geochemical - usgs · geography of soil geochemistry of missouri agricultural soils by ronald r....

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


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


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


GEOGRAPHY OF SOIL GEOCHEMISTRY OF MISSOURI AGRICULTURAL SOil.S


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 continu-

ing 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


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 8

82 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


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?


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, pet-

C, 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.


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

se =sampling error, sa2 =analytical error


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


,- 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

1-----~-: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 + 1 ~------< -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:-

-+--------- + + 11+ : 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


>u

750

t5 500 ::::> d w a: u...

250

3 1201581 7 1 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


Geometric mean 580 Geometric deviation 1 .46 Analytical error variance


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.


0


>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


FIGURE 5.-Beryllium distribution in selected agricultural soils of Missouri. Map symbols correspond to frequency classes as shown in the histogram.


,- 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, 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 +,! + +"


> 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


FIGURE 6.-Boron distribution in selected agricultural soils of Missouri. Map symbols correspond to frequency classes as shown in the histogram.


----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~ ~~( __ ,_;_'_, ,--~---;---·-\, \.

f -----~ ,~-/· ~----.-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 ( + ). ·



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



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..



13 22 22

c cc c-.i N

TOTAL CARBON, IN PERCENT


(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.


, - 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 + 11 \.--- / + 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 i1 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+ r-1 + + + ·----*'--!' +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 -1~ I il I ,T-t,'

0

0


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 11! I ,'"

' + ! I ,'

200 KILOMETERS

, __ - ....


(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.


>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



FIGURE H.-Chromium distribution in selected agricultural soils of Missouri. Map symbols correspond to frequency classes as shown in the histogram.


'- ~""-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 t1 + 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+ I-I :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'"


+ ::t tt

" I + , 50 100 MILES 1 __ 1_ .:., t



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.


•- ~ "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 111' + , "> -= ..± / ~ .: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


>u z w :::> d w

500

~250

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

;=~~~~~§:~

COPPER, IN PARTS PER MILLfoN-



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::)


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

\



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


1 +I~ I il: I I I I

I

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

GALLIUM, IN PARTS PER MILLION



FIGURE 15.-Gallium distribution in selected agricultural soils of Missouri. Map symbols correspond to frequency classes as shown in the histogram.

H25


----' 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----~~~------\ "- --- i:t: [__+_--- ! ! :to ! ! i \

,_) '-------/ I -1 I I i +' 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 " " i , __ .:__1

Arithmetic mean 4.4 Standard deviation 1 .65 Analytical error variance

::J 25 d


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.


>u z w

0 50


+ :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


FIGURE 17.-Iron distribution in selected agricultural soils of Missouri. Map symbols correspond to frequency classes as shown in the histogram.


,- :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~ I-I :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


48 36 16 I+ # I I I

500


u. 250


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.


,- =-:_ --- 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 .... - '

,~ +!-- I I. ! - I ,./'i\.._- ·--+- I - ~~--=----~- I I - I ' I I -1-i I ---+ - •"'- ; 1. I L -...__ I - + ~--, - -. __ ,

.... · r...:::-<.. 1- '""~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~'

II 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 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


5 250


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.


50


>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



FIGURE 20.-Lithium distribution in selected agricultural soils of Missouri. Map symbols correspond to frequency classes as shown in the histogram.


,-~ +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 ___

11__ -~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 ~ ..

( +,! # #~


+ :t:

~ I * , 50 100 MILES ,_-_..:. _,

Geometric mean 0.26 Geometric deviation 1.65 Analytical error variance a 250 (percent of total variance) 4 Number of analyses 1140 w

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.


,- # -+- 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 ~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--~- '* ' * + 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


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



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


cc N

0 co

0 cc N

MERCURY, IN PARTS PER BILLION

0 co (")

0 (") co



FIGURE 23.-Mercury distribution in selected agricultural soils of Missouri. Map symbols correspond to frequency classes as shown in the histogram.

H33


.----,.._ __ \ :

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


, 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 ( + ).


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 + 1~++ 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_ 1 -------~;- -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

11 , 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'


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.


,-,~ "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: ". #• + f1

I ::1:" I I 1 L-

1 ' ---- - --* ( +~-----'- 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:r-1 + " ----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 ++! + #.,


17 12 I 45 1 15 11 I I +I -+ #

, I + , 50 100 MILES ,_+_ .;,. 1


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.


,- ~, -,- 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 + 11

' ' 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 1 1. 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 ''-


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


(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.

•

•


.-~"'+--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 -

11 ' 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

II 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:---f1 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' ..

II 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:, (..._) - - I I ' -;t: I I ' I - :f= .- ::;: :t:' ' +I +++~I L ___ t ____ -_

1 _ ___l ____ . __ :t: __ ;::,._j. ___ I ___ ..J. ___ ..J _r., r ::;:•1,

L..:t: ~----:':;:\.)

50


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



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.


0 50


>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

" ~ '---



FIGURE 29.-Potassium distribution in selected agricultural soils of Missouri. Map symbols correspond to frequency classes as shown in the histogram.


0

0


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



FIGURE 30.-Scandium distribution in selected agricultural soils of Missouri. Map symbols correspond to frequency classes as shown in the histogram.


>u z w

50


+

6 250 w ex: LL.

0 v

N 0

M 0

co 0

SELENIUM, IN PARTS PER MILLION

100

50 100 MILES

200 KILOMETERS



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


0 50

0


+ +I #

~~~~~c;;~~~~~:;;:~ SILICON. IN PERCENT

50

100

100 MILES

200 KILOMETERS

Arithmetic mean 35 Standard deviation 2. 77 Analytical error variance


FIGURE 32.-Silicon distribution in selected agricultural soils of Missouri. Map symbols correspond to frequency classes as shown in the histogram.


,----,-- -~---r \ 1 . --:--,----r-l--T-\.. I ' L ~ \ i / i i '

I ' -----; I ~------ ':> ' I \ "\

'--- • 1 • I 1 r _ ___: ____ t _ 1 1 ---~~ . I ~-----· 0 7 ,-----. -/

'\ I_ 0

o l + • i ! ~-----/ t ------_, !--------, , ' I , ' ~ r' -----.1, I 1 1 , 1 ,

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

~---1 j ! i i 1-----·i·-----, ,..J '--------j'------1 l i I ' I

' I -,----·-- ' I ~ ) i ! 1------, I I r _____ :__,------- "

L____ I ' t o-------- I .·, '\ --~ .-------i ' I I , / ' r--------4 l, I I I / I i -;(._ I I · , '-...

\ ' I o"'- l,.l ''--l, /~--~ ~-------! ___ \ ', .;,..._J../_,~( '"".-L-~-1 ~· '-J -~ _ _;_ ___ , I, ~-------\

I 'r' :/ I <..' I I r---~---:---1 • -"""- / f-------; I

I ' I ( ---~-(, I I L \ l ,_ ___ __J----~------~ ;\ i I I ·~ -- ~-r\ , -::_' ,-------i I ' - ' I ~ _J --: - .... /~· -~'

i I L _____ ./ I)_ / ---+-~-1.-, ' _j ;{ I I I "-,, / ' I ' I / I

L~---- , , , '- ___ / ! I --~.:_.-'1 \,' I ---l--.r---~ "-, 1 , 1• I 1' '

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 - I I ~ , 1, __ _;-----( ~ ..

I i i 1 'I 1. I I I .r '

J ________ ; ~-------L.,__ __ ; ~- 1 !_. :-~-r· " ; r----~ 1~ _:...__; _____ _, ,-- [ ___ ., ,._~-- , )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 ( + ).


,-: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- 1 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

'+ I I I - I L I + +L-------1 I +~ \ + ' -+- ' I' ' I ' ~ + ·+ ' ~

1 +r----:t---1--'1, 1 ~(a __ ,--'-, + 1 ::;:' ·--~--------, + ' + ! I I , , + ;_ + + + + ~+ ~+ + I ' + ~ ~

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 1 L'----*- 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--1 ---=~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

11 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 1 ' 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 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 Analytical error variance u

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


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.


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::

*''# * } ' .:t I * * *I I * • * * ' * # ~- .:t * \ """'\ --..---1.+* * I r-----=~-4------~* *I *~

... , * - *' * *I .... I , * * * .. ~~ # .:t I :... ...-----. + I .:t +-,.--~--~·--.------~- * • ... I I It: '+

'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 ' __ _. __ ~

L,_, * I * * *I * 1-=------' # I * * 4- ~-------*, * '\, \.._~ *I * . +* *( :r ~----r· * I ..... -¥-------1 **# L-.---t ** I* * * I I+ * * + ' 1- * /' '

.it # I- ....# + * ~' I I I I* /' l ""* * *-+ --1 * '-. I * ~ I * ' * * .... , • I *' I * . ..:._. I+ * * I+ *\ * -

#1%# # ! I # ,.1 %',__ # ,_. * + ~------...tt: ___ l * *'*' ~ I * ~I * "*.., ::tt -~_A'#-; .:t \:~;t ------.., _ _;_ ___ * ~ * \ *--~----\

.... ' ('_/ "(. # '"' ' • ./ . I I I *;' * * -I * I ""....--J# *'r-1 :/ * * * ' .. ~ * * * ~*.L-_,.,.#

I • *'* * * I it < * I + rt- r + ot"# * * I ' it * #) it I + .L------' I * I

* *' * '* * ' ~ .. # ' + 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* ' I I * * ' I#; + I I %{ , # I I * 1---.:t:-. ¢: ) ( * --~+--!.--~-, **' * --·:r** I I * ' # * * I * -tr * I I* --!t: / - ..,_'' * y ** i * * i '----.., I / * * f I * ,* L ~--*"*- --_I * , * * *,If- "--- -/ * , 1- * , . :_ #"' ! ** \,

I * I * * r r---~ "t I /!1-* -t-J, * I +I* * I ,.,.-~ ----. # ~ I .:t , I .:t I+ * +r·J* • ) I + ~-- i I * * j * + + I + + * "t- .t =-t + :~ * i ~ * + i 'Y * + ' .:t r .:t: r I , J* I_-- , I 1- I * ' .:t: I ' I

11- - + I * I /, 1 * *1_- -- --- -1 * I * t* . \ I ' r ,~ ' + I + ' ' ~ ~

I # T/*'---l-r"/, ~ ~(1.__,--'-, + I * *'*•-·'---·;---.;_-- ' I * I , 1- :_ .:t: -+ + .:t: ~ · 1.:t: 1- 111 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 --,--, 1J' 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 [-1----'--~~Ll~--~--~~-...l-I __ J [:: ______ __;_- l 11

1J .:t: 1

1 1!1*+;

,l--=-1-*-~~l~--il li 1: 1,11 I i I i L1 ,-IT __ j-,----;'1 +!:**_,... ..

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;,.,.

I ' - I '-------"------1-----1· 'J '----=--1., \..* -t-1 ·'* # J 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,


50 100 MILES

~* ~---;'*'J ~' * *' '*~**!I..'

( **! * *"""' , I ** , , __ '*:_..:. __ ,


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



FIGURE 35.-Strontium distribution in selected agricultural soils of Missouri. Map symbols correspond to frequency classes as shown in the histogram.


,---- r- - -, - - "~"""-----,---\ I l + l ' # ' -,- - * -#~ -# l -- T- '\.

: 1' ~~--~-±J * \1• , +L--~--+. .~ i * ! * ~' *· I '· I I ' 'I "'\ \,.__ r, -+-----, l

~---_:;; 'i ! ,---+-·1

,---+~r------1

>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

.L I ! 1------' 1 # I [ _____ ;_,.,------~ \:---- + I ' \ >------~· I - ,

, #-~-----~---_--- j * l. ! 1 ! * I / / , i i * ~* I I • , '-...

\ i* i l •' 1 ,/ \ __ 1, /-.:.______ ~------- 1 ---\ I *-. , "',...-J'./·---<-~~·~-~-----""-j -._. ''/* f _ _;_ ___ l + I, ~-------\

I * i * !* _,.,~ * / *- ,l:_-----i---~-T-* ,· L-----~~~---_J---=~=1----~-f ---~-'-!,\ ! i * ~~--t--~-\ ... '-;;:_ ', I

I • + i # / i I ,;-·J * : r'~ -~( I I 1--;:v--.: /)_ ~ /i----1.-" ' .-- '+ /

# L I ' I I "\ // i i , ______ I ~< I I

1

-- -----_/-. - -~--- -~ ., r-- ~ ' "'I /'+- r. i I - . ~. , \-., . j '* , r-'* , *~r-·-:tt./ ! + ! , ,J _ _.__I __ ,) ! * i ' I I I_ I * -:._1._ _______ _, * i I

+ -r-------'~. ~'(a __ ,_:_:_, i ~ ,--~---;----...:, "\. f·=---v-.J, + * !------~ - \_ I I '\'\'1 I ,r' '

I I * --;--~:t'~."" ___ _, :L-·---~~ - ... i":» , ___ , r' * _,__ 1 , 1 , , ..._ ,

Lt-;-~---- ~+ -; -~-\ . ./; + I -'-, I I! '-,, / + \

1 iF ' ' _._ L - ---·=-~. -·,_~ 1 ' # .... \

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_;-~-----\ \ ~~

1

1;,., ; , 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



FIGURE 36.-Thorium distribution in selected agricultural soils of Missouri. Map symbols correspond to frequency classes as shown in the histogram.


,---- 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 ( + ).


>u z w

0


500

2 5 69 I 23 1 I : + :t I .t:t 17851

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



FIGURE 38.-Titanium distribution in selected agricultural soils of Missouri. Map symbols correspond to frequency classes as shown in the histogram.


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---~------~ ;\ # , +~ _ _j I ~--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


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


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-t-

I -t-

0

SYMBOL AND PERCENTAGE 0 F TOTAL SAMPLES

10 7

LnCCCCCC -NMLn,......OLn


50 100

50 100 MILES

200 KILOMETERS



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.


.- 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._1:-:,..----~-.: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+,! + +'"


8 176 16 1 +I ~

1 1sss

N M Ln ,..._

v

, I I , 50 100 MILES 1 __ 1_ .:. 1

Geometric mean 3.2 Geometric deviation 1 .31 Analytical error variance


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.


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 \."

( +,! + + .......


9 70 21 1+1 + I I I 803

, I + , 50 100 MILES '-- 1

_ ~ 1


(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.


,- 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 * + ~ -· -~'

I + if/ #.:~: + II .:1:+ .:1: I + '.:~: -~ r' + * I *I· * ~ * ( *=r # # I I + * I -, ~ + I I +/ ~

I I + ~---~- ¢ }_ ~ .:1: --*--1-.£,-~-, I+ I + ---** I I I ' # .:1: #I I 11+ +I* -If 4-, '-· *Y # I+ +'I '--- I / # *# I I + .:1:+ Lr--;t-'!t---.1 + 0 # # -, '-. __ / + 0 I

0 '.:._,.-1 * "'

I .:1: I + * ~-- r--. ~ ~ I Ill-* ±1. + I *.I I + # , ----- # 1--- I ·t , - * -,:r '+ ~ *"·1·1='~ I I + # ~-; i .:1: * + I + * I I + + * ~j~ =,· + :.&.1 + i i + + # i # y

' I I # # ,J --- I # I + ' . + ' ' 1.:~: ~ I I I L I + It_ _______ , + I -f* --1

+ o o I' ' # o * ,+ o • I tt *1*---~-r"', + ~ ~,, __ , ..... , * I I, I.-- ... ---~----. t '

f ' # I I ~+ I --.. # -+I+ +I ~-,I I ~ + * ~ ~

--1--:·-._;_-,] +- I# !---l-~ \ \-1 I ! +I ,..,_;;__± _ _,+~ ~ - I 'I # •'h.}t -~.....- .Ji'' -+ ' I I I # .. .-T~ _._ -.-- I # i ~ + '> ~ .....

I +I c', I - I t I I -- 0 # I I I L I I • * I + y f # ~ :' I "---, I : # -;-1:_...#-, __ , I I 'I ..! I I - I I ' ' * / .. '

I * I '--,-J. I ~- I - '\ J' I* ~ I I I + ~ ' \ I + +, i- I . .:r 11 -,----1- II ~ - !+I - I :----~--.L J.~.!...-~~~ .... -f.,* +:1 *+ •* ~ •# # ~- + l I - .... ' I I + - I --· * • ~r"l • * ' r+---·---j I -~ - -~ _ ! ~- I ·-.., I ' # ! _ .... -----1 ·t __ : __ _7__ )

I + # ""--=F·---~ +I t I # "--------'-- I _T _____ I ~ + ; # ' ... '-, 1 + 1• 1

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 • 1L 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 _::_ ,'



~250


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.


'- +-- --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•-,-----~

~ - - Ti+ + I I - * ! I I I + I I I + ,+ + ** \ ,...) * I ~----- I I I I I + + + + * . +--+---.., * + + l _+ l + + - I, +I + + I' + + I ,. -+ :t;j + ' + I + + - --- • + + *

L + ' - +I ++ I+ +' + I -*1 .I + ' ---+--~ c __ ~ + 1 + + 1 • ::.+ ,----,.¥ + "+_±_.±_+ !-----_;-+; -~-* ** __ 'ft -+-, I+ ~-l----·1j + r + 1 I + + **f+ + ' - * / ' ~+ I [....--- ..± . .., * it- + -it. I + I - I+ / ~

, + + + * + , - + ~- b + + I + , t- -+< + "-

>u z w

*!+' * ! ! + ,.1 +\ __ + . ' + + ' =._ __ _:!-___ ...±) I I + + .... " I ++- I * -- ~ I •""'· ;- l ,-+ ----1- --....- : I + - -- I * +I ' 4 .. ~ I <'./<.::-(-::;.. ,r+;+-·/------1-~ + '-)+ * ;-:+~--+-, I + I + _______ \

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

I ,,.. --~-1- --+ -( + -T-~-~ f' I + I '-;~- * I_\ --1 +++f---- . ..J #f'# ·-< ** *, ::j: '++ I -\j.. I .:t; ~r.\ I 1 _, -------,; I I \ * I +** +t\ +I ; -r,_ _ _j* ~-oi~-1- + ,., .=>''it~'

I I +I + * * ' +I I + * '-*!: ' + I *' + ' + ( I ( + ' I * I + ;+ ~ I -t- + ' I .I -~ -t- ' +_

'*'+ I I + >----4-----.....;±" /1. ( I /++-~-~*'\,. .... .:t:*' * ,-?-"'*-r I I t_ * , +I + '1* + r.,.. *' '·'- + 7""- i+ -t-1 '-- ..... I / * + I '

,** + ++ ~---r=t----~ + ; ..., + t~:- • __ / + , * , .:_,~I + \.,

1---... -+· - ! ::j: - ~- ~.r-+. i '>!;- + f+ + +-f. + k I ~ * + ' ; , ---f: ~

.. ~--• + -fLI ''*' , * *+''!!= , * *r-5* ~ J +! +I + I + + * I++ I '-f~ +.~+ + I -+ * + i y I

+ I + + '_jl- I_---..,-+ + I + ' + ' I

I+ -* + I I I * +1--------l I *f + *' + ' (' ' + ' * * '* ' +'

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

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-'\...)

** *I**' --, + ~ + +I* I* I r-:-r I _-r . + . + t-Il + "'

I ****+j ' + I ! + +I ~----'--.- . ..$ ___ , + ' I -t- ·-;- - - ' -r! ** '9-*1 '+ ; + \ --- I* *1+-----#L,.. I* * I * l--;--- ---....L, I*+ I + * +I -

----• I * * , + -- + I • ,.,1 1+**-t- + '--t ..t** * :t:l **..,.. 1· * I* +I L i 1·------' **It r + '** - - - -'.1. ' + +- ' ' + + - - * loo *"' ' ;.- .. I *+ I' * I' .. + I * 'I l I I 1. + ; + + ' ** *I .,....,..-...r '

+ ' ** ' -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-+-, + \ -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 -...,


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


:::> 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


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 agricul-

tural 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 CLASSIFICATION BY FACTOR ANALYSIS OF MISSOURI AGRICULTURAL SOILS


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


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

t-z 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


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.


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-


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


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----------

sc2or-------Sio2, percent-

SrO-----------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, percent-

Sr0-----------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


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-------


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


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.


0 50

50

SYMBOL AND PERCENTAGE OF TOTAL SAMPLES 300 16 I 23

1

18 23 20 I 1 I+ ~ #

250

200 >-u z w ~ 150 w a: LL

100

50

0 N :! 8 s N

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


0 50


+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.



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


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


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

Yb2or---- .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~03, 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-


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 appar

ent 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,


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.

REFERENCES CITED

Adams, J. W., 1973, Scandium, in D. A. Brobst and W. P. Pratt, eds., United States Mineral Resources: U.S. Geological Survey Professional Paper Paper 820, p. 567-571.

Adams, J. W. and Staatz, M. H., 1973, Rare-earth elements, in D. A. Brobst and W. P. Pratt, eds., United States Mineral Resources: U.S. Geological Survey Professional Paper 820, p. 547-556.

Albrecht, W. A., 1957, Soil fertility and biotic geography: Geographic Review, vol. 47, p. 86-105.

Armstrong, R. W., 1962, Cancer and soil-review and counsel: Professional Geographer, vol. 14, no. 3, p. 7-13.

--1964, Environmental factors mvolved in studying the relationship between soil elements and disease: American Journal of Public Health, vol. 54, no. 9, p. 1536-1544.

Brobst, D. A., 1973, Barite, in D. A. Brobst and W. P. Pratt, eds., United States Mineral Resources: U.S. Geological Survey Professional Paper 820, p. 75-84.

Connor, J. J. and Ebens, .R. J., 1980, Geochemical survey of Missouri-geochemistry of bedrock units in Missouri and parts of adjacent states: U.S. Geological Survey Professional Paper, 954-F, 55p.

Connor, J. J., Feder, G. L., Erdman, J. A., and Tidball, R. R., 1972, Environmental geochemistry in Missouri-A multidisciplinary study: International Geological Congress, 24th, Montreal, Canada, 1972, Symposium I, p. 7-14.

Deer, W. A., Howie, R. A., and Zussman, J., 1966, An introduction to the rock-forming minerals: London, Longmans, Green and Co., 528p.

Ebens, R. J. and Connor, J. J., 1980, Geochemical survey of Missouri-geochemistry of loess and carbonate residuum: U.S. Geological Survey Professional Paper 954-G, 32 p.

U.S. GOVERNMENT PRINTING OFFICE: 1985-576-049/20,014 REGION NO.8

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

Harman, H. H., 1967, Modern factor analysis: Chicago, University of Chicago Press, 474 p.

Joreskog, K. G., Klovan, J. E., and Reyment, R. A., 1976, Geological factor analysis: New York, Elsevier, 178 p.

Krauskopf, K. B., 1967, Introduction to geochemistry: New York, McGraw-Hill Book Co., 721 p.

Krusekopf, H. H., 1966, Delta soils of southeast Missouri: Missouri University Agricultural Experiment Station Bulletin 854, 38 p.

Kuchler, A. W., 1964, Potential natural vegetation of the conterminous United States: American Geographical Society Special Paper 36, 116 p., map.

Losee, F. W., 1962, Soils and human health, with particular reference to dental health, in G. J. Neale, ed., Transactions of joint meeting of Commissions IV and V: International Society of Soil Science, Nov. 13-22, 1962, p. 889-894.

Miesch, A. T., 1976a, Q-mode factor analysis of compositional data: Computers & Geosciences, vol. 1, no. 3, p. 147-159.

-- 1976b, Q-mode factor analysis of geochemical and petrologic data matrices with constant row-sums: U.S. Geological Survey Professional Paper 574-G, 47 p.

-- 1976c, 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.

-- 1980, Scaling variables and interpolation of eigenvalues in principal component analysis of geologic data: Mathematical Geology, vol. 12, no. 6, p. 523-538.

Missouri Crop and Livestock Reporting Service, 1972, Missouri farm facts: Jefferson City, Mo., Missouri Department of Agriculture, 54p.

Norton, J. J., 1973, Lithium, cesium, and rubidium-the rare alkali metals, in D. A. Brobst and W. P. Pratt, eds., United States Mineral Resources: U.S. Geological Survey Professional Paper 820, p. 365-378.

Rose, A. W., Hawkes, H. E., and Webb, J. S., 1979, Geochemistry in mineral exploration [2nd ed.]: New York, Academic Press, 657p.

Sauer, H. I. and Donnell, H. D., Jr., 1970, Age and geographic differences in death rates: Journal of Gerontology, vol. 25, no. 2, p. 83-86.

Stout, L. N., and Hoffman, David, 1973, An introduction to Missouri's geologic environment: Missouri Geological Survey and Water Resources Educational Series no. 3, 44 p.

Tidball, R. R., 1984, Geography of Soil Geochemistry of Missouri Agricultural Soils: U.S. Geological Survey Professional Paper 954-H, p.

Tidball, R. R. and Sauer, H. I., 1975, Multivariate relationships between soil composition and human mortality rates in Missouri, in Jacob Freedman, ed., Trace element geochemistry in health and disease: Geological Society of America Special Paper 155, p. 41-59.

geochemical - usgs · geography of soil geochemistry of missouri agricultural soils by ronald r....

Documents