-------+5 ~ -;-~-----; \+3 ! \.. ) I ' I ' ! ! I ! l' ·, I ' I 

1 3 ! ' ! 1 1 +3 \ I I /---.----· r\..J 

L + I I ---1 I ' ' ' ' • ! '• -------~- ----·----~---'---...L---..1--f,. l 'rt.' 

L.. ~---;'--\j 

,.'i 

f I 

0 50 100 200 KILOMETERS 

, I 50 100 MILES , __ ,;__., 

FIGURE 24.-Molybdenum concentrations, in parts per million, in selected agricultural soils of Missouri. Only samples with concentrations 

above the lower limit of determination are shown. Location of sampling site is indicated by plus ( + ). 
ELEMENT DISTRIBUTIONS, AGRICULTURAL SOILS H35 

I- ~ -+- r +- - -, - - -=rr - - ~ - + ~ + + ,-- - r+- l + - T -+ '\.. 

\ I + -t I + I t I : + 1; + \ + ,! I + I+ I I + +' I'+ I ;+ I + ' 

I ' L+ _± -+ ' +, ' I I I + + '', +1 + +I + ~++ I + \ • I I + I' - - +t I + I r- ----'1=, ' + ' ++ +I I ""'> "1..±+ __ +_:__ - 1 + . ' q_ I, + , 1 r-;-:r--r-1 ____ ...; ' ' 1 v++ + ~ + +!+ t+ L

1 

++ 1-::.--+-;-; , ++ i+ + + ~+ + 'r-----1/ I + f--- +- 'l + ' ++- -~ ~ + +' + I I I ' + + I + ~ + I 

'\ + '+ I ..;,_ ______ J,I+ +; + 1 +I I _J 1 +, 1 + , + +I "'" 1 + ~++ +' + I + + r----~·--1-----1+ +I I I 1_\ '"V~ ++ 1 I+ I I I ,-+----~ I I L + 1-.--,---tC-~ ~ 

...__ __ +i++ Ill I!+ +I+,' I I!, ++'I''+, 

,.....) + + -+I_ -1+++--1 + +' I I I I I ' I + + I 

I + l + I, 'I I I + + + + r I+ I + ' 1 + 1 I 1 -I--- 1 '-t] I :'\. l + '+ I +I +' 1+ 1 + + + _J_ -------~;- -J----_;'- ~ -'- +I +-t- I' + + :-----, +I + 1

+ -------- + I I+ ~----=--+-, I+ --+- _:lj + -+ + + I I+ +f + + ' I + ' ~ + + ~--- ~- -1 I ~ + '(- I ' ' I !+ ,I 

+ + + I + ' + + ~+ I, + '+ I + + + I I ~/ -r + ' 

' I + + I I + J I ''- - + _,.;_ + + ~ ----- - .I; I I + ' "t +'+ ' I ' ,· I I ~ I + ,_ +I' "-+ I +++I + + ~ + •'- · + i ------ · + + + .., ' + 0_/·-+-( II ...., J-. ./~-1 +~ I '-)+ 1 ;:;~ +-~ I + - \ -.....--J+ +',-' '/ 1 ~ + 1+/ I + 1 +L + 1

+ 

I -t-+,4-+ ++''I + < +' I '+ ,-r- !--:!++ + + +; I I ,t+_- ' I I 

+ +I+ I + I'+ + I +" +_ + + + I L_ I ' + ( - ~ ( f+ +. + ' + I ....____ 

1 + + 1 f----.J---+-f'_-=F ____ 1 +1+ + '-, + '+j I+-;+ + __ : r\ 1 , 1-, 

--- _ _ _ , + + I + I + +t\ + I, ~ _j + +I + + "" _,j,.· "; --' 

I + ~ I + + i ++ + i + + i+ f I I + + I' I I' + / -r +( + + I ' + '--+-- _ __,'+ ,')_ ( + -~++._1__..--0--'. '++! --':..+ - I + + , + + I I + 11+ 'I+ 't- I '--,· +-v+ i+ li ··~------' .: +++I I 

+ j L r--~-- I + I + j + ,'+- '' + ' + + ' . ~ + + ,( 

~ - +- - + I + + - r I r -, 1 "''I I ;+ + + +l, I 4- +i + + . f 5' -+' '71-' J 

I + ___ , t I+ + '-(,_J....:'* + +),''"+ ' + I + "fy + +! + + + : + + + + , I j+ I I +,~+ -lr + + 

1-t- I I I + I I I_'+ i + -- ~L-- ~ - --j I + I I 

t +r:::---t.;-•~ + ~il. _;_ I++ l++: ++ +~+~~_;-+ __ ;;+ \+ + -t-'~ -+--~- .. --./ + + f---+--~ + \_ I + I +i + ·~r,+ ~ -~ +' ... + + , I I '+ + I I i----lrr--,-:!'__;_+_i__,.._.f--l +, 1 t +++ 1L-t + '> ++ ~ 

++ I + + ! ~ I + ! ,+ ,· + +I + I 1: I ~ + I + :t ~I ...... ' 1 

1

"--- • r + +:-- - _r_ ,- - - , 1 1

• + + , ' ! , "' 

I

++ '+' Lr-,-t± ___ __!_~+ + ' ',,_JI'++'' * I I'+ _._ '-"' +-' + \ I ' ,+ ++ I -- -- -~ -- ' ' + I + 1-' I + I ; + 

++ 1 + ) J I '-- I + ~ : + L- _:- 1- --+ + :t-- ~;' + 't I 't \ 

f'!"-----~~ I+,;+++,+ I+++- I , I ~----+ ~ . .J--) I I + "--+----:t: ++ /I ,; + + ---~-_j-1/ ~-r-- -,-, 1 + ~ · · --f',_'\ 

I I I I I + I + + + + I + + -t-1 + + +, i -r ~ + I ' 

I I I I I ' I + ~ + I I ,-- - I_- ' - - _j - l I I + ' ' I + I I + _______ !I + +r+-----jL,, ' I' ++ + :_ ~' ++ . : t- . I I . + . +i +t- ~ I + I + + ~-+--- t + + I, +I ~ I I + + I l + I,- J i--- I+ I , + ~ ., I ++ + 'I - ' + 1 '+ I + 1 I + I ' I I I -"- ' 

I ! I + ! + -h '+ ++ I + I I ' ; t + + -.,' + +I .: I I ' -"1 -t +I ~ ---+~--TJ ++ 1 Jt:--+---'~--+--:r-_____ 1

1

1 , 1 I ! + ,_ '"'T + l ( + + I +' +-t- ~ --------,--~--ll ' + ~-- -11: __ "'?_ + + ,.~-,_+ '1 111 1 ~,' 

I ·t- + +t~-'--~--,4-+-+lf;-t++ !' \ II I i ~ + i I ~~ I+ I\-:/- - --{ + + -~I_'. ,_;.~J II;--~ I + , + +"t!,++++~--~-- ~---' ' I + ,.--r-- 'L.,. T--'-~, ' ' t--,L---t---t".Jt- I+ ' ++I-++ I• ----t---+-t J i ~+ +! I -,1\1 I) 

+ ' + I + + I I I I I I! +. ++ \ II I I + '+ +' 

:-~--~- + + ~-~- + + . , , ~~ i , + I I \ + I + I :- -- -,-. - - -, '"-._) 

I + +' I I 1 , 1 I I;+ I • II I +'' L - - -I_ - ___.J -~- _j_ - - - - :_ - +- - w _I - - _:t_ ~ - -' - ...! _rl't- I' ' -t-'r-t' 

SYMBOL AND PERCENTAGE 

OF TOTAL SAMPLES 

35 65 < 1 

1+1 ~ 

750 I I 

>-

~ 500 w 

::J 

d 

w 

0:: 

u. 

250 

0000 

,.....,......~~ 

v 

NEODYMIUM, IN PARTS 

PER MILLION 

50 100 

50 100 MILES 

L.,l ~ ___ ;','..) 

\1 1

. + I, 

I" I, I I .... 

f: i I +' " I I " 

200 KILOMETERS 

'--~ _;_ _, 

Geometric mean 63 

Geometric deviation 1 .1 7 

Analytical error variance 

(percent of total variance) 

not determined 

Number of analyses 1140 

FIGURE 25.-Neodymium distribution in selected agricultural soils of Missouri. Map symbols correspond to frequency classes as shown in the histogram. 
H36 GEOCHEMICAL SURVEY OF MISSOURI 

,-,~ "lt- :=-#""; I ~-- -r-- ~ ---.-~ ~ ~- r+- l+- T -+'\. ;p # # t # + + , I - '*' , + +'*' + + r+- + #=*= lf ·~#+=il \* + .. + * + /* -+1 +b- +' 

: # i * J..-:-3'--tt '*'+ · ++ + L-----;, * .;'l + 't:t +! ++* + _-t< + +', 

~-*--:_, I \+ i"' +t !~-~-~] f-;-~-:_.,~~----J -~+--~ +** + + 1.;. # #!* + . * 1 * + +I + # + r ~++ + + r I * r---:;.--i + ~-!-_2:_-v--~ + .:t• + + + ..- '+ - i +, + I 

' #'')+- # ~-----J.I+ +I .:t + .:tl + * ++ '+ + ~ + + \ .. # I# +# #*' * I + +~----T~--1----~+ :I + + +\ .. ~.~ *I ++ I_+ ____ I I + ... + ---,-"'1---r-·-----;.;.----~ 

~--~i+ + +I - * ! + # I + # * I + ! I + -+j + # \ 

> u 

z 

w 

\ # + '-------1 * I - ' I I '- + + I ,....J +--4----1 ++ .:t #+ l + + + I+ I +I +'*'- + ,. ~ -+l + +' +# I I I +,-----.·-+ '+- + ' ~--+--~ ~ # '* + ! ++ 1_:1:_ _____ ' I ] + + :i ~-----~, +" \..:.__~ # 1 + + + + :t:{ * ~----r· I I I# . _ '41'----±-#..- 1 I* 1_--<1<---!'li * + '*' .4* + + I - + + + + ' # + / ' 

T# * I---- __:f-_ -1 + ~ -ll, I + ' - I+ / +' 

, + -f, * I + ' I I+ ~# I+ I + I * + ' + -+< ' I * * I # / #' '*' ' ' I +I I I I + ' 

~ #o+ o #I ' '---, '""1¢ + - r--------,___ ~' I ++#I # + =If + ·'- : ·*+ -..____ , - + , + '*' ..,. , :t: "-"'*-(_~ "'~·_.,--._1~ I '-)'# *;:-f.~-,--1 - + \ -------\ 

"',..--J+ +'!it'~ :t: :;. * ' :#t/ +: I + + +-+±__+~JI I * *, * + + # I # '*') + + / - I t-------: * i+ t - ,' + # b + # i + + - ':t: ". #• + f

1 I ::1:" I I 1 L1 ' ---- - --* ( +~-----'- I -4- 1 I ·~- + +.} I 4L_ 

l + + + f-- - - __J I ..,.. ---t - -' + * ' - + + I I . + ' '*'- -~ ~\ * ~ ' ---~ ___ • # * \ + I * +'!'\ * I, · ~ _ J ~ -+1 + + " . u' + ~' 

I + ill '*' * + ' + I ' + +# -n- I I I #I + I' + ( I # ( # · I * 1 + I 4: + + · 1it + I + +' - * I I + '----"'---- ¢: 1)_ ~ + /~+-_!__.-~+...._ +I ' -+ .---L+# I 

I I I ' # + +I + l+ + l* --+-+ 4-, '"\ + 1>"-+ ; I +I '-------I / + + I I 

+ # # L~--~----~ + , # * . __ _,.. # . ++, .:__i:~l '*' \, 

~---- #! + I ~-,.r·:;-J '\- I f::~o + +{ + h- +I+ * ~-5'-.,.-,.._y 1 ~--< I' 'l:: · + +_J.'I • , + + + ~ 

+ # I * + * I + * + I I + + ' -~ 4t I Jt-+ # I -it- -+ + ; ' - I + I + ' __j I_ - - ' I I I - ' + : I 

I+ _ -+ ! - ! !-. ! : +!---.;----1 + I+ -f +' I # +rit---+-r1, + ~ {.1. __ ,-'-, + I -+ +'' ,--~--------, - " 

I , # + ' I' - - '": + -+ -+ + ~- 1'*' I ti I - \+ ~ 

-=-~-v--1 '*' +# 1----+-) +, \ + +! -- ,_,-2--f :i + 1 'l'l:t:~----:"- £, ~ i :t: I ~- -- 'i I _+ +-~----'----r,· ::1:" --' --t- ~ +::t:-1 ll.l- *+.:'> .:t ::1:"~ 

500 

-·---, +r'##+±___, _ _r_., ____ l ~+ :-~ 1 I- !+,/ *+1._, 

I I I L_ ,. :±- -- L ~ I ' i \.- J I'+~ I ,I I ' I I - 'f-. * + ' + '*' \ - + ' - ' - I - I' ~------ 1 I + # +::t- f' #I + '*' ~* + +* 1 _+ \ - -;:-I ~ +t I - * L __ :-+----~-.:t. -~-A/+ *+ ~, 

·+-:---=-~- -~- # t+ I~ - ' -/:: ';_-----~-- - # __ j_----r-~ ';-~--;-'r\-_;---_.J--+-,_{ I -- - I+ T + --i * I - -,+ 1- ! + ~ I -\i + # +: i +l * -+' 

J 

---- '- 1 11 _________ ____]_ ___ , [+ ~--+ '*'' '# + ,_ + ' 

- I +I'+---- -+U I - + I + ------- __.___ I + I + i -+ I * 

---=--=----.- * ' ,-- ' +' ' '*' _-#+, + ' +' * ~ - - l,:--=----t 1 -+ ~ ,+- 1 ,_- ! + '*' 1 + L * l,_.r: ____ i=--:_ ! + +_J"' ... 

I ++ I I' I' * 1 'I l + l ' + I + -+ ' + I .:t.r'- ' 

J 

+ I ,... I ~ + I # - '*' I ' i-' + ~ - ' +: , - l - ·- - I - - I +-# + -,I + I + , -----1<- r "-+ -, I .., -----=-=----:! 1 ~ r- 1--; 7

+--·--.._ ___ 1-=-----"-::-r-----i *1 1--"f':it __ ,...l.. + .... -~ 1. '-tt- + ><:, - l ---=- I ~ -+-,1 I - + ~ _:__ ' ::!: ,- ' ·+ ~ *-+ / '*' I,+ t-.f #~ t:r1 + " ----l---,+ 1/,* I _I I ! + I II - +-------- + + !+-t:-+ **/ ,_+ t - ~++_I I I + - I I ,----,-----=:__-[_ + - ~I "'*, ,~ 1",, 

t_ -, -- I l----=----·------+-----1. l --.-~-"T--+-, -~I #I I ~. + =-- ---~<----1 I ' # -- £ -· + _- ' + - ' I ' ' ' + : I I ' ' I I I + I I ' -- I I ' # # I 

:~- + -~ ! i ' ;= -+ i 1 + 1 + ' I j- I 7-j-.----"* r''v ;-- -- # t' I ' - ' ' - ' I - i- I '+ - _, . - ! + + # \..: I 

.._ - - - - - __ + -~ - --l. - - - - ·- -**- - .J.....L. - - _I - - - ..J. - - - _~ -' ,._ r ** , "" 

L. + ~---;'n"J \1 :j #I '*'' 

0 50 100 200 KILOMETERS ~"+ '

1 '*' !it." f ++! + #., 

SYMBOL AND PERCENTAGE 

OF TOTAL SAMPLES 

17 12 I 45 1 15 11 I I +I -+ # 

, I + , 50 100 MILES ,_+_ .;,. 1 

Geometric mean 14 

Geometric deviation 1.59 

Analytical error variance 

5 250 

(percent of total variance) 22 

Number of analyses 1140 

w 

a: 

u. 

v c c Ln .... 

NICKEL IN PARTS PER MILLION 

FIGURE 26.-Nickel distribution in selected agricultural 

soils of Missouri. Map symbols correspond to frequency 

classes as shown in the histogram. 
ELEMENT DISTRIBUTIONS, AGRICULTURAL SOILS H37 

,- ~, -,- r- r - -,,- - "'t'r ------, -, -.-·-f'" T r:- - r+- l 1- T -, '\. 

} 'I 1 I l I I + ' I 1 1 1 • I 1+ 1 I 1+ 1 

\ I I 1 ' ,, + I I~ \ I I ' I I I I I' I I I ' 

: I i ~~--±--H +, ' ,' I L-----~ + ';->+ i '! +I I,,,+ I 1', 1....2t_l_:.__ ! ~ 'I 1\ ! I + tl r-,--,-,._Ll_~_-'j I I ~ ) I I I I I I ,-----· + I ' 1- , I I I ~ !+ I , +I ' I I I I I I I i I ! I I I I I r- ~ -- , , r---,--i 1 ~+---v-- 1 1 '· 1 , , , 1 , 1 • 

'"""\ 1·')1 I "*-- ---lt+ I '+ I +I I ! tl I I '+ I ~ I I I ... ' I I, il I' + I I + .-----, .. --1-----1+ +I + I I\ .. .J._l '11 II 'i I I ! I I ,-,----~ I I !, I ~~-~--*-·~------"\ ..,_ __ !· 1 1 1 1 1 , 1 1 1 1 , 1 + 1

1

' ' 1 \ . \ I 1 I..._- I ' I I I I 'I I I .-.J ,__ _ ___.._!.__, + !+--] +' I 1 1 I I 1 1 I +' ++-+;I 

,. II I!+ I' ,, I I ,, l,,----;-·.!....tl ,, I ! '--~--~ ~ I I I ! ,, I_!_ _____ ' * I I I ~-------1-, +"' 

Ll .± , 1 , , , , ,, , 1-::f:----r· + I +I • '\+"-- ..... , I I '--t-----'1' + +I (.' I + I I I + I + ' I I / ' ~ + + ~ ___ __~ _ -1 1 1 ~. I , , ' 1

+ / ,, + h+ I I' I I I ~- I I ·I I I '+ + I ' , ! I I I I I ,./'1·~ I . ·' * I ' ~ _ _.! ___ __jl I I + I ·.\!_ I I I ' I I I ' I .. , { ---4-- I I I l---I 11' \. 1 I I I 1 I I ! I ' - . I , I ...__ , I 1 I 

' ... ' <' .. /T-(. I ~ J~ • ./---1 I'- '--)' + ,-:,~-r-, I I ,-------\ "' ...... -_; 1 I 'r-' Y 1 -to I , II/ I + I 1 +--+1... + 1+ 

I 1 1 '+ + 1 + 1 + < + , 1 :r r j"lf+ , 1 , 

4. ' + + +) + I I .L-,-----' I + I I I I 1

• I I I "+"- I• 1 f't I I 1 t_ I ' + ( ·--~ <... I I. I + \ .......... 

l ' ' ' 1---.. ..J---rt--"""t----< I++ + .. , + , ' ' I '1j I,'~' -t-_) .. ,~ ' +~ ... 

-------' I I \ + I + J!\ +I ' __ J +"+I I * .., ,J) T~' 

I , :f.! , + + 

1

• , + + , , ;'+ -~ 1

· + , 1 , , • , , , 1 r ' , ( I I ' I I I ' ,, * I + I' .. I I I ,__-+- •I ) <: ' ---1- . .!_..-.J...,:-', I I ' I .--{ I I 

1 ' 1 • + ' ' 1 + -tr+ 1 ,, .. ....J, / - '·· + v .. , +i 1 1 '

1 

,__ 1 / ' , ' , , 

I+ I I l~~-t-~----'1 I ; '+ + + .'{" \.._../ + , I I ' ""'.:......, ..... ! + \._, 

----- , I 1 ~-,.r·1·.; 't::, 1 , It 1 11. 1 11 +I 1 ' ~-r.......-""/ 

I + ~--• j 'l .L: I I f.'1 ' , * I 1 T I I I + I I I I + ! I.+ + ~ I 1] I , Jl + I I ~ + + j ' I I I I ,J' I I I + ' I ' I II '+ I I I 1.. I I --+t.. _______ j + I ,,, \ 

I I ' ' I' ' I ' + I .+ ' I + I ~~---+-r'l, I ~ ~,"2.__,......_, I I +'I,--~---~---·-, ' 

' I I , i' I I ..._ I .+ I I +I ~ -~+ I 4-it I \_I ~ 

f

-.J.. . ...l I I I ~- J ~ I \. I I I I' I -~ I /" ' I·-,,.-. I + , - -:,.. I ·...1 . +' ++ ""'+ ___ ..,., tl I 1' 1 1:'..-< f ' ' + 1 1 I r~~- ...L. ·.r;-.. I , + 1-r + "> I ..,.,_ 

I ++ I I ! \ I+ I + ,·I I I+ '', •I + I I ~- I ,.., 

1 , ___ , ' r 1 +-'-1...Y.,.... --. * '+ :: 1 , I 1 ' • 1 

1""t ' 

I 

1 I I I I Lt- 1 -;± ___ :!:_~+ • 1 '\_ .. ../I'+ 1 1 11 I '* I + ), I +, 1 \ + + · ' , 1 * 1 ' • ~---~--, 1 1 1 · ++ r + 1 1 1 • l ++ 1 . I I I -!r ' ) + I + ' I L :---.. - .. T. ~ '' " ' I ,.. .. 'I I 1 + +) I '--, , I + + -- I + 1 • / 1 I I \ .---------r I' I ' I + I ..., I ' + I "t-----"'F"""- + I I , .. ____ II tl t + ' 11 I , _____ _.J_ I + --~----r-, I + ~-----,-·-+""\...~ 

I * I II T .. , + I +I+ I* I I I I I ' I ' I +I I 

J 

1+11 'I+ ! I Jl ----'--.--..1 .. __ , +,I I ·r--;1 I I' 1! 1 1 +J+I 'I , 1 \ 

+ I, 'r*-----+u' I+ + I * l _______ ~ I+ I I ~· + ~~ +. ----- 1 ' I * , ' • + . ++ I • + ~ 

, + ' ' i-L. _ t ~ + -r- -+1 +1 1

• ' 1 + ' 1 L ' 1 1

·------· , ' 1 , r + '-F ----~ 1 + +t 1 + 1 + > + T-· + ~ * 0 + ...r' .. 

I +I i .j. i + + ~ * i ~ I I 1. + I * + I i I ! +:"'-+ ' 

J + , + *, ' +,' ~ 'I + I + I I i I ,' I I -,' + ~- I I : r . "'t -.~ I \. + IJ + r-*--:t-+·-~- I I I I ·--1'"-l _,, I { '\ r --- +--~ * -r- ' + + -lt'---------C....., _____ _, I I I __ ..., I ,;-·-r I • II+ I )~\ 

• * ! + )f.: -+"11* 1 I' 1 • t + , , 1 ~ + + - I 1 1:-J 1 ~- 1 * +t, ___ ,;a: __ , I ~+ t , ' -tf + I ' * I I I' ' --------[ + + 't I ·I I I/ 

I+ ' + +-:'71 I*' + I I I i + ,--,--·-·[_ *+ I ~+ -1', ,~Ji;, t- ±... + '-!* + L..--r--+·------1------h 'J 1 ·,.-·~-,--+.., · 'I 1 >~ 1 , 

T --~--+ ' I I +, II I i + ,+ i i + I i I ~ *I 1...,1 i I \., + I 

~ I + ~I ~ I I' + I I ' ' I' I , 1~-~-~--~·-·t ,~.+,I ~ ' ' ' I I I I I I + + I+ * I I t I ( I i , ~ L. * I t + I I I I ' ' ' * * + ' I I' r' I ' I+ I ~I - - - - - - -'- ___. - - - - ·- _1 - - ~ - - _I - - - ..J. - - - ..J - 1'1 ~ I '\.. 

~I ~---J'f\J \1 1

. I I , 

0 50 100 200 KILOMffiRS ,.., !t 1 \.. .... r I I! I ''-

SYMBOL AND PERCENTAGE 

OF TOTAL SAMPLES 

671 291 4 

I+ I+ 

I 765 

I 

500 I 

I 

I 

I 

I >- u 

z I w 

:::> 

@250 

a: 

u. 

0 

v 

NIOBIUM, IN PARTS 

PER MILLION 

50 100 MILES , I ! I I ; I ___ ... I 

Geometric mean 7 

Geometric deviation 1 .38 

Analytical error variance 

(percent of total variance) 1 0 

Number of analyses 1140 

FIGURE 27.-Niobium distribution in selected agricultural 

soils of Missouri. Map symbols correspond to frequency 

classes as shown in the histogram. 

• 
• 

H38 GEOCHEMICAL SURVEY OF MISSOURI 

.-~"'+--r,--

, ~ ·~ ;t: -~-ll - +- ~ - ~ : - ~ I+ -r: ~ -, ~I;-, l,+ ~ 1- :+ '\.. \ * ~ ~ ~ ' '+- I -+ #! \ I * + +J: ;t: I I il I + ' 

: ;t: i + -+~ _ _±_1-i +J:_ I ;t: \ ~-----'=t- + ',++I +! I +I ~I I + +\' 

>- u 

z 

w 

\.._-=..._'*:_;__ I ::1: , ' *~' I, + I r'-~'~=-----:t"+_1 + -~ + + ) -+- l__::t:: I I I + + ---- __, I -r::t::+J: ::1: ~ -~- ::t::!+ ::t:: I .:?+ r-;--+-;i ::1: I ;t: ~ + + h:' - I r--1---+j 

' + ! 1- -~ - ~ - -w -~ + ' . + + + , ' I ' , -

' ::1: ~+J: + t.-----l.:i::t: ;t: I + + +J: I I +J: __j - 1

1 ' I ~ !' + :1: I 

500 

... •::1: il-11 +' + 1_-~---t~;----T~--1----~+ :1 I .:t +\ .. ~~ ', ': '+I I I 1+ I I 1/ + +-r=-.--'F·~-----~ 

..,__ __ -ti+ I ,I I + ! I ++ I + !, '+ 'i' :t: + \ 

,...J ;t: =F-1 ---+--:_--j~,-,i--1 + :+ l :t: :1: ;t: +, i, 'I I I 'I I+ I ~ 'lj I 

,. =l;j- I I ' I 1 + + --,---I"-- 'I + ~ .J. + ' +J: *I 1 1 

~ I* I' + I - + ,I ~---- .:__;-·---1---, ' I I + ' ::t: I ,------, :t: \;t---A . .:t:- 1 "t** 1 I =f:1 1 + :t: :t: l>::z:-~1-;r; I ! ~ + ,/ '- ~::1: ::1: J__ _ _:t_~-~-~+----1, + ;t: If_ I I I - 1 1 / _; 

, + i I * ::t::' i ':t: ,(._* ~ I :t: I + 'I -+< :t: + ' 

~ :t:l::t::* :t: I _.,_I i ..1 *''- ;t: ·---!. - ;t: ~~ _ __:o ___ __F! I I :t:1, I ::t:: ++7 i ;t: I +-~ ;t: I'- : - 1 ,::t;: :1: -........ ' I ;t: ---I I I 

.., . f'./':i-(::t;: l*\-'Y-·-/~ . ...1+'- '-;-'* -i'"'i~ ~-~ I I \ -- ----\ 

"'/-JJ:j: ::1:' ''./ + ~l ::1: +l I I I I + 1-

1 

::1: ;t:!; ::1: + i I < I I I I 1'1!---l-'--~-

- - i :f= + + ' I I ~)" ~ +J:/ I - ,t +----- - i ~ I' ~ I 

I ;::t: + I + I ( ~ T-~-z.._ J- I + + L_ I ........__ 1 :t: ::t;: I 1---- _j---~- ~--- - < ;f: ;f: ' / - I ~ I '~ ll f r.\ I :t: ~ ' 

------' - + \ + I I I :f= +1\ +' ' ·~_j, £----=~-+ I "'.J<'. 1-' 

I I il I+ ;t: '+I I ~ ;'~ ·r; -I+ I, +1. I +'- :t: / 1

/+J:-( + + ' I + I + : I 1+::+- I I lj - 1 I 1 ,... __ ,__ _ _,,, , ) , + -~r-, ... !._..---'--f " + 1 , , .--++, I I L;t: I +I :f= il 'I' I'-,, l.p'+ ·,+I, __ I /+l=+ I I 

I

I I ~--~----:t- I ' I '1- \., / + I I '-~-~I I \..._ + I + ::1: I j -'- 1 - - 1 1 -+- I ':;- I · I t;. r--,.r--;- ' 1 1- I 1.-+- k. 1l + 1 .;-"""'#"--:1:/ 

1

-- ,- ~--< I' + ' + 1 ('I I r 1 ~ * I I + :t: I I - I I ~I ~-:;?-'H + 1

), I I I II I /

1 

:t:, ( I + I* fr I ·- I :t: ,, 

I 

I I I I_ i + ---L_ ______ -1 i I I i' I 

' ' I' ' +J: I' + I + .+ ' - ,, + ttr:---f 1 r"', ~ <,t. __ ,-'-:... * 1 + ~ 

+, 

I I ::1:-- • J:j: "'++- ~~-~~~ ---ti;--=--,\+ '\. "*--~--v-./ + ;t: 1---l--~ \ \. 1 ! -1 ,..,.,-_.!.-~ ~~ 1 ·~I~< .1', *~ + ' 1 1 i 1 1 +• 1=1= Jt if-= w-;t--'----- :t: 1 1 I + 1 lt.-· 1 "> ':t: .,..._ '* I I ' :;. I I ' * I I :f= * I, I X ¢ I + y' + i-, r---, + r I 1,-1

-,_g--,--, + I ~·~ I X I ' ' + ""'' I I I '--=1:: 'I - I ' _/ 1 +J: :t:- I I I I :f= ~ / + \ 

1

-, + ~ :f= I I;-'-'-----. -;L I I - '- I#-+ I, ~--- ~- -, I I : ' ""1: " + + +; I :;: 

:1 :t: * 1 II 1 * ~ -I li +'I L __ :-~---·ri --~----/ !, :t-\ 

r+-------j + +I ' '~ I ..., , + I .._ --· :t: + I I +J: r-T----~ -- I - t ~--·--___j-- ,. _ _..: __ ~- 1 --~-;--/ ~--;----,~-----/>'-? I ::1: l:t: '+ I + II, 1- I I I :t:. ' ' I 

I I I I I ' I :f= ! I :f= I --- -I_- • - - _±- - -' I ' * . ,--, : +:1 I - I ! I - + -- i ! i 'I I I + ;fc '\ 

_______ !, , +r+----~L! 1 + I+ ~ ! I l_+ ______ ~' ~:._+ 1 + 1 1 -, :f= ~ 

I I :f= :f= I ~-=-l ____ =i_ ~ ~ +' i :f=;t: + ! i * L :f= + I l, __ j-,---·;='- -I -r + ...r' .. 

I

I I :f= I i +- i + + }_ I_ I I I~ ;t: 1' I _I I :f= + I ::;: I I +<:;: ' +J: , .... ' ~ I 'I I I I 4,. I .,_,I ::: I - : ~. +r 1:t ·.i: - ~ ---+-._-j -+-1 I +-*--~--1_ _ _ _I I , , - , ( "'") <: I ::1: l· :f= I ' I ::1: ;t --------,-+--il -t; ~--#jl __ ~·, ::;: ;~-~+ ':t:i::;: + ) \ 

1 t - Ji -*,+ I 11 I ' 1 1 •+ ~ ::;: + 1.+ uJ ::;:~ :po-" 

I I I Tr----+--, I Ill+ I I I :tJ ,I I I I :f= I+ ' ---- I '+ -'!;. -+- I '/

_...._ __ , I-+- ' ,- --"}_ ', .J:r +J: 

J-:f= I :f= I _ ... -+- I I 1=1= I + I - --=..--. - -+- , " - . " -+- + I I l..-----+c - L - ' :f= \ I :;: ·~ -,----~-*q. I I :t:' ,-,-.----+-----( -;-~+,---t; \+ +, .::;: +J: / 

I - ' I I I I I :f= J I I I I I - I! +. : I \ ++ + I :t:+J: \~#::;:I ,,- +f i + IIi i I \ + I I I + t-=*=-.-----:r:, (..._) 

L - - ___ I t I ____ -_ ' -;t: I I ' I - :f= .- ::;: :t:' ' +I +++~I 1 _ ___l ____ . __ :t: __ ;::,._j. ___ I ___ ..J. ___ ..J _r., r ::;:•1, 

L..:t: ~----:':;:\.) 

50 

SYMBOL AND PERCENTAGE OF TOTAL SAMPLES 

11 35 I 18 30 6 

I +1: 

I 

I 

100 

50 

~. +J: * ... ,.::;: '\ +J::;: ~o..--

f +:f=! + +J:'"" 

" I 1=1= , , __ #_ ~ __ , 

200 KILOMETERS 

100 MILES 

5 250 

Geometric mean 0.059 

Geometric deviation 1.61 

Analytical error variance 

(percent of total variance) 30 

Number of analyses 1140 w 

a: 

u.. 

In 

c; 

0 

v 

In 

c; 

0 

N M In ..... In 0 0 0 0 N 

c::) 0 0 c::) c::) c::) 0 

PHOSPHORUS, IN PERCENT 

M In 

c::) c:i ..... 

0 

FIGURE 28.-Phosphorus distribution in selected agricultural soils of Missouri. Map symbols correspond to frequency classes as shown in the histogram. 
ELEMENT DISTRIBUTIONS, AGRICULTURAL SOILS H39 

0 50 

SYMBOL AND PERCENTAGE OF TOTAL SAMPLES 

>- u 

z 

w 

500 

5250 

w 

a: 

u. 

11 26 30 24 9 

1 I+ I ~ ;t 

I : 

I I I I 

0 C') 

LnCION LnCION LnCIONLnCIO 

oo_:_:...:NNNMMM 

POTASSIUM. IN PERCENT 

100 

50 100 MILES 

200 KILOMETERS 

" ~ '---

Arithmetic mean 1.43 

Standard deviation 0.40 

Analytical error variance 

(percent of total variance) 3 

Number of analyses 1140 

FIGURE 29.-Potassium distribution in selected agricultural 

soils of Missouri. Map symbols correspond to frequency 

classes as shown in the histogram. 
H40 GEOCHEMICAL SURVEY OF MISSOURI 

0 

0 

SYMBOL AND PERCENTAGE 

OF TOTAL SAMPLES 

750 4 5 1621221 7 - I 1+1.:;: -1i 

>- 500 u 

z 

w 

:::::> 

d 

w 

a: 

1.1.. 250 

0 

..n"'~~~ 

v 

SCANDIUM. IN PARTS PER MILLION 

50 100 

50 100 MilES 

200 KilOMETERS 

Geometric mean 8 

Geometric deviation 1.34 

Analytical error variance 

(percent of total variance) 26 

Number of analyses 1140 

FIGURE 30.-Scandium distribution in selected agricultural 

soils of Missouri. Map symbols correspond to frequency 

classes as shown in the histogram. 
ELEMENT DISTRIBUTIONS, AGRICULTURAL SOILS H41 

>- u 

z 

w 

50 

SYMBOL AND PERCENTAGE OF TOTAL SAMPLES 

500 19 18 27 20 17 

+ 

6 250 

w 

ex: 

LL. 

0 

v 

N 

0 M 

0 co 0 

SELENIUM, IN PARTS PER MILLION 

100 

50 100 MILES 

200 KILOMETERS 

Geometric mean 0.28 

Geometric deviation 2.54 

Analytical error variance 

(percent of total variance) 30 

Number of analyses 1140 

FIGURE 31.-Selenium distribution in selected agricultural 

soils of Missouri. Map symbols correspond to frequency 

classes as shown in the histogram. 

• 
>- u 

z 

w 

500 

6 250 

w 

a: 

LL 

GEOCHEMICAL SURVEY OF MISSOURI 

0 50 

0 

SYMBOL AND PERCENTAGE OF TOTAL SAMPLES 

8 19 19 241 30 

+ +I # 

~~~~~c;;~~~~~:;;:~ 

SILICON. IN PERCENT 

50 

100 

100 MILES 

200 KILOMETERS 

Arithmetic mean 35 

Standard deviation 2. 77 

Analytical error variance 

(percent of total variance) 23 

Number of analyses 1140 

FIGURE 32.-Silicon distribution in selected agricultural 

soils of Missouri. Map symbols correspond to frequency 

classes as shown in the histogram. 
ELEMENT DISTRIBUTIONS, AGRICULTURAL SOILS H43 

,----,-- -~---r \ 1 . --:--,----r-l--T-\.. I ' L ~ \ i / i i ' 

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'--- • 1 • I 1 r _ ___: ____ t _ 1 

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r----~--, i [ .~r__;_l__ .s-- i ;-r--~--; 

i i L I -1_ _______ _, 15 ; I 

r-------r~ ~ '(,1. __ ,_;_, i ' ,±.:_________ '\. 

1-----v~-i ~--- __ j \_r--~---"' ___ j·: , \,·ftt~!:/' I I t /;. ~ 

·---~----,-C _____ ~-·---.---\,../'1 ! ' I ·, // ..... '\ 

1

' I ' I :----~--, I ' ,,_ ' l 'JQ '-- I L :--------~ '."/ ,--------j i ' +_:]· '" i ' --1 1 ~-------. ! 1 I _____ _J_I r----'--- '--~-----\-----.~-----._~ 

I , I I ----~-- , , • I i ! ' I /--------1 ~------1 l_-;- _____ 'J_ i • 1 ' ,-------; , ------l· ,i 1' i I L -1, __ _;-----( I I ~ ~ .. 

I i i 1 'I 1. I I I .r ' 

J ________ ; ~-------L.,__ __ ; ~- 1 !_. :-~-r· " ; r----~ ~ _:...__; _____ _, ,-- [ ___ ., ,._~-- , )s, ~------· I I I ' \ s ' J -

J- _______ J ', ~------i--,---------.! '-------L-.-~----f·-----\ )~ <: I 

• ! I I I , \. i \ : 1 ! ! ! i i \ i 

1

1 )-------· r\J 

L - - -I_ - - j- ___l - - - - :_ - - - ---1. - - _i - - - .,1 - - - _; - -'~ I ~' 

"' ~---;"-·'\j 

50 100 200 KILOMETERS , I 

, r' ' I " '-- ~ _,. 50 100 MILES 

FIGURE 33.-Silver concentrations, in parts per million, in selected agricultural soils of Missouri. Only samples with concentrations above 

the lower limit of determination are shown. Location of sampling site is indicated by plus ( + ). 
H44 GEOCHEMICAL SURVEY OF MISSOURI 

,-:a-: =t:- ~~- - -!t:- - 'FI---,-- ~ -,--w ~ ~- r+- )£- T ~'\.. } -~ ~ ~ ~ l- + * + ' I ~ ~ · ~~+ + i* :t:t '\.j:t~ t:f '\++~ ~~ ::;:-h + ~ ~ I+ I +1. ~' I ' L: .::t ' ~ ' + I ~ ~ ' ~ ~ ,.;+~ + ~\ .. ~I # +, - ·i.:tt I I + + o----~--=F, ;-> ~ ' +++~+I "\ "';-~:_, I i ,+ +! ,-~-. ~ +I r-+-~---:t"-~----~ ~ ~ J 

l_.;t 1 ~ ~+ I ,-----• ~ + ---4 "'":t:t~~ ~I~,~ + ,.:t:+l+ ~+ kt I+ ,+r -- ·~ L .... ~ ' ,. ~ ~. :t:t ' # r----'lo--i I • :t:t .... __ +--1 ~ +·++ ~ '+ .:t: I tt- • '~-~ :tj-------4¢ ~~~~+I+ ~ ~ ~+·+ ~. ~ #' 

.. ~ *" ~+ + + · ~ I __ :t__ __ :t; ~---- + ~- +---- ~ # ~ I ~ .:t: .:t: \ 

"" ~~~I +! +~ ~~ 1+ + + +--rl--w·~------~ 

-~--'tl'+ + I + ~ I ~ I ~ + t + I + 'f + # \ \ # + ~'--------I ~ + I + + I + ~ I~ ~ .tt 

,..._j :t---#----1++~ 1 ;tl# # + ~ +I+ ~I .:t: ~· r .:q; :i;i ~ • ~+ 1 + ~ -1 ----=F•--t 1 ~ , ~--~--~ L # '~ ~ #! ~+ ~~-----~' ~ 1 ~ ~-----~, + "\. ~ - ~ I ~ ~ , ~~ ~ ~-~- --+· .:t: I ++ · '1.-----#-:$>--, ~~~ !-4---.:J:i ~ ~~ + ~ + I '+ ~r + + + , + # /. ' 

~# ~ 1----- ~- -j + ~ -+t, I ::1:; I ~ / J , # ,~ ~ ~ i I -~ ~+ 4- ~ .:t:! + ~ i + ~ .:t: ~ b.-. ~~~~ ~ , I ~ ,/ tt\ .... tt •-; + ~ r-----! ___ ...1;1 __ .::.\ tt ~' ~ I tt#::l;.l ~ ~+# _tt •"';_____; 1+-/; ------------., _ _____:_ ~ + ~ ~ .. '+ <' .. ..:tt-("1 #\;t~·--' ---._1-f # '-;tt I +•t -~-1 - ~ I b-------\ ... ,...---J;; .:t:tt~~-'J ~ ~ i .:t: ~ <' +~/ + .:t:~ .:t: .:t: ~r~L+~+#~ ~ • ' tt ~ .:t:) . I + .-1'-------' I .:t: I 

I ~ ~~ -~~ ~~ ~-~ ~(tt'--.!-~~ ~ .~ + ! .:t: ~~ ~--;t: .:t: J 1 

1 .:t: ~ tt 1----...J :F'f 1f --, ~$ ~ , tt + ~ I \ ·+ , -l< __ Ji- ~\.; ~ ... -------' + ~ + \ ;; I ~ 1!\ ::;:1 ' __ J ~+1 ~ ·*' -~' 

I ~ il ~ ~ .:t: ,· ~.:t: ~ I ~ ~ '4: I + + I tt I ~ +I' tt ~( # : ( + ' I + + ' .,:Mt ~ + tt - ~ I I ~ ,__.._ _ _).I: ')_ ~ .:t: .----+--+--~". ~~' .:t: .--tttt I 

I + 'L + .:t: ~ I ~ :!:If~ + f "f A '--' ~ .y- ~ ~ i~ ~ I '~ - I / tt tt ~ I I 

+ ,;; ~--~----~ .:t: , + ~ + '-. __ / + , + ' ".:__.~I tt \, 

!-~--_t_l+ .:t: r-~-r- J ~<~, ~+.t.:t: 4-.:t:~l~+ .:t:~-r~-'lt 

I ~ - , i I+ ~ _,___,: + +r-~ , , .:t: +, + ~~ ~ I ! + ~ + + + I I .:t: + ' -+ ~ ~ :).r~ ~ I ~ ~ + I + I + I ,J+- --- +' + I ~ ' .:t: ' I 

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J

-+ ---+- I I f----- - 1-j I \ I I I +' + I I + 'I-. + '.r ' .,,-, I f --~ I +' ++ ,_, _ __± _ _, I 1'1 ---- ;t ' 

I + ' I + '+ +• I I j__j_'+--:1--L __ , I + +, +++ ll!t-+ "> +::;: ~ I ~ I I +' I ,, ,, +I 'L tl I -t-' .:t:~ 

1 '+- + r' 1 1 1L'----*- 1 , 1 1 1 1, ::;:'*'"', ~---~ J.. ' I --, --, I ' I I+ + I I I + " I ' 

+~ 1!._ +---=:- ___ __I_~,' i I \, • ../1++1 j, ;----~--~ II + I J,+'.,__ I++/ -? ~\ 

- II l,t 1 It 1- ~ +! lj I I I l __ -j----r; +~~/ i~~~ I 1----- -1 I ' I +' I I ...., I ' I I L.,------ - + + ) I I I- ; ______ I! II I I ' :t. " _____ _j_ I I -,___:----...:-1 I~ + I ~-i"·--,-7.,~, 

I I 1- I I I I I ·' I! I It I I ~----, I I I I I+ I +, I +! + .:t:' I till_ 1'- tj'-t-- ---=~L~-----·~-1 _ _j__l __ , 1 [_--:__ ____ ~__;__--- i- '1 I I I '1 I +1 1 +r ,, -------.-1 , __ 1, 1' ' ' -1-, ,'~ 

II -I I I L ' ,I II I I I I L- -I J------ I --r-1 ~ ,, ----IL I ' I I I ' I - ,-- I ~ ' ~ ...... ~ 

I II + ,· I' I 1 I 'I l I l. I I I : I + I .r"'-

J 

I I 1

1

1 1 1' _ -.., - I I ' ...:s' r ' 

---> I I i I II I r' +--~-;----1__ I i't I ! -- , '=- !----r-7 ! I I·~~ _;-~-(tt tt ~ r ~---,, + 1 ' I I ;r------------,--_::---_.:1 - I I -- 12 /- -~+ 'f#1 .:t: >::--' 

I I ~--Jl ' It- ' I ._ - ,:J:t =rJtt ~ I I I e - --+ -- ,I i I I - I - I I ---( + + ( .:t: -~ tt I I I I t-J11- I ,I I i I I' I ,-----::_-----·- -I -~I • +\ ,~~. + I ' - 1 L------· --j - L-,-·~--=---r., I .:t: lt t--,L--~---:1 jl , _1 _-_(-:_-,-:___--~--~-:--;- , I _ , - , l,;t' +, '-f t:tl 

I I ' I ! I - I - I I , + I I \ .:t:tt .:t: I tt ''1 + + I 

_, ' ' I' I I I ' , , I .:t:-----.----·.:t: tt r I 1, ' ' ' I - - I I I - I - I ' i .:t: ( ~ I , • 'J 

I - I I , ' - ' - - - ' I ~ r' tt · .:t: + '- I 

L.-- - - ~- - ---l _I- ___l- - --·- --- - ........... -- _I- - -=- .... - ~- ..J - - ~ jt: ~ ~. \, 

l...:t: ~---;"it"'J ~ . .r tt' 

0 50 100 200 KILOMETERS '# "'*b .:t: tt ~ ( tttt! + .:t:, 

0 50 100 MILES , ' __ .:t: -... ! .:t: 

SYMBOL AND PERCENT OF TOTAL SAMPLES Whole population: 

250 >-

9 25 23 33 10 

+ :t: .l:t 

Arithmetic mean 0.53 

Standard deviation 0.23 

u Analytical error variance z 

w 

::::> 

0 

w 

c: 

~ 

0 

co ~ c;; ~ 

c:::i c:::i c:::i c:::i c:::i 

.n-CO&nNCO&n 

..,..n.ncc ........ co 

c:::i c:::i c:::i c:::i c:::i c:::i c:::i 

SODIUM, IN PERCENT 

N en en en c:::i c:::i 

(percent of total variance) 2 

Number of analyses 1140 

Lower population (<0.4): 

Arithmetic mean 0.26 

Standard deviation 0.08 

Number of analyses 380 

Upper population (>0.4): 

Arithmetic mean 0.67 

Standard deviation 0.1 5 

Number of analyses 760 

FIGURE 34.-Sodium distribution in selected agricultural soils of Missouri. Map symbols correspond to frequency classes as shown in the 

histogram. 
ELEMENT DISTRIBUTIONS, AGRICULTURAL SOILS H45 

1- r-* ~- r *- - --; - - -.r - - .,... - "'"--..- ~ ~ ~ - r*- l * - r ~\.. } :P it * * ~ * :t * · I * * · * ** * + I* * '"** 'f •+.:t:r... \% + I*+ 1% :t +I *' I • b._*.~ • ' + I * # '-.,.:t * *' .:t *~ .:t *' • itl • ~. --- *1 * I + +..------~. · * , "* **+I "' ~-~;__, I* ·*~ 1+* +I r·;-*---.-t ____ _,** I 

)} * * ~ • •1 ;* ! * 1--;,--,.;--;j + *+ 1·* * * ~* * * r·:*--*' 

'* I *"* ' + *• .. I 1 + r---~--i + ~----v-1 * *' :r * '+ * 1 1:1:: 

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'L --~· + * *' + * ' * .:t I * I • I + ~ .:t .:t 1! .:t * \ 

,...) .:t 1 * ~----- * I + I 'I ' .:t .:t I *·-*·---/ ++ + l ** l * * .:t I* I *I *# * * ,. ~ • * o :* I T * ~~--- """"*'-+J ~ .:t ' __ _. __ ~ 

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* *' * '* * ' ~ .. # ' + I * *L I ,# --~ I_ --~ '( #~-~-1...,_ f* I '*i* I'---<* * ~*-} I~ ... 

1 # # * f----...J ** --=1: -< +..,..... * ' 1- + * I * '* I *-- ~.. *-.... ---- ' * * I # I * :t::!F\ * \ I - • J * -,.:~ * '.. *~' it --:tl * .:t * ' ** * I * ;** -~ I .:t * I #1. + ~ it / # *( I

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I * ' # * * I * -tr * I I* --!t: / - ..,_'' * y ** i * * i '----.., I / * * f I 

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11- - + I * I /, 1 * *1_- ------1 * I * t* . \ I ' r ,~ ' + I + ' ' ~ ~ 

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11 1- '\.* ~ l - ' I -!' I I I I I' * '1-. * ,r ' r--...:t-. .,-.J ' 1- f----T-.~ ~ \j 1-. +1- ,.., _ __!-_ __, " I I I* ~~---- #. ... I # ' I ; I 1- I i * -* 1" :?·..J....-~, I + : -1 + + ; *y> 1- *~ 

** I 1 r' 1 * + + I 3 I · + '

1 + I ' :r • * 'W ' ~---;_ 'I I ::;-·I --,--, 1

J' 1 ~ + 1- I l ' I I ), / * \ '.:t: '!r ,- I ;·c.:. _____ ~l I I"\.- 1+11 ' ~---~--, I I + +' +'1: f. *-t-+1 * ** ~ *1- l I I i I I :J I ~ I I +' - I L __ ;-+----~-i ~----~~- T . * * .. \ f-1-·----i-t- I I -;; I, /_ 11- -t- '1 ' I ! '"1--!---+--~-----_J*--*''-) ~ II ~ I 1- e-----_J- I . 1 .- + * , ' 

II I I I;,.-.-·; 1- I I I I, I I ! I L .., I I I i I I 1-1 i ~ * T ' 

~--I:: i-T [-1----'--~~Ll~--~--~~-...l-I __ J [:: ______ __;_- l 1

11J .:t: 1

1 1!

1*+; 

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I I I I ,I - ' 1- l I+ 1. I I I + - I I + ! *:"'- * ' 

J 

I I I I I 'il I' 'I I I - - l -t---!1 ~- 'l,' 1- I ,I r·-'.:t·;~ * ~ ___ 1_:-__ d 1 I 1 f-1---.1--r--L.'lf.---1_:. _____ :_~ -=---- , I ---"'·IL--r-, ·--:-~._,; \~ + ,_<:, I f, I I ' I I ' - ' ; - f l I I -- I ! * I* J * ...... ·1 I 4=-+---,,- I f _ ~ I J , 'fE- # 

I I + " ___ _J,_ __ , I 1111- I I- I ! I 1- - I -~------t * 1- t_::~:·* "/ + I I lj I - I I I I - - I ,--=.--- --:__·[._ - I I ~ '· ' * "t;,.,. 

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J--IL._\_l7 I' i I I I I II -, I _I i I ' *· I I \ 1-.:t: 1- i * \"*I 

I I I I I' 1- I I ' ' ' I + * 7-*-,.---'* * , .. .....; L I 1- , , I I - I I - ~ I I I I I I * r' 1- ! * - ** (...: ' L---I_ ___ I_! _ __1 __ 1- _ : __ I __ ;;:;....;_ _- __ I::--~ ~ - --=- ...1 - ~"~- f - *'I, 

0 50 100 200 KILOMETERS 

50 100 MILES 

~* ~---;'*'J ~' * *' '*~**!I..' ( **! * *"""' , I ** , , __ '*:_..:. __ , 

SYMBOL AND PERCENTAGE OF TOTAL SAMPLES 

t 

z 

w 

500 

~ 250 

w 

a: 

IL. 

C) 

N 

6 10 

C) C) 

C") In C) C) C) C) C) C) 

N M In 

STRONTIUM, IN PARTS PER MILLION 

Geometric mean 110 

Geometric deviation 1.60 

Analytical error variance 

(percent of total variance) 23 

Number of analyses 1140 

FIGURE 35.-Strontium distribution in selected agricultural 

soils of Missouri. Map symbols correspond to frequency 

classes as shown in the histogram. 
H46 GEOCHEMICAL SURVEY OF MISSOURI 

,---- r- - -, - - "~"""-----,--- \ I l + l ' # ' -,- - * -#~ -# l -- T- '\. 

: 1' ~~--~-±J * \

1

• , +L--~--+. .~ i * ! * ~' \,.__ *· I '· I I r, -+-----, l ''I "'\ ~---_:;; 'i ! ,---+-·1 

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>- u 

z 

w 

50 

625 

w 

a: 

u. 

' J • L ' I I I I I l ' -'[* ____ i . -----~ I ' I, ! I ' 

' -- r' _____ J, +~ ... # ' I #r----~~------1 # i +\ ... -..../ , i I - ~------~ I ~~----·~------\ 

·.,___--~i *i I i i I + 1 , 

,_.J L __ . ----~~--_,_--1 #' ' : # ' *I ,. * I* ' I +l_, ____ !__ ' I I 

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, #-~-----~---_--- j * l. ! 1 ! * I / / 

, i i * ~* I I • , '-... \ i* i l •' 1 ,/ \ __ 1, /-.:.______ ~------- ---\ I *-. 

, "',...-J'./·---<-~~·~-~-----""-j -._. ''/* f _ _;_ ___ l + I, ~-------\ 

I * i * !* _,.,~ * / *- ,l:_-----i---~-T-* ,· 

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I

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I I 1--;:v--.: /)_ ~ /i----1.-" ' .-- '+ / # L I ' I I "\ // i i , ______ I ~< I I 

1

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I I I_ I * -:._1._ _______ _, * i I 

+ -r-------'~. ~'(a __ ,_:_:_, i ~ ,--~---;----...:, "\. 

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Lt-;-~---- ~+ -; -~-\ . ./; + I -'-, I I! '-,, / + \ 

1 iF ' ' _._ L - ---·=-~. -·,_~ ' # .... \ 

r·------1 ' , + I ' I ..,.. --· ..,.. --- * 1,;,------

1

! * ! i 1--J __ _;_I r_j__ L--)---·-\-----.~---'-{ 

l + I * ' ·-, I + i ! * ' I i*-----~-!·-----~------j [ _______ ~ i # j I ' 

---#-~------i ! # j i + I L l ___ _j·---·( + i * f' I i i l - 'I 1. _I ."" ...r' ~ -..,, I r "=·.-' I\ I · , 1' • + I 

-------~ I r-------·- ;----~--------,----- # ~--~-l ___ ., '--;--:_ _ _j \ I>(, 

I l ~----, I I ~ ,r \ f ' 

e------, i # - + 1- ~-------( + '( / ~-

~------'F! ~r* ~-:: ____ i_(,------ L_;-~-----\ \ ~~ 11;,., 

; , I ..,.. I I t, , ,\ J 

+ I I + I i I ' ' ' I. :-·-,--·-! ·,~ #I 

I ' ; ' I I ~ I - I +I' I , • J L ___ I __ __.1 _ 1 

_ ___1 ____ :_ -* __ ___J. ___ 1 ___ _; ___ ...1 _ _ r,. 1 \""L • 

0 50 100 

0 50 

SYMBOL AND PERCENTAGE OF TOTAL SAMPLES 

17 18 I 25 1 20 20 

I I+ I~ # 

,.... - on 

c0 cx:i cri - N 

THORIUM, IN PARTS PER MILLION 

100 MILES 

~-~ ____ ;"-·\j 

~' i 

200 KILOMETERS ' ~ f ! * ~ I , 

, __ .:__1 

Arithmetic mean 9.6 

Standard deviation 2.47 

Analytical error variance 

(percent of total variance) 86 

Number of analyses 199 

FIGURE 36.-Thorium distribution in selected agricultural 

soils of Missouri. Map symbols correspond to frequency 

classes as shown in the histogram. 
ELEMENT DISTRIBUTIONS, AGRICULTURAL SOILS H47 

,---- r-- -~ - - -r-----.-- --.-·-- --r- l--r- '\. 

\ l l, ~ \ ! ~ I i ' I ' I____ ' ' I ·-.., I I \ ! ' --! I ~------, -~----t' I ' ~----~, 1 I 1 r . ------. --/ 1 ! ,-----; I 1 r----- ' I L ' ' I ' ' r· ------i , -----l · +15 1 1 ' ·, r-----~ 1 ~-----~------~ 1 \ 

-.../'' I I ~------~ ! ..... ----·--:·-----) 

"-----i I ! I I ! I ' 

,.,..J ,------r------1 l_, ____ j__ ! i ·~ 

\- i ! !------t L-----L~-----~-;----- ~-, ~-----~------iL ______ i t, . • i / / ' 

,\ i i ,.~~.'-- -~ l _______ ) I '', ,.,i i ----. ·'~; -1. I --...... ~ ---, ... ' ('_/ '( ",-·../ -1 '-) --:-~---1 \, ,-------\ 

-."'-J 'r' :,..- I <' / I r---~--::f--15 • I i ! ·,)'- / ,.L------; I I 

I ' I ( _______ l I L.. \ ..._ 

1 ,

1----.J·---r------; "-, 1 I '~ ~-r\ I , 

-------1 I I I\ ~-~ '---f-- ., .~·"-~' 

I i I i / ~) 'I __ l_~--L, : __ / ;{ I ;-----~ ' --...._', /- ' ' ', I t' 

L I 15 \._ / I I --....... :__.~'1 ~ I 

~--------; ___ r---~.·. , lit- -;. ,I 'I , '-I 

t- "', ~ • . ;-----;_! -----~--. I, I "-:-....:..! r-- , 

I I J ,.J I I I L i ---1._ _______ ., i I 

r-------r~ ~ '(,1.._,__;_'... Lt-15 ~ -~--~---;-·---\ "\. 

f·----,.--1 ~--. __ j \ ! ,__----~ , I -~(_.-----<' ' 1 I -y--~--T ! /> ~ , 

~---;___;_C_ ___ ~-'+30---\_) I :----~--, i ! +15 ;/ \ 

, 1 ~ L __ i _______ ~-----:-:._.~/ 1 

r·------~--- ____ i 1 _____ _;_1 r+5o----, ~ ~----r---'\._~ 

J 

I ' ___ I_ , . ....., , I 1 , ' 

----- i ;--------! -,------! l_-;- _____ _;_ ~ i i ! ~ 

--~------l L l, __ _j-----( I .J"'r.. 

i ! ! ;15 1 i ; 1~- ~~ !_. :-~r:" \ --------! :-------·--;-__ _1 ______ :.....__,- ____ _, ,-- l ___ .,_ ;~-- \ /~'-

~------r---, I ; I +15i ~-------( .! / I ~-------J ~I ~------i--,---------.1 r------L_;-~----\ \, i~ -t;,\ 1 

I

' i ! ! ! ! I. ~-------! r\ .' I ' i ! I I ~ I I, : .._, 

L - - - I_ - - .... 1 - --1 - - - - :_ - - - ___;_ - - -' - - - ...1 - - - ...l - -',. I ~I L. ~----.:'--\.)' 

" I r I 50 100 200 KILOMETERS 

I I 50 100 MILES , __ ~ _, 

FIGURE 37.-Tin concentrations, in parts per million, in selected agricultural soils of Missouri. Only samples with concentrations above the 

lower limit of determination are shown. Location of sampling site is indicated by plus ( + ). 
H48 GEOCHEMICAL SURVEY OF MISSOURI 

>- u 

z 

w 

0 

SYMBOL AND PERCENTAGE 

OF TOTAL SAMPLES 

500 

2 5 69 I 23 1 I : + :t I .t:t 1

7851 I 

I 

I 

I 

I 

I 

I 

I 

I 

I 

I 

::::> 250 

0 

w 

a: 

LL 

0 Lr) Q Q Q Q 

N M In r-. 

Q cici ci ci 

TITANIUM, IN PERCENT 

50 100 

50 100 MILES 

200 KILOMETERS 

Geometric mean 0.33 

Geometric deviation 1.31 

Analytical error variance 

(percent of total variance) 45 

Number of analyses 1140 

FIGURE 38.-Titanium distribution in selected agricultural 

soils of Missouri. Map symbols correspond to frequency 

classes as shown in the histogram. 
ELEMENT DISTRIBUTIONS, AGRICULTURAL SOILS H49 

1- - - - r - - - r- - - ......., - - -,_ - - - - r - l - - r - \. 

\ + * l. _ ~ I ~ ! I +j *-f' : , ' ' \-----:_-- ~-f , - - ~--- ~-- .:" ! - : I -\ "'\ 

'" '--- I I I ! ! I r -.=------ -- t--- :-~ 

>- u 

z 

w 

50 

:::> 25 

0 

w 

c:: 

LL 

-r----~~. -1 ! ~---+-• ' I i I r------1 

' , L , I I , , # ' r------l , -----~ · + ' 1 1 

' .. --i-2 r+----~ * i * ~----=-~------~ # i \ 

... J, i I - ,------~ ! 1-.-----·~--- _:-_\ 

~--~i +I ! I I ! 1 

,.....) ~--- ---t#--*--1 + t' i I- i + I I 

,. I I, ' I I -,---=·-- ' . ~-----~ 

0_ ; ! !------t ~--.!.l_!·------4=, *# :, 

"\ ------, + '-------j I I + · / ' 

' I ~-----~ - I l, * i ! ( '- , i I * -;(., I "'-

~ o# I ,_/ ''----,, ;<._ ~-------~---~~ + ), I *i I •'- 1 ' - .. .:. __ Jr-.-:-·-~__- "---/~-1 ~· '-;'+ ----, _ ___;_ ___ \ # I, ~~----·\ F ',----' '_/ '*' I * ~ .... I + ; +!I /~ I / *- )-"'-----;·-- 'T" 11 

I ' I * ( * -----~ I ~~ I -\ I --

1 + !---. .J---~------~ ;\ # , +~ _ _jI ~--f--~ "' .::::·'-~' 

1

-------1 * I / I ! I' ' / ( 

# ~_!-#,-.-- __ ; ,f!_ ( ~--+-- ,.l,," ' + ;' 

'I I# I '-.: /' I' - ' ' I / I I # L~- , ./ I I ----....:.____~'! \, 

I --- # -- -~ -=F- r- - j '""- - 0tF r. I i I I ~. I'---~L/ ' * '"'- . (''!= ' I I ~-~-~ .) I 1 

+ I ,J ---' I # ' I 

F I + *L_ _______ , I ! \ # #r-------r~ ~ ·~"---·___;_~ i ~ ,- ~-------- \. "\ 

'-----.,,-,).' * + ~-----~ I \_ , ++ -,__.,.----~ '\-1 + ..-:' ' 

r # ~---'--- ~L--- " ":'-:, I I * ' - .,, * I :P' I 

~---~ r' ~·---.---\ ) 1 , i ·,, ;"- '\ 

"""'·L_ ____ ~ ,_ I + --, I# #. r / ' l # ~ , 1 - L __ :--------11:-~ ·,_~/ + "' 

,-----~-1---~---i +) __ l __ _j_ r_j __ ---, '"-)-----\-----.~---'--~ II i * 1 +! # ·--, ! i + i ! I \ I ___ '_ i i#-----~-! ----- [ _______ __:__ - I I- i I ~ ---· • 1 + i ' j J,_ i + r I + ~-- - -- .i: # ' # I _, " 

I # i i : # I ' ! l. I -" 

J ' # ' _______ I . # I I ~- I '-,'f. __ -~-(,· ~ 

-------~ + f---. ·--r--~------'---;------~ r-- [_ __ ·-~\ # / ~ /s,_ I ,_ ______ , i + '- ! # I !- ~-------~ ,( r" ; 

1 I #' I I ,-------L ~ ~, ,~""'~:;, 

r---------*~ -1+ ~-~----·---:_::,- ----------11' J ·;-~----~ l, ! - \\ J 

+ + i + I I ! ! . , ll :---,-- _! ~~- '/ I ' ' : I # I \ + I _, - ( I ,. ._ 

L ___ I __ ___; _! _ _1 ____ :_ -+- _ ___.L. ___ i ___ - ~ ___ ...l _ _ r,. 1 \-L • 

0 50 

50 

SYMBOL AND PERCENTAGE OF TOTAL SAMPLES 

21 23 23 16. 

I I+ I :1: I 

I I 1 

I I I 

I 

I 

I 

I 

17 

~ 

M ~ ~ ~ ~ ~ 0 M ~ ~ 0 

N N N N M M M ~ ~ ~ ~ ~ = 

URANIUM, IN PARTS PER MILLION 

100 

100 MILES 

~-~ ___ /"-·'\j 

,-. 

,. I "' f ! I I I , 

200 KILOMETERS 

J __ .:._, 

Geometric mean 3.8 

Geometric deviation 1 .34 

Analytical error variance 

(percent of total variance) 62 

Number of analyses 228 

FIGURE 39.-Uranium distribution in selected agricultural 

soils of Missouri. Map symbols correspond to frequency 

classes as shown in the histogram. 
H50 

>- u 

z 

w 

500 

:::::> 250 

0 

w 

a:: 

LL. 

1-tI 

-t0 

SYMBOL AND PERCENTAGE 

0 F TOTAL SAMPLES 

10 7 

LnCCCCCC 

-NMLn,......OLn 

GEOCHEMICAL SURVEY OF MISSOURI 

50 100 

50 100 MILES 

200 KILOMETERS 

Geometric mean 69 

Geometric deviation 1.50 

Analytical error variance 

(percent of total variance) 30 

Number of analyses 1140 

VANADIUM, IN PARTS PER MILLIONS 

FIGURE 40.-Vanadiurn distribution in selected agricultural 

soils of Missouri. Map symbols correspond to frequency 

classes as shown in the histogram. 
ELEMENT DISTRIBUTIONS, AGRICULTURAL SOILS H51 

.- r- -+- r- - - - ) + ::+- * + ~ - +- "'+ - - ; - "f- --.--F ~ -r.- - r+- l + - T -+ "-

' + + t + + l, I + + -A + \ + ~ + + + * + I + ++ +l+ + lr+ + + ' I ' L+ ._._ ' ' + I I ' * I + .. + I + -f, - ..... L ......... ++ + + + + ') + + + + ++ + + \ "" +I I >------"""F· ' + ' + +,... > 

s--1:.~. I i: .+ tt I I + II r--,_~-t + +I + + 

1l + + ~ _+ +!+ ~+ ! ~+ ,~--+-;-i + + + r-+ + + ~-:--:-~-r--+---J 1 , r --+--i + ~+--$'""- 1 + +·*+ + '+ 1 +. + ' 

' +'~+ + t.-----~ +I+ + +l~--~ -4._ +~ 0 + \ f + + 1 

" .. +, l + + -h..,_++ ++I' ~ l__±__ __ t-l+ T I -1----~+ +I + + +\ 

.,;±;;- .. + I +' + I+ I I '1- + +-.,_--F•-.-----~ 

~--'!'i I + +I I + ! + I + + I I I + -+t I * \ ,_.) + + '-------- + + ' + + ' '+ + I + ,. ..;)--+---~+++ 1 **L+ ++I, +1, +i "*'+ +' J '++ '+ + +I +++ II++ + .p--+---;:-•-t] jt + , +~-.:!+--~ 't-+ + + ' + + _,_ ,-----.o..-h + '\. \..:_"'---~-t.! *+ L ++ ~ ----++~ + + ~-+--F""· + + I ++ ,' V= +I . -+----1 + + .+ * I I +I + ' + + / ' 

t+ + 1-*--,~---1 + it- -it. I + ' I I+ / -¥ 

, + I + , I + + ~+ 4- + + I + , + ,... + "- 'It *'++ + ! . ' + ,.1 +\. ... + . ' + ' :.._ _ __!_ *' +\ + + ' \.t- I + ++:t,1 + ++ -1/- + •'-;__; + -1-+-1- --+ . ....__ +: + -+-'---, + * ++' ... .:, r../+'(.~ ,";-f--•../-.-1-1' '-;;i+ +;:-f-~-+-1 + + \ ---~---\ r·J+ + r- Y * '*' + , 4*/ +I + + ±_ * I+ 

I + +~ + +*I * + < + I + ..[ * : .... + +~+* + I 

+ +I + + + '+ + _):-, * +/ * +' +-----1 +I + I 

I .+ I * +( * ---~-~ f+ I + + L \ .........._ 

1 + * + f---- . .r--+1"'-"'F·---< +* + ' + ' + + / if, I '-.+ . ..,+ fr.\ I +-~ -------.; + * I * I + + +t\ +I , + _ _j+ ~--R -+ + ., ;t.---<:: __ , 

I * "" ++ * ' +* ' + + 'f; ' + I ~ + , , ++ + * ' . I * I + ;+ I :f- + ' I I+ + 4 + + / +_( * I I + .__--j..,....._-4 )_ ( * --++-:t..--1!.:1-" I*' + ,-::t-4-* I I ' * + +I * 1+ + l+ ' "'-... * ~ + ' +' ' I / + + + I 

+ + ++ L~---rJ----' + ' * + +4- '-.. ./ * I++ I ---.._, -~'1 * \,_I 

'

! _____ +! + + ·r_T_r-~-J 't:,l + /+'+ + +~ + ~ + -t-i + + -+ ~ ---t:~ ' 

* --j + + + j + + * I+ + 'i::.±.:=H + +L--~ + · · + + +, '

5

+ ~~ + + ' + I + J+ + I +,~+ I -if- + I 

I+ 1+ ! * + i c_* i + --;,.L---~---~ + I ++;+ I 

I + + +-- + ' ' , + ' :~ + ·+ +I + f -- +r'l, + ~ ~,1. __ ,--'-., + I +'+·--~-------_.: T ' 

l ' * ' -+' + + --:. + --+ ++ + -t- ~ -~* + '±i-i + + ''\+ "!\. ._J._ _ _±_-, _ J + * f---+ ~ + \_ I * 1 To * '1-. + r' , * .;._ ·, + * '+ -+, + + .:;_...± *_;_-r+ ""-f--+ +I+ I' ++ ~~--< .-t_' • *+ 1 + , + + , ++ · ;r-+""- -~=r I· i+ ·I + : :!;+> + +~ 

I ·---, * :· + + *;t--·-3--, --, + I ' '* -f .... ~ * I + ' + /' I+ ..... ' 

I

+ +++ ! + L..t----,-.! ___ ±_1* 1 • + "\,../'*: i _.! ' I ' I * )._ / \ * j + * ' -:+ ++ ~ .._ ! -r + ,, ~---~--, I+ + *' n "'·+*+I *+ + 

1

:;,---- ___ _;+ + +* +: *++ +l + 1 '+ ..____ ! +t + + + + L._ :-:,..----~-.:j_ -f ~---·/ + 't+ ~' I Col + ' + + + -..., I ' + ":+----~--~ * ) I * ++ 1+-,=----~ * * t + +i+ + + l+ ____ _j_l+ r-~-----r-i +* ~ + :-+--~~-"'*''-" 

I 

"*'+++ ' + * I + I ____ I __ - ...± ' + ' + '-r1 I + ' t-1 *+*~+I 'I+ -t-' 

----~ __ 1+ :to +14>------±+t.! I + j +- =,.--! + [_+-;--- ___ __;_' + I++ i + + i + +I * + \ 

,+I+ * i._t ___ =t * + ~ +,.. i + +*I + +I L* +I+ J'------' *i + ~ I + :+ - ' , + , + ' ' + ' * , -- + H- ++ , * ..r "' 

*+ I * I + * !... * I 1 + I + l. * I .... + I ' + I +..r'- • 

J 

* *i' * ,., + ' + • ... I . , + ___ o;~--*l *+ + -f-"'--~'*--~-- -~J+ + ! : ! -+-;*~--~-* I + +,.......,. +-"+-\i- + ~ + ~ ::j:: + ' ,..* ;to --------,-----l +I *--~ + .~-,. 'I I )<:, I + 1 + ~ -*""!'+ * 11-1 , ' + 1 o+ -t'-. + * !' * l t+ f ' ;-

1 * * ~---"""--· v + I' ! -t' I + ::j:: ' + I .. ~ .J 'I 1:-" ++ 

>- u 

z 

w 

500 

~250 

w 

a: 

u. 

* f * *~-t +*I + i + i· ·, + + !--,..-----'+ + * + l,"f·----~ + + \~+-r: I +I I ' +- + L.. - I i1 I l + ' \ I ' J-=t-'L--+-=1: I I* ' -+--+;.-,-,----+-------'¥ J -;-~-=r:--+o -1 + + + >l, I + J * =F ' I -+- ++ + I ·t- ++ ' + + + ' + ' ' '\ 

'+* + + ~ * ~ I ' + I + ! + ' +! + +. + + ~ I I I ! I I ''I+* I 

~ ' ' ! I i 1 + I + \ + I * + I -t + /-;-.---- I (-...) L.. + + t +I __J + ' '+ '+ +++,+ ' I' ',,I +'' ------- -1- ----·- _+_- ±......L.-- _I--- ..... --' -...! -',;- t + +'r(,l 

L.. I ~---J'-f\j 

\1 ,· + I ' 

0 50 100 200 KILOMETERS ,., !I I I \.., 

I+,! + +'" 

SYMBOL AND PERCENTAGE 

OF TOTAL SAMPLES 

8 176 16 1 +I ~ 

1 1

sss 

N M Ln ,..._ 

v 

, I I , 

50 100 MILES 1 __ 1

_ .:. 1 

Geometric mean 3.2 

Geometric deviation 1 .31 

Analytical error variance 

(percent of total variance) 68 

Number of analyses 1140 

YTTERBIUM, IN PARTS PER MILLION 

FIGURE 41.-Ytterbium distribution in selected agricultural 

soils of Missouri. Map. symbols correspond to frequency 

classes as shown in the histogram. 
H52 GEOCHEMICAL SURVEY OF MISSOURI 

1- ~ -+- r=~=- - - r -+ \.. 

} '+ + +I+- ; T - -;.; - "'""-...--~ "' ~ - r+ ++ li- -:--- i* + 

'\ + + "' + l, ++ +-+', \ + I I I + * +I *+ -f +I + ' I I +L-~ _ _;t * '+++I + +'')+++1 "'+..,++ ++' • +I + ' + ·+ I ~------+1 . + ' ++ I I ' ~-~;_- ! *+ .+ -+t I I + 1 1 r+·~-+-t---- .... + + t 

,+* + + ~ -t- +!+ t ! +*+ r~.--+~j + ++ i+ + + ~+ + + r---l---+f 1 1 r---,.--i + 1 ~--~- 1 + +· *+ + '+ + 1 +. + 1 

+ + :-+ .... I + .I + f ' ~+ '*r.' --=.---1.+* +I + + + I "it + +' + + + \ ' + *- +" +' + I + * r-.. - .. I~- -1- .. ---j + -t- i + + + \ .. ~ ... ~ 4 ++! I+ ~-+----~ + I ~ + +-,."F"-t•--:_;.----~ 

"L.--~i+ * +I I + ! + * I ++ + I ~ ++ 'I I *' 

,_) + ...._ _ _._-1:__-1'-+++--1 + *I + + + I i +I I +, I * + t I 

, ++ +I + ' + + I -t- *+ l .. , .. - .. --t-. ~+ '+- + I + + ~ ~ + , + + ~ +-r 1.±..----~' + I + + + ~-----.:.........---+-+" L' :~:+1 ++ ++ 11 + ~----~- +I* · v:·----;.. 1 ++ ~--+---1 + + + ,.:t + :1: I I+ +I + + ' -t- + / ' 

t+ + 1-~--~...:t---1 + it- + "'t. I + I I I+ / ~ , + +· I -t- "+ ~++I + 'I ... + ' 

>- u 

z 

w 

I + + 1 I + /f:, + . · + + *I +\ :a:"' · 'if :i:l+ ' +I ' '-- '----+ + I r-----f---,___ +~ ' I + ++.:+:.1 + + + t - + ·'- ; + '.+f -...__ __;_ + + I + * ' 

500 

c~-... . !' . ..:+-!I ,.h,-t~·-' ""'-1-1>-- '-;+ -t-i:+ "=F"I + I ~-------\ ""r·J 1- -f'r.' :/ * -h + ' ++-/ +' + + +L * * 

I + +>t- + + * I * < + ' I t' * r +- +"'1f-+ + + • ' + + +) * I + +-----' I + I 

+ + '-t * i + + + . *" + * t'+ I + + L... I ' * ( . ::F .. ~·"- I --q, + I ' :+ + + \ ........_ 

1 + .. * + 1---. ..J·--'i:+---:f<--·-< ++ + ' + ' + + I + ·:I:--: *--~-r~ f 1-~' 

--.. -- ' + * I * I + +t\ + \ I J + ·+~ + + ., -:J;' +~' 

I + -'*I + + * ' *+ * I + -+-+ t I + + I : ~- + ~ + / + +( * * I I + I + ' I+ + I + +/ - + I + -r:----~----t ')_ ~ * -.f-l-4--±-·-"-f;t, +*' + .--*** I I + L * + + I + I+ +I + 4- '-'( * y i+ +I ,_-....... I / + + I I 

I* + + ~---=~:-*----~* + ' * +I * . __ ./ * . + + ' .:._+~! * 'v .. - -- - * I * + ~ --=f--· r-;:; ·j '* + I + + +.+; + 4- +I + + ~ 4-+ '* y * ---· + + +I + * I+ ''t I' + =~=~-"4 + ' ~ * + +,. .,., * *! + * + + j+' ·=F") + ~+ I , +I + I + I + , --·:t_' + I + o + +' I+ I+ I * I I_ I + * -------~ + I r- .• + :a:' ' ' ' . + ' * . + . + 'T" I * r-·-l+r'l. * ~ ~.l. __ , ....... _ * I + +'+·--~---~----, ' 

' * ' -+- + ..... + .+ ++ + ~- ,* + "lt-i + + "+ P).. 

1

-.l... . ..±_ _ / + * f---+- J + \_ I * 1 +, * , '\14--+ _r , * ':;. ' + * ' +i + ~ *' ++ ,_,.+--~+I I I ++ ~----- .t ' I + I' + I+ + + I + ++ ~-..1...--Fj, I:. I+ rt- * II *.,> * +.,..., + * I + :i: + I * ..... + I + 7 ++ 1 ·---, r * *;--'+---,--. + + '* *+ 1 + · . 1.,..' 

I

+* +"!;. ! I +L..~:-C:- __ _:!::_4' +. i * "-Ji*+ I ~ ~---~--, i + + *! ~ +_.}. + *+/ *+ '*\ 

- ~+ + ~* 1 *+ +\ : t + ~ + +I+ I+ L__:-+----*·i ··-~/ * t++' 

I 'fi----- --- -j + +' + ' I . + + .... ' + I '*" - ---=F" - * + + •- ----.:If ~ t + , t + ~-----_]- I + .....,....:.---.....-~ ) + ~-.;·--.~---'-{ I * I r+ T -, * + +I+ I+ + I r I +* . * , *' + 

J 

*+-rt ' + * ! + +;:+- 1---- 1--.--..± .. __ , l' + + ~ I I * • *! *-t- :+! 'I + + \ 

I+ +~~----+-,I I+ + I + -~-----...l... 1++1 + I+ +I * ---+---. ~ ~ :i:· • ' * -+ * ' * ~ I+ I * L_t_ '* ~ + -+1 +I I, + I + ~ L +I J·------· + I+ * r +1-F ---J.. '+ ++ ' + ~ .--+ ~ . J"'" 

I ** ,· + I' +* 1 + ·, 1 + + l. * I * + + I + +I +--"'-+ ' 

J 

* ~t * -+i + I * ., .. I . -1' + ~ + ' *+ ' ~ 3; -11- + + + I + I I ~** ' * I * +' l--o+-,.,.. ., ---+:t:·-!1 * : f +-; *--·---,. ___ 1__1_ _____ :...._~,-+" .. _-Fl ~ ~--*il_ __ ,..~ * ~-4* \Itt- I )~\ 

I-t- 1 I ft;-+---=1:>+ * f+ I '+ I + ~ +* - \1 IJ+ .._. I * * *---3:._, * '*l:r + I I + + ! ~ * I + 1-t- + + _T _____ _J * + '!+±-'I T +/ :i: I* ~+** 1 -t- I + I +--+-----' * ~ .. .~1:; I ,__'L __ -T_":l I++ ~-=+-+·-+-:-r--,-,- 1 

___ ......_ __ +_~ ~ I L.;-~+-~7--+-, '·I+ +! I ·-~.+ I J r-, + .,. I ~ + + + + . + I , , I .... I + * ' * * I' ' + I I + I . +! + +. *+ ·, I I I I I '+*I -t-* r- * ' I It I+ ' + ' + * + I ,_ + +.-,-.----·1 ,~J '-t- :1: -t- ' I ' + I I I ~ + + + '+ I' I ( I I I +,' L - __ t ____ + _1 _ __l ____ : __ + __ ±....J. ___ I __ _.:!:.. ...l - - 1 - .J -' ,.._ il * + ""'t, 1 

~I ~---;"-f';_.) 

\1 li + I , 

0 50 100 200 KILOMETERS ,.1 ,I + I \." ( +,! + + ....... 

SYMBOL AND PERCENTAGE 

OF TOTAL SAMPLES 

9 70 21 

1+1 + 

I I 

I 803 

, I + , 50 100 MILES '-- 1

_ ~ 1 

Geometric mean 32 

Geometric deviation 1 .35 

Analytical error variance 

(percent of total variance) 55 

Number of analyses 1140 a 250 

w 

a: 

u.. 

QQil)QQQQ 

---NMLt'),..._ 

v 

YTTRIUM. IN PARTS PER MILLION 

FIGURE 42.-Yttrium distribution in selected agricultural 

soils of Missouri. Map symbols correspond to frequency 

classes as shown in the histogram. 
ELEMENT DISTRIBUTIONS, AGRICULTURAL SOILS H53 

,- w:-# "1i- rt:r - -~- - ..., -- ---r- 'lt~-~ ~ -r.-- r*- l :r- T ~'\. \ f # # # l .:1: I + ' ! ** *' #~ * * r* * 

> u 

z 

w 

I# # ' J._ !r *.t:t # _: tt \ + I + I # # .:1: # / -:~:+ ~ ~ *+ ~\ • #I # ' --- +T '* I .:1: *~-------+· ~ 11_· *+*+_, ' \.....!.--~:__- ! b ·* ~ I 1 # +I r---_.:--+ t ____ .... * * J 

1--it l . .t:t li# I ~-----• tt # + · --* 

T' * # t: *!+ * · ~ I # * *I 1 * + i• '** + * r- --

500 

1 1 r---~--1 + h-7--w-1 .t:t *' ++ • · 1 1 •· * ' 

' #'')# # }- ---.l.+-:1: .:1:' .:1: .:1: .:~:1- # # .:~:-\' .:1: * ~ * *' .... .t:t .:~: ~ .:~:+' .:~: ~--~--~-~-----=F~--1----~ + ! I .t:t + +\ !h)t'# + .t:t! +I '.:1: I+ # +1- * i-T-:...--~·-.-----~ 

~---1!1'+ + .:~:1 + + ! .:1: # I #I I + I - f + *' \ .:1: + '---- # 0 + # I ¢ * - * 2; 

.-J 1----#----1 ++ +--1 +t * .:1: I I II I *i * :J:I 

,. -*tt ~ + ' :t* I + ## +~-----r•!_f 'f- .:1: o *~-~--~ .L.. .:1: ++ # .:1:! ++ I* ' * 1 + + J ,-----_,., II " 'HI'+ #I .... , ... .:~: -----:.:( tt ... :J: 

~---~-#-. #i• ~4---~ .:~:• .At * • ~-=-+-;r.;. * + ' ~ I /·, 

~· # ~--- ~- -1 I 1:t * "'- I * I I I+ / -J , .:1: :til-:1: I#' I .:1:* -;--. b: + +I * '- ... + ' tt .t:t I .t:t .t i· .t:t · ' +t * .JJ! +\ + tt , 

\; .:1:•# ' ..t:t# 1 "' r' '--1 , . ...__ + * r----+-- '---, **' I .:1: ##!t I # # • # ' . . + .# ------,. ' # * I + .... . ,.. _ _::~-(+ .-.~ • .....-~-1#- ._j +tt·+~-~-, * I -------\ ""....--J# +" 'y # # . #I '*' * + JL + I+ 

I #*Iii# .:~: , .:~: < 1 , 1 ,t + r.... iiF1 + + , # ttl .:1: .:1: #'I + ~)~ .:1: . I * *' #----; +I * I 

I :tt # I .:1: +( # -----~ I* I + # L. I \ ....... 

1 * * * 1----...l·--n---r·---· +tF +- , • . * + I \ ! ~·--:+ + __ ,...+-'7\ ' •. ..("' -------' # # \ + I .:1: fit\ .:~:1 I ..... .J +"+I * + ~ -· -~' 

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f 

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1 

# I - +i, 1- 1 I r 1 ++ 1 ••• 1 .tJ * 

J 

--I-= ' - # I I -1 ____ I __ , __ _J, ___ , t' + I ·r; I + # . I,+* ..,.+, ·- * *\ I_ +1 _______ ..;::..1_ 1- - I I _______ _._ I I I - I+ *I # 

,+--=-i_:i-_1_-::+ .: I I ~ ) I' I I i - i L + I i +•j· __ : ___ , *i f -~ +,I ____ .., ' I ** I I * .-- I II I ' * ........ 

I ## i * i ++ 1r I I l I• - o + l. I _I + + - i - +! ~- # ' 

J 1 • +t • 1

L I ... + 1 - 1 1 :t:-!** '1, * 1 + 1, r·-.··"i I ~ ---L -J I f-·-**--L. I* , I , # .--#-'1. I ,. a \ r ,--~ + # ' I+ -,.-----------T-----, + I -----1'.. ;--T ' .... - ,~, 

I I + I --=- lj.: -lli+ + t !_ I . : _I I '+ ~ + + J- + l.+ 'f:J # *- 1 + t~ --#--, J II I + I - - ! I I + I I - I -------- + 1- "+ ··,J # + ~~~·I I + I * - I I ~--=------L_ # ~+ #, .~+,:;, - I~ 1-r I L.--r-·+·------_... ___ .., IJ + ·-r-~-"T:t..+-, I . #I - 'r * * -~----:_--, I ; * I+ J _, # 1- I ' + I ' I I + '~ ' I \: I I - ' .:1: I I I + I I I I -! - +. ++ \ -- I I ••• , ++ + r - 1 I+ I • 1 1 +--------* * /1 . , 

!_ I ' ' I I *+ I I \ - I I I f I - i .. '-' 

L - 1

- ~I_- ---3= j_ --l.- -*- _:_ -*- _ w_-:_ _i:: --~-~ 1

--=-:i- -~~- t -. ##TL' 

L..- ~---l'+\J '1-1 # * .... 0 50 100 200 KILOMETERS "1 r- # * ~" f I_!# .~ 

50 100 MILES / __ 1_ l _::_ ,' 

SYMBOL AND PERCENTAGE OF TOTAL SAMPLES 

10 19 24 24 23 

Geometric mean 49 

Geometric deviation 1.55 

Analytical error variance 

~250 

(percent of total variance) 3 

Number of analyses 1140 

w 

a: 

u.. 

0 

Q 

N CCI N ~ ~ ~ ~ ~ ~ ~ ~ 

ZINC. IN PARTS PER MILLION 

FIGURE 43.-Zinc distribution in selected agricultural soils 

of Missouri. Map symbols colTespond to frequency classes 

as shown in the histogram. 
H54 GEOCHEMICAL SURVEY OF MISSOURI 

'- +-- --r- r +- : -, - - ~ - - --r - =f- ~-~ r r- - r, - l +- - T -+ '\. 

\ + 'I I + t I I + ' I + +' - + + - r+ + I* * + ' ~- I I~ \ I + I " + - * / +I 4 + I + ' • * I + I~- _J -1i +I I . I + L---- -~' I ;-> + I +, + I + -t<++ * I \ .... L!+_,_;__ 1 * . ' *+ ! + + , 1 r--:r--,---t_:_~J + ' ) * I + I *+ I ,-----' + + I ' --+ I ,+- * * r - + + ' + I - + I I I I - i I ~+ + + r- --t-f 

' r---+--i + L~,J-±-w-l + +· +, , '+ 1 +. + ' 

' +\+ + t-----ll* +I+ * +I I + -tl I'*' I - t + +I 

"'._1 ++ ,..-+' _,. + l__±_ __ t~-, ----:r:-,--1-----~* :1 ++ +\ .v~ + I I! *+ '+ I + + I '*'-r:r---'F•-,-----~ 

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>- u 

z 

w 

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500 

/·J- + r.- Y + + I , 1+/ f-1 + + +L + k 

I + +:+ + I +I + < * I + ± * ;<~>-- j"'lt+ + + I 

+ +I I + '* I ~)" * +/ + +I *-----1 -t-1 + I 

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1

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I + I + + '_jl- I_---..,-+ + I + ' + ' I 

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f 

' 1 :j! ::j: + . I -+ -+ + r ·1+ I ~ ::j: '\_+ ~ -=-.J. j :f: + f-.-_ * ~ 1 \.. I + 1 +• * ·~-, + r , *-:;.--, + * , - -~. + -...± -!~ **.""+--++I + i ++ It:_.--< -t ' I +** I + I* + * I + ++ + -:+--;+ -fj I I +I •I + : +}-> + + ~ 1 ·---, + r' ++*!!_, _ _r_,..... __ *I t+ ~ 1 I + · -r, * ...._, 

I

* +* I* 4-,-~---~j+ + , **\,J'**' i+ 1 '+ I -r'+. / + \ + + ' + ' . ~ +. I I I -li- ~--- ~- -, I + + ' "'* " I *+I -t- * ) ++ 1 :t- l' '+ -t< + ' + I +' I L ------'f-..J I·, ' + -to -:t;----- + + + I * * + I * .... ' t I I --~· I + +-"':1 + + -t- I 

: ** * ·t ____ ~ :r ~ * ' +- + ~ __ j __ _j_ + * -t- '----~-, ';t-)--;~-~------,3 . .....p-'\...) 

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+ ' ** ' -It- + + ' I + I ++-+ "1, + 1- * + r·-"1"·.- "' 

J 

* .... :t:;'*' + -f, + I I I * I . __,' + \ 

---#---!J * * :f-**--:1--.._.__ I* , + ' + ---'i'~ ·~ ..,.. \ ( I * I * + ' *I ~-----------;-*--#l I i ---4"::!_ * + ;~--,t* \'1<1' I >, \ 

**   "_=:_ _ _. __ lj;-+~**  ++ t-! , 1 + -'* ' + '* 1 .,.. s- ,+ r=-J '+-- 1 * 1 + '*4-*- I + * I I 1- * -------- + + ( -t- -- I I* I ** *'I***+' + I - + i -t- ,-,-----' *+ c,-1* # .~+1:; - J---L **' -1'-1* * l..--.::.--+·------1------"" ~ - L-,.-~."T- -+-, + \ -1 -.- ·.,- ** -~--~ * ' i - +, -f. +· * ++ i ' + + i * ' + ++ \.,~ ' -t- \.

1 

--' J 

'++ # ** I'*+ * I ' * ! + ' ' -1*' + *· +:-~=- -_I_-! I \ I I 

~ ' ' ! I* II I + \ ** I **I-t+ ( -· - ... f.J L I - T. + I I + I I + ' * + I* ,-I* - I' ' -I I - • j 

- - - - - -- _, - --...~. - - - - ·- -' - - ~ - - _I - - - .... - - - .J -',.. r I -..., 

SYMBOL AND PERCENTAGE 

OF TOTAL SAMPLES 

9 15 I 49 1 21 6 

I I+ I+ # 

I I 

I I 

50 100 

50 100 MILES 

'"'I ~---;"-·1'\j \1 ' - I ,.4__-: 

200 KILOMETERS ( +)- _, , - I , ___ .:.. _, 

Geometric m~an 310 

Geometric deviation 1.53 

Analytical error variance 

(percent of total variance) 50 

Number of analyses 1140 

:::> 250 

d 

w 

a: 

LL. 

ooooooo 

.-..o..noooo - - N C'l? LO ,..._. 

ZIRCONIUM, IN PARTS PER MILLION 

FIGURE 44.-Zirconium distribution in selected agricultural 

soils of Missouri. Map symbols correspond to frequency 

classes as shown in the histogram. 


Geochemical Classification by 

Factor Analysis of 

Missouri Agricultural Soils 

By RONALD R. TIDBALL 

GEOCHEMICAL SURVEY OF MISSOURI 

G E 0 L 0 G I C A L S U R V E Y P R 0 F E S S I 0 N A L P A P E R 9 5 4 -I 

A multivariate study of agricultural soils from 

1140 locations in Missouri by Q-mode and R-mode 

factor analysis 

CONTENTS 

Abstract ....... . 

Introduction . . . . . . 

Acknowledgments 

Samples ....... . 

Q-mode factor analysis 

Compositional model of Missouri soils . 

Residuals ........... . 

Naming the factors . . . . . . 

Oblique composition loadings 

R-mode factor analysis 

Discussion . . . . 

Epilogue ..... 

References cited 

ILLUSTRATIONS 

FIGURE 1. Surficial deposits of Missouri . 

2. Geometry of sample vectors 

3. Factor variance diagram . . 

4. Q-mode oblique factor Q-I . 

5. Q-mode oblique factor Q-U 

6. Q-mode oblique factor Q-UI 

7. Q-mode oblique factor Q-IV 

TABLES 

Page 

I1 

1 

1 

1 

2 

5 

7 

8 

10 

16 

17 

18 

19 

Page 

I3 

4 

6 

12 

13 

14 

15 

Page 

TABLE 1. Methods of transformation with hypothetical data. . . . . . . . . . . . . . . I5 

2. Total and natural variation explained by preliminary 4-factor model of Q-mode 

factor analysis and analytical error variance of Missouri agricultural soils . 7 

3. Oblique composition scores, CmN, from Q-mode factor analysis of Missouri agricultural soils . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 

4. Original compositions of the 10 most extreme sample vectors near to factor Q-I 8 

5. Original compositions of the 10 most extreme sample vectors near to ·factor Q-II 9 

6. Original compositions of the 10 most extreme sample vectors near to factor Q-UI 9 

7. Original compositions of the 10 most extreme sample vectors near to factor Q-IV 10 

8. Descriptive notes for extreme samples near to each Q-mode factor . . . . 11 

9. Coefficients of correlation between R-mode sample scores and chemical values . 17 

III 

GEOCHEMICAL SURVEY OF MISSOURI 

GEOCHEMICAL CLASSIFICATION BY FACTOR ANALYSIS OF 

MISSOURI AGRICULTURAL SOILS 

By RONALD R. TIDBALL 

ABSTRACT 

Samples of 1140 agricultural soils from the State of Missouri were 

classified according to similarity of chemical composition by factor 

analysis. The samples were classified into four groups by Q-mode 

analysis using an oblique rotation. The factors are interpreted as clay, 

resistate, glacial material, and silica. 

R-mode analysis was used to identify the suite of elements associated with each group of samples. Lithium, iron, and several trace 

elements are associated with the clay factor; lithium and iron are 

likely structural elements but adsorption is also a dominant 

mechanism especially for the trace elements. Zirconium, titanium, 

ytterbium, and yttrium are associated with the resistate factor. The 

alkalies and alkaline-earth elements and aluminum are associated with 

the glacial factor; feldspars are more abundant in this material. Silicon 

and zironcium are the principal elements associated with the silica 

factor. 

Extreme samples in each group represented soils that were developed from (1) shale and clay alluvium, (2) residuum of limestone 

of Mississippian age, (3) loess, glacial till, and outwash, and (4) residuum of dolomite of Late Cambrian to Early Ordovician age. 

INTRODUCTION 

Samples of 1140 agricultural soils from throughout 

the State of Missouri were analyzed for total element 

concentrations. The geographic variations in the concentrations of each element are illustrated on maps in 

a companion paper (Tidball, 1984). With over 40 maps 

that represent individual elements it was most difficult 

to define associations among samples of similar composition or to suggest common origins or soil-forming processes. Clearly a multivariate approach that can examine 

the variations in all of the elements simultaneously was 

needed. 

In this report, Q-mode factor analysis is used to classify the samples by defining the interrelationships or 

similarities between the samples on the basis of element 

concentrations. The assemblage of elements associated 

with each group of samples is determined by R-mode 

factor analysis. The extreme types of samples are 

characterized by their composition and by their probable mineralogy. The identity of the Q-mode factors is 

deduced from the geographic distributions of the sample-vector loadings. 

ACKNOWLEDGMENTS 

Soil samples were obtained through the cooperation 

of the Statewide staff of the Extension Division of the 

University of Missouri under the supervision of Dr. 

Walter F. Heidlage, Program Coordinator, Extension 

Environmental Health. Chemical analyses of all samples 

were done by the U.S. Geological Survey in Denver, 

Colorado and Reston, Virginia by the following: L. A. 

Bradley, semiquantitative spectrograph; Johnnie Gardner and Violet Merritt, magnesium, and sodium; I. C. 

Frost, G. T. Burrow, and G. D. Shipley, carbon; J. 

P. Cahill, cadmium; J. A. Thomas, lithium and zinc; 

J. S. Wahlberg, M. W. Solt, and Mike Brown, X-ray 

fluorescence; R. L. Turner, mercury; F. W. Brown, 

Joseph Budinsky, B. A. McCall, Leung Mei, and 

Roosevelt Moore, arsenic and fluorine; A. J. Bartel, iodine; A. J. Bartel, E. Brandt, J. P. Hemming, R. J. 

Knight, H. T. Millard, R. J. Vinnola, R. J. White, uranium and thorium. Computer programs for mechanical 

plotting were written by M. R. Mall. Discussions with 

A. T. Miesch concerning the use and interpretations 

of his computer programs for factor analysis are gratefully acknowledged. 

SAMPLES 

Methods of sample collection and methods of laboratory analyses were described previously (Tidball, 1984). 

The soil samples, which represent the plow zone (A 

horizon, 0-15 em in depth), were collected in each of 

the 114 counties of the State at the rate of 10 per 

I1 
I2 GEOCHEMICAL SURVEY OF MISSOURI 

county. In most counties, the sampling localities were 

scattered extensively throughout the county. The sample-vector-loadings maps illustrate the locations of the 

sampling sites. 

The samples represent soils that were developed 

from all of the major parent-material types that occur 

in the State. The glaciated terrain of the northern half 

of the State includes glacial till and loess (fig. 1) and 

outwash alluvium in the valleys of the Missouri and Mississippi Rivers. Surficial material on the Mississippi Alluvial Plain is alluvium from both the Mississippi and 

the Ohio Rivers (Krusekopf, 1966). The Ozark Plateaus 

province is a very old, deeply weathered, nonglaciated 

land surface developed on cherty carbonate rocks. The 

northern flanks of the plateaus near the southern limit 

of glaciation support a mantle of loess that diminishes 

in thickness toward the south. 

Q-MODE FACTOR ANALYSIS 

The general methodology and application of factor 

analysis in the geological sciences was reviewed by 

Joreskog, Klovan, and Reyment (1976). The method of 

Q-mode analysis used here is the conventional form as 

described by Miesch (1976a, b, c) for use with geochemical and petrological data. Q-mode analysis was chosen 

as a tool for this study because one of its uses is that 

of classifying a large number of samples into a minimum 

number of common assemblages, particularly where 

each sample has numerous measured properties and 

where the genetic significance of those properties is unknown. The operational objectives of Q-mode analysis 

are (1) to determine the minimum number of end members (extreme sample types), (2) to find the compositions of the end members, and (3) to describe the proportions of each end member that are mixed in each 

sample. These proportions (sample loadings) become a 

new multivariate property of each sample that when 

mapped illustrate the geographic components that are 

associated with each end member. 

It will be helpful to view each sample initially as a 

mixture of a number of actual or theoretical end members equal to the number of chemical properties meassured. Several of these properties are probably correlated with each other because of one or more common 

controlling mechanisms. In a more concise model, therefore, the number of end members required to describe 

a given amount of variation in the data can be reduced 

to a much smaller number than the original number 

of properties. 

Samples, for which a large number of properties (variables), M, have been determined, can be represented 

as vectors with a common origin in M -dimensional space 

where each dimension is represented by a reference 

axis (factor). It is common when numerous samples are 

so represented that the sample vectors tend to cluster 

into a space that can be described by fewer dimensions, 

m. The factors represent the compositions of theoretical 

end members. As each sample may be viewed as a mixture of the end-member compositions, so each sample 

vector is a linear combination of the end-member vectors (factors). The location of each sample vector in 

space is specified by the coordinates (loadings) of the 

vector as projected on each factor. 

Factors that are orthogonal to each other are uncorrelated. That is, if two orthogonal factors each represent particular processes, then the two processes are 

independent of one another. If the factors are not orthogonal, then the processes are interdependent. A factor 

may be viewed as the end member of a mixture series 

or as a type sample for a classification system. The 

hypothetical composition of the factor (expressed in normalized units of measurement) is specified by inital factor "scores." The locations of the factors in relation to 

the sample vectors determine the magnitude of the factor scores, which appear in a scores matrix, FMM· When 

the sample vectors are projected onto the factors, the 

initial loadings of the sample vectors become fixed and 

constitute the loadings matrix, ANM (where N is the 

number of samples, M is the number of variables). According to the general Q-mode analysis model these two 

matrices are related to the normalized data matrix, 

ZNM, with m equal toM, 

(1) 

but it is also possible to estimate Z NM with fewer than 

M variables, that is, m is less than M, 

.... 

ZNM=ANmFmN (2) 

In either case, equations 1 and 2 estimate the normalized data matrix, ZNM, which is not in the original 

units of measurement rather than the original data matrix, XNM, which is in original units. Miesch (1976b) described a procedure whereby XNM could be estimated, 

XNM=PNmCmN, (3) 

by transforming ANm to PNm, a matrix of sample-vector 

composition loadings and F mN to CmN, a matrix of com-
CLASSIFICATION BY FACTOR ANALYSIS, AGRICULTURAL SOILS 

0 50 100 200 KILOMETERS 

EXPLANATION 

C) Alluvium 

Glacial deposits 

CJ Silt-clay residuum of shales 

and clays, locally sandy D Cherty-clay residuum of 

limestone and dolomite 

Bouldery residuum of igneous rocks 

[,:':'":,';:'.:,"d Cedar Glades vegetation area 

- Southern limit of glaciation 

--5-- Approximate thickness of 

loess, in meters 

FIGURE !.-Surficial deposits of Missouri (Stout and Hoffman, 1973; Kuchler, 1964). 

13 
14 GEOCHEMICAL SURVEY OF MISSOURI 

tz 

w 

u 

a: 

~50 

a: 

0 

~ ~ 

4 

50 100 

MINOR PERCENT 

A. Original data 

1.0 2 

z 

0 

i= 

a: 

0 

0.... 

~0.5 0.... 

a: 

0 

~ ~ 

3 

L-----------~----------4 0.5 1.0 

MINOR PROPORTION 

C. Normalized scaled data 

z 

0 

i= 

a: 

0 

0.... 

1.0 2 

~ 0.5 3 0.... 

a: 

0 

~ ~ 

0.5 

MINOR PROPORTION 

B. Sea led data 

D. Spherical projection 

(PI, principal components 

axis; Ql, oblique axis) 

4 

1.0 

FIGURE 2.--Geometry of sample vectors for different forms of the same hypothetical data. 

position scores. PNm is derived by a transformation of 

ANm that fixes the signs of the loadings and changes 

them into true proportions that sum to unity across 

the rows. C mN is derived through a transformation of 

F mN that restores the original units of measurement 

to the scores. Recalling the operational objectives of 

Q-mode analysis stated previously, C mN fulfills objective 2 and P Nm fulfills objective 3. 

The original chemical data are expressed as oxides 

and adjusted to sum to a constant of 100 percent for 

each sample (each row of the data matrix is one sample). Miesch (1976b) showed that the constant row-sum 

is desirable to be able to derive a Q-mode model in 

terms of the original data. The data are then transformed first, by columns (scaling) and second, by rows 

(normalizing). These transformations are illustrated by 

means of hypothetical data as shown in table 1, and 

the resulting geometry of the sample vectors for these 

data appears in figure 2. 

'fhe original data matrix, XNM, in table 1A is scaled 
CLASSIFICATION BY FACTOR ANALYSIS, AGRICULTURAL SOILS 15 

TABLE 1.-Methods of transformation with hypothetical data 

A. Original data, XNM =matrix of Xij values in ith row and jth colum 

Samples= N = 4, Variables = M = 2. 

Oxides, percent 

Samples Major Minor Row sum 

1 90 10 

2 100 0 

3 80 20 

4 60 40 

xmaxj 100 40 

xminj 60 0 

B. Scaled data 

xii = (xij- xmin;)l(xmaxj- xminj) 

1 0.75 0.25 

2 1.0 0 

3 .5 .5 

4 0 1.0 

C. Normalized scaled -iata, Z NM = matrix of xij 

xij= xi)(}: xilf12 

j 

1 

2 

3 

4 

0.95 

1.0 

.71 

0 

0.32 

0 

.71 

1.0 

100 

100 

100 

100 

1.0 

1.0 

1.0 

1.0 

Row-sum squares 

1.0 

1.0 

1.0 

1.0 

to range from zero to one within each column as shown 

in table 1B, where xii is expressed as a pr~portion of 

th~ ra~ge. The purpose of scaling is to equalize the 

weighting of the variables so that oxides present in 

large amounts (major) do not have an inordinate effect 

on the factor model. Scaling has the effect of spreading 

out the original cluster of sample vectors; vectors 2 and 

4, for which the samples each contain the largest 

amoun~s ~f the major and minor elements, respectively, 

now comcide with a factor. (See figs. 2A and 2B.) 

The scaled data are then row normalized by dividing 

each scaled value, x'ij, in the row by the square root 

of sum of squares for the row giving the matrix Z NM 

in table 1C. The purpose of normalizing is to adjust 

the sample vectors to unit length (fig. 2C). The comparison of vectors is now more convenient because of 

being able to compute the communalities (communality 

equals the square of the vector length after projection 

into a smaller m-space). The diagram of sample vectors 

in figure 2C can also be viewed as a slice of a sphere 

as in figure ?.JJ. The locations of the first two principalcomponents factors (Joreskog and others, 1976, p. 74) 

are shown at P1 and P2; oblique factors, Q1 and Q21, 

are shown at one of many possible locations. These factors will be discussed later. 

COMPOSITIONAL MODEL OF MISSOURI SOilS 

Analyses of 31 elements were initially included in the 

factor analysis. These were aluminum*2 , arsenic, barium*, boron*, calcium*, carbon, chromium*, cobalt*, 

copper*, fluorine, gallium*, iron, lanthanum*, lead*, 

lithium*, magnesium*, manganese, mercury, nickel*, 

phosphorous, potassium*, scandium*, silicon*, sodium*, 

strontium*, titanium*, vanadium*, yttrium*, ytterbium*, zinc, and zirconium*. The ranges of concentration 

for most of the elements are well within the limits of 

determination of the analytical method that was used; 

that is, the elements have uncensored frequency distributions. The lower end of the ranges for a few elements, however, is less than the lower limit of determination of the method, and some of the values are indeterminate (censored). Where the number of censored 

values is small, they were replaced with arbitrarily 

small values (equal to 0. 7 times the lower limit of determination) to complete the frequency distribution. 

The analytical values of each element were expressed 

in percent of the common oxide except fluorine and 

mercury, which are assumed to occur in the soils either 

in ionic or in elemental form. All the values were first 

adjusted to a common sum of 100 percent, and then 

the data were scaled and normalized as described previously. 

The minimum number of end members (fulfills objective 1), m, is determined from the factor-variance diagram (fig. 3), which is a plot of the proportion of variance accounted for (coefficient of determination from 

Miesch, 1976b, p. G 19) against the number of factors 

in the model. Factors that explain the variation in several variables simultaneously are called common factors 

(Harman, 1967, p. 15; Miesch, 1976b, p. G21). A unique 

factor explains a large part of the remaining variance 

(including error) in only one variable. Conventionally, 

the factor model is simplified by retaining only the common factors. 

The common factors may be very effective in describing the variance of some variables but ineffective for 

certain others. In order to enhance the effectiveness 

of the final model, after an initial computation those 

'Labels of Ql and Q2 distinguish fat-tors in demonstration from QI, QII, and so forth 

used later in actual factor model, but the concept remains the same. 

2Elements with asterisk were retained in t.he final factor analysis after omitting elements 

that were poorly described by the factor model. 
16 

a: 

0 

u. 

0 

UJ 

fz 

:::::> 

0 

u 

u 

<( 

UJ vo ~ Fe203 

~ 0.5 

a: 

~ u. 

0 

z 

0 

i= 

a: 

0 

a.. 

0 

a: 

a.. 

2 3 

GEOCHEMICAL SURVEY OF MISSOURI 

EXPLANATION 

--0 AI203 --~ K20 ---0 SrO 

--0 8203 --· La203 ---/l. Ti02 

--/l. BaO --EB u2o --- + vo2 

--+coo --11 MgO ---Xv2o3 --X cra3 ---EB Na20 --- <> Yb£03 

--<> CuO --II NiO --- V Zr02 --V Fe203 ----D Sc203 

--IBIGa203 --- D Si02 

4 5 6 7 8 9 10 

NUMBER OF FACTORS 

FIGURE 3.-Factor variance diagram for 22 oxides in Q-mode factor analysis. 
CLASSIFICATION BY FACTOR ANALYSIS, AGRICULTURAL SOILS 17 

oxides that were poorly described were removed to 

eliminate the possiblity of spurious or accidental effects. 

The criteria that were adopted for retaining an oxide 

were that (1) the variation in the data had to reflect 

mostly (arbitrarily set at 50 percent) natural variation 

rather than analytical error, and (2) the variation that 

was explained had to be on the common factors. Excess 

analytical error was the basis for most of the omissions 

(table 2). A total of 22 elements were retained for 

further analysis. (See footnote 2.) The factor-variance 

diagram in figure 3 indicates that four factors accommodate most of the variables explaining an average of 60 

percent of the total variance. The few variables that 

are not well explained by four factors generally require 

numerous additional factors. 

A factor model was derived initially using the varimax criterion in which the factors are orthogonal. The 

TABLE 2.-Total and natural variation explained by a preliminary 

4-factor model of Q-mode factor analysis and analytical error variance of Missouri agricultural soils 

[Values, percent. Asterisk(*), variable is included in the final factor analysis] 

Analytical 

Oxide 

SiOr------------- 26 

Na 2o-------------- 2 

Alzor------------ 10 

Fezor------------ 4 

vo2--------------- 43 

sc 2or------------ 39 

Liz o--------------

SrO--------------- 31 

ca2or------------ 27 

ZrO--------------- 61 

KzO--------------- 5 

Ti02-------------- 48 

Bao--------------- 45 

MgO--------------- 5 

NiO--------------- 39 

cror------------- 38 

Yzor------------- 54 

CoO--------------- 49 

Ybzor------------ 63 

La 2or------------ 51 

As 2or------------ 17 

MnO--------------- 17 

Ca0--------------- 4 

CuO--------------- 56 

B2or------------- 76 

Co2---------------

ZnO---------------

Seo2-------------- 68 

P 2°5-------------- 20 

F----------------- 89 

PbO--------------- 56 

Hg---------------- 65 

Proportion of variance explained 

by the factor model 

Total Natural 1 

94 100* 

92 94* 

88 98* 

78 81* 

77 100* 

u. 100* 

7 5 7R* 

73 100* 

73 100* 

67 tnO* 

64 67* 

60 100* 

59 100* 

55 58* 

48 79* 

46 74* 

45 98* 

44 R6* 

40 100* 

35 71 * 

31 37 

27 33 

26 27 

25 57* 

24 [00* 

24 25 

19 20 

15 47 

10 

27 

1 Percentage of natural variation explained is normalized to natural base: 

Total variance, pet ~--=------~ x 100 =natural variance explained, percent. ( 100 - anal. error, pet) 

four sample vectors of most extreme composition were 

then identified (Miesch, 1976, p. G22). Because the composition scores of the varimax factors contain numerous 

negative values and were judged, therefore, to be unrealistic, an oblique model was derived by moving the 

factors to nonorthogonal positions that are very close 

to the extreme sample vectors, respectively. The compositions of the factors were then more nearly equivalent to those of nearby sample vectors which facilitates 

the interpretations of the factors. The oblique composition scores, CmN, are given in table 3. 

TABLE 3.-0blique composition scores, CmN, from Q-mode factor 

analysis of Missouri agricultural soils 

[Values in parts per million, except as noted in percent] 

Factors Oxide 

Q-I 0-II Q-III o-rv 

Al2o3, percent------- 19.7 5.0 10.6 3.0 

B2or---------------- 97 170 99 76 

Bao------------------ 950 840 1040 170 

Coo------------------ 34 18 6.8 7. 2 

Cro3----------------- 240 140 110 30 

CuO------------------ 59 15 14 7. 9 

Fe2o3 , percent------- 9.2 2.3 2.8 1.2 

Ga2o3---------------- 45 11 20 4.3 

KzO, percent--------- 2. 7 1.6 2.7 .79 

Lazor--------------- 95 69 46 25 

Li2o----------------- 130 40 43 30 

MgO, percent--------- 1.7 .12 .68 .061 

Na2o, percent-------- .71 .51 1.7 .16 

NiO------------------ 60 11 22 7.4 

sc2o3---------------- 33 10 11 5.4 

SiOz percent--------- 65.2 89.0 80.9 94.5 

SrO------------------ 280 98 270 21 

TiOz, percent-------- .58 I. I .45 .28 

voz------------------ 370 97 120 20 

Y2o3----------------- 75 68 28 24 

Ybzor--------------- 6.0 5.9 2. 7 2.3 

zro2----------------- -49 1200 360 190 

RESIDUALS 

Residuals represent the discrepanc!es between the 

original compositions of the samples, XNM' and thereproduced compositions, XNM, as computed from the factor model by equation 3. Thus residuals serve as measures of how well the factor model represents the samples. The matrix of residuals, RNM' is computed as, 

(4) 

Even though four factors account for only 60 percent 

of the variation, the residuals for all samples were 

found to be small. Because the factor model is represented in fewer dimensions than the original data 

was, the residuals are associated with all of the un-
I8 GEOCHEMICAL SURVEY OF MISSOURI 

specified factors that were omitted. To insure that none 

of the unspecified factors had an important and overlooked systematic geographic component, the residuals 

for all samples were plotted on maps (not shown here). 

The maps exhibit a more or less random pattern indicating that a systematic component is absent'. Analytical 

error and sampling error are examples of random components. 

NAMING THE FACTORS 

The identity of each factor was judged by the character of the extreme sample vectors that lie close to the 

oblique factor. Character in this sense implies sample 

composition, sample locality, parent material, and inferred mineralogy. The original compositions of the 10 

most extreme sample vectors for each factor are given 

in tables 4-7 in order of decreasing distance away from 

the factor. The scores will differ slightly from the original compositions of the most extreme sample vectors 

because the factors were projected into a space of fewer 

dimensions than that of the original data. 

Within each sample group, the sample vectors have 

similar compositions and the samples were collected 

from similar sites or parent materials. Descriptive notes 

for each sample group are given in table 8. 

Factor I represents a composition with comparatively 

large amounts of nearly all of the heavy metals plus 

Al20 3, Fe20 3, K20, and MgO, but a comparatively small 

amount of Si02• Sample vectors close to factor I represent soils developed from clayey alluvium that occurs 

on the flood plains of the major rivers, the Missouri 

and the Mississippi. The sample of the most extreme 

vector was collected from a soil developed from a black 

shale of the Chattanooga Formation. Factor I is, therefore, named the "clay factor." 

Factor II represents a composition with comparatively large amounts of B20 3, Si02, Ti02, and Zr02, 

and nearly all other oxides occur in intermediate concentrations. Sample vectors close to factor II represent 

soils on upland sites that were developed from cherty 

residuum of limestone in the Kaskaskia sequence that 

occurs in southwest Missouri. These strata range in age 

from Middle Devonian to Late Mississippian (Connor 

and Ebens, 1980). Factor II is named the "resistate 

factor." 

Factor III represents a composition that is similar 

to that of factor I m terms of some oxides such as B20 3, 

BaO, K20, SrO, and Ti02 • There are comparatively 

large amounts of N~O and Si02 but all other oxides 

have concentrations equal to one-half or less of factor 

TABLE 4.-0riginal compositions ofthe 10 most extreme sample vectors near to factor Q-1 

[Sample vectors aiTanged in order of increasing distance from the factor. Values in parts per million, except as noted in percent] 

Sample vectors 

Oxide 

D146417 D145447 D146005 D146278 D145813 D145956 D145610 D146518 Dl45457 Dl45734 

Alzo3, percent 18.8 16.5 16.2 16.8 14.5 15.6 16.6 16.8 14.8 15.2 

Bzor--------- 120 76 120 120 110 120 120 54 180 100 

BaO----------- 420 920 970 940 870 940 930 940 640 850 

CoO----------- 24 22 16 23 21 23 15 ll 22 21 

Cro3---------- 170 160 170 160 150 160 160 120 150 150 

CuO----------- 47 44 110 110 70 75 45 30 28 20 

Fe2o3 , percent 6.7 6.4 7. l 6.1 6.3 6.5 5.9 6.6 6.5 5.7 

Ga2or-------- 51 32 33 32 30 32 32 24 31 22 

K2o, percent-- 5.6 2.9 3.4 3.0 3.0 2.8 3.3 2.5 2.7 2.5 

La 2or-------- 74 97 73 70 65 9il 98 99 93 il9 

Li2o---------- 89 120 99 120 110 100 100 110 110 98 

MgO, percent-- 2.3 1.2 1.7 1.6 1.6 1.2 2.0 1.2 .92 1.1 

Na2o, percent- .23 . 70 . 78 .il4 . 77 . 79 .80 .71 .ill . 72 

NiO----------- 110 45 48 46 99 76 30 31 43 41 

sc2or-------- 29 27 29 28 26 28 27 18 26 25 

Si02, percent- 65.6 71.0 70.0 70.9 72.6 72.3 70.4 71.3 73.1 74.0 

SrO----------- 150 280 300 280 200 210 420 210 200 190 

Ti02, percent- .63 .98 .62 .60 .93 .60 .59 .60 .95 .54 

vo2----------- 310 290 300 290 270 290 290 200 280 270 

Y2or--------- 48 75 47 46 71 76 45 46 72 69 

Yh2or-------- 4 4 4 6 4 4 4 

zro2---------- 120 240 250 160 300 490 240 110 310 150 
CLASSIFICATION BY FACTOR ANALYSIS, AGRICULTURAL SOILS 

TABLE 5.-0riginal compositions of the 10 most extreme sample vectors near to factor Q-II 

[Sample vectors aJTallged in order of increasing distance from the factor. Values in parts per million, except as noted in percent] 

Oxide 

Al 2o3 , percent 

B203----------

Ba0-----------

CoO-----------

cror---------

Cuo-----------

Fe 2o3 , percent 

ca2or--------

K20, percent--

La2or--------

Li20----------

Mg0, percent--

Na2o, percentNiO-----------

sc 2or--------

Sio2, percentSrO-----------

Ti02, percentvo2-----------

Y2or---------

Yh 2or--------

zro2----------

Sample vectors 

0145511 0145912 0145892 0145987 0146292 0145985 0145973 0145952 0145968 0145889 

5.59 

180 

870 

10 

150 

10 

1.9 

11 

1.6 

66 

46 

.27 

.39 

10 

12 

88.7 

93 

1.3 

91 

71 

4 

110 

6.09 

260 

640 

15 

110 

43 

2.4 

11 

1.8 

67 

57 

.32 

.33 

15 

12 

87.8 

5.28 

170 

830 

20 

100 

13 

3. 1 

10 

1.6 

87 

48 

.24 

.38 

20 

11 

88.0 

95 87 

.96 1.2 

94 120 

100 67 

9 

110 

6 

100 

6.18 

110 

380 

15 

150 

22 

5.6 

15 

1.3 

67 

52 

.30 

.33 

22 

12 

85.1 

5.37 6.02 

104 180 

600 870 

14 21 

150 150 

20 14 

2.6 2. 7 

10 15 

1.3 2.0 

63 65 

46 53 

.22 .29 

.48 .46 

21 

12 12 

88.6 87.3 

95 89 92 

.96 1.3 

190 120 

100 68 

9 

110 

6 

100 

130 

99 

9 

110 

.93 

5.55 

190 

650 

10 

160 

22 

2.8 

11 

1.6 

68 

50 

.24 

. 39 

10 

12 

88.2 

7.81 7.03 

190 110 

900 920 

15 22 

160 160 

29 29 

2.8 3.6 

15 16 

2.0 1.4 

94 69 

52 56 

.34 .33 

. 52 . 42 

22 15 

12 13 

85.4 85.9 

6.42 

100 

840 

20 

100 

13 

2.8 

10 

1.6 

38 

51 

.29 

.36 

14 

11 

87.1 

96 95 97 89 

.96 .96 .98 1.2 

94 130 130 120 

73 73 74 41 

110 110 110 

4 

100 

TABLE 6.-0riginal compositions of the 10 most extreme sample vectors near to factor Q-Ill 

[Sample vectors aJTallged in order of increasing distance from the factor. Values in parts per million, except as noted in percent] 

Oxide 

Al 2o3 , percent 

B2or---------

Bao-----------

coo-----------

cror---------

cuo-----------

Fe 2o3 , percent 

Ga2o3---------

K2o, percent--

La2o3---------

Li20----------

Mg0, percent--

Na2o, percentNiO-----------

sc 2or--------

Sio2, percentSr0-----------

Ti02' percent--

vo2-----------

Y2or---------

Yb203---------

Zr0T---------

Sample vectors 

0146327 0146480 0145523 0145455 0146575 0146042 0146524 0146089 0145873 0146554 

9.55 

100 

120 

9 

61 

20 

2.5 

21 

2.7 

87 

41 

. 71 

1.6 

20 

11 

82.1 

9.62 11.9 9.89 11.1 

48 100 110 110 

84 121 86 120 

10 10 10 

62 150 150 110 

9 14 14 21 

2.2 2.9 2.6 3.3 

14 22 -22 22 

2.5 2.7 2.5 2.9 

38 63 39 39 

41 51 45 60 

.90 .88 .90 1.1 

1.5 1.6 1.6 1.5 

20 27 21 28 

8 12 12 12 

82.7 79.2 81.7 79.3 

6.87 

49 

85 

42 

10 

1.4 

10 

2. 1 

38 

19 

.27 

1.4 

21 

6 

87.6 

10.7 

48 

84 

41 

13 

2.8 

10 

2.6 

38 

51 

• 7 5 

1.3 

14 

11 

81.5 

8.25 8.63 12.5 

76 100 110 

92 60 89 

10 10 10 

68 62 110 

10 14 21 

2.5 2.7 3.3 

24 22 23 

2.1 2.6 2.8 

41 38 40 

36 39 61 

.92 .64 1.6 

1.6 1.5 1.5 

30 21 43 

13 12 12 

84.0 83.4 77.6 

630 250 260 260 260 190 190 140 190 270 

.53 .36 .54 .55 .56 .27 .27 .39 

120 87 180 130 130 53 87 96 

40 27 41 28 42 21 20 30 

4 

220 430 

4 

440 

4 

300 

4 

230 220 140 240 

• 36 . 57 

88 130 

21 43 

220 

4 

230 

19 
I10 GEOCHEMICAL SURVEY OF MISSOURI 

TABLE 7.-0riginal compositions of the 10 most extreme sample vectors near to factor Q-IV 

[Sample vectors arranged in order of increasing distance from the factor. Values in parts per million, except as noted in percent] 

Oxide 

D146537 D146569 D146399 D146229 

Al 2o3 , percent 3.28 2.31 4.31 3.16 

B2or--------- 70 74 69 100 

BaO----------- 183 193 181 176 

CoO----------- 7 3 4 9 

Cror--------- 42 160 62 41 

CuO----------- 10 10 9 13 

Fe 2o3 , percent 1.1 1.5 2.3 1.6 

Ga2o3---------

K20, percent-- .ss .46 .65 .42 

La2?r-------- 38 41 38 37 

Li 2o---------- 24 17 42 27 

MgO, percent-- .13 .10 .15 .18 

Na2o, percent- .12 .13 .14 .12 

NiO----------- 10 10 13 

sc2or-------- 6 <4 8 6 

Sio2 , percent- 94.5 95.1 92.0 94.1 

SrO----------- 26 41 38 37 

Ti02 , percent- .27 .29 .36 .35 

vo2----------- 27 28 53 51 

Y2or--------- 21 15 27 40 

Yb 2or-------- 1 4 

ZrOz---------- 220 230 220 210 

I. Sample vectors close to factor III represent soils developed either from sandy or silty alluvium on the 

major river flood plains or from loess. It is probable 

that the prominent deposits of loess that occur on the 

bluffs along the river valleys are the source of at least 

part of this type of alluvium. Factor III is named the 

"glacial factor" because the samples distinctly outline 

(fig. 6) the glaciated terrain and deposits of glacial outwash. 

We see there are some differences between the 

oblique composition scores of factors I and III (see table 

3) but some similarities in the sites (flood plains) of 

the extreme samples that are associated with each factor. The differences are believed to be due to the 

mineralogical compositions: samples near factor I contain about 60 percent clay minerals, 30 percent quartz, 

and 10 percent feldspar; samples near factor III contain 

about 25 percent clay minerals, 50 percent quartz, and 

25 percent feldspar. (Percentages were derived from 

X-ray diffraction analysis.) These feldspars surely explain the relatively large N ~0 and K20 scores of factor 

III. 

Factor IV represents the lowest concentrations of all 

Sample vectors 

D145828 D145533 Dl46550 Dl45750 Dl46237 Dl45958 

3.10 2.15 2.09 3.12 3.25 3.92 

100 100 67 100 110 110 

230 240 180 170 240 250 

9 4 9 10 28 

30 31 100 40 31 32 

13 13 9 9 28 

1.3 .75 1.6 1.2 1.1 1.5 

5 5 5 

1.3 1.1 .42 .83 1.3 .56 

36 <35 37 37 38 39 

29 23 22 34 21l 29 

.18 .18 .l() .12 .18 .17 

. 12 .19 .10 .19 .22 .IS 

20 10 7 7 21 

6 6 6 6 6 6 

93.5 95.2 95.3 93.9 93.5 93.3 

37 38 37 37 38 40 

.35 .36 .35 .52 .36 .37 

34 26 34 34 35 36 

26 21 26 20 21 43 

4 

210 290 420 210 220 230 

the oxides except 8i02 and Zr02• Sample vectors close 

to factor IV represent soils on upland sites that were 

developed from cherty residuum of dolomite of the Sauk 

sequence (mostly Jefferson City Formation) that ranges 

in age from Late Cambrian to Early Ordovician (Connor 

and Ebens, 1980). This residuum is the most thoroughly 

weathered material in the study area as suggested by 

the highest concentration of Si02 and the lowest concentrations of most other elements. Factor IV is named 

the "silica factor." The large concentration of Si02 represented by both factors II and IV reflects the contribution of chert, which is a significant constituent of the 

residuum. 

OBLIQUE COMPOSITION LOADINGS 

The oblique composition loadings, PNm, are too 

numerous to tabulate but are plotted as gray-level symbol maps in figures 4-7. The frequency distributions 

of loadings for each factor were divided into five classes 

with approximately 20 percent of the loadings being 

placed in each class. A symbol identifying each sample 

I appropriate to the class of its loading is plotted on the 
Sample 

Number 

Dl46417 

Dl45447 

Dl46005 

D46278 

Dl45813 

Dl45956 

Dl45610 

Dl46518 

Dl45457 

Dl45734 

Dl45511 

Dl45912 

Dl45892 

Dl45987 

Dl46292 

Dl45985 

Dl45973 

Dl45952 

Dl45968 

Dl45889 

Dl46327 

Dl46480 

Dl45523 

Dl45455 

Dl46575 

Dl46042 

Dl46524 

Dl46089 

Dl45873 

Dl46554 

Dl46537 

Dl46569 

Dl46399 

Dl46229 

Dl45828 

Dl45533 

Dl46550 

Dl45750 

Dl46237 

Dl45958 

County 

McDonald---

Bates------

Mississippi 

---do------

---do------

Lewis------

Saline-----

Grundy-----

LivingstonPike-------

McDonald---

Lawrence---

Newton-----

---do------

---do------

Dade-------

Barry------

Lawrence---

Greene-----

---do------

Jackson----

Ray--------

Mississippi 

---do------

Platte-----

Dunklin----

Pemiscot---

Ho 1 t -------

Pemiscot---

Perry------

Ripley-----

Reynolds---

Texas------

Carter-----

Douglas----

Ozark------

Cedar------

Oregon-----

Douglas----

Dent-------

CLASSIFICATION BY FACTOR ANALYSIS, AGRICULTURAL SOILS 

TABLE B.-Descriptive notes for extreme samples near to each Q-mode factor 

Site 

upland-----

flood plain 

---do------

---do------

---do------

---do------

---do------

---do------

---do------

---do------

upland-----

---do------

---do------

---do------

---do------

---do------

---do------

---do------

---do------

---do------

---do------

flood plain 

---do------

--do------

---do------

terrace----

flood plain 

terrace----

flood plain 

---do------

upland-----

---do------

---do------

---do------

---do------

---do------

---do------

---do------

Parent material Other remarks 1 

Samples associated with factor Q-I 

black shale-----------------

alluvium--------------------

---do-----------------------

---do-----------------------

---do-----------------------

---do-----------------------

---do-----------------------

---do-----------------------

---do-----------------------

---do-----------------------

Chattanooga Shale. 

Osage silt. 

Mississippi Alluvial Plain, Sharkey clay. 

Do. 

Do. 

Mississippi valley. 

Missouri valley, Wabash clay. 

Glaciated area, probable Sarpy series. 

Do. 

Missouri valley. 

Samples associated with factor Q-II 

cherty residuum of limestone 

---do-----------------------

---do-----------------------

---do-----------------------

---do-----------------------

---do-----------------------

---do-----------------------

---do-----------------------

---do-----------------------

---do-----------------------

Samples associated with factor Q-III 

probable loess--------------

alluvium 

---do-----------------------

---do-----------------------

---do-----------------------

---do-----------------------

---do-----------------------

loess-----------------------

alluvium--------------------

---do-----------------------

Missouri valley, Sarpy very fine soil. 

Mississippi Alluvial Plain. 

Missouri valley, probable Sarpy series. 

Missouri valley, Sarpy sandy loam. 

Mississippi Alluvial Plain, Dexter 

fine sandy loam. 

Mississippi Alluvial Plain, 

probable Sarpy series. 

Missouri valley. 

Mississippi Alluvial Plain, 

probable Sarpy series. 

Mississippi valley, probable Sarpy series. 

Samples associated with factor Q-IV 

cherty residuum of dolomite- Probable loess mixture. 

---do-----------------------

---do-----------------------

---do-----------------------

---do-----------------------

---do-----------------------

sandstone------------------- Krebs Formation (Pennsylvanian). 

cherty residuum of dolomite-

---do------ ---do-----------------------

---do------ ---do-----------------------

1soil series name given when known; for example Osage silt. 

Ill 
112 

250 

200 

>-

~ 150 w 

:::> 

d 

~ 100 u. 

50 

0 

cf 

GEOCHEMICAL SURVEY OF MISSOURI 

SYMBOL AND PERCENTAGE OF TOTAL SAMPLES 

14 I 22 I 22 118 I 24 

1 1 I+ I~ I # 

ID N Cl Cl 

cf d 

1 I I I 

I 

I 

I 

I 

~ ID c::; d d d 

GO ~ :;;: ,... N Ollt 

d d d d 

LOADINGS ON 

~ Cl 

CCI 

d d 

Q-1 

,... M CCI ,... d d 

FIGURE 4.---Q-mode oblique factor Q-1: sample-loadings 

map of Missouri with histogram and frequency-class symbols. 
CLASSIFICATION BY FACTOR ANALYSIS, AGRICULTURAL SOILS 

0 50 

50 

SYMBOL AND PERCENTAGE OF TOTAL SAMPLES 

300 16 I 23 118 23 20 

I 1 I+ ~ # 

250 

200 

>- u 

z 

w 

~ 150 

w 

a: 

LL 

100 

50 

0 

N 

N :! 8 s 

cf cf cf ci 

I I 

C) co co • ~ C) co co N • "" "' "' co .... ci ci ci ci ci ci ci ci ci 

LOADINGS ON Q-11 

N C) 

co en ci ci 

100 

co 

en 

ci 

200 KILOMETERS 

100 MILES 

FIGURE 5.-Q-mode oblique factor Q-11: sample-loadings 

map of Missouri with histogram and frequency-class symbols. 

113 
114 GEOCHEMICAL SURVEY OF MISSOURI 

0 50 

SYMBOL AND PERCENTAGE OF TOTAL SAMPLES 

300 22 17 19 23 19 

+I :~:I tt 

250 

>- 200 

u 

z 

w a 150 

w 

a: 

u. 

100 

50 

I I 

I I 

~ ~ s ~ ~ ~ ~ ~ m ~ c;ic;ic;icccccc::i 

LOADINGS ON Q-111 

100 

50 

200 KILOMETERS 

100 MILES 

FIGURE 6.-Q-mode oblique factor Q-III: sample-loadings 

map of Missouri with histogram and frequency-class symbols. 
CLASSIFICATION BY FACTOR ANALYSIS, AGRICULTURAL SOILS 

SYMBOL AND PERCENTAGE OF TOTAL SAMPLES 

300 14 23 23 17 23 

l,l+l:t +t 

250 

>- 200 

u 

z 

w 

:::> 150 

0 

w 

a: 

LL. 100 

50 

I I I 1 I I 

M~~b~~~~~~~ cyi cyi cyi c::i c::i c::i c::i c::i c::i c:i c:i 

LOADINGS ON Q-IV 

FIGURE 7.-Q-mode oblique factor Q-IV: sample-loadings 

map of Missouri with histogram and frequency-class symbols. 

115 
I16 GEOCHEMICAL SURVEY OF MISSOURI 

map at the location of collection. The maps, therefore, 

illustrate the locations of samples and their degree of 

similarity in composition to that of the factor. 

Samples closely associated (large loadings) with the 

clay factor (I) exhibit a wide distribution across several 

types of parent material, although the glaciated terrain 

of northern Missouri is slightly better represented than 

the nonglaciated terrain of southern Missouri (fig. 4). 

There must be some common feature throughout the 

region that results in a similar composition among soils 

that represent an apparent diversity of parent materials 

and possible contrasting ages. That common feature 

could be the widespread effect of loess superimposed 

over the effect of the residual parent materials. 

Samples closely associated with the resistate factor 

(II) occur predominantly in southwest Missouri on 

cherty residuum of the Kaskaskia sequence (fig. 5). 

These soils contain moderately large amounts of Si02 

(about 88 percent) and comparatively large amounts of 

Ti02 (about 1.1 percent) and Zr02 (about 0.1 percent). 

Samples with dissimilar compositions occur on the Mississippi Alluvial Plain and throughout northwest Missouri and tend to be associated with factor III. 

Samples related to the glacial factor (III) form the 

most distinctive distribution pattern of all the sample 

groups (fig. 6). The most closely related samples outline 

the Missouri and Mississippi River valleys and adjacent 

terrain where the most prominent deposits of loess and 

glacial outwash occur. Other samples with moderately 

large loadings fill in other parts of the glaciated terrain. 

This distribution pattern is markedly similar to that of 

the individual elements: aluminum, calcium, magnesium, potassium, sodium, and strontium, (Tidball, 

1984). Samples that are not related to factor III define 

the area of the Ozark Plateaus and are related to factors 

II or IV. 

Samples that are similar to the silica factor (IV) are 

largely confined to the Ozark Plateaus where cherty 

residuum of carbonate rocks occurs (fig. 7). Other similar samples in the Mississippi Alluvial Plain and in 

northern Missouri represent sandy alluvium or sandstone parent materials. Samples with compositions that 

are unrelated to factor IV are coincident with the prominent loess deposits and associated alluvium of northwest Missouri. 

R-MODE FACTOR ANALYSIS 

The Q-mode factors represent the compositions of the 

most extreme sample types, and they were named by 

interpretation of a small group of extreme sample vectors. Each sample group, however, includes sample vectors with compositions that diverge evermore from that 

of the factor until eventually a sample vector represents 

an intergrade of two or more factors. In order to determine the association of oxides that are unique to each 

of these more extended groups of samples, the associations of 1140 Q-mode sample loadings with the 22 chemical variables was expressed by a correlation matrix. 

With the inclusion of the Q-mode loadings as "new variables" in the data matrix, it was no longer closed. The 

chemical variables, except Si02, were transformed to 

logarithms (base 10) to achieve more nearly normal distributions. The correlation matrix served as input to 

R-mode factor analysis (Miesch, 1980, method 2), which 

was used to simplify the analysis and interpretation of 

the matrix. In R-mode analysis, 

(5) 

which differs from equation 3 only by the subscripts, 

m and N. P mN is the small matrix of loadings, and 

CNm is the large matrix of scores. 

The eigenvalues and the eigenvalue ratios (Miesch, 

1980, p. 532) for the first six factors are as follows: 

No. Eigenvalues Ratio 

1 11.7 0.45 

2 4.61 .63 

3 2.54 .73 

4 1.05 .77 

5 .77 .79 

6 .74 .82 

The ratios multiplied by 100 express the average 

cumulative percentage variance accounted for by each 

additional factor. A three-factor model with a varimax 

rotation was adopted. 

In the varimax solution, the matrix of loadings, P mN, 

is also a matrix of correlations between the varimax 

scores, C Nm, and the variables. Correlations larger than 

0.2 are shown in table 9. Under each R-mode factor 

all those variables with a large positive correlation tend 

to be associated or behave in a similar manner. Any 

. one factor may represent a process that directly controls the amount of the oxide in the sample, and therefore the several variables with a large correlation on 

that factor all reflect a common controlling process. 

Some oxides with intermediate correlations are simultaneously controlled by two or more processes. Oxides 

with small correlations tend to behave more independently; the process represented by the factor has little 

effect on these oxides. A large negative correlation indicates that an oxide is still controlled by the process 

but the behavior is opposite to that of variables with 

positive correlations. 

Under R-I the clay factor, Q-I, is positively associated with Li02, Fe20 3 , and so forth, and most negatively associated with Si02. If the interpretation of Q-I 

as a clay factor is correct, then the abundance of the 

highly correlated oxides under R-I is very responsive 
CLASSIFICATION BY FACTOR ANALYSIS, AGRICULTURAL SOILS 117 

TABLE 9.-Coefficients of correlation between R-mode sample scor~s 

and chemical values and Q-mode sample loadings 

[Only coefficients of eoiTelation greater than 0.2 are given] 

_!-mode factors 

II III 

Variable Correlation variable Correlation Variable Correlation 

0-I------- 0.98 

Q-II----~­

Q-IIr-----

:§--I v------ -. 33 

u 2o------ .86 

Fe2or---- .85 

sc2or---- .so V02------- • 7 5 

Ga2or---- . 69 

cao------- . 68 

MgO------- .68 

AI 2or---- .67 

NiQ------- .66 

CoO------- . 57 

cr2o3----- .55 

Y2or----- . 42 

La2or---- .42 

sro------- . 38 

Yb2or---- .37 

Sio2------ -. 7 3 

ZrO------- -.27 

Q-I------- 0-I-------

0-II------ 0.93 

Q-III-----

Q-II------

0-III----- 0.92 

:Q-I v------ :§--I v------ -. 81 

zro------- . 77 TiOz------ • 76 

Na2o------ . 9 3 

SrO------- . 8 4 

Yb 2or---- .67 K2 o------- . 7 s Y2or----- .66 Bao------- . 7 4 

B2or----- .56 AI2or---- .64 

La2or---- . 46 MgO------- • 60 

cr2o3----- .41 

Coo------- • 40 Ga203----- . 54 

vo2------- .43 

Bao------- . 2 7 NiQ------- • 3 7 

cr2or---- .33 

Si02------ -. 6 2 

to the abundance of clays and suggests that either adsorption or crystalline structural positions are domininant. The "clays" include as reactive colloids, the clay 

minerals, organic matter, and the sesquioxides of Fe 

and AI that are common in oxidizing environments 

(Rose and others, 1979, p. 144) often as coatings on 

other mineral grains. The high correlation for Fe20 3 

suggests that sesquioxides are a dominant part of the 

colloidal complex. Li+ 1 is. a relatively mobile cation in 

the surficial environment (Rose and others, 1979, p. 24) 

and is often dispersed in clays (Norton, 1973, p. 366). 

Thus, the principal process of enrichment for Li + 1. as 

well as the other trace oxides associated with R-I is 

probably adsorption (Krauskopf, 1967, p. 593). The 

large correlation for Sc20 3, however, may not relate 

to adsorption because Sc + 3 is a relatively immobile cation (Rose and others, 1979, p. 24). Sc20 3 typically occurs as a trace constituent in the ferromagnesian minerals, pyroxenes, hornblendes, and biotites (Adams, 1973, 

p. 568); these minerals may be redistributed into sedimentary deposits where concentrations of Sc20 3 can exceed crustal abundance. 

Under R-II the resistate factor (Q-II) is most highly 

associated with resistate-type oxides, Zr02, Ti02, 

Yb20 3, and Y 20 3• Minerals that could be present in the 

resistate-group of soils include zircon (Zr02), sphene 

(Ti02, Y~0 , Y 20 3), tourmaline (B20 3), and ferromagnesian minerals (carriers of rare earths, L~03 

and Y 20 3) (Adams and Staatz, 1973, p. 550). Although 

tourmaline contains B20 3, this oxide is also adsorbed 

from sea water onto argillaceous sediments (Deer and 

others, 1966, p. 96) that may be incorporated in some 

carbonate rocks. 

Under R-III the_ glacial factor (Q-III) is most highly 

associated with the bases, N~O, SrO, K20, BaO, and 

MgO, and also with Al20 3; there is a negative association with Si02 and Q-IV. Most of these oxides are principal constituents of the feldspars including both the 

plagioclase series and the alkali feldspars. Barium may 

substitute for potassium in feldspar and mica-group 

minerals (Deer and others, 1966; Krauskopf, 1967), or 

it may be adsorbed to clays or occur as barite minerals 

(Brobst, 1973, p. 77). Most of the glacial material was 

probably derived from local source rocks, which would 

be chiefly sedimentary rocks of Pennsylvanian age and 

to a lesser degree cherty, interbedded limestone of Mississippian age. The dominant rocks of Pennsylvanian 

age, shales and sandstones of the Absaroka sequence, 

were found by Connor and Ebens (1980) to be enriched 

in many elements compared to limestones and dolomites. 

The silica factor (Q-IV) is negatively associated with 

R-Ill and also to a minor extent with R-I. In both 

cases, Si02 is the dominant oxide, and Zr02 is a minor 

one under R-I. Si02 in samples of the Q-IV group occurs largely in the form of chert, a major component 

of the weathered residuum of carbonate rocks over 

much of southern Missouri. Otherwise, Si02 in samples 

of group Q-I occurs as small grains of quartz or as 

a component of silicate minerals. 

DISCUSSION 

Q-mode analysis has identified four extreme types of 

soils; and accordingly, all the soil samples may be classified as belonging to one of the four groups or as intergrades between groups depending on their degree of 

compositional similarity to that of the end members. 

Each end member represents a unique aggregation of 

constituents: these are the end products of not only particular mixes of original minerals but also differing duration of weathering. 

The R-mode factor analysis indicates that a unique 

assemblage of oxides characterizes each group of samples. The basic pattern is that soils associated with relatively littlfl weathered parent materials have relatively 

abundant amounts of alkali and alkaline-earth oxides 

(bases) and oxides of the aluminosilicates, Al20 3 and 

Fe20 3; resistate oxides, Si02, Ti02, and Zr02 are present in minor amounts. Soils associated with highly 

weathered parent materials have an abundance of resistates and little or none of the bases and silicates. 

Factors R-I and R-III represent the case of limited 

weathering where the presence of bases (positive as-
118 GEOCHEMICAL SURVEY OF MISSOURI 

sociation) is contrasted with the absence of resistates 

(negative association). The positive assemblage of R-1 

undoubtedly reflects the mechanism of adsorption which 

accounts for the inclusion of the several trace oxides. 

Adsorption may also apply to the positive assemblage 

of R-Ill, but a reservoir of primary minerals, such as 

the feldspars, may be a more important feature. · 

Factor R-11 and negative associations of R-1 and RIll represent the case of advanced weathering. Factor 

R-II is characterized by resistates and rare-earth 

oxides. Soils having this assemblage are derived mostly 

from residuum of limestones, calcareous shale, and 

sandstone of the Kaskaskia sequence of Mississippian 

age (Connor and Ebens, 1980). The assemblage of resistates associated with R-1 and R-111, however, is found 

in soils developed from residuum of mostly dolomite of 

the Sauk sequence of Late Cambrian to Early Ordovician age (Connor and Ebens, 1980). 

The results of this study based on the A horizons 

(or plow zone) of agricultural soils of Missouri may be 

compared to a study of the B horizons of 60 native soils 

of Missouri by Erdman, Shacklette, and Keith (1976, 

p. C19-C23). The samples of native soils were classified 

by Q-mode factor analysis with a varimax rotation, and 

four factors were interpreted as being related to parent 

material, although the samples were collected from 

within vegetation-type areas which often cross over 

parent-material types. Their factor-variance diagram 

suggests that perhaps five factors should have been 

selected, and the varimax factors had numerous negative scores. Their first factor, which they related to 

Al-rich parent materials on the prairies of northern and 

western Missouri (area of shales, sandstones, and limestones of Pennsylvanian age) is similar to the clay factor 

(Q-1). Their second factor, which represents silicon-rich 

compositions and was associated with cherty residuum 

of carbonate rocks in the Ozark plateaus, is similar to 

both the resistate (Q-11) and the silica factors (Q-lV). 

Their third factor represents soils developed from 

dolomitic rocks in the Cedar Glades vegetation area 

near the southern border of Missouri-there are no 

similar samples in the present study. Their fourth factor was related to a feldspathic- sand facies in the Mississippi Alluvial Plain and is vaguely similar in composition to the glacial factor (Q-111), but the distribution 

of the sample loadings is not at all similar. Their X-ray 

diffraction analysis of factor-four samples indicates feldspars rather than feldspathic minerals; feldspars were 

found in Q-111 samples. 

There are two widely occurring parent materials, 

loess and carbonate residuum, in which the contrasting 

duration of weathering has resulted in the two basic 

patterns of either limited or advanced weathering. The 

original compositions of these two parent materials are 

given by Ebens and Connor (1980). They sampled parts 

of the parent material from strata well below the soil 

profile and reported as follows: (1) the mineralogy of 

loess consists mostly of quartz and clay plus minor 

amounts of dolomite, potassium-feldspar, and plagioclase; (2) loess contains more of the bases, K20, Na20, 

MgO, CaO, strontium, and barium, and more boron and 

Si02 than residiuum; (3) residuum is comprised mostly 

of quartz and clay with the quartz being concentrated 

in large fragments of chert rather than being disseminated as small grains; ( 4) residuum contains larger 

amounts of Al20 3, Fe20 3, lithium and manganese than 

loess; and (5) there are about equal amounts of gallium, 

scandium, yttrium, ytterbium, and zirconium in these 

two parent materials. 

Comparing the compositions of these two principal 

parent materials with those of the soils developed 

therefrom (Tidball, 1984), there are some marked reversals in the proportions of some elements as a result 

of soil development. The principal reversal is that of 

silicon: residuum parent material contains a smaller 

amount of silicon than loess parent material, but re-

~iduum soil contains a larger amount of silicon than 

loess soil. I believe that the reason is that the large 

fragments of chert, which are scattered as lenses 

throughout the residuum parent material, become concentrated in the soil profile as a resistant lag material; 

thus, the apparent proportion of silicon is increased. 

Residuum parent material contains nearly twice more 

Al20 3, Fe20 3, and lithium than loess parent material, 

but loess soils contain larger amounts of these elements 

than residuum soils. Loess is younger, less weathered, 

and less leached than residuum; thus, the original composition of the loess parent material-particularly in respect to calcium, potassium, magnesium, and sodiumis more nearly preserved in the soil. 

EPILOGUE 

As one travels throughout Missouri, it is soon apparent that regions with more chemically diverse soils also 

tend to exhibit the better looking farms and tend to 

produce a higher level of agricultural income (Missouri 

Crop and Livestock Reporting Service, 1972). Also, 
CLASSIFICATION BY FACTOR ANALYSIS, AGRICULTURAL SOILS 119 

some evidence suggests that better health may be expected among people living on the more fertile soils 

(Albrecht, 1957, p. 102-103). One of the original motivations for conducting this study was to provide geochemical information toward understanding the role of the 

environment in the health and nutrition of animals and 

humans (Connor and others, 1972; Miesch, 1976c). Because diseases and premature mortality exhibit a geographic distribution (Sauer and Donnell, 1970), it is appealing to presume that soils may have a role (this is 

supported by an extensive literature, for example, 

Armstrong, 1962, 1964; Losee, 1962), but no significant 

relationship was found between soil composition and 

human-mortality rates in Missouri (Tidball and Sauer, 

1975). Perhaps a more sensitive experiment using only 

the t!Xtreme soil types as identified by this study would 

provide an alternative conclusion. 

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