Factor Analysis of the

f*

Y^r Ol

U.S. GEOLOGICAL SURVEY PROFESSIONAL PAPER §74-1
Factor Analysis of the 

Chemistry of Spanish Moss

By JON J. CONNOR and HANSFORD T

STATISTICAL STUDIES IN FIELD GEOCHEMISTRY

SHACKLETTE

U.S. GEOLOGICAL SURVEY

An examination of the sources of 

airborne elements in an epiphyte by 

use of factor analysis

PROFESSIONAL PAPER 574-1

UNITED STATES GOVERNMENT PRINTING OFFICE, 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

Connor, Jon J.

Factor analysis of the chemistry of Spanish moss.

(Statistical studies in field geochemistry) (Geological Survey Professional Paper; 574-1)

Bibliography: 20 p.

Supt. of Docs. No.: 119.16:

1. Spanish moss Southern States Composition-Statistical methods. 2. Spanish moss Composition Statistical methods. 3. Spanish moss Southern States Ecology Statistical methods. 4. Plant indicators 

Southern States Statistical methods. 5. Air Pollution Measurement Statistical methods. 6. Factor 

analysis.

I. Shacklette, Hansford T. II. Title. III. Series. IV. Series: Geological Survey professional paper ; 

574-1.

QE75.P9 no. 574-1 557.3 s [584'.22] 84-600008 [QK495.B76]

For sale by the Branch of Distribution

U.S. Geological Survey

604 South Pickett Street

Alexandria, VA 22304
CONTENTS

Page

Abstract ............................................. II

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

Factor analysis .......................................... 3

Factors 1 and 2 Natural particulates .......................... 3

Factors 3 and 4 Technological metals .......................... 12

Factor 5 Metabolic constituents ............................. 15

Summary and conclusions .................................... 17

References cited ......................................... 19

ILLUSTRATIONS

Page

FIGURE 1. Factor-variance diagram relating variable communalities(h2) to number of factors in the varimax model of geochemistry

	of Spanish moss ........................................................ 16

2. Relations of chemical variables (vectors) to each other and to factors 1 and 2 in the five-factor varimax model of variation . 7

3. Sodium in ash of Spanish moss ................................................ 9

4. X-ray diffraction pattern of ash of Spanish moss ...................................... 10

5. Contour map of scores for factor 1 .............................................. 11

6. Contour map of scores for factor 2 .............................................. 13

7. Relations of chemical variables (vectors) to each other and to factors 3 and 4 in the five-factor varimax model of variation . 14

8. Contour map of scores for factor 3 .............................................. 15

9. Contour map of scores for factor 4 .............................................. 16

10. Contour map of scores for factor 5 .............................................. 17

TABLES

Page

TABLE 1. Correlation coefficients among 26 variables measured in Spanish moss .......................... 14

2. Eigenvalues (\) and cumulative variance associated with the first 10 principal components of the chemistry of Spanish

moss ash ............................................................ 4

3. Loadings of chemical variables on the factors of the five-factor varimax model ..................... 8

4. Typical concentrations (in parts per million) of selected elements in ash of Spanish moss and soils of the eastern United

States .............................................................. 8

5. Parameters for use in computing component scores ..................................... 12

6. Sources of elements in Spanish moss ............................................. 18

in

STATISTICAL STUDIES IN FIELD GEOCHEMISTRY

FACTOR ANALYSIS OF THE CHEMISTRY OF SPANISH MOSS

By JON J. CONNOR and HANSFORD T. SHACKLETTE

ABSTRACT

One hundred twenty-three samp! es of Spanish moss (Tillandsia usneoides L.) were collected from over its geographic range in the 

southeastern United States. The j,sh of these samples was analyzed 

for a variety of major and minor elements, and the resulting data 

were factor analyzed for pertinent geochemical associations. The first 

five eigenvalues of the correlation matrix account for 71 percent of 

the variation in these data, and a five-factor varimax model of element variation was constructed. Varimax factors 1 and 2 together 

describe most of the variation in the logarithmic concentrations of 

13 elements: aluminum, barium, cilcium, cobalt, gallium, iron, manganese, sodium, strontium, titanium, ytterbium, yttrium, and zirconium. The first 10 of these elemerts constitute a common pedologic 

association and, in fact, typical concentrations of these elements in 

the ash of Spanish moss are reaso lably close (except for manganese) 

to the expected concentrations in soils of the eastern United States. 

Sodium in plant ash increases oceanward and reflects accumulation 

of sea salt. The source(s) of calcium and strontium is ambiguous, 

but a source of at least some part of these two elements appears 

to be airborne limestone dust. This, factors 1 and 2 are interpreted 

as reflecting essentially inert accumulation of airborne particulate material, most of it of natural origin, Varimax factors 3 and 4 together 

describe most of the variation in the logarithmic concentrations of 

boron, cadmium, chromium, copper, lead, lithium, nickel, vanadium, 

and zinc. Lead reflects automotive exhaust inasmuch as most samples 

in this study were collected alorg roads. The remaining elements 

in this association may also reflect automotive-related effects, at least 

in part, but more likely all nine elements constitute a suite of urban, 

industrial, or technologically induced metals. This association is 

stochastically independent, or nearly so, of factors 1 and 2 (airborne 

particulates) and is viewed as largely anthropogenic in origin. Varimax factor 5 accounts for most af the variation in the logarithmic 

concentrations of magnesium, piosphorus, and potassium. These 

three elements are major metabolic constituents of living plant tissue, 

and the association is nearly independent of the other four factors 

(the airborne particulates and the technological metals). This 

suggests that, regardless of sourc<!, the concentrations of magnesium, 

phosphorus, and potassium in plant ash are being controlled more 

by metabolic need than by environmental influence.

INTRODUCTION

The effect of airborne materials on the quality of the 

human environment has prompted many investigators 

to search for means of measuring ambient atmospheric 

concentrations of these materials. Commonly, the 

methods consist of various procedures for collecting the

materials by filtration processes followed by chemical 

analysis of the materials, or for continuous instrumental 

monitoring of gaseous or airborne compounds. 

Shacklette and Connor (1973) described the results of 

a study in which Spanish moss (Tillandsia usneoides 

L.) was used to assess the variability of airborne elements in the southeastern part of the United States. 

They concluded that elemental analysis of Spanish moss 

or its ash seems to be an economical and rapid method 

with which to examine the relative average concentrations of airborne elements.

Spanish moss is classed as an epiphyte (generally 

called "air plants") and most commonly grows on trees. 

It is not parasitic because it gets all essential elements 

and water from the air and produces its own food by 

photosynthesis. Like most other species of the pineapple family (Bromeliaceae), Spanish moss has highly 

specialized morphological adaptations that assist in obtaining water and other materials from the air. Thus, 

it appears to be an ideal natural "monitor" with which 

to investigate element burdens in the local atmosphere 

of its native habitat. Previous studies of elements in 

Spanish moss, in addition to Shacklette and Connor 

(1973), include Maclntire and others (1952), Martinez 

and others (1971), Benzing and Renfrew (1971), Robinson and others (1973), Caruccio and others (1975), and 

Schrimpff (1981).

The elements available to Spanish moss from the air 

have many natural sources. The most obvious sources 

are dust consisting of soil and rock particles and, near 

the sea, salt from ocean spray. The mineral content 

of air and rainwater, and its importance to plant 

growth were discussed by Ingham (1950), and the effects of solutes leached from tree foliage and deposited 

on Spanish moss were noted by Schlesinger and Marks 

(1977). Although Spanish moss may at places benefit 

from elements in these leachates, it is not dependent 

on them, as shown by its growth on wire fences and 

utility wires (Daubenmire, 1974, p. 308).

The air carries much particulate matter of plant origin, characterized by Benninghoff (1965, p. 142) as

II
12 STATISTICAL STUDIES IN FIELD GEOCHEMISTRY

"...in enormous variety and large quantity," including 

spores, pollen, bacteria, single-celled algae, fungal 

mycelia, deciduous plant tissue parts, and fragments 

of vegetable humus. The exudates from forest trees and 

other plants contribute a share of the natural metal 

burdens of air. The volatile exudates from coniferous 

forests were analyzed by Curtin and others (1974) and 

were found to contain antimony, arsenic, barium, beryllium, bismuth, cadmium, chromium, cobalt, copper, gallium, iron, lanthanum, lead, lithium, magnesium, manganese, molybdenum, nickel, silver, sodium, strontium, 

tin, titanium, vanadium, yttrium, zinc, and zirconium. 

These volatile exudates consist largely of a variety of 

terpenes, and the world production of plant volatiles 

released into the atmosphere was estimated by Rasmussen and Went (1965, p. 220) to be 438 xlO6 tons 

per year. Went (1971) reported the polymerization of 

airborne terpenes into large (to 1 mm) clumps, which 

he called "air-soot," and that a certain amount of these 

clumps become attached to leaves and other plant 

parts.

Sub-micrometer-size particulate matter released by 

plants into the atmosphere was shown by Beauford and 

others (1977) to contain lead and zinc. Nyemyeryuk 

(1970) reported that the transpiration water given off 

by plants contained ammonium, calcium, chloride, magnesium, potassium, sodium, and sulphate ions. Fish 

(1972) found that strong electrical fields caused release 

from plants of airborne particles with diameters less 

than 0.6 micrometers.

In addition to these airborne particulates of plant origin, elements from inorganic sources iorm a 

background atmospheric burden of worldwide circulation. Zoller and others (1974), on the basis of air sampling at the South Pole, concluded that the elements 

were derived from crustal weathering or the ocean. 

These elements include aluminum, calcium, cerium, 

chromium, cobalt, europium, iron, lanthanum, manganese, potassium, samarium, scandium, sodium, thulium, 

and vanadium. Brocas and Picciotto (1967) believed that 

most of the nickel in Antarctic snow was of extraterrestrial origin, and they calculated that the extraterrestrial matter deposited over the entire Earth's surface is 3-10 million tons per year. Although these elements are potentially available to Spanish moss, their 

absorption is probably overwhelmed by effects of dust 

deposition, salt spray, and airborne anthropogenic pollutants from local sources.

For selected metallic elements, higher than average 

concentrations in ash of moss may reasonably be inferred to reflect higher than average atmospheric concentrations, suggesting the utility of Spanish moss as 

a monitor of the local atmospheric element load. For 

example, ash of plants collected close to roadways contains 18 times as much lead as ash of plants collected 

far from roads (Connor and Shacklette, 1973); presumably this lead is derived from lead-bearing automotive 

exhaust. Also, plants collected close to the ocean contain elevated concentrations of sodium in ash, and four 

of six samples containing detectable tin in ash were collected within 100 km of the only tin smelter in the 

United States.

Difficulties in the use of Spanish moss as a natural 

atmospheric monitor, however, are both varied and 

serious. For example, Spanish moss is composed of living tissue which undoubtedly interacts chemically with 

the atmosphere and substances in it. The concentration 

in ash of any element whose airborne compounds are 

selectively absorbed or repelled by the living plant will 

not faithfully reflect its ambient atmospheric concentration. Moreover, periodic "cleansing" of the plant by rain 

or wind may remove loosely held substances. In addition, such washing effectively enlarges the volume of 

atmosphere available to the plant by virtue of the fact 

that rainfall may chemically scavenge a considerable 

volume of overlying atmosphere. Also, over the life of 

the plant, or the life of the collected part, the chemistry 

of the local atmosphere may drastically and erratically 

change. Thus, at best, the chemistry of the plant ash 

can only reflect a time-averaged atmospheric composition.

Nevertheless, the potential use of Spanish moss as 

an indicator of airborne metals seems obvious, and this 

report examines the limits of that potential. The examination was based on a study of the correlations among 

logarithmic concentrations of 25 elements in 123 samples of plant ash. Of the 25 elements used in this examination, aluminum, cobalt, gallium, ytterbium, yttrium, 

and zirconium occurred in concentrations too low to be 

detected in one or more samples, and one sample was 

not analyzed for lithium (Shacklette and Connor, 1973). 

In order to include these seven elements, arbitrary values were assigned as needed to produce a completely 

numeric data set. The substitute values are listed 

below.

Element

Aluminum, percent

Cobalt, ppm

Gallium, ppm

Lithium, ppm

Ytterbium, ppm

Yttrium, ppm

Zirconium, ppm

Substituted value

15

5

7

22

1.5

15

15

Number of samples 

(of 123) substituted

3

21

28

1

32

29

2
FACTOR ANALYSIS OF THE CHEMISTRY OF SPANISH MOSS 13

The single sample lacking a lithium analysis was assigned a value equal to the geometric mean of the 122 

other lithium concentrations. The use of such values 

is admittedly arbitrary and is justified primarily by the 

belief that substitution of any reasonable value will not 

materially alter the conclusions derived from the factor 

analysis. Percent ash in each sample was added to the 

data set as a twenty-sixth variable.

Methods of sample collection and laboratory analysis 

as well as descriptions of sampling localities, element 

distribution maps, and element summaries may be 

found in Shacklette and Connor (1973). The factor 

analytical techniques were based on computer programs in Dixon (1975), and the U.S. Geological Survey's STATPAC system (VanTrump and Miesch, 1977).

FACTOR ANALYSIS

Techniques of .R-mode factor analysis were applied 

in an attempt to identify element associations in the 

ash of Spanish moss which may shed light on the probable sources of these metals in the atmosphere of the 

southeastern United States. .R-mode factor analysis has 

been widely applied as a means of examining the 

covariation in a data set by describing such covariation 

in terms of some minimum number of new variables, 

k (called "factors"), always less than the number of 

original variables, ra. Geometrically, the process involves defining each original variable as a unit vector 

in m-space, all originating from a common center, and 

with the angle between any two vectors inversely related to the covariation between the two variables. If 

examination of this vector complex indicates that the 

complex lies mostly in fc-space (k less than ra), then 

the original data will likely be more easily interpreted 

in terms of k factors. Projections of the ra vectors into 

the reduced space always results in shortening of the 

vectors, and their new lengths are taken as measures 

of the adequacy of the factor model. The square of the 

vector length is called the communality. The correlations of the vectors with the k factors are called the 

factor loadings. Numerous texts describe the mathematics of factor analysis. A widely used geologically 

oriented text is that of Davis (1973). Hopke (1980) described an application of factor analysis to aerosol composition of the Boston metropolitan area.

Correlation coefficients among the logarithms of 25 

element concentrations in ash and with log ash are 

given in table 1. The first 10 eigenvalues of this correlation matrix are listed in table 2. The first two eigenvalues are large compared to the remainder and indicate that the minimum number of factors in a geochemical model of these data should be at least two. Such 

a model would account for over half (52.7 percent) of

the total variation in the original data. Only five eigenvalues exceed 1.0, and a five-factor model accounts for 

an acceptably high 71 percent of the variation in the 

data.

Variable communalities for models containing as 

many as eight factors are represented in figure 1. In 

a five-factor model, all communalities exceed 0.50, and 

a five-factor varimax model was used to summarize the 

chemical variation in ash of Spanish moss. Varimax 

loadings of each chemical variable on these five factors 

are listed in table 3.

The elements with the highest loadings on the first 

two factors are titanium, zirconium, yttrium, ytterbium, aluminum, iron, gallium, manganese, sodium, 

strontium, calcium, barium, and cobalt (table 3). As discussed in the following paragraphs, we believe most 

of these elements are present in Spanish moss principally as surface coatings of natural airborne particulates, mostly as windblown soil dust or sea spray. Thus, 

we have labeled these factors together as "natural particulates." The most important elements in the third 

and fourth factors are zinc, lead, copper, cadmium, 

nickel, chromium, boron, lithium, and vanadium (table 

3). As these are believed to reflect largely urban or 

industrial sources of metals, we have labeled these factors together as "technological metals." The last factor 

appears to be biological in nature. It has a strong inverse correlation with ash content and positive correlations with magnesium, phosphorus, and potassium, 

which are major metabolic elements in plants. We have 

labeled this factor "metabolic constituents."

FACTORS 1 AND 2 NATURAL PARTICULATES

These factors are the most important descriptors of 

element variation in the varimax model of Spanish moss 

ash chemistry. Together, they account for over a third 

(37.4 percent) of the total observed variation in the ash 

data, and they describe more than half of the variation 

in the logs of titanium, zirconium, yttrium, ytterbium, 

aluminum, iron, gallium, manganese, sodium, strontium, calcium, barium, and cobalt.

A graphic evaluation of ash composition in terms of 

these two factors is shown in figure 2. The two factors 

define a cross section of the five-factor varimax model, 

and all chemical variables are represented as vectors 

projected onto this cross section. The distal end of each 

vector is defined by the loadings of the respective variable on the two factors (table 3). The strength of association of any variable to another, or to any factor axis, 

is inversely proportional to the angle between the two 

vectors or between the vector and the axis. A small 

angle reflects a strong positive association. A 90-de-
14 STATISTICAL STUDIES IN FIELD GEOCHEMISTRY

TABLE 1. Correlation coefficients among

[All chemical elements

Log Mg Log Ti Log Mn Log B Log Ba Log Co Log Cr Log Cu Log Ni

Log Fe -0.19 0.76 0.61 0.07 0.63 0.53 0.57 0.22 0.51 

Log Mg -.26 -.02 .25 -.23 -.03 -.11 .25 .12 

Log Ti .55 -.03 .63 .48 .55 .16 .37 

Log Mn -.17 .68 .48 .33 .16 .35 

Log B -.09 -.02 .02 .23 .28

Log Ba .58 .39 .03 .30 

Log Co .46 .13 .48 

Log Cr .36 .60 

Log Cu .57

Log Ni 

Log Pb 

Log Sr 

Log V 

Log Y 

Log Zr 

Log Al 

Log Ga 

Log Yb 

Log AshLog Ca 

Log LiLog Na 

Log K 

Log P 

Log Cd 

Log Zn

Log Pb

0.22 

.12 

.07 

.21 

.02

.20 

.15 

.25 

.48

.35

Log Sr

-0.54 

.34 

-.63 

-.39 

.11

-.36 

-.23 

-.27 

.03

-.12 

-.02

gree angle reflects no association, and a highly obtuse 

angle reflects a strong negative association. Short vectors (those with distal ends near the origin of the plot) 

are inadequately represented by these two factors, and 

their relations should be ignored.

The diagram in figure 2 is dominated by a fan of 

vectors that subtend an angle of some 60 degrees between the log barium vector and the log ytterbium vector. The 10 elements represented in this fan are common constituents of soils or near-surface sediments in 

the southeastern part of the United States. A comparison of the typical amounts of these elements in plant 

ash to typical amounts in soil (table 4) is close enough 

(with the exception of manganese) to suggest that the 

average plant ash is composed largely of soil material. 

Thus, the first two factors in the model reflect, to a 

large extent, simple accumulation of windblown soil or 

other near-surface material.

Log sodium, log strontium, and log calcium are negatively correlated with log aluminum and other variables 

of the soil component. Evidently, plant ash contains 

either relatively large amounts of the soil-related metTABLE 2. Eigenvalues (\) and cumulative variance associated with the first 10 principal components of the 

chemistry of Spanish moss ash

Principal 

component

1 

2 

o

4 

5 

6 

7 _

8

_ _ _ _

9 

10 

Eigenvalue 

(A)

8

0 O

4.89

2.13

1.55

1.16

.99

QO

.76

£Q

.54

Cumulative variance 

(in percent)

33.9 

52.7

61.0 

66.9

71.4

75.2

78.4

Q 1 Q

Q1 Q

af. n

als or relatively large amounts of sodium, strontium, 

and calcium. The most likely explanation for this inverse relation is that the ash consists of two dominant 

constituents (or their ashed equivalents), one of which 

was derived from soil and the other derived from mate-
FACTOR ANALYSIS OF THE CHEMISTRY OF SPANISH MOSS 15

26 variables measured in Spanish moss

were measured in ash]

Log V

0.29

.19

.25

-.03

.27

-.17

.03

.42

.36

.56

.17

-.04

Log Y

0.58

-.27

.70

.48

-.08

.40

.44

.42

.20

.30

.03

-.46

.26

Log Zr

0.70

-.34

.87

.62

-.11

.67

.42

.51

.15

.28

.10

-.66

.09

.67

Log Al

0.84

-.22

.83

.51

.13

.66

.56

.53

.17

.43

.16

-.55

.25

.61

.77

Log Ga

0.57

-.21

.66

.35

.04

.41

.53

.47

.19

.39

.12

-.35

.35

.70

.57

.67

Log Yb

0.57

-.27

.68

.47

-.07

.39

.36

.39

.15

.25

-.02

-.49

.21

.85

.66

.60

.57

Log Ash

-0.10

-.62

-.03

-.29

-.34

-.14

-.14

-.09

-.43

-.40

-.39

-.14

-.25

.00

.05

-.04

-.06

.01

Log Ca

-0.49

.16

-.63

-.43

.10

-.31

-.27

-.30

-.06

-.20

.09

.61

-.19

-.47

-.61

-.47

-.39

-.48

.02

Log Li

0.39

.21

.34

.12

.32

.14

.27

.33

.28

.33

.14

-.08

.38

.24

.26

.45

.38

.26

-.26

-.26

Log Na

-0.51

.45

-.60

-.59

.34

-.62

-.38

-.23

.07

-.15

-.04

.39

.10

-.57

-.64

-.49

-.47

-.56

-.11

.35

.11

Log K

0.14

.41

.18

.43

-.06

.33

.26

.09

.18

.21

.33

-.08

.00

.09

.12

.11

.11

.09

-.68

-.23

.22

-.14

Log P

-0.11

.34

-.12

-.04

.24

-.18

-.11

-.03

.24

.18

.19

.15

.25

-.11

-.23

-.16

-.09

-.15

-.56

-.06

.14

.27

.41

Log Cd

0.29

.37

.14

.21

.21

.26

.24

.33

.48

.48

.57

.03

.26

-.04

.07

.21

.09

-.05

-.60

-.02

.27

.08

.55

.44

Log Zn

0.20

.32

.09

.16

.17

.20

.17

.31

.64

.41

.80

.10

.22

.00

.05

.15

.11

-.02

-.52

.08

.25

.03

.44

.32

.74

rials high in sodium, strontium, and calcium. The 

amount of ash bears no apparent relation to the relative 

amounts of either of these two constituents, inasmuch 

as log ash has loadings near zero on both factors (table 

3), and the inverse relation of the two element suites 

likely reflects local differences in the average long-term 

atmospheric particulate load.

Sodium in ash is clearly related to nearness to the 

ocean (fig. 3) and, hence, reflects accumulation of salt 

from that source. The inverse relation of log aluminum 

to log sodium (fig. 2) is noted in figure 3 by the contour 

line representing a ratio of aluminum to sodium of 1.0. 

This contour closely follows the Atlantic and Gulf 

coasts.

Calcium is an essential constituent of living plant tissue, but its lack of correlation with the other metabolic 

constituents, magnesium, phosphorus, and potassium 

(table 1), is puzzling. Calcium in ash apparently occurs 

as calcite (fig. 4). The ash represented in figure 4 contains 16 percent calcium, equivalent to 40 percent calcite. Other constituents include dolomite, langbeinite (a 

potassium magnesium sulfate), and minor clay and

quartz. The clay and quartz content undoubtedly reflect 

airborne clay and quartz, but the calcium and potassium 

compounds probably reflect oxidative changes upon 

ashing of the dried organic-rich material. In most 

higher plants, of which Spanish moss is one, calcium 

occurs between the cell walls as a salt of pectic acid. 

Pectic acid is a long chain polysaccharide that would 

oxidize completely during the ashing process, leaving, 

perhaps, calcite (L. P. Gough, written communication, 

1982).

Alternatively, at least some of the caleite in the plant 

ashes of this study almost certainly reflects accumulation of airborne limestone particulates. Gatz (1977, 

table 6), in a St. Louis-based study, found that as much 

as 18 percent of the particulate load in air was limestone dust. Probable sources for such particulates could 

include clouds of limestone dust from carbonate aggregate road surfaces, limestone quarries, cement factories, or agricultural liming. Conceivably, any covariation of tissue calcium with tissue magnesium, phosphorus, and potassium is being overwhelmed by the surface accumulation of limestone dust, accounting for the 

failure to find a positive logarithmic correlation of calci-
16 STATISTICAL STUDIES IN FIELD GEOCHEMISTRY

4 5 

NUMBER OF FACTORS IN MODEL

FIGURE 1. Factor-variance diagram relating variable communalities (h2) to number of factors in the varimax model of geochemistry of Spanish moss.
FACTOR ANALYSIS OF THE CHEMISTRY OF SPANISH MOSS 

FACTOR 2

17

FIGURE 2. Relations of chemical variables (vectors) to each other and to factors 1 and 2 in the five-factor varimax model of variation.

um with magnesium, phosphorus, and potassium. 

Clearly, the role of calcium in this study is complex.

Factors 1 and 2, as indicated in figure 2, appear to 

reflect two chemically distinct soil types: The first (factor 1) is high in yttrium and ytterbium; the second is 

high in barium and cobalt. As noted previously, both 

types are inversely related to sea salt, but the yttriumytterbium-rich soil has a stronger inverse relation to

calcite (log calcium) than does the barium-cobalt-rich 

soil.

A measure of the importance or intensity of each factor in each sample of this study may be seen in the 

factor score for each sample. These scores are computed from Dixon (1975, p. 179) as:

F=ZR~1A, (1)
18 STATISTICAL STUDIES IN FIELD GEOCHEMISTRY

TABLE 3. Loadings of chemical variables on the factors of the five-factor varimax model

[*, loading is significantly different from zero at the 0.05 probability level; number in parentheses is percent of variation described by factor]

Loadings

Factor 1 Factor 2 Factor 3 Factor 4 Factor 5 Sum of percentages

Variable

Metabolic 

Natural particulates Technological metals constituents (100 h )

Log titanium 

Log zirconiumLog yttrium 

Log ytterbiumLog aluminum 

Log iron 

Log gallium 

Log manganeseLog sodium 

Log strontiumLog calcium 

Log zinc 

T -1 J

uOg IGciQ

Log copper 

Log cadmium 

Log nickel - 

Log chromium 

Log boron 

Log lithium 

Log vanadium 

Log ash -

Log magnesiumLog phosphorus

Log potassiumLog barium 

Log cobalt 

0,87(76)*

.84(71)*

.83(69)*

.82(68)*

.72(52)*

.71(50)*

.67(45)*

.57(33)*

-.64(40)*

-.74(55)*

-.78(60)*

-.06«1)

-.02«1)

.12(2)

-.02«1)

.31(9)*

.48(23)*

-.16(3)

.27(7)*

.30(9)*

.04«1)

-.36(13)*

-.07(1)

.15(2)

.47(22)*

.37(14)*

0.26(7)*

.31(9)*

.05«1)

.04«1)

.43(18)*

.39(15)*

.20(4)

.49(24)*

-.39(16)*

-.02«1)

.09(1)

.12(1)

.12(1)

-.15(2)

.19(4)

.14(2)

.17(3)

-.01«1)

.09(1)

-.43(19)*

-.09(1)

-.04«1)

-.35(13)*

.24(6)*

.77(60)*

.65(43)*

0.10(1)

.09(1)

.08(1)

.02«1)

.16(2)

.25(6)*

.17(3)

.13(2)

-.03«1)

.07(1)

.14(2)

Q c / ~J O \ 4- o_>(, / JJ X

.84(70)*

.74(55)*

.66(44)*

.59(34)*

.49(24)*

.04«1)

.11(1)

.37(14)*

-. 34(12)*

.09(1)

.20(4)

.19(4)

.14(2)

.16(3)

0.12(1)

-.04«1)

.08(1)

.05«1)

.31(10)*

.23(5)*

.30(9)*

-.18(3)

.38(15)*

.14(2)

-.01«1)

.03«1)

-.14(2)

.22(5)*

.16(2)

.45(20)*

.30(9)*

7 oy c o \ 4-

 / J\ _> 3)*

.66(44)*

.55(30)*

-.24(6)*

.33(11)*

.13(2)

-.12(1)

-.10(1)

.23(5)*

-0.01«1)

-.08(1)

-.08(1)

-.07«1)

-.09(1)

-.03(1)

-.11(1)

.31(10)*

.12(2)

.02«1)

-.24(6)*

.31(10)*

.16(3)

.14(2)

.49(24)*

.08(1)

-.16(3)

.12(1)

.20(4)

.03«1)

-.80(64)*

.64(41)*

.66(44)*

.83(69)*

.08(1)

.03«1)

85

82

72

68

83

77

62

70

73

58

69

84

76

66

74

66

62

57

57

72

Q1O J

66

64

82

86

65

TABLE 4. Typical concentrations (in parts per million) of 

selected elements in ash of Spanish moss and soils of the 

eastern United States

Spanish moss ash 

Element (geometric mean, 

Shacklette and

Connor, 1973)

Titanium 

Zirconium 

Yttrium 

Ytterbium 

Aluminum 

Iron 

Gallium 

Manganese 

Barium 

Cobalt 

2,300

110

30

2.4

40,800

15,800

9.8

2,300

564 

9.8

Eastern U.S. soils 

(geometric mean, 

Shacklette and

others, 1973)

3,000

250

23

3

33,000

15,000

10

285

300 

7

where F is a matrix of factor scores (of 123 rows and 

5 columns), Z is the data matrix transformed to standard measure (123 rows and 26 columns), R~l is the 

inverse of the logarithmic correlation matrix (table 1, 

26 rows and 26 columns), and A is the matrix of factor 

loadings (table 3, 26 rows and 5 columns).

If the matrix Z is recast into logarithmic form ("unstandardized"), the factor scores can then be computed 

using the original logarithmic data. This change can be 

accomplished by:

(2)

where Xy- is the logarithmic concentration of variable 

i in sample j, s^ is the log standard deviation of variable 

i, Zij is the standardized value of the logarithmic con-
FACTOR ANALYSIS OF THE CHEMISTRY OF SPANISH MOSS 19

HTS-81

20

10

o

SODIUM IN ASH, IN PERCENT

FIGURE 3. Sodium in ash of Spanish moss (modified from Shacklette and Connor, 1973, p. E34). Points interior to the contour line, except 

for HTS-294, have Al > Na; points seaward of the line, except HTS-81, have Na > Al.

centration of variable i in sample .;', and ra; is the log 

mean of variable i.

The score for factor 1 in an individual ash sample 

is computed from:

+ 62(LogA% + . . . + 626 (LogZr)j, (3)

where F^ represents the score for factor 1 in the jth 

ash, the 6's represent the constant (60) and the coefficients listed in the first column of table 5, and the variables are logs of element concentrations (expressed in 

the units listed in table 5) in the jth ash. Scores for 

factor 2 used the coefficients in the second column of 

table 5.

Maps of the scores for factors 1 and 2 are shown 

in figures 5 and 6. High scores indicate relatively large 

amounts of soil-derived metals in ash; low (negative) 

scores indicate relatively large amounts of sodium (from 

sea salt) or calcite in ash. The sample ash exhibiting
no STATISTICAL STUDIES IN FIELD GEOCHEMISTRY

	EXPLANATION

D Dolomite

P Potassium hydrogen phosphate, K2H2P2O??

L Langbeinite

Q Quartz

C Calcite

U Unknown

Cl Clay

Degrees 29 CuK,

FIGURE 4. X-ray diffraction pattern of ash of Spanish moss.

the highest score for factor 1 (that is, the ash with 

the largest ratio of yttrium-ytterbium-rich soil to calcite 

and sodium) comes from a sample collected in southwest Georgia. The ash with the lowest score (the ash 

with the smallest ratio) comes from a sample collected 

near Fort Lauderdale, Fla. The sample ash with the 

highest score for factor 2 (large amounts of bariumcobalt-rich soil) comes from a sample collected near

Baton Rouge, La., and the ash with the lowest score 

comes from a plant collected near Lakeland, in central 

Florida.

Both factors have strong regional trends (figs. 5 and 

6). These trends were estimated using stepwise trend 

analysis as described by Miesch and Connor (1968). Fifteen potential regressors were defined: X, Y, X2 , XY, 

Y2, Xs, X2Y, XY2 , F3, Log X, Log Y, (Log X)
FACTOR ANALYSIS OF THE CHEMISTRY OF SPANISH MOSS

o SAMPLING SITE 

FIGURE 5. Contour map of scores for factor 1. Regional trend accounts for 41.6 percent of the variation.

(Log F), ex, eY, and exeY, where X is north latitude 

divided by 100 and Y is west longitude divided by 100. 

A statistically significant trend in the first factor was 

found to be:

7\=-97.77-0.000253(LAT)3 + 70.76(Log LAT), (4)

where Tl estimates a score for factor 1 and LAT stands 

for north latitude. The trend equation in (4) accounts 

for 41.6 percent of the total variation in figure 5; that 

is, over 40 percent of the variation seen in the scores 

of factor 1 is regional. The strong northward increase 

in the yttrium-ytterbium-rich soil component (factor 1) 

presumably reflects a northward increase in such soil 

in the atmosphere. The highest atmospheric concentrations, then, would appear to lie along a rough east-west 

line, from northern Louisiana through southern Mississippi and Alabama into southwestern Georgia.

Scores for the second factor were also examined by 

trend analysis, and the best predictor equation was 

found to be:

.00002261(LAT)(LONG)2, (5)

where T2 stands for an estimated score on factor 2. 

The equation in (5) accounts for 50.5 percent of the 

total variation in the scores for factor 2. The westward 

increase in the barium-cobalt-rich soil component (factor 2) presumably reflects high atmospheric concentrations of such soil in central and southeastern Texas.

Additional variables involved in a statistically significant way with these natural particulates are the 

logarithms of nickel, chromium, lithium, vanadium, 

magnesium, phosphorus, and potassium (table 3). Nickel, chromium, lithium, and vanadium are common constituents of soil, and they are probably being accumulated to some degree as part of the soil components. 

Potassium, and perhaps magnesium, are also probably 

being so accumulated, but as primary constituents of 

living plant tissue, they are being controlled more by 

the physiological demands of the plant than by simple 

surface capacity for accumulation. In addition, log magnesium is positively related in a weak way to log calcium and reflects the association of minor dolomite with 

calcite in the ash (fig. 4). Also, log phosphorus is negatively related in a weak way to the barium-cobalt-rich 

soil component. Conceivably, this reflects a phospho-
112 STATISTICAL STUDIES IN FIELD GEOCHEMISTRY

TABLE 5. Parameters for use in computing component scores

Variable

Aluminum, percentBarium, ppm 

Cadmium, ppm ------

Calcium, percent -

Chromium, ppm 

Cobalt, ppm -

Copper, ppm 

Gallium, ppm 

Iron, percent ~

Lithium, ppm 

Magnesium, percent

Manganese, ppm 

Phosphorus, ppm 

Potassium, percent

Sodium, percent 

Strontium, ppm 

Titanium, percentVanadium, ppm 

Ytterbium, ppm 

Zinc, ppm -

Zirconium, ppm -

1

Natural

0.2348

.1071

-.1372

-.1992

-1.1044

.0981

-.3247

.0975

.4080

.1863

.0230

-.2377

.1255

.4589

.1663

-.1273

-.6506

.4369

.4619

.7497

-.1815

.3696

2

particulates

-1.7691

.4403

.9967

.2850

1.1298

.0328

1.5217

-.5647

.0755

.3863

.3478

.2469

.3519

-1.2703

.2230

-.1166

.5876

-.0487

-1.2981

-.6367

-.0061

.0188

Components

3

i Technological

Constants (bQ )

-8.3097 -9.

Coefficients

-.0857

-.0650

.6698

.6320

.6740

-.2012

.8986

.0194

.0722

-.5993 1.

-.4700

-.0819

-.0900

-.3029

-.1641

.1124

-.0871

.4261

-.0794

1.1476

.0093

4

metals

4415

4418

0484

0875

2749

3246

6632

1195

6455

3049

7382

6307

2686

1944

4916

3270

4326

0652

6560

1197

4402

1618

5

Metabolic

-3.1189

-.1676

.0421

.3746

-.9718

-.6319

-.1265

-.2140

-.3319

-.1514

.2788

.9953

.3486

1.4286

1.4581

.0270

-.2161

.0590

-.1920

.0668

-.0722

-.0198

rus-enriched atmosphere along the Atlantic coastal 

plain of North Carolina and Florida, where over fourfifths of the nation's phosphate is mined (National Research Council, 1979, p. 52).

In summary, the two most important factors appear 

to reflect simple accumulation of natural atmospheric 

particulates. These particulates apparently include two 

types of soil dust, ocean salt, and limestone dust. 

Where the soil fractions in plant ash are enhanced, the 

salt and limestone fractions are diminished, and this 

relation probably reflects a similar relation in the local 

atmosphere: the landward atmosphere is enhanced in 

soil dust, and the seaward atmosphere is enhanced in 

salt and limestone dust. Variation in total ash content 

is unrelated to variation in these fractions, suggesting 

that the surface of the living plant tends to be continually "saturated" with whatever fraction is dominant in 

the local atmosphere.

FACTORS 3 AND 4 TECHNOLOGICAL METALS

Factors 3 and 4 account for 23.0 percent of the total 

variation in the original data and describe over half of 

the variation in the logs of zinc, lead, copper, nickel, 

and boron (table 3). A vector diagram illustrating the 

relations among these variables is shown in figure 7.

Like the soil metals (fig. 2), the technological metals 

also form a vector fan. The vectors in this fan represent 

cadmium, chromium, vanadium, and lithium, as well as 

the metals listed above. Most of the short vectors represent elements in the natural particulates (fig. 2), 

which vary in a manner nearly independent of the technological metals. Thus, accumulation of the technological metals in Spanish moss appears to occur almost independently of the accumulation of the natural particulates. Also, as ash content increases, the accumulation 

of the technological metals tends to decrease slightly.

Although all of the nine technological metals occur 

in trace amounts in soil, the generally low logarithmic 

correlations of these metals with log aluminum indicates that sources other than soil control their occurrence in Spanish moss ash. The source of lead (factor 

3) is unquestionably vehicular exhaust emissions, which 

have been estimated to account for as much as 98 percent of the atmospheric lead in the country (Cannon, 

1976, table 35). Over three-fourths of the Spanish moss 

samples in this study were collected along roads; the 

ash of one sample collected along Interstate Highway 

75 in northern Florida contained 5 percent lead. The 

close relations of zinc, copper, and cadmium to lead in 

the vector fan indicate that these metals are also related to vehicular traffic, if not in exhaust fumes then 

perhaps to road materials (asphalt, for example) or the 

vehicles themselves (tires, grease and oil, and metal 

body parts, for example). Cannon and Anderson (1971) 

noted elevated levels of chromium, zinc, nickel, and 

copper in vegetation adjacent to highways.

Boron, lithium, and vanadium lie at the other end 

(factor 4) of the technological-metals vector fan. Zoller 

and others (1973), in a study of atmospheric vanadium, 

concluded that a major source in the northeastern cities 

of the United States is the combustion of vanadium-rich 

residual oil for heat and electric-power generation. 

Schroeder (1970, p. 802) noted, "The mean concentrations of vanadium in the air of Atlantic cities was twice 

as high during the first and fourth quarters of the year 

as in the second and third. These variations suggest 

that fuel oil used for heating contributes half the vanadium in air." Even in Alaska, Rahn and others (1981) 

attributed high vanadium-aluminum ratios in the atmosphere (with respect to such ratios in the Earth's 

crust) to air pollution.

Even if the vanadium in Spanish moss ash is derived 

from the combustion of fuel oil, it is unlikely that either 

boron or lithium is reflecting the same source. Cadmium, chromium, nickel, and vanadium are important 

in steel manufacturing; cadmium, chromium, copper, 

lithium, nickel, and zinc are commonly alloyed with 

other metals; copper and zinc are in brass; and boron
FACTOR ANALYSIS OF THE CHEMISTRY OF SPANISH MOSS 113

EXPLANATION

COMPONENT SCORES

FIGURE 6. Contour map of scores for factor 2. Regional trend accounts for 50.5 percent of the variation.

and lithium are in glass products. Caruccio and others 

(1975) found elevated nickel in Spanish moss near a battery-fabrication plant in South Carolina.

Coal combustion is an additional obvious source of 

these (and other) metals to the atmosphere. Stolzenburg and others (1982, p. 82), in a study of suspended 

particulates in an unidentified industrial site, estimated 

that 34 percent of the particulates came from coal and 

fuel oil fly ash, automotive emissions, and iron and steel 

manufacture. In a nearby rural site, these same sources 

still accounted for 13 percent of the atmospheric load. 

A similar study in St. Louis (Gatz, 1977, p. 22) attributed 10-20 percent of the total urban aerosol load to 

these same sources. The technological metals in 

Spanish moss obviously reflect accumulation of artificial 

aerosols, in contrast to accumulation of natural particulates represented by factors 1 and 2.

Aluminum, cobalt, gallium, iron, magnesium, and sodium are positively associated in a minor way with the 

boron-rich end of the technological-metals fan. Although all six elements are involved in industrial processes of one kind or another, the element association

as a whole is a geologic one. All are common constituents of sedimentary rock or soil, as are boron, 

lithium, and vanadium. Thus, the boron-rich end of the 

technological spectrum (factor 4) probably reflects, to 

some small extent, accumulation of natural particulates 

as well as accumulation of anthropogenic aerosols.

Scores for factors 3 and 4 (the lead-rich and boronrich ends of the technological-metals spectrum) are 

shown in figures 8 and 9. The score for an individual 

ash is computed from:

-, . .+626 (LogZr),, (6)

where F3j represents the score for factor 3 in the jth 

ash, the b's represent the constant (60) and the coefficients listed in the third column of table 5, and the 

variables are logs of element concentrations (expressed 

in the units listed in table 5) in the jth ash. Scores 

for factor 4 used the coefficients in column 4 of table 

5.
114 STATISTICAL STUDIES IN FIELD GEOCHEMISTRY

FIGURE 7. Relations of chemical variables (vectors) to each other and to factors 3 and 4 in the five-factor varimax model of variation.

Plants whose ash exhibits the highest and lowest 

scores on factor 3 (the lead-rich end) were both collected in Florida. The highest score was for a plant 

collected in central Florida, and the lowest was for a 

plant collected from the southern tip of Florida, on 

Paradise Key, Everglades National Park. The fact that 

the lowest score occurs in an area where man's impact 

on the local environment has been minimal further reflects the fact that this component is an anthropogenic 

one. Other areas represented by high scores for factor 

3 are the Galveston-Houston area in Texas (where tin 

was also detected) and much of Louisiana, the Florida 

panhandle, and the northern fringe of the plant's range 

through Mississippi, Alabama, and Georgia. The sample 

with the highest score on factor 4 (the boron-rich end) 

is one collected near Montgomery, Ala., and the sample
FACTOR ANALYSIS OF THE CHEMISTRY OF SPANISH MOSS 115

EXPLANATION

COMPONENT SCORES

O SAMPLING SITE

FIGURE 8. Contour map of scores for factor 3.

with the lowest was collected in northeastern 

Louisiana. Scores for ash from samples along the eastern seaboard tend to be high (where Schroeder, in 

1970, noted elevated levels of atmospheric vanadium), 

but scores for ash from local areas in Alabama and 

Texas are also high.

The scores for factors 3 and 4 were examined by 

stepwise trend surface analysis, using the same 15 potential regressors used in the analysis of factors 1 and 

2. No significant regional trends were found, and we 

conclude that these factors, unlike factors 1 and 2 (natural participates), display only local variation. Thus, 

the source or sources of the elements important to 

these factors are widely distributed and presumably diverse in character, as are industrial and urban activities.

FACTOR 5 METABOLIC CONSTITUENTS

Factor 5 accounts for 11.0 percent of the total chemical variation in the data, and it accounts for more of 

the variation in the logs of ash content, magnesium, 

phosphorus, and potassium than any other factor (table 

3). Because magnesium, phosphorus, and potassium 

constitute major metals active in plant metabolism,

their concentration in living tissue should be controlled 

largely, if not exclusively, by physiological demand. 

Simple (inert) accumulation, which has been invoked to 

explain the presence of other metals in Spanish moss 

ash, seems untenable here.

The strong inverse relation of magnesium, phosphorus, and potassium to ash content (table 1) most likely 

reflects the increase in total sample mass by accumulated aerosols. As integral components of living tissue, 

magnesium, phosphorus, and potassium might be expected to occur in fixed proportions both to themselves 

and to the living mass of the plant as a whole. Thus, 

a plant with a large ash content reflects a large dilution 

of metabolically controlled elements by airborne materials; and a plant with a low ash content, because of 

a smaller accumulation of airborne materials, exhibits 

a greater proportion of the major metabolic elements 

in its ash.

The specific atmospheric source(s) of the magnesium, 

phosphorus, and potassium that were found in the ash 

is unknown. Although ordinary soil dust probably contains a supply sufficient to account for the amounts 

found, the independence of the metabolic and naturalparticulates components suggests specific biological interactions of plant tissue with these elements in ordi-
116 STATISTICAL STUDIES IN FIELD GEOCHEMISTRY

 - ""^~'~^Bj\

i -"~" t'-zf/ff^

f NC» /S*VJ

EXPLANATION

COMPONENT SCORES

FIGURE 9. Contour map of scores for factor 4.

nary atmospheric sources. Schlesinger and Marks 

(1977) found that trees with a high rate of foliar leaching (for example, cypress and oaks) provided an abundant supply of calcium, magnesium, phosphorus, and 

potassium for the growth of Spanish moss. They also 

found that this plant, if growing on trees having a low 

rate of foliar leaching (for example, pines), contained 

low concentrations of these elements. The metabolically 

essential elements, as well as others, may conceivably 

be supplied to Spanish moss by leachates and exudates 

from the host trees. However, at sites such as dead 

trees, telephone wires, and, possibly, pine trees, other 

sources must provide these elements.

Aerosol accumulation by Spanish moss is undoubtedly a lifelong process, and the plant mass probably 

supports a more or less continual aerosol "cover," but 

it need not follow that the specific material composing 

this cover never changes. The cover will presumably 

experience a slow continual partial turnover. Sloughing 

by wind or leaching by rain, for example, may serve 

to intermittently and partly clean the plant prior to additional accumulation. In this way, the plant may continually extract the magnesium, phosphorus, potassium, or other nutrients required for vital functions over 

its lifetime.

Scores for the metabolic-constituents factor are 

shown in figure 10. The score for an individual ash is 

computed from:

i(Log Ash),-

.+&26(LogZr)> (7)

where F5j represents the score for factor 5 in the jth 

ash, the b's represent the constant (60) and the coefficients listed in the fifth column of table 5, and the variables are logs of element concentrations (expressed in 

the units of table 5) in the jth ash.

Variation in this factor reflects to a large extent simple variation in ash content. An ash with high concentrations of magnesium, phosphorus, or potassium (that 

is, a plant with relatively low ash content) will exhibit 

a large positive score, and an ash with low concentrations of these elements will exhibit a large negative 

score. Plants with relatively low ash contents seem to 

be fairly well restricted to eastern areas of the plant's 

habitat (fig. 10). The highest score on factor 5 is for 

a plant collected on the Gulf Coast in Alabama, and 

the lowest score is for a sample from southern Texas.

The scores for this factor were examined by stepwise 

trend analysis using the same 15 potential regressors
FACTOR ANALYSIS OF THE CHEMISTRY OF SPANISH MOSS 117

i""-*""* / :>^5O £V

~4_ess8-/^ , J /s / !^/

^x\r k*~*i» -» ^-ri»

COMPONENT SCORES

[m^Cl +1 _2 ^^

FIGURE 10. Contour map of scores for factor 5. Regional trend accounts for 13.9 percent of the variation.

as before. The best predictor equation for the regional 

variation is:

T5=^24.8-0.00001353(LONG)3 

-109.3(Log LAT)(Log LONG)

+ 218.6(Log LAT + Log LONG), (8)

where T5 stands for an estimate of the score, LAT 

stands for north latitude, and LONG stands for west 

longitude.

The trend equation in (8) accounts for a small, but 

statistically significant, 13.9 percent of the total variation shown in figure 10. This trend indicates that the 

ratio of accumulated materials to the content of 

metabolic elements tends to increase to the southeast 

and southwest. The data at hand are insufficient to determine whether such an effect reflects a broad-scale, 

but weak, variation in atmospheric dust levels, or a 

similarly weak regional variation in metabolic activity 

of some kind.

A few other metals appear to be associated in a weak 

way with the metabolic constituents. Logarithms of 

manganese, zinc, and cadmium are positively associated

with factor 5 (table 3), suggesting that these metals 

may be related to metabolic activity in the plant. Log 

calcium is negatively associated with factor 5, but as 

pointed out previously, the role of calcium is complex 

and poorly understood; the weak relation between log 

calcium and factor 5 remains unexplained.

SUMMARY AND CONCLUSIONS

This study was done to test the utility of Spanish 

moss as a chemical monitor of the local atmosphere. 

The increase of sodium in samples near the ocean and 

the enormous amounts of lead in samples along highways demonstrate the feasibility of using the plant as 

a natural air monitor. The factor analysis described in 

this report has resulted in a specific descriptive model 

of chemical variation in ash of Spanish moss. The model 

appears to be mathematically adequate, in that five independent factors describe nearly three-fourths of the 

total observed variation, and also empirically informative, in that the factors have aided in identifying some 

major compositional phases accumulated by living tissue. Some of these phases were expected (lead-rich
118 STATISTICAL STUDIES IN FIELD GEOCHEMISTRY

vehicular exhaust, for example), and others were not 

(two kinds of airborne soil dust, for example).

The concentrations of magnesium, phosphorus, and 

potassium in Spanish moss relate inversely to the 

amount of ash and reflect largely physiological demand. 

The specific atmospheric sources of these three elements are unknown, but if, as we have theorized, they 

occur in clean tissue in constant amounts, then their 

observed variations in ash result from simple dilution 

by accumulated aerosols. Although accumulation of airborne substances, as pointed out earlier, likely involves 

something more than simple filtration of air, the chemical variation observed in ash is most easily interpreted 

in just such a filtration sense.

The accumulated material apparently consists of a 

number of compositional phases, and each appears to 

be reflecting one or more distinct sources, some of 

which are thought to be natural and others artificial 

or anthropogenic. The naturally occurring material 

forms the bulk of the airborne substances and seems 

to consist largely of particulates of soil, sea salt, and 

perhaps limestone. The strong inverse relation between 

soil-related elements and the salt and limestone-related 

elements in ash suggests a competition for depositional 

sites on plant tissue. Such a competition could reflect 

a similarity in average size or surface properties of the 

naturally occurring substances.

Variation in metals thought to be artificially introduced into the atmosphere reflects a variety of 

urban and industrial sources, at least one of which is 

lead-rich vehicular exhaust, and a second of which may 

be vanadium-rich heating fuel. Because variability in 

the technological metals is only weakly related to variability in the natural particulates, the accumulation of 

the anthropogenic and natural materials appears to be, 

for all practical purposes, independent of each other. 

This may reflect a lack of site competition in element 

accumulation between the two kinds of materials. If the 

artificial substances are aerosols of a different size or 

shape (or perhaps gaseous) than the naturally occurring 

particulates, the living tissue may be interacting with 

these two differing materials independently. For example, Friedlander (1973, fig. 2), in a study in Pasadena, 

Calif., showed that automotive exhaust aerosols were 

mostly less than 1 micrometer in diameter, whereas atmospheric soil and dust particulates were mostly greater than 1 micrometer in diameter.

An additional difference between the two kinds of 

materials is that the natural particulates appear to vary 

regionally in their source composition (figs. 5 and 6), 

whereas the artificial aerosols do not (figs. 8 and 9). 

Natural sources, like soil dust or sea salt, are relatively 

uniform in composition and occur continuously over

large areas, but anthropogenic sources act as many 

highly diverse and widely distributed point sources, so 

that resulting atmospheric concentrations may fluctuate 

widely over relatively short distances. Failure to find 

regional trends in data points spaced at about a 50-km 

interval (figs. 8 and 9) suggests that anthropogenic 

point sources significantly contribute to the local atmospheric load for distances on the order of a few hundred 

kilometers or less.

Of the total chemical variation observed in ash of 

Spanish moss, about 37 percent appears to reflect variation in local atmospheric levels of naturally occurring 

materials (factors 1 and 2), about 23 percent appears 

to reflect variation in local atmospheric levels of artificially introduced materials (factors 3 and 4), about 11 

percent is due to simple dilution of metabolically controlled elements by accumulated dust (factor 5), and 

the remaining 29 percent reflects variation from unknown sources, the most important of which is probably 

related to sampling and laboratory errors. Probable 

sources of the 25 elements in Spanish moss discussed 

in this study are listed in table 6.

TABLE 6. Sources of elements in Spanish moss

Element Most probable source, or sources

Aluminum Soil dust.

Barium Soil dust.

Boron Various industrial sources.

Cadmium Automotive exhaust?

Calcium Cement manufacture?, road aggregate?

Chromium Automotive exhaust?, soil dust.

Cobalt Soil dust.

Copper Automotive exhaust?

Gallium Soil dust.

Iron Soil dust.

Lead Automotive exhaust.

Lithium Various industrial sources.

Magnesium- Unknown.

Manganese Soil dust.

Nickel Various industrial sources.

Phosphorus Unknown.

Potassium- Unknown.

Sodium Sea water.

Strontium- Cement manufacturing?, road aggregate?

Titanium Soil dust.

Vanadium Fossil fuels.

Ytterbium- Soil dust.

Yttrium Soil dust.

Zinc Automotive exhaust?

Zirconium- Soil dust.
FACTOR ANALYSIS OF THE CHEMISTRY OF SPANISH MOSS 119

REFERENCES CITED

Beauford, W., Barber, J., and Barringer, A. R., 1977, Release of 

particles containing metals from vegetation into the atmosphere: 

Science, v. 195, p. 571-573.

Benninghoff, W. S., 1965, Atmospheric participate matter of plant 

origin, in Sukalo, L. H., ed., Proceedings of the Atmospheric 

Biology Conference, April 13-15, 1964: Minneapolis, University 

of Minnesota and National Aeronautics and Space Administration, p. 133-144.

Benzing, D. H., and Renfrew, A., 1971, The nutrient status of populations in south Florida, pt. 1 of The biology of the epiphytic 

bromeliad Tillandsia circinata Schlecht.: American Journal of 

Botany, v. 58, no. 9, p. 867-873.

Brocas, J., and Picciotto, E., 1967, Nickel content of Antarctic 

snow Implications of the influx rate of extraterrestrial dust: 

Journal of Geophysical Research, v. 72, no. 8, p. 2229-2236.

Cannon, H. L., 1976, Lead in the atmosphere, natural and artificially 

occurring lead, and the effects of lead on health, in Lead in the 

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Statistical Studies in 

Field Geochemistry

U.S. GEOLOGICAL SURVEY PROFESSIONAL PAPER 574

Published separately as 

chapters A-I
DEPARTMENT OF THE INTERIOR 

WILLIAM P. CLARK, Secretary

U.S. GEOLOGICAL SURVEY 

Dallas L. Peck, Director
CONTENTS

[Letters designate the chapters]

(A) Theory of error in geochemical data, by A. T. Miesch.

(B) Methods of computation for estimating geochemical abundance, by A. T. Miesch.

(C) Geochemical environments and cardiovascular mortality rates in Georgia, by Hansford T. 

Shacklette, Herbert I. Sauer, and A. T. Miesch.

(D) Elemental composition of surficial materials in the conterminous United States, by Hansford

T. Shacklette, J. C. Hamilton, Josephine G. Boerngen, and Jessie M. Bowles. 

(E) Airborne chemical elements in Spanish moss, by Hansford T. Shacklette, and Jon J. Connor. 

(F) Background geochemistry of some rocks, soils, plants, and vegetables in the conterminous

United States, by Jon J. Connor and Hansford T. Shacklette. 

(G) Q-mode factor analysis of geochemical and petrologic data matrices with constant row-sums,

by A. T. Miesch. 

(H) Compositional structures in two batholiths of circumpacific North America, by A. T. Miesch

and Bruce L. Reed. 

(I) Factor analysis of the chemistry of Spanish moss, by Jon J. Connor and Hansford T.

Shacklette.