Evaluating the Utility of
Natural Vegetation in Assessing Arctic
Accumulation of Air Toxics

-------
EVALUATING THE UTILITY OP NATURAL VEGETATION IN ASSESSING ARCTIC
ACCUMULATION OF AIR TOXICS
May 7, 1991
Dr. Mary V. Santelmann
Department of General Science
Oregon State University
355 Weniger Hall
Corvallis, OR 97331-6505
Final draft
Prepared for Arctic Accumulation of Air Toxics (AAAT) Project
US-EPA Corvallis Research Lab
Order Number:0B0348NATA

-------
Table of Contents
List of Figures		i
List of Tables	vi
1.0. Introduction 		1
2.0 Methods used in the present study		5
2.1	Site selection			5
2.2	Sample collection and handling ..........	11
2.3	Standards	15
2.4	Detection limits 		16
3.0 Discussion of data from the present study	17
3.1 Comparison of the different species 		17
3.2.1	Relationship between element concentrations
in moss and atmospheric deposition	78
3.2.2	Comparison of lead concentrations in Sphagnum
fuscum and measured atmospheric deposition . .	79
3.3 Use of enrichment factors in assessing metal
enrichment			82
4.0 Sources of variability in the data	107
4.1 Analytical variability 		107

-------
4.2 Within-site variability 		107
4.2.1	Between-sample variabilty 		107
4.2.2	Seasonal variability 		109
5.0 Recommendations	127
5.1	Site selection	127
5.2	Sampling methods 		130
6.0 Summary	136
6.1	Recommendations for sample collection, handling and
analysis	136
6.2	Summary of data presented	137

-------
List of Figures
Figure 1. Location of sampling sites.
Figure 2a. Aluminum concentrations (ug/g) in moss and lichen
samples compared with those in S_s_ fuscum collected from the same
sites.
Figure 2b. Aluminum concentrations (ug/g) in spruce samples
compared with those in S_s_ fuscum collected from the same sites.
Figure 3. Arsenic concentrations (ug/g) in moss, lichen and spruce
samples compared with those in Sj_ fuscum collected from the same
sites.
Figure 4a. Cadmium concentrations (ug/g) in moss and lichen
samples compared with those in Sj_ fuscum collected from the same
sites.
Figure 4b. Cadmium concentrations (ug/g) in spruce samples
compared with those in §jl. fuscum collected from the same sites.
Figure 5a. Chromium concentrations (ug/g) in moss and lichen
samples compared with those in £L_ fuscum collected from the same
sites.
Figure 5b. Chromium concentrations (ug/g) in spruce samples
compared with those in fuscum collected from the same sites.
Figure 6a. Copper concentrations (ug/g) in moss and lichen samples
compared with those in S. fuscum collected from the same sites.
Figure 6b. Copper concentrations (ug/g) in spruce samples compared
with those in S_s_ fuscum collected from the same sites.
Figure 7a. Manganese concentrations (ug/g) in moss and lichen
samples compared with those in Sj_ fuscum collected from the same
i

-------
sites.
Figure 7b. Manganese concentrations (mg/g) in spruce samples
compared with those in S_;_ fuscum collected from the same sites.
Figure 7c. Manganese concentrations (mg/g) in moss and lichen
samples compared with those in S^_ fuscum collected from the same
sites, using the same scale as for spruce samples.
Figure 8a. Nickel concentrations (ug/g) in moss and lichen samples
compared with those in fuscum collected from the same sites.
Figure 8b. Nickel concentrations (ug/g) in spruce samples compared
with those in S_j_ fuscum collected from the same sites.
Figure 9a. Lead concentrations (ug/g) in moss and lichen samples
compared with those in fuscum collected from the same sites.
Figure 9b. Lead concentrations (ug/g) in spruce samples compared
with those in S_;_ fuscum collected from the same sites.
Figure 10. Antimony concentrations (ug/g) in moss, lichen and
spruce samples compared with concentrations in S. fuscum collected
from the same sites.
Figure 11. Vanadium concentrations (ug/g) in moss, lichen, and
spruce samples compared with those in S. fuscum collected from the
same sites.
Figure 12a. Zinc concentrations (ug/g) in moss and lichen samples
compared with those in fuscum collected from the same sites.
Figure 12b. Zinc concentrations (ug/g) in spruce samples compared
with those in S_;_ fuscum collected from the same sites.
Figure 13. Plot of enrichment factor for As vs. Al concentration
per unit dry mass (logarithmic scale on axes) in Sphagnum fuscum
ii

-------
samples. Solid line has a slope of -1.0 through the centroid of
the data.
Figure 14. Plot of enrichment factor for Cd vs. Al concentration
per unit dry mass (logarithmic scale on axes) in Sphagnum fuscum
samples. Solid line has a slope of -1.0 through the centroid of
the data.'
Figure 15. Plot of enrichment factor for Cr vs. Al concentration
per unit- dry mass (logarithmic scale on axes) in Sphagnum fuscum
samples. Solid line has a slope of -1.0 through the centroid of
the data.
Figure 16. Plot of enrichment factor for Cu vs. Al concentration
per unit dry mass (logarithmic scale on axes) in Sphagnum fuscum
samples. Solid line has a slope of -1.0 through the centroid of
the data.
Figure 17. Plot of enrichment factor for Mn vs. Al concentration
per unit dry mass (logarithmic scale on axes) in Sphagnum fuscum
samples. Solid line has a slope of -1.0 through the centroid of
the data.
Figure 18. Plot of enrichment factor for Ni vs. Al concentration
per unit dry mass (logarithmic scale on axes) in Sphagnum fuscum
samples. Solid line has a slope of -1.0 through the centroid of
the data.
Figure 19. Plot of enrichment factor for Pb vs. Al concentration
per unit dry mass (logarithmic scale on axes) in Sphagnum fuscum
samples. Solid line has a slope of -1.0 through the centroid of
the data.
iii

-------
Figure 20. Plot of enrichment factor for Sb vs. Al concentration
per unit dry mass (logarithmic scale on axes) in Sphagnum fuscum
samples. Solid line has a slope of -1.0 through centroid of data.
Figure 21. Plot of enrichment factor for V vs. Al concentration
per unit dry mass (logarithmic scale on axes) in Sphagnum fuscum
samples. Solid line has a slope of -1.0 through centroid of data.
Figure 22. Plot of enrichment factor for Zn vs. Al concentration
per unit dry mass (logarithmic scale on axes) in Sphagnum fuscum
samples. Solid line has a slope of -1.0 through centroid of data.
Figure 23. Seasonal changes in aluminum concentrations in S.
fuscum collected from Toivola Bog, MN. Day 10 is June 16, 1983.
Figure 24. Seasonal changes in cadmium concentrations in S. fuscum
collected from Toivola Bog, MN. Day 10 is June 16, 1983.
Figure 25. Seasonal changes in chromium concentrations in S.
fuscum collected from Toivola Bog, MN. Day 10 is June 16, 1983
Figure 26. Seasonal changes in copper concentrations in S. fuscum
collected from Toivola Bog, MN. Day 10 is June 16, 1983.
Figure 27. Seasonal changes in manganese concentrations in S.
fuscum collected from Toivola Bog, MN. Day 10 is June 16, 1983
Figure 28. Seasonal changes in nickel concentrations in S. fuscum
collected from Toivola Bog, MN. Day 10 is June 16, 1983.
Figure 29. Seasonal changes in lead concentrations in S^_ fuscum
collected from Toivola Bog, MN. Day 10 is June 16, 1983.
Figure 30. Seasonal changes in zinc concentrations in S_;_ fuscum
collected from Toivola Bog, MN. Day 10 is June 16, 1983.

-------
List of Tables
Table 1. Locations and site numbers for bogs from which samples
were collected in this study.
Table 2. List of samples collected at each site and years in which
samples were collected.
Table 3. Aluminum concentrations in moss and lichen samples.
Table 4. Arsenic concentrations in moss and lichen samples.
Table 5. Cadmium concentrations in moss and lichen samples.
Table 6. Chromium concentrations in moss and lichen samples.
Table 7. Copper concentrations in moss and lichen samples.
Table 8. Mercury concentrations in moss and lichen samples.
Table 9. Manganese concentrations in moss and lichen samples.
Table 10. Nickel concentrations in moss and lichen samples.
Table 11. Lead concentrations in moss and lichen samples.
Table 12. Antimony concentrations in moss and lichen samples.
Table 13. Thorium concentrations in moss and lichen samples.
Table 14. Vanadium concentrations in moss and lichen samples.
Table 15. Zinc concentrations in moss and lichen samples.
Table 16. Coefficients of correlation between concentrations of
elements in Sphagnum fuscum (Sf) and other species (Sr = Sphagnum
rubellum. Cs = Cladina stellaris. and Cr = Cladina ranaiferina).
Table 17.	Coefficients of correlation between element
concentrations in Sphagnum rubellum (Sr) and other species (Cs =
Cladina stellaris. and Cr = Cladina rangiferina).
Table 18. Coefficients of correlation between concentrations of
ellements in Picea twigs and other species (Sf = Sphagnum fuscum.

-------
Sr = Sphagnum rubel lurn, Cs = Cl adina stel 1 aris, and Cr = Cl adina
ranqj ferina).
Table 19. Coefficients of correlation between concentrations of
elements in Picea needles and other species and sample types (Sf
= Sphagnum fuscum, Sr = Sphagnum rubel1um, Cs = Cladina stellaris,
Cr = Cladina rangiferina. and Pt = Picea twigs).
Table 20. Comparison of Pb concentrations and calculated flux of
Pb in Sphagnum fuscum to measured deposition values from literature
Table 21. List of average enrichment factors for each element in
Sphagnum fuscum samples from the study sites.
Table. 22. Coefficients of variation (%) for element concentrations
in moss and lichen samples collected from the same site.
vi

-------
1.0. Introduction
Accumulation of toxic, airborne pollutants in the arctic and
sub-arctic is of growing concern to scientists (Barrie 1986, Heidam
1986). Levels of atmospheric deposition of these elements in the
arctic prior to anthropogenic augmentation of their cycling are
unknown, and in many cases, current concentrations of these
elements in surface vegetation and their rates of deposition in the
arctic are also unknown. In remote regions, where it is difficult
and extremely expensive to monitor atmospheric deposition by
collection of precipitation, samples of natural vegetation have
been used as a proxy. Sphagnum moss and lichens of the genus
Cladina have been useful in such studies in the sub-arctic
(Glooschenko 1986; Nieboer and Richardson 1981, Pakarinen
1981a,b). Studies in higher latitudes have used species such as
Pleurozium schreberi and Hvlocomium splendens (Ross 1990, Ruhling
et al.. 1987 J1.
Element concentration data from samples of natural vegetation
can be used to estimate the deposition of certain elements to a
site, especially when they can be calibrated by measured values of
atmospheric deposition for the same study region (Ross 1990,
Ruhling et al. 1987). In addition, such data give baseline
information for estimating potential bioaccumulation of elements
along the food chain.
* Nomenclature follows Isoviita (1966) for mosses, Hale (1979)
for lichens and Fernald (1970) for vascular plants.
1

-------
The purpose of this document is to provide species-specific
information on the use of natural vegetation to monitor trace-
metal deposition and accumulation in high-latitude regions of North
America. Data are presented on. element concentrations in samples
of Sphagnum f us cum and St. rubel lum moss , Cladina stel laris and
C. ranoiferina lichens, and Picea mariana (black spruce) twigs and
needles collected from nineteen ombrotrophic bogs in northeastern
North America.
These data will help in research design for arctic
contamination studies, because they aid in estimating expected
concentration ranges and between and within-site variability of
element concentrations in vegetation samples of this type.
Knowledge of expected concentration ranges is important for
designing analytical procedures and in determining the number and
i .
mass of samples needed to obtain accurate analyses. Between-site
and within-site variability estimates aid in determining the number
of replicate samples and sampling sites needed.
In this document, the following questions will be addressed:
1)	What are concentrations of the trace elements As, Cd, Cr, Cu,
Hg, Mn, Ni, Pb, Sb, Ti, Th, V, and Zn in Sphagnum. Cladina. and
Picea samples collected during 1981.and 1982 in northeastern North
America?
2)	How similar are element concentrations in the different species?
2

-------
3)	Are trace element concentrations in the different species
correlated? Do these correlations reflect expected patterns of
deposition? i.e.. do all species show similar patterns of
enrichment in sites near urban/industrial areas where atmospheric
deposition is probably high, and lower or no enrichment in rural
and remote regions where atmospheric deposition is probably lower?
4)	Do Pb concentrations in Sphagnum fuscum samples accurately
estimate Pb deposition, according to published data on Pb
deposition from precipitation sampling stations near moss sampling
sites?
5)	Do enrichment factors (Zoller et al . 1974) indicate enrichment
of trace metals in these plant samples above what would be expected
if most of the element were brought in on particles of unpolluted
mineral soil? If so, which elements appear to be enriched?
It should be noted that these samples were collected as part
of a large project studying the ecology and biogeochemistry of
Sphagnum bogs in northeastern North America. This project had
several research goals, among them calculation of peat accumulation
rates, study of bog processes such as decomposition and
productivity, study of bog development and geographic patterns of
landforms and vegetation in bogs, investigation of the historical
record of atmospheric deposition of pollutants through short cores
3

-------
as well as studies of present-day atmospheric deposition as shown
by element concentrations in surface vegetation.
Because sampling of surface vegetation was not the only goal
of the bog project, the sampling was sometimes constrained by other
facets of the project. For example, ideally one would hope to have
an initial season for reconnaissance to identify all bogs suitable
for sampling within the desired geographic regions. Selection of
paired or triplicate bogs to be sampled across the desired study
region could then be done randomly. During reconnaissance, the
investigators could identify species found throughout the desired
sampling regions and identify standard habitats within the bogs
from which samples would be collected. During subsequent field
seasons each bog would be visited in each season and the same
number of replicate samples of each species would be collected from
each bog.
Budget and time constraints on this project limited us to two
field seasons, and sample collection took place during both. Bogs
in Manitoba, Ontario and northwestern Quebec were visited only
during the second field season, thus confounding year of sampling
with geographic location for some sites. In addition, over the
duration of the project our sampling procedures improved. During
the first field season, replicate samples of all species were not
always obtained from each bog site, owing to their absence from a
site, lack of time or lack of communication among individuals doing
the sampling. The research group was fully occupied with
collection of short and long cores, water samples, set-up of moss
4

-------
growth and decomposition studies and the need to cover a large
number of sites in a broad geographic region in a limited time.
During the second field season more attention was paid to obtaining
replicates of each species at each site.
2.0 Methods used in the present study
2.1 Site selection
In sections 2 through 4 of this document, the word site refers
to a particular raised Sphagnum bog. In section 5, the word site
is used similarly to refer to landscape units, defined by their
vegetation and landforms, which are present in the arctic. The
locations within each site from which samples are collected will
be referred to as microsites or habitats.
Sampling microsites within each bog were selected to be the
same habitat type all across the region sampled. Thus, Sphagnum
fuscum was always collected from hummock tops, Sphagnum rubellum
was collected from the margins of wet hollows (or from Sphagnum
lawns if no hollows were present). Cladina lichens were collected
from hummocks or in slightly lower areas between coalesced
hummocks, and Picea twigs and needles from trees on hummocks.
Table 1 and Figure 1 show locations of sampling sites. Table
2a shows which species were collected and analyzed by plasma
emission spectroscopy (ICPAES) from each site, and in which years
those samples were collected. Table 2b shows at which sites
samples of each species were collected and analyzed by neutron
activation analysis (NAA).
5

-------
Table 1. Locations of bogs sampled in North America
N. Lat. V. Long.
Minnesota
1.	Arlberg
Ontario
2.	Diamond Lake
Quebec
3.	Lac Parent
4.	Lac St. Jean 1
5.	Lac St., Jean 2
6.	Sept lies
Maine
7.	Great Sidney Heath
8.	Bar Harbor
New Brunswick
9.	Bull Pasture Plain
10.	Point Sapin
11.	Point Escuminac
12.	Miscou Island
Nova Scotia
13.	Cape Sable Island
14.	Fourchu
Newfoundland-Labrador
15.	Conne River Pond
16.	Gander Bay West
17.	Eagle River 2
18.	Gilbert
19.	Ranger
46°55'
48°52'
48°47'
48°54'
48°55'
50°18'
44°23'
44°15'
46°03'
46°59*
47°04'
47°56'
43°28'
45°42'
48°10'
49021»
53°27'
52°44'
53°55'
92°47'
80°38'
77°10'
71°54'
71°47'
66°00'
69°48'
68°15'
64°20*
64°51'
64°49'
64°30'
65°36'
60°15'
55°30'
54022•
57°27'
56°52'
59°50'

-------
Figure 1. Location of vegetation sampling sites in the present
study. Site numbers are the same as those given in Table 1.
7

-------
60
50
100.
90
80
70
.18
16
13
N.
500
40
km

70
90

-------
Table 2a. List of samples (analyzed by ICPES) collected at each
site and year of collection. Species codes: Sphagnum fuscum = Sf,
Sphagnum rubel1 urn = Sr, Cladina stellaris = Cs , Cladina rangiferina
= Cr, Picea mariana needles = Pn and Picea mariana twigs = Pt.
Site numbers are the same as those listed in Table 1, a
three-letter code is also provided.


Sf
Sr
Cs
Cr
Pn
Pt
1
ARL
81
ns
81
81
81
81
2
DIA
82
82
ns
82
82
82
3
PAR
82
82
82
82
82
82
4
LSJ1
82
82
ns
82
82
82
5
LSJ2
82
ns
82
82
82
82
6
SEP
82
82
82
82
82
82
7
GSH
82
82
ns
ns
82
82
8
BAR
816.82
82
815.82
82
816.82
816.82
9
BUL
815.82
82
81&82
82
81
81
10
SAP
81&82
82
81&82
82
ns
ns
11
ESC
81S82
82
816.82
82
81
81
12
MIS
816.82
82
815.82
82
81
81
13
SAB
815.82
82
816.82
ns
816.82
816.82
14
FOU1
815.82
82
815.82
ns
816.82
816.82
15
CON
815.82
82
815.82
ns
816.82
816.82
16
CMV
82
82
82
82
82
82
17
EAG2
81
ns
81
ns
81
81
18
GIL1
81
ns
81
ns
81
81
19
RAN
82
ns
82
ns
ns
ns
ns
= no
sample colllected
from
this site
for this
species


-------
Table 2b. List of samples (analyzed by NAA) collected at each site
and year of collection. Species codes: Sphagnum fuscum = Sf,
Sphagnum rubellum = Sr, Cladina stellaris = Cs, Cladina rangiferina
= Cr. Picea mariana. needles = Pn and Picea mariana twigs = Pt.
Site numbers are the same as those listed in Table 1, a
three-letter code is also provided.


Sf
Sr
Cs
Cr
Pn
Pt
1
ARL
na
ns
na
81
na
na
2
DIA
82
na
ns
82
82
82
3
PAR
82
82
82
na
na
na
4
LSJ1
82
82
ns
na
ha
na
5
LSJ2
82
ns
82
na
82
82
6
SEP
82
82
82
na
82
82
7
GSH
82
82
ns
ns
na
na
8
BAR
81
82
na
na
na
na
9
BUL
81
82
na
na
81
81
10
SAP
81
82
81
na
ns
ns
11
ESC
81
82
na
na
na
na
12
MIS
81
na
81
na
na
na
13
SAB
81
82
na
ns
81
81
14
F0U1
81
na
na
ns
82
82
15
CON
81
82
na
ns
82
82
16
CMV
82
na
82
na
na
na
17
EAG2
na
ns
na
ns
na
na
18
GIL1
81
ns
81
ns
na
na
19
RAN
82
ns
82
ns
ns
ns
ns
= no
sample colllectecl
from
this site
for this
species

na
= no
sample analyzed by NAA
from this
site for
this speciei
10

-------
Sampling sites selected were all raised Sphagnum bogs (i.e.,
ombrotrophic bogs, which receive their hydrologic and elemental
inputs wholly from atmospheric deposition (Glaser and Janssens
1986)). Use of these site types (rather than fens, wetlands that
are also influenced by inputs from ground and surface waters that
have been in contact with mineral soil) maximized the influence of
regional atmospheric deposition on the chemistry of plant samples
and minimized effects of local hydrology/geology. In addition,
because these sampling sites have a similar vegetation cover and
underlying substrate (peat), comparisons among sites were not
complicated by variations in hydrology or the influences of mineral
soil in different parts of the study region. Most of the sites
were unforested, open bogs (Glaser and Janssens 1986) with the
exception of Arlberg Bog (1), Diamond Bog (2), Lac Parent (3) and
Lac St. Jean 1 and 2 (4 and 5) (See Table 1 and Figure 1 for
locations). Moss and lichen samples from these sites were
collected from open areas away from the trees. Picea samples from
sites 6-19 were all collected from the small, shrubby spruce
typical of those sites. Spruce samples from sites 1-5 were
collected from the larger trees typical of those sites.
2.2 Sample collection and handling
Species were selected for collection based on four criteria:
1) present over a broad geographic range (distributional range
encompassing the region to be sampled)
11

-------
2)	occurring commonly and abundantly on the site types sampled,
and thus forming a significant proportion, of the plant cover
3)	relatively easy to identify in the field (use of microscopic
characters or chemical tests not critical)
4)	comparative data available on elemental chemistry of these
species from studies in other regions in North America and Eurasia
Several species were chosen. Two types of Sphagnum moss, one
a hummock-forming moss fS. fuscum). the other found primarily along
margins of wet hollows (S. rubellum) in order to compare element
deposition and retention in hummock and hollow environments. The
two Cladina lichens tended to grow in similar microsite types,
often together. Budget constraints prevented sampling more species
from each type of microsite.
Samples were collected from all sites in mid-July to mid-
September in both 1981 and 1982. All sampling was done at least
200 m from the bog margin, to prevent contamination from road dust
or automobile exhaust. Sphagnum fuscum was collected from hummock
tops where it made up at least 95% of the moss cover. Sphagum
rubellum was collected from the margins of pools or wet hollows,
again, where it comprised at least 95% of the moss cover, except
at Diamond Bog, where no pools or even true hollows were present.
There, S^. rubel lum was collected from a lawn area between
12

-------
hummocks of S_^ fuscum.
The Cladina species were collected from hummock tops and broad
lawn areas. Cladina stel1aris was commonly collected from nearly
pure stands, occasionally with some C^_ rangiferina or C_;_ mitis
mixed in (usually less than 10%) that was cleaned from the sample
in the field. Cladina rangiferina was more often mixed with other
lichen species, but efforts were made to collect from stands in
which it was the dominant lichen, and the other species were
removed in the field.
For Sphagnum fuscum. the uppermost 3 cm of living moss was
taken. This represented 4 to 15 years growth at most coastal
sites, and about 1 1/2 years growth at mid-continental sites such
as Arlberg or Diamond Bog (Santelmann unpublished data, Pakarinen
and Gorham 1983). Samples of S_;_ rubel lum were collected to a
length of 5 cm, because this moss tends to grow more rapidly in
length than S_;_ fuscum (Clymo 1973, Tolonen et al . 1988) and a 5 cm
sample was considered approximately comparable to a 3 cm growth
increment of S_^ fuscum.
Lichen samples varied in length, but were trimmed to include
only the live portion of the lichen (live top plus live base), and
not the dead base (distinguished by its darkened color). The
length of live portion ranged from about 1.5 to 2.0 cm,
representing 3 to 4 year's growth (Nieboer and Richardson 1981).
Samples were collected in plastic bags (CMS sample bags),
using disposable PVC (powderless) gloves obtained from Scientific
Products Co. The PVC gloves not only prevented contamination of
13

-------
samples by hands of collectors, they protected them from biting
insects such as black flies and mosquitoes. Because using insect
repellents increases the risk of sample contamination, we preferred
to use mechanical protection against insects.
Samples were collected in duplicate or triplicate each year,
but not all replicate samples were analyzed. Voucher specimens of
each species were collected from each site, placed in paper bags
and dried in the field.
Samples were kept in a cooler until shipped back to the
laboratory (usually less than one week). At the lab they were
frozen until they could be cleaned of twigs, leaves, and all parts
of other plants. Cleaning was done by hand using PVC gloves.
Samples were not rinsed or moistened, since doing so removes
trapped particles which may account for a significant portion of
the trace elements present. Moss and spruce samples were dried 24-
48 hrs at 65 0 C, then ground in a Wiley mill with blades of grade
440C stainless steel. Lichen samples were crushed to a fine powder
in their plastic bags after drying, and did not require grinding.
Ground or crushed samples for analysis by ICPAES were redried
for a minimum of 4 hours at 55-65 0 C before weighing, and
transferred quickly to a vacuum desiccator. Samples of 1.000 ±
0.002 g were weighed into 20 ml high-form crucibles of fused quartz
or Vycor. Crucibles were covered and ashed at 485 to 500 0 C for
ten to twelve hours plus the time required for the furnace to reach
maximum temperature (about 2 hours). Ashed samples were allowed
to cool, then 5 ml of 2N HCl were added to the ash. Crucibles were
14

-------
placed on a hot plate and boiled to near dryness, then elevated off
the surface as the last traces of acid were slowly removed.
Crucibles were removed from heat immediately and cooled. To the
evaporated residues in the crucible, 10 ml of 2N HCl were added,
and crucibles were swirled intermittently over a 30 minute period,
then left for at least 4 hours or overnight after covering with
plastic wrap. The supernatant was then decanted into 7 ml
disposable polypropylene tubes for direct analysis by ICPAES.
For a subset of samples, a portion of the ground sample was
sent to be analyzed for additonal elements by neutron activation
analysis (NAA); either at the University of Wisconsin, Madison
(mosses) or at the University of Toronto (lichens).
For NAA, approximately 1.8 ml of dried sample was sealed in
polyvials. A batch of 36 standards and samples was irradiated at
100 kV in the vials for 30 minutes, and after a 12 minute delay,
counted for 10 minutes on a GeLi detector coupled to a Tracer
Northern computer-based Multi-Channel analyzer. A week later, the
batch was packed in a container and irradiated for 2 hr in "whale
tubes" designed so that the sample container rotates during
irradiation, thus giving the same neutron exposure to each sample.
After a decay time of 7-10 days, samples are counted again for 1
hour, analyzing for the longer-lived activation products.
2.3 Standards
The NAA analyses were calibrated with National Bureau of
Standards (NBS) orchard leaves and NBS pine needles. In addition,
a sample of an internal standard consisting of wel1-homogenized
15

-------
bulk sample of Sphagnum (hereafter referred to as SMS) prepared by
our research group, was run with each set of samples. This
provided an estimate of the precision one could expect from
multiple analyses of a homogenized sample collected from one site,
including variation owing to the nature of the matrix, procedures
of collection, drying, and grinding.
The ICPAES analyses were calibrated with spectroscopic grade
chemicals of ultra-high quality; our own internal Sphagnum
standard (SMS), and NBS pine needle and orchard leaf standards.
Where data were available from replicate analyses, average
element concientrations for a species at a particular site were
calculated by first averaging element concentrations in 1981 and
1982 separately, then combining those two averages. No replicate
analyses were performed using NAA owing to the high cost of such
analyses.
2.4 Detection limits
For the elements analyzed by ICPAES, concentrations in most
samples were above detection limits except for Ni, and for Cd, Cr,
Ni, and Pb in Picea needles. Detection limits in ICPAES are
determined by the solution standards run with the sample and the
sample dilution factor. For elements analyzed by ICPAES,
therefore, the detection limit will usually not vary unless
different standard solutions are used or unless there was
insufficient sample to obtain the standard dilution factor of 1:10.
Elements close to the detection limit have a higher variability.

-------
Precision at detection limits is generally considered to be about
+. 50% (R. Munter, personal communication).
For elements analyzed by NAA, (As, Hg, Sb, Th, Ti , V)
detection limits were encountered more frequently. According to
R.J. Cashwell, University of Wisconsin Nuclear Reactor Laboratory,
the detection limit for elements analyzed by NAA will vary due to
the total activity in the sample (particularly activity that emits
gamma rays of a higher energy than the element in question) and
sample mass. A more radioactive sample will require more counts
in the net peak area to detect an element. Their program for
calculating element concentrations uses a "classical " peak area
determination method. It attempts to find a gamma-ray photopeak
at the appropriate energy for the element being determined. If the
centroid energy is within a pre-set tolerance level, the peak area
is computed. The statistical accuracy of the peak is calculated,
based on Poisson statistics and the observed net and gross peak
areas. If the peak is statistically significant (based on an
arbitrarily set maximum standard deviation in net peak counts) the
results are printed. The arbitrary level was set near 90% for our
samples. If a statistically significant peak was not found, or if
the energy of the peak does not match the target element photopeak,
a calculation is performed to determine how much of the element
must be present in order to be detected. This calculation assumes
that the peak area would have to be 6 times the standard deviation
of the background region count to be detectable.
17

-------
3.0 Discussion of data from the present study
3.1 Comparison of the different species
If element concentrations in these plant samples reflect
regional patterns of element deposition, then the concentrations
of those elements should be correlated in the samples, with all
species showing relatively high levels of these elements near urban
regions which are sources of heavy metal pollution (Lazrus et al.
1970, Pacyna 1986), lower levels in rural regions of moderate
contamination, and lowest levels in remote regions (sensu Galloway
et al. 1982).
Figures 2a-12b are plots of element concentrations in Sphagnum
rubellum. Cladina stellaris, C.ranaiferina. and Picea twigs and
needles vs. the concentrations of those same elements in JL. fuscum
collected at the same sites. The element concentration data
themselves are presented in Tables 3-15, except for Ti, which was
below detection limits in all but five samples of S_j_ f us cum
Titanium concentrations in those samples ranged from 0.38 to 0.63.
Detection limits for Ti in the other samples ranged from 0.17 to
0.93. Means for each species in Tables 3-15 were compared by
paired sample comparisons (Snedecor and Cochran 1980) for all
sample pairs above detection limit. Lower case letters above the
means are different if the means were significantly different (p
<0.05). Tables 16-19 give- correlation coefficients of element
concentrations for each species combination for which sufficient
data are available to calculate the coefficient.
18

-------
Figure 2a. Aluminum concentrations (ug/g) in moss and lichen
samples compared with those in S_;_ fuscum collected from the same
sites. The solid line is the 1:1 line of equal concentration.
19

-------
Comparison of Element Concentrations
in Moss and Lichen Samples
800
700
600
500
400
300
200
100
0
0	200	400	600	800
Al concentration (ug/g) in S. fuscum
~ S. rubellum	+ C. stellaris O C. rangiferina

-------
Figure 2b. Aluminum concentrations (ug/g) in spruce samples
compared with those in fuscum collected from the same sites.
The solid line is the 1:1 line of equal concentration.
21

-------
Comparison of Element Concentrations
in Moss and Spruce Samples
800
700
600
500
400
300
200
100
~~
0
600
800
0
200
400
Al concentration (ug/g) in S. fuscum
~ Picea needles + Picea twigs

-------
Figure 3. Arsenic concentrations (ug/g) in moss, lichen and spruce
samples compared with those in S_;_ fuscum collected from the same
sites. The solid line is the 1:1 line of equal concentration.
23

-------
Comparison of Element Concentrations
in Moss, Lichen, and Spruce Samples
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
1.2
1.4
0.4
0.6
0.8
0
0.2
As concentration (ug/g) in S. fuscum
~ S. rubellum	+ C. stellaris O C. rangiferina	A Picea twigs

-------
Figure 4a. Cadmium concentrations (ug/g) in moss and lichen
samples compared with those in S_;_ f us cum collected from the same
sites. The solid line is the 1:1 line of equal concentration.
25

-------
Comparison of Element Concentrations
in Moss and Lichen Samples
~
Cd concentration (ug/g) in S. fuscum
S. rubellum + C. stellaris o C. rangiferina

-------
Figure 4b. Cadmium concentrations (ug/g) in spruce samples
compared with those in S. fuscum collected from the same sites.
The solid line is the 1:1 line of equal concentration.
27

-------
Comparison of Element Concentrations
in Moss and Spruce Samples
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0.8
0.6
0.4
0.2
0
Cd concentration (ug/g) in S. fuscum
~ Picea needles + Picea twigs

-------
Figure 5a. Chromium concentrations (ug/g) in moss and lichen
samples compared with those in S_j_ f us cum collected from the same
sites. The solid line is the 1:1 line of equal concentration.
29

-------
Comparison of Element Concentrations
in Moss and Lichen Samples

0.2 0.4 0.6 0.8
1
1.2 1.4 1.6
Cr concentration (ug/g) in S. fuscum
~ S. rubeltum + C. steltaris O C. rangiferina
1.8

-------
Figure 5b. Chromium concentrations (ug/g) in spruce samples
compared with those in S. fuscum collected from the same sites.
The solid line is the 1:1 line of equal concentration.
31

-------
Comparison of Element Concentrations
in Moss and Spruce Samples
5
4
3
2
1
0
1.8
0
0.2
0.6
0.8
1,2
1.6
0.4
1
1.4
2
Cr concentration (ug/g) in S. fuscum
~ Picea needles + Picea twigs

-------
Figure 6a. Copper concentrations (ug/g) in moss and lichen samples
compared with those in fuscum collected from the same sites.
The solid line is the 1:1 line of equal concentration.
33

-------
Comparison of Element Concentrations
in Moss and Lichen Samples



~

+



~

~~
V
o
—
yU ~

/6 o ~

~ ° + o° ° °



+ ++ + +

// + +

+++
/ 1 1 1 1 1 1 1 1
0	2	4	6	8
Cu concentration (ug/g) in S. fuscum
~ S. rubellum + C. stellaris o C. rangiferina

-------
Figure 6b. Copper concentrations (ug/g) in spruce samples compared
with those in S_;_ fuscum collected from the same sites.
The solid line is the 1:1 line of equal concentration.
35

-------
Comparison of Element Concentrations
8
7
6
5
4
3
2
1
0
0	2	4	6	8
Cu concentration (ug/g) in S. fuscum
~ Picea needles + Picea twigs
in Moss and Spruce Samples

-------
Figure 7a. Manganese concentrations (ug/g) in moss and lichen
samples compared with those in S_^ fuscum collected from the same
sites. The solid line is the 1:1 line of equal concentration.
37

-------
260
240
220
200
180
160
140
120
100
80
60
40
20
0
Comparison of Element Concentrations
in Moss and Lichen Samples
~
~
0
~
&
~
$ +
CO
+
+
3
%
+
200
15
o
+
400
600
800
~
Mn concentration (ug/g) in S. fuscum
S. rubellum + C. stellaris O C. rangiferina

-------
Figure 7b. Manganese concentrations (mg/g) in spruce samples
compared with those in S. fuscum collected from the same sites.
The solid line is the 1:1 line of equal concentration.
39

-------
Comparison of Element Concentrations
in Moss and Spruce Samples
Mn concentration (mg/g) in S. fuscum
~ Picea needles + Picea twigs

-------
Figure 7c. Manganese concentrations (mg/g) in moss and lichen
samples compared with those in S. fuscum collected from the same
sites, using the same scale as for spruce samples.
The solid line is the 1:1 line of equal concentration.
41

-------
Comparison of Element Concentrations
in Moss and Lichen Samples
2.8
2.6
2.4
2.2 -
0.8
0.6
0.4
0.2
1.4
1.2
0.6
0.8
1
0.4
0
0.2
Mn concentration (mg/g) in S. fuscum
~ S. rubellum + C. stellaris o C. rangiferina

-------
Figure 8a. Nickel concentrations (ug/g) in moss and lichen samples
compared with those in S. fuscum collected from the same sites.
The solid line is the 1:1 line of equal concentration.
43

-------
Comparison of Element Concentrations
in Moss and Lichen Samples
2.8
2.6
2.4
2.2 -
0.8
+ +
0.6
0.4
0.2
2.4
2.8
1.2
1.6
2
0.8
0
0.4
Ni concentration (ug/g) in S. fuscum
~ S. rubellum + C. stellaris o C. rangiferina

-------
Figure 8b. Nickel concentrations (ug/g) in spruce samples compared
with those in £L_ fuscum collected from the same sites.
The solid line is the 1:1 line of equal concentration.
45

-------
Comparison of Element Concentrations
in Moss and Spruce Samples
2.8







2.6
-





/'
2.4
-
++




/
2.2
-

+


/
/

2
-




/
+
1.8
-






1.6
-






1.4
-
+





1.2
-
~
+ AS
+
~




1
—

~




0.8
-






0.6
-
yS + D

+



0.4
-
~





0.2
-






n

/ill 1 I I
1
'
1
1
1 1 1
0	0.4	0.8	1.2	1.6	2	2.4	2.8
Ni concentration (ug/g) in S. fuscum
~ Picea needles + Picea twigs

-------
Figure 9a. Lead concentrations (ug/g) in moss and lichen samples
compared with those in Sj_ fuscum collected from the same sites.
The solid line is the 1:1 line of equal concentration.
47

-------
45
40
35
30
25
20
15
10
5
0
Comparison of Element Concentrations
in Moss and Lichen Samples


X °
~
+


~ ffl
+
~
o


~
A
+
A

~ /

~
~
%

n
++ ~

o+
+
LJ
+0
o
O
T
o
tf-
o



+




o
+


0	4	8	12	16	20
Pb concentrations (ug/g) in S. fuscum
~ S. rubellum + C. stellaris o C. rangiferina
24

-------
Figure 9b. Lead concentrations (ug/g) in spruce samples compared
with those in S^_ fuscum collected from the same sites.
The solid line is the 1:1 line of equal concentration.
49

-------
Comparison of Element Concentrations
in Moss and Spruce Samples
45




/
/
40

/
+




+
35
—



+ // +
30
*



+
25

+ + +
20




+
15
-
+
10

+++ +


yf +
5


n

r0L ^ p ~ E [f
/ i i i i"-Huiui r i i1-1! i i
0	4	8	12	16	20	24
Pb concentration (ug/g) in S. fuscum
~ Picea needles + Picea twigs

-------
Figure 10. Antimony concentrations (ug/g) in moss, lichen and
spruce samples compared with concentrations in S. fuscum collected
from the same sites. The solid line is the 1:1 line of equal
concentration.
51

-------
Cl
q.
w
L.
o
¦C
o>
\
o»
3
U
c
o
V
JO
U)
0.6
Comparison of Element Concentrations
in Moss, Lichen and Spruce Samples
0.5 -
0.4 -
0.3 -
0.2 -
0.1 -
0.2
0.4
~ S. rubellum
Sb concentration (ug/g) in S. fuscum
+ C. stellaris O C. rangiferina
0.6
A Picea twigs

-------
Figure 11. Vanadium concentrations (ug/g) in moss, lichen, and
spruce samples compared with those in S. fuscum collected from the
same sites. The solid line is the 1:1 line of equal concentration.
53

-------
Comparison of Element Concentrations
in Moss, Lichen and Spruce Samples
8
7
6
5
4
3
2
Cfr
1
0
8
6
0
2
4
V concentration (ug/g) in S. fuscum
~ S. rubellum + C. stellaris O C. rangiferina	A Picea twigs

-------
Figure 12a. Zinc concentrations (ug/g) in moss and lichen samples
compared with those in S_;_ fuscum collected from the same sites.
The solid line is the 1:1 line of equal concentration.
55

-------
150
140
130
120
110
100
90
80
70
60
50
40
30
20
10
0
Comparison of Element Concentrations
in Moss and Lichen Samples
0
20
40
Zn concentration (ug/g) in S. fuscum
S. rubellum + C. stellaris O C. rangiferina

-------
Figure 12b. Zinc concentrations (ug/g) in spruce samples compared
with those in S. fuscum collected from the same sites. The solid
line is the 1:1 line of equal concentration.
57

-------
150
140
130
120
110
100
90
80
70
60
50
40
30
20
10
0
Comparison of Zn Concentrations
in Moss and Spruce Samples
~
~
+
+
¦+
~
¦++Q
~	b
fijp
~	p
+ n
20
40
Zn concentrations (ug/g) in S. fuscum
~ Picea needles + Picea twigs

-------
Table 3. Concentrations (ug/g) of aluminum in moss, lichen and
spruce samples, determined by ICP-AES. Species codes: Sphagnum
fuscum = Sf, Sphagnum rubellum = Sr, Cladina stellaris = Cs,
Cladina rangiferina = Cr, Picea mariana needles = Pn and Picea
mariana twigs = Pt. Site numbers are the same as those listed in
Table 1, a three-letter code is also provided. The coefficient of
variation for Al in our bulk Sphagnum internal standard (SMS) was
2.9. Lower case letters above the means are different if the means
were significantly different (at 5% level) in paired sample
comparisons.
Al concentrations (ug/g)

Sf
Sr
Cs
Cr
Pn
Pt
1 ARL
766
ns
500
275
69
448
2 DIA
290
363
ns
185
37
213
3 PAR
306
249
118
145
41
182
4 LSJ1
231
225
ns
185
34
189
5 LSJ2
372
ns
270
284
50
208
6 SEP
301
163
148
144
29
82
7 GSH
364
397
ns
ns
34
145
8 BAR
227
228
193
160
32
210
9 BUL
264
251
138
167
31
157
10 SAP
151
158
131
131
ns
ns
11 ESC
265
154
172
136
26
101
12 MIS
349
253
197
177
51
120
13 SAB
204
318
127
ns
46
196
14 FOU1
179
223
102
ns
24
89
15 CON
164
131
82
ns
20
69
16 CMV
208
124
99
80
28
89
17 EAG2
72
ns
51
ns
14
44
18 GIL1
60
ns
37
ns
10
35
19 RAN
86
ns
90
ns
ns
ns

a
a
b
b
c
b
Mean
256
231
153
172
34
154
Std. deviation
155
84
109
58
15
97
Minimum
60
124
37
80
10
35
Maximum
766
397
500
284
69
448
ns = no sample of this species collected at this site
na = element not analyzed in this sample
59

-------
Table 4. Concentrations (ug/g) of arsenic in moss, lichen and
spruce samples, determined by NAA. Codes as in Table 3. The
coefficient of variation for As in our bulk Sphagnum internal
standard (SMS) was 19. None of the means were significantly
different according to paired sample comparisons.
As concentrations (ug/g)

Sf
Sr
Cs
Cr
Pn
Pt
1 ARL
na
ns
ha
0.36
na
na
2 DIA
0.43
na
ns
0.69
<0.16
0.28
3 PAR
1.20
1.32
0.72
na
na
na
4 LSJ1
0.27
0.29
ns
na
na
na
5 LSJ2
0.20
ns
0.36
na
<0.45
<0.16
6 SEP
0.59
0.32
0.38
na
<0.13
0.14
7 GSH
0.50
0.59
ns
ns
na
na
8 BAR
0.31
<1.00
na
na
na
na
9 BUL
1.06
0.80
na
na
<0.28
0.12
10 SAP
1.10
0.97
0.90
na
rls
ns
11 ESC
0.70
0.55
na
na
na
na
12 MIS
<0.44
na
0.44
na
na
na
13 SAB
0.28
<0.69
na
ns
<0.40
0.15
14 FOU1
0.13
na
na
ns
<0.23
<0.11
15 CON
0.15
<0.54
na
ns
<0.41
<0.10
16 CMV
0.18
na
0.17
na
na
na
17 EAG2
na
ns
na
ns
na
na
18 GIL1
0.13
ns
0.34
ns
na
na
19 RAN
<0.23
ns
0.13
ns
ns
ns
Mean
0.48
0.69
0.43
0.53
dl
0.17
Std'. deviation
0.37
0.37
0.26
-
-
0.07
Minimum
0.13
0.29
0.13
0.36
<0.13
<0.10
Maximum
1.20
1.32
0.90
0.69
<0.45
0.28
60

-------
Table 5. Concentrations (ug/g) of Cd in moss, lichen and spruce
samples, determined by ICP-AES. Codes as in Table 3. The
coefficient of variation for Cd in our bulk Sphagnum internal
standard was 18. Lower case letters above the means are different
if the means were significantly different (at 5% level) in paired
sample comparisons.
Cd concentrations (ug/g)


Sf
Sr
Cs
Cr
Pn
Pt
1
ARL
0 . 31
ns
0.13
0 .17
<0.10
0.12
2
DIA
0 . 52
0 . 23
ns
0 . 34
0 .07
0 .17
3
PAR
0.88
0.71
0.54
0.68
0.11
0.82
4
LSJ1
0 . 21
0 .15
ns
0.51
0.09
0 .13
5
LSJ2
0 . 24
ns
0.21
0.06
0.09
0 .15
6
SEP
0 . 34
0 . 24
0.12
0.19
0 .11
0 .04
7
GSH
0 . 21
0 .53
ns
ns
0 .13
0 .29
8
BAR
0 . 23
0 .50
0 .26
0.12
<0 .10
0 .16
9
BUL
0 . 22
0 . 24
0.17
0 .19
0.06
0.10
10
SAP
0 .17
0 .05
0.19
0 .18
ns
ns
11
ESC
0 . 20
0 .13
0 . 24
0 .08
<0 .10
0.09
12
MIS
0 . 23
0 . 32
0 . 27
0.16
0.05
0 .10
13
SAB
0 .17
0 . 39
0 . 35
ns
0 .10
0 .16
14
FOU1
0 .18
0 .25
0 . 25
ns
0.09
<0 .04
15
CON
0 .14
0 .15
0. 21
ns
<0 .10
0 .15
16
CMV
0.15
0.17
0.17
0.16
0.07
0 .13
17
EAG2
0 . 21
ns
0 .17
ns
<0 .10
0 .14
18
GIL1
0 .14
ns
<0 .10
ns
<0 . 10
0 . 21
19
RAN
0.20
ns
0. 20
ns
ns
ns
a	a	a,b	a,b	c	b,c
Mean 0.26	0.29	0.23	0.24	0.09 0.19
Std. deviation 0.17	0.18	0.10	0.18	0.02	0.18
Minimum 0.14	0.05	0.12	0.06	0.05 0.04
Maximum 0.88	0.71	0.54	0.68	0.13 0.82
61

-------
Table 6. Concentrations (ug/g) of chromium in moss/ lichen and
spruce samples, determined by ICP-AES. Codes as in Table 3. The
coefficient of variation for Cr in our bulk Sphagnum internal
standard was 7. Lower case letters above the means ares; different
if the means were significantly different (at 5% level) in paired
sample comparisons.
Cr concentrations (ug/g)


Sf
Sr
Cs
Cr
Pn
Pt
1
ARL
1.25
ns
0.49
0.70
1.08
2.67
2
DIA
0.90
1.41
ns
0.90
nd
nd
3
PAR
0.83
1.25
<0.17
0.65
nd
4.59
4
LSJ1
0.92
0.80
ns
0.59
nd
1.16
5
LSJ2
1.15
ns
0.38
1.30
nd
nd
6
SEP
1.08
0.73
0.54
1.11
nd
nd
7
GSH
1.40
1.03
ns
ns
nd
0.92
8
BAR
0.79
1.45
0.30
0.48
1.22
1.88
9
BUL
0.67
0.65
0.27
0.69
1.27
0.83
10
SAP
0.75
0.69
0.23
0.51
ns'
ns
11
ESC
0.62
0.59
0.27
0.60
0.33
0.42
12
MIS
0.70
1.21
0.30
0.53
<0.09
0.72
13
SAB
0.67
1.07
0.20
ns
1.83
0.81
14
F0U1
0.67
1.17
0.17
ns
nd
nd
15
CON
0.63
0.52
0.13
ns
0.74
0.68
16
CMV
0.66
1.00
0 . 25
0.56
<0.09
2.04
17
EAG2
<0.08
ns
0.13
ns
0.61
0.65
18
GIL1
0.20
ns
<0.08
ns
0.65
0.51
19
RAN
1.15
ns
0.17
ns
ns
ns


a
a'
c
b
a,b
a
Mean

0.83
0.97
0.27
0.72
0.97
1.38
Std. deviation
0.29
0.31
0.12
0.26
0.48
1.17
Minimum

<0.08
0.52
<0.08
0.48
<0.09
0.42
Maximum

1.40
1.45
0.54
1.30
1.83
4.59
N. B. Picea samples marked nd here were below the detection limit
(<0.09 ug/g) for Cr in an analytical run that was not sensitive for
Cr (All of the Picea samples in that run came up as below detection
limit for Cr). Analyses of replicate samples indicate that the Cr
data in that run are not comparable to those for the other samples
analyzed, therefore, they are not included here.
62

-------
Table 7. Concentrations (ug/g) of copper in moss, lichen, and
spruce samples, determined by ICP-AES. Codes as in Table 3. The
coefficient of variation for Cu in our bulk Sphagnum internal
standard was 14. Lower case letters above the means are different
if the means were significantly different (at 5% level) in paired
sample comparisons.
Cu concentrations (ug/g)


Sf
Sr
Cs
Cr
Pn
Pt
1
ARL
2.85
ns
1.51
1.78
1.38
4.24
2
DIA
5.75
6.48
ns
3.67
1.56
6.68
3
PAR
4.40
4. 61
1. 47
2.39
1. 44
5.72
4
LSJ1
3 .05
2.96
ns
1.79
1. 39
4.32
5
LSJ2
3.35
ns
1.81
1. 95
1. 44
4.47
6
SEP
3.15
4.45
5.31
2.72
1.57
5.08
7
GSH
5.05
2.33
ns
ns
2.52
7 . 20
8
BAR
3.25
3.60
1.78
1.83
1.58
4. 99
9
BUL
3 . 22
3.77
1.49
2.18
1. 32
4. 62
10
SAP
3.45
2.46
2 . 21
3. 64
ns
ns
11
ESC
3.70
3.00
2 .26
2.03
1. 34
5 .01
12
MIS
3.82
2.74
1.85
2.17
1. 38
3 .71
13
SAB
2 .80
2. 68
1. 66
ns
1. 27
4.25
14
FOU1
2 .20
2.07
1.55
ns
1. 54
3.69
15
CON
1.78
2.18
1.20
ns
1. 93
4.42
16
CMV
2 .35
2.12
1.17
2.17
1. 41
3 . 92
17
EAG2
1.80
ns
0.75
ns
0.80
2.84
18
GIL1
1.60
ns
0 . 66
ns
1.15
3.25
19
RAN
1.95
ns
0.77
ns
ns
ns
b	b	c, d c	d	a
Mean 3.13	3.24	1.71	2.36	1.47	4.61
Std. deviation 1.11	1.24	1.07	0.66	0.35	1.13
Minimum 1.60	2.07	0.66	1.78	0.80	2.84
Maximum 5.75	6.48	5.31	3.67	2.52	7.20
63

-------
Table 8. Concentrations (ug/g) of mercury in moss and lichen
samples, determined by NAA. (Lichen samples were not analyzed for
mercury.) Codes as in Table 3. The coefficient of variation for
Hg in our bulk Sphagnum internal standard was 67. None of the
means were significantly different in paired sample comparisons,
although Picea needles appear to have lower concentrations of Hg
than the moss samples, since nearly all of the values were below
detection limit.
Hg concentrations (ug/g)
Sf ,	Sr	Pn	Pt
1	ARL	na	ns	na	na
2	DIA	<0.03	na	<0.05	0.28
3	PAR	0.16	0.31	na	na
4	LSJ1	0.10	0.23	na	na
5	LSJ2	0.16	ns	<0.21	<0.10
6	SEP	0.12	0.26	<0.05	0.13
7	GSH	0.28	0.41	na	na
8	BAR	0.72	0.38	na	na
9	BUL	0.31	0.41	<0.06	0.08
10	SAP	0.15	0.34	ns	ns
11	ESC	0.10	0.41	na	na
12	HIS	0.17	na	na	na
13	SAB	0.20	0.32	<0.06	0.06
14	F0U1	0.15	na	<0.08	0.12
15	CON	0.19	0.33	<0.05	0.06
16	CMV	0.13	na	na	na
17	EAG2	nd	ns	na	na
18	GIL1	0.44	ns	na	na
19	RAN	0.18	ns	ns	ns
Mean	0.22	0.34	dl	0.12
Std. deviation	0.16	0.06	-	0.08
Minimum	<0.03	0.23	<0.05	0.06
Maximum	0.72	0.41	<0.21	0.28
64

-------
Table 9. Concentrations (ug/g) of manganese in moss, lichen, and
spruce samples, determined by ICP-AES. Codes as in Table 3. The
coefficient of variation for Mn in our bulk Sphagnum internal
standard was 2.7. Lower case letters above the means are different
if the means were significantly different (at 5% level) in paired
sample comparisons.
Mn concentration (ug/g)
Mean
Minimum
Maximum


Sf
Sr
Cs
Cr
Pn
Pt
1
ARL
216
ns
63
74
1509
689
2
DIA
136
112
ns
35
1106
559
3
PAR
714
150
65
83
1460
580
4
LSJ1
594
114
ns
71
2650
1258
5
LSJ2
468
ns
13
59
2688
997
6
SEP
204
68
40
63
2395
937
7
GSH
265
48
ns
ns
1261
649
8
BAR
213
77
18
58
1492
1021
9
BUL
338
80
31
51
2157
1211
10
SAP
394
65
26
62
ns
ns
11
ESC
75
36
11
38
610
229
12
MIS
71
24
12
8
818
181
13
SAB
149
48
19
ns
564
236
14
F0U1
96
52
14
ns
1127
562
15
CON
146
35
27
ns
1407
665
16
CMV
415
244
42
101
2576
1019
17
EAG2
31
ns
27
ns
1415
688
18
GIL1
26
ns
30
ns
1523
647
19
RAN
326
ns
36
ns
ns
ns


c
d
f
e
a
b


256
82
30
58
1574
713
ition
192
58
17
24
686
325


26
24
11
8
564
181


714
244
65
101
2688
1258
65

-------
Table 10. Concentrations (ug/g) of nickel in moss, lichen, and
spruce samples, determined by ICP-AES. Codes as in Table 3. The
coefficient of variation for Ni in our bulk Sphagnum internal
standard was 18. Lower case letters above the means are different
if the means were significantly different (at 5% level) in paired
sample comparisons. However, the large number of values below
detection limit decreased the power of the paired sample comparison
to detect a significant difference, while indicating that Ni
concentrations are probably lower in Picea needles than in the
other samples.


Ni concentration




Sf
Sr
Cs
Cr
Pn
Pt
1
ARL
1.25
ns
0.63
<0.40
0.60
2.42
2
DIA
1.00
1.55
ns
0.57
<0.40
1.41
3
PAR
1.20
1.96
<0.77
0.79
0.41
2.46
4
LSJ1
1.20
0.92
ns
<0.71
<0.40
1.17
5
LSJ2
1.40
ns
<0.40
0.62
<0.40
nd
6
SEP
1.70
0.78
0.93
0.98
<0.40
0.56
7
GSH
2.60
2.40
ns
ns
<0.40
2.05
8
BAR
1.40
2.44
0.71
0.78
0.96
2.22
9
BUL
1.43
1.52
0.64
0.84
1.10
1.24
10
SAP
1.18
0.45
0.61
0.49
ns
ns
11
ESC
0.94
0.73
0.49
0.62
<0.52
0.64
12
MIS
0.95
0.96
0.51
<0.40
<0.52
1.11
13
SAB
1.08
0.84
0.72
ns
1.28
1.10
14
F0U1
0.97
1.26
<0.61
ns
<0.40
<0.40
15
CON
0.80
0.92
<0.51
ns
0.75
0.75
16
CMV
0.70
0.93
<0.40
0.46
<0.40
<0.57
17
EAG2
<0.52
ns
<0.52
ns
<0.52
0.84
18
GIL1
<0.50
ns
<0.52
ns
<0.52
0.67
19
RAN
<0.40
ns
<0.40
ns
ns
ns


a
a
b
a,b
a,b
a
Mean

1.24
1.26
0. 65
0.68
0.85
1.33
Std. deviation
0.44
0.63
0.14
0.17
0.32
0.68
Minimum

<0.40
0.45
0.49
0.40
<0.40
<0.40
Maximum

2.60
2.44
0.93
0.98
1.28
2.46
66

-------
Table 11. Concentrations (ug/g) of lead in moss, lichen, and
spruce samples, determined by ICP-AES. Codes as in Table 3. The
coefficient of variation for Pb in our bulk Sphagnum internal
standard was 7. Lower case letters above the means are different
if the means were significantly different (at 5% level) in paired
sample comparisons.
Pb concentrations (ug/g)
Mean
Std. deviation
Minimum


Sf
Sr
Cs
Cr
Pn
Pt
1
ARL
9.8
ns
7.4
3.4
1.05
16.2
2
DIA
6.3
12.8
ns
7 . 7
<0 . 69
10.1
3
PAR
13.0
14. 9
3.8
8.5
1.10
31.3
4
LSJ1
12.4
11. 9
ns
13.8
<0 . 69
24. 6
5
LSJ2
11.0
ns
10.8
7 . 2
2 .18
15. 4
6
SEP
21.0
12.4
9.5
17 . 2
1.63
17 . 6
7
GSH
19.0
22.3
ns
ns
1.76
26.5
8
BAR
15.1
31.0
17.8
13.7
2.76
40.8
9
BUL
17 .7
19.1
16.7
16. 6
1.54
24.6
10
SAP
13.0
10.3
23 . 5
19.6
ns
ns
11
ESC
20.7
13.0
18.8
10.3
1.23
30. 9
12
MIS
16.2
11.8
15 .0
8.6
1.23
24. 9
13
SAB
13.8
16.7
16. 6
ns
1.89
36. 5
14
FOU1
11.5
17.1
10.5
ns
1.01
10 . 5
15
CON
9.3
9.6
8.6
ns
0 . 98
9.4
16
CMV
9.7
6.6
5.4
8.3
1.23
9.8
17
EAG2
10.0
ns
7 . 4
ns
<1.48
9.0
18
GIL1
4.4
ns
1. 9
ns
<1.48
5.9
19
RAN
6.4
ns
9.2
ns
ns
ns


b
b
b
b
c
a


12. 6
14.9
11.4
11.3
1.5
20. 2
4.8 6.1 6.0 4.9 0.5 10.7
4.4 6.6 1.9 3.4 <0.7 5.9
Maximum
21.0 31.0 23.5 19.6
2.8 40.8
67

-------
Table 12. Concentrations (ug/g) of antimony in moss ,lichen, and
spruce samples. Codes as in Table 3. The coefficient of variation
for Sb in our bulk Sphagnum internal standard was 79.5. Lower case
letters above the means are different if the means were
significantly different (at 5% level) in paired sample comparisons.
No letter indicates too few samples above detection limit for a
comparison of means.
Sb concentrations (ug/g)
Mean
Std. de\
Minimum
Maximum


Sf
Sr
Cs
Cr
Pn
Pt
1
ARL
na
ns
na
0.32
na
na
2
DIA
0.24
na
ns
0.37
0.026
0.147
3
PAR
0.14
0.28
0.41
na
na
na
4
LSJ1
0.13
0.17
ns
na
na
na
5
LSJ2
0.25
ns
0.61
na
<0.060
<0.064
6
SEP
0.14
0.25
0.41
na
<0.034
0.108
7
GSH
0.29
0.22
ns
ns
na
na
8
BAR
0.51
0.13
na
na
na
na
9
BUL
0.56
0.17
na
na
<0.057
0.203
10
SAP
0.33
<0.12
0.40
na
na
na
11
ESC
<0.20
0.11
na
na
na
na
12
MIS
0.47
na
0.43
na
na
na
13
SAB
0.16
0.14
na
na
0.056
0.255
14
FOU1
0.16
ns
na
na
<0.047
0.156
15
CON
0.26
<0.07
na
ns
<0.059
0.121
16
CMV
0.05
na
0.41
na
na
na
17
EAG2
na
ns
na
ns
na
na
18
GIL1
0.32
ns
0.37
ns
na
na
19
RAN
0.04
ns
0.34
ns
ns
ns


b
b
a


b


0.25
0.18
0.42
0.35
0.04
0.17
tion
0.16
0.06
0.09
-
-
0.06


0.04
<0.07
0.34
0.32
0.03
<0.06


0.56
0.28
0.61
0.37
0.06
0.26
68

-------
Table 13. Concentrations (ug/g) of thorium in moss and spruce
samples as determined by NAA (Lichen samples were not analyzed for
Th). Codes as in Table 3. The coefficient of variation for Th in
our bulk Sphagnum internal standard was 43.4. None of the sample
means were significantly different at the 5% level in paired sample
comparisons.
Th concentrations (ug/g)
Sf
Sr
Pn
Pt
Mean
Minimum
Maximum
1
ARL
na
ns
na
na
2
DIA
0 .044
na
0.016
0 .072
3
PAR
0.114
0.035
na
na
4
LSJ1
0.089
0 .046
na
na
5
LSJ2
0.055
ns
0.055
<0.029
6
SEP
0.196
0 .109
<0 .022
0 . 037
7
GSH
0.102
0.144
na
na
8
BAR
0 .038
0 .093
na
na
9
BUL
0.093
0.134
<0.049
0.061
10
SAP
0.024
0 .020
ns
ns
11
ESC
0.023
0 .068
na
na
12
MIS
0 .077
na
na
na
13
SAB
0.023
0 .038
0 .023
0.060
14
FOU1
0 .112
ns
<0 .034
0.027
15
CON
0.023
0.095
0.047
0.013
16
CMV
0 .013
na
na
na
17
EAG2
nd
ns
na
na
18
GIL1
<0.053
ns
na
na
19
RAN
0.008
ns
ns
ns


0 .065
0 .078
0 .035
0.045
ition
0 .051
0 .043
0 .019
0.023


0 .008
0 .020
0 .016
0 .013


0.196
0 .144
0.055
0.072
69

-------
Table 14. Concentrations (ug/g) of vanadium in moss, lichen, and
spruce samples, determined by NAA. Codes as in Table 3. The
coefficient of variation ^or V in our bulk Sphagnum internal
standard was 38. Lower case letters above the means are different
if the means were significantly different (at 5% level) in paired
sample comparisons. Picea needles were ,a 11 below detection limit
for V, suggesting that they are significantly lower in V than the
other plant samples. No letter indicates too few samples above
detection limit for a comparison of means.



V
concentrations
(ug/g)



Sf
Sr
Cs
Cr
Pn
Pt
1
ARL
na
ns
na
1.11
ns
ns
2
DIA
1.00
na
ns
0.75
<0.42
0.86
3
PAR
0.83
1.40
0.49
na
na
na
4
LSJ1
1.20
1.59
ns
na
na
na
5
LSJ2
2.00
' ns
1.05
na
<1.10
<0.51
6
SEP
2.30
1.77
1.30
na
<0.67
0.84
7
GSH
8.30
7.61
ns
ns
na
na
8
BAR
3.40
4.41
na
na
na
na
9
BUL
3.60
2.95
na
na
<0.88
0.64
10
SAP
2.00
1.90
0.89
na
ns
ns
11
ESC
2.20
2.52
na
na
na
•' na
12
MIS
2.60
na
1.70
na
na
na
13
SAB
2.50
1.68
ns
na
<0.84
3.14
14
FOU1
1.60
na
ns
na
<1.04
0.93
15
CON
1.30
1.17
ns
ns
<0.67
0.44
16
CMV
0.92
na
0.61
na
na
na
17
EAG2
na
ns
na
ns
na
na
18
GIL1
2.00
ns
0.28
ns
na
na
19
RAN
0.62
ns
0.40
ns
ns
ns


a
a
b


a
Mean

2.25
2.70
0.84
0.93
dl
1.14
Std. deviation
1.77
1.96
0.48
-
-
0.99
Minimum

0.62
1.17
0.28
0.75
<0.42
0.44
Maximum

8.30
7.61
1.70
1.11
<1.10
3.14
70

-------
Table 15. Concentrations (ug/g) of zinc in moss, lichen, and
spruce samples, determined by ICP-AES. Codes as in Table 3. The
coefficient of variation for Zn in our bulk Sphagnum internal
standard was 5.4. Lower case letters above the means are different
if the means were significantly different (at 5% level) in paired
sample comparisons.
Zn concentrations (ug/g)


Sf
Sr
Cs
Cr
Pn
Pt
1
ARL
15.5
ns
15.4
15.7
77
83
2
DIA
23.5
31.6
ns
26. 9
57
88
3
PAR
16.0
42.5
18.8
20.9
54
69
4
LSJ1
15.0
16. 4
ns
18.6
62
72
5
LSJ2
17.5
ns
22. 2
18.3
83
60
6
SEP
20.0
20 . 2
26. 6
28.9
56
56
7
GSH
20.5
41. 4
ns
ns
59
97
8
BAR
18.0
33.1
20.1
15.2
76
77
9
BUL
16.2
24.4
17.1
24.4
70
81
10
SAP
26.5
18 . 8
28.1
32.8
ns
ns
11
ESC
23.0
21.8
22.8
20.4
89
68
12
MIS
17.8
18.6
17.4
27 .0
63
66
13
SAB
14.8
24.8
16.7
ns
143
86
14
FOU1
13.0
19.5
14. 9
ns
54
61
15
CON
13.0
18.9
13.1
ns
82
83
16
CMV
11.9
18.1
12.7
18. 6
85
69
17
EAG2
15.0
ns
9.9
ns
69
56
18
GIL1
11.5
ns
13.3
ns
74
65
19
RAN
13.5
ns
11.8
ns
ns
ns
Mean
c
17 .0
b
25.0
b, c
17.6
b
22.3
a
74
a
73
Std. deviation
4.2
8.7
5.3
5.6
21
12
Minimum
11.5
16.4
9.9
15.2
54
56
Maximum
26.5
42 . 5
28.1
32.8
143
97
71

-------
Table 16.	Coefficients of correlation between element
concentrations in Sphagnum fuscum (Sf) and in other species (Sr =
Sphagnum rubellum. Cs = Cladonia stellaris. Cr = Cladina
ranoiferina).
Correlation coefficients



Sf-Sr
Sf-Cs
Sf-Cr
Al


0.552*
0.952***
0.727***

n
=
14
16
12
As


0.728
0.908**
-

n
-
7
6
-
Cd


0.600*
0.710***
0.753***

n
s
14
16
12
Cr


0.150
0.637**
0.662**

n
-
14
13
12
Cu


0.651**
0.426
0.596*

n
-
14
16
12
Hg


0.419
-
-

n
—
10
-
-
Mn


0.633**
0.524*
0.685**

n
—
14
16
12
Ni


0.562*
0.855***
0.819***

n
-
14
8
9
Pb


0.323
0.592**
0.530

n
-
14
16
12
Sb


-0.521
0.223
-

n
-
7
8
-
Th


0.382
-
-

n
-
10
-
-
V


0.958***
0.744*
-

n
=
10
8
-
Zn


0.186
0.874***
0.659**

n
s
14
16
12
*
P
<
0.05,
two-tailed
test
**
P
<
0.02/
two-tailed
test
***
P
<
0.01,
two-tailed
test
72

-------
Table 17.	Coefficients of correlation between element
concentrations in Sphagnum rubel1um (Sr) and lichen species (Cs =
Cladonia stel1aris. Cr = Cladina rangiferina). For the elements
As, Hg, Th, Sb, Ti, and V there were too few data points in common
to make calculations of a correlation coefficient between species
meaningful.
Correlation coefficients


Sr-Cs
Sr-Cr
Cs-Cr
Al

0.288
0.786***
0.832***

n =
11
10
10
Cd

0.816***
0.504
0.821***

n =
11
10
10
Cr

-0.008
-0.100
0.649*

n =
10
10
9
Cu

0.055
0.182
0.684*

n =
11
10
9
Mn

0.693**
0.817***
0.698**

n =
11
10
10
Ni

0.120
0.369
0.784

n =
7
10
5
Pb

0.311
0.192
0.622*

n =
11
10
10
Zn

0.036
-0.264
0.598

n =
11
10
10
* p < 0.05, two-tailed test
** p < 0.02, two-tailed test
*** p < 0.01, two-tailed test
73

-------
Table 18.	Coefficients of correlation between element
concentrations in Picea twigs and other samples (Sf = Sphagnum
fuscum. Cs = Cladonia stellaris. Cr = Cladina ranaiferina. Pn =
Picea needles, Pt = Picea twigs). For As there were too few points
in common to make calculation of a correlation coefficient
meaningful.
Correlation coefficients


Pt-Sf
Pt-Cs
Pt-Cr
Al

0.856***
0.913***
0.745***

n =
17
14
11
Cd

0.801***
0.805***
0.758***

n =
16
13
11
Cr

0.318
0.713*
0.274

n =
12
9
8
Cu

0.870***
0.493
0.763***

n =
17
14
11
Hg

0.584
-
-

n =
5
-
-
Mn

0.534*
0.253
0.579*

n =
17
14
11
Ni

0.332
0.090
0.077

n =
12
7
6
Pb

0.640***
0.694***
0.369

n =
17
14
11
Sb

0.242
-
-

n =
6
-
-
Th

0.168
-
-

n =
6
-
-
V

0.203
-
-

n =
6
-
-
Zn

0.221
0.184
0.175

n =
18
16
11
«r
P
<
0.05,
two-tailed
test
•hit
P
<
0.02,
two-tailed
test
¦kit*
P
<
0.01,
two-tailed
test
74

-------
Table 19.	Coefficients of correlation between element
concentrations in Picea needles and in other samples. (Sf =
Sphagnum fuscum. Sr = Sphagnum rubellum. Cs = Cladonia stellaris.
Cr = Cladina rangiferina, Pn = Picea needles, Pt = Picea twigs).
For the elements As, Hg, Th, Sb, Ti, and V there were too few data
points in common to make calculations of a correlation coefficient
between species meaningful.
Correlation coefficients
Pn-Sf	Pn-Cs	Pn-Cr	Pn-Pt
Al

0.872***
0.856***
0.796***
0.859***

n =
17
14
11
17
Cd

0.215
0 .379
0.466
0 . 423

n =
11
8
8
10
Cr

0.309
0 .158
0 .057
0.813***

n =
7
7
4
8
Cu

0.453
0.319
0.513
0.726***

n =
17
14
11
17
Mn

0.607***
0.303
0.632*
0 .898***

n =
17
14
11
17
Ni

0.139
0.638
0.531
0.602

n =
6
4
3
6
Pb

0 .235
0.493
0 .389
0.554*

n =
13
12
9
13
Zn

0.200
0 .082
0 . 614
0 .228

n =
17
14
11
17
* p < 0.05,
** p < 0.02,
*** p < 0.01,
two-tailed test
two-tailed test
two-tailed test
75

-------
Concentrations of many elements in these samples are
correlated with those in other samples collected at the same
sites, particularly for S_s_ f use tun and the Cladina lichens. For
example, statistically significant (p < 0.05) correlations exist
between element concentrations in S_j_ f us cum and C. stel laris for
9 of 11 elements; for fuscum and Cj_ ranqiferina. concentrations
of 7 of 8 elements are correlated. Sphagnum rubel lum and S.
£uscum are correlated for 6 of 13 elements (Al, Cd, Cu, Mn, Ni, and
V). Interestingly, Pb and Zn concentrations in S. rubel lum are not
corelated with those in jL_ fuscum. perhaps because of
post-depositiorial mobility of Pb and Zn in the wet hollow
environment (Damman 1978, Urban et al. 1990). (In addition, no
samples of Sj_ rubel lum were collected from the remote sites in
Labrador, which tend to be low in all trace elements, thus
eliminating the possibility of correspondingly low concentrations
of elements in S_i_ f us cum and S. rubel lum samples, which would
improve correlations). Some elements for which correlations are
very low are those which exhibit high C.V.'s in standards (i.e..
Hg, Sb, and Th). Lack of correlation for these elements may be due
to low analytical precision.
^ '
Correlation coefficients between element concentrations in C.
stellaris and C. ranqiferina are fairly high, and statistically
significant (p < 0.05) for~A1, Cd, Cr, Cu, Mn, and Pb, but not Ni
and Zn (Table 17).
Concentrations of Al, Cd, Cu, Mn, and Pb in spruce twigs are
significantly correlated with the concentrations of those elements
76

-------
in Sphagnum fuscum and the Cladina lichens (Table 18). For spruce
needles, only concentrations of Al and Mn showed significant
correlation with those element concentrations in other species,
although concentrations of Al, Cr, Cu, Mn, and Pb were correlated
in spruce twigs and needles (Table 19).
Pakarinen (1982) also found significant correlations among
concentrations of Ca, Cu, Fe, Mg, Pb and Zn in the moss and lichen
species he sampled, with a regional pattern of decreasing
concentration of Fe, Pb, and Zn from south to north Finland,
reflecting proximity to sources of these metals.
Although there were statistically significant differences
among the means for different sample types in paired sample
comparisons of element concentrations (Tables 3-15), for most of
the elements studied here (Al, As, Cd, Cr, Cu, Hg, Ni, Pb, Sb, Th,
and V) element concentrations were of the same order of magnitude
in samples of moss, lichen and spruce twigs. Concentrations of
several elements (Al, As, Cd, Cu, Hg, Ni, Pb, Sb, and V) were
distinctly lower in spruce needles, often with many values below
the detection limit. The major exceptions to these generalizations
are for the elements Mn and Zn. Concentrations of Mn were 5 to 10
times higher in spruce twigs and needles than in the moss and
lichen samples, and significantly higher in Sphagnum fuscum than
in the other moss and the lichens. Concentrations of Zn in spruce
needles and twigs were 3 to 4 times higher than in moss and lichen.
The trace metal concentrations in these moss and lichen
samples are similar in magnitude to those found for moss samples
77

-------
in rural areas of Sweden, Norway, Denmark and Finland (Ruhling et
al. 1987) except for Ni, which tends to be lower in these samples.
3.2.1 Relationship between element concentrations in moss and
atmospheric deposition
Concentrations of trace metals in these moss and lichen
samples appear to reflect patterns of their atmospheric:deposition.
Samples collected from remote regions (sites 15-19 in Labrador and
Newfoundland), have the lowest concentrations of heavy metal
pollutants. Samples from regions near sources of trace metal
pollutants show relatively high concentrations of these trace
metals. For example, Sphagnum samples from sites 7, 8, and 9,
located near industrial and urban areas in the northeastern U.S.
(Lazrus et al. 1970, Pacyna 1986) have the highest concentrations
of Hg, Ni, and V. The primary source of V in air is combustion of
residual oil in power plants, and V emissions are much higher in
the northeastern U.S. than in the midwest (Husain 1986).
Lac Parent (site 3) is about 150 km east of the mining
operations and copper smeltec at Rouyn-Noranda, Quebec, which
retease As, Cu, Pb, Zn to the atmosphere (Glooschenko 1986).
Diamond Bog .(site,2) is located 80 km north of Timmins, a mining
region, and 140 km west of Rouyn-Noranda. Samples from these sites
are among the highest in As, Cd, and Cu.
Lead and Zn are produced in northwestern New Brunswick,
Canada, moderately close, to sites 10, 11,. and 12, and these three
sites tend to have higher than average concentrations of Pb and Zn.
78

-------
Sept lies (6) is also located in the vicinity of mining operations,
and samples from this site are relatively high in Cd, Cr, Ni, Pb,
and Th. Samples from the more continental sites (Arlberg Bog, MN)
are highest in elements supplied in soil dust (Al and Cr, for
example), as might be expected in samples collected near the
agricultural midwest.
3.2.2 Comparison of lead concentrations in Sphagnum fuscum and
measured atmospheric deposition
To assess how accurately lead concentrations in moss
approximate actual atmospheric deposition of Pb, concentrations of
Pb in moss samples from this study were compared to published data
on Pb deposition in atmospheric precipitation (Eisenreich et al .
1986, Chan et al. 1986, Smath and Potter 1984). Lead was choosen
because it was the element for which the most data were available,
and because Pb has been shown to be sorbed and retained quite
efficiently by mosses such as Hvlocomium splendens (Ruhling et al.
1987). In order to provide more data points for comparison, Pb
concentration data from Sphagnum collected at four additional bogs
were included here (Alfred and Mead, Ontario; Red Lake and Toivola,
Minnesota). Table 20 shows the locations of all moss sampling
sites, lead concentrations in moss samples from those sites,
calculated fluxes of lead based on moss growth in length and bulk
density of the moss at that site, and measured lead deposition data
from the closest sites. Total deposition values were calculated
to be 1.5 times the wet deposition given in the literature, except
79

-------
for the values from Maine, which were already expressed as bulk
deposition - values. This approximation agrees with the estimated
ratios of wet/dry deposition given by Chan et al. (1986) and
Galloway et al. (1982).
The regression of calculated flux of lead to the moss oh
measured deposition of lead: in the same region was significant
(t = 4.18, 6df; R2 = 0.744, Dffleas = 0.632(Fcalc) + 0.583, where Dmeas
is measured deposition and Fcajc is calculated flux). On the
average, calculated fluxes tended to be about 75% of the estimated
total deposition, thus approximately 25% of the lead deposited is
not retained by the surface moss. This is in good agreement with
the results of other investigators for the relation between metal
concentrations in Hvlocomium solendens and Pleurozium schreberi and
measured deposition values (Ross 1990, Ruhling et_al_. 1987).
Concentrations of Pb in surface Sphagnum thus provide a good
estimate of recent deposition (past 1 to 3 years). Other elements
are not sorbed as strongly by mosses (Ross 1990, Ruhling et al.
1987) and moss concentrations of these elements (for example, Cd,
Ni, and Zn) may underestimate actual deposition.
80

-------
Table 20. Comparison of lead concentrations and calculated fluxes
of lead in Sphagnum fuscum moss with atmospheric deposition of lead
in Maine, USA, Minnesota, USA and Ontario, Canada. The
calculations of Pb flux to the moss were obtained by multiplying
Pb concentrations in the moss by the measured annual moss growth
in length (Santelmann, unpublished data) and bulk density of the
upper 10 cm of the moss at the site (Gorham and Santelmann,
unpublished data). Deposition data are calculated by multiplying
published values of wet-only deposition at the nearest site or
sites by 1.5, from the following references: a) Eisenreich et al.
1986, b) Chan et al. 1986. Values for deposition from reference
c) Smath and Potter 1984 are considered to be bulk deposition
values.
Site N Lat W Long Pb conc. in Calculated	Atmospheric
moss (ug/g) flux (mg m^ a"^) deposition
TO I
47°
04'
92°
52'
9.4
4.08
4.5
a
ARL
46°
55'
92°
47 '
9.8
4.65
4.5
a
RED
48°
15'
92°
37'
6.0
2.47
2.5
b
MEAD
49°
26'
83°
56'
4.7
1.14
3.7
b
DIA
48°
52'
80°
38'
6.3
2.28
3.5
b
ALF
45°
34'
74°
53'
16.5
7 . 45
11. 5
b
GSH
44°
23'
69°
48'
19.0
5.3
6.0
c
BAR
44°
15'
68°
15'
15.1
3.6
6.0
c
a Eisenreich et al. 1986
b Chan et al. 1986
c Smath & Potter 1984
81

-------
3.3 Use of enrichment factors in assessing metal enrichment
Crustal-enrichment factors (EF) can be useful in assessing the
enrichment of trace metals in moss samples relative to what one
would expect if all of the element present in the sample were
present in particles of unpolluted soil dust or rock. The crustal-
enrichment factor is calculated as follows, normalizing to Al
because it is strongly lithophile, not taken up actively by plants,
and present in concentrations high enough to be easily measured.
[El ement ]gample/ 3sample
EF = 	-	
[Element 1 earth's crust /C^^earth's crust
The element concentrations in crustal rock used to calculate EF
values are from Mason (1966) as reported by Rahn (1976).
If an element is present in the moss only as a result of the
deposition of unpolluted soil or rock particles, the EF will be
approximately one, and will be constant over a wide range of Al
concentrations. Thus, there will be little or no slope to the
regression in a plot of EF vs Al. If most of the element in a moss
sample is supplied by a source other than unpolluted soil
particles, the EF will be greater than 5, if an element is highly
enriched, it may be greater than 100. Also, if concentrations of
an element are relatively constant in the moss samples, and
independent of Al concentration, the EF should change as a function
of Al concentration and the slope of the regression line in a plot
82

-------
of log(EF) vs log[Al] should be -1. Thus, the value of the EF
indicates whether an element is enriched relative to aluminum in
the sample, aswould be expected for heavy metal pollutants. The
plot of the log(EF) vs log[Al] indicates whether the primary source
of the element is probably unpolluted soil particles (EF > 5, slope
of regression of log(EF) on log[Al] not significantly different
from 0) or whether the primary source of the element is likely to
be atmospheric pollution, with the element concentration
independent of the input of Al in soil or rock (EF > 5, slope of
regression of log(EF) on log[Al] = - 1).
Table 21 shows the average enrichment factors for each element
in Sphagnum fuscum samples.	Figures 13-22 show plots of
enrichment factors vs aluminum concentration on a logarithmic scale
for the elements As, Cd, Cr, Cu, Mn, Ni, Pb, Sb, V, and Zn.
83

-------
Table 21. Average enrichment factors for trace metals in samples
of Sphagnum f us cum.
Element
Average enrichment factor
Relative enrichment
As
96
highly enriched
Cd
501
highly enriched
Cr
3
unenriched
Cu
22
moderately enriched
Mn
101
highly enriched
Ni
5
moderately enriched
Pb
378
highly enriched
Sb
532
highly enriched
Th
3
unenriched
V
6
moderately enriched
Zn
104
highly enriched
84

-------
Figure 13. Plot of enrichment factors for As vs Al concentration
per unit dry mass (logarithmic scale on axes). Solid line has a
slope of -1 through the centroid of the data.
85

-------
Enrichment Factor vs. Al concentration
3.5
3
2.5
2
1.5
1
0.5
Al concentration (log)

-------
Figure 14. Plot of enrichment factors for Cd vs Al concentration
per unit dry mass (logarithmic scale on axes). Solid line has a
slope of -1 through the centroid of the data.
87

-------
Enrichment Factor vs. Al concentration
Cd
3.5
o>
o
L.
0
u
o
u.
-*->
c
©
o
L
c
Ld
3 -
2.5 -
2 -
1.5 -
1 -
0.5 -
1.7
1.9
2.1	2.3	2.5
Al concentration (log)
2.7
2.9
3.1

-------
Figure 15. Plot of enrichment factors for Cr vs Al concentration
per unit dry mass (logarithmic scale on axes). Solid line has a
slope of -1 through the centroid of the data.
89

-------
Enrichment Factor vs. Al concentration
Cr
3.5
2.5 -
0.5
~ ~
2.7
3.1
2.3
2.9
2.5
1.7
1.9
2.1
Al concentration (log)

-------
Figure 16. Plot of enrichment factors for Cu vs Al concentration
per unit dry mass (logarithmic scale on axes). Solid line has a
slope of -1 through the centroid of the data.
91

-------
Enrichment Factor vs. Al concentration
Cu
3.5
o>
o
u
o
u.
*>
c
©
E
r.
u
L
c
Ui
3 -
2.5 -
2 -
1.5 -
1 -
0.5 -
1.7
1.9
2.1	2.3	2.5
Al concentration (log)
2.7
2.9
3.1

-------
Figure 17. Plot of enrichment factors for Mn vs Al concentration
per unit dry mass (logarithmic scale on axes). Solid line has a
slope of -1 through the centroid of the data.
93

-------
Enrichment Factor vs. Al concentration
3.5
3
2.5
2
1.5
1
0.5
Al concentration (log)

-------
Figure 18. Plot of enrichment factors for Ni vs Al concentration
per unit dry mass (logarithmic scale on axes). Solid line has a
slope of -1 through the centroid of the data.
95

-------
Enrichment Factor vs. Al concentration
Ni
3.5
2.5
0.5
2.3
1.9
2.5
2.7
2.9
2.1
3.1
Al concentration (log)

-------
Figure 19. Plot of enrichment factors for Pb vs Al concentration
per unit dry mass (logarithmic scale on axes). Solid line has a
slope of -1 through the centroid of the data.
97

-------
Enrichment Factor vs. Al concentration
3.5
Pb
a>
o
o
-*->
o
o
u.
+¦>
c
a>
E
.c
u
L
c
UJ
3 -
2.5 -
2 -
1.5 -
1 -
0.5 -
J	I	I	L
J	L
' ' ' '	I	L
1.7
1.9
2.1	2.3	2.5
Al concentration (log)
2.7
2.9
3.1

-------
Figure 20. Plot of enrichment factors for Sb vs Al concentration
per unit dry mass (logarithmic scale on axes). Solid line has a
slope of -1 through the centroid of the data.
99

-------
Enrichment Factor vs. Al concentration
Sb
3.5
o>
o
»_
o
u
o
u.
+->
c
©
E
¦C
u
'C
c
UJ
3 -
2.5 -
2 -
1.5 -
1 -
0.5 -
1.7
1.9
2.1	2.3	2.5
Al concentration (log)
2.7
2.9
3.1

-------
Figure 21. Plot of enrichment factors for V vs Al concentration
per unit dry mass (logarithmic scale on axes). Solid line has a
slope of -1 through the centroid of the data.
101

-------
0>
o
k.
o
v
u
O
Lt.
+>
C
®
E
j:
u
L
c
UJ
3.5
3 -
2.5 -
2 -
1.5 -
1 -
0.5 -
Enrichment Factor vs. Al concentration
V
1.7
1.9
2.1	2.3	2.5
Al concentration (log)
2.7
2.9
3.1

-------
Figure 22. Plot of enrichment factors for Zn vs Al concentration
per unit dry mass (logarithmic scale on axes). Solid line has a
slope of -1 through the centroid of the data.
103

-------
Enrichment Factor vs. Al concentration
3.5
Zn
2 -
~ ~ ~ ~
1.5
0.5
» ¦ ¦
¦	i	i . i	i	i	i	i
1.7	1.9
2.1	2:3' 2.5
Al concentration (log)
2.7	2.9	3.1

-------
The elements tend to fall into three categories, unenriched
(EF < 5 ), moderately enriched (5 <_ EF < 100), and highly enriched
(EF > 100).	In these samples, the elements Cr and Th are
unenriched; Cu, Ni, and V are moderately enriched; and As, Cd, Mn,
Pb, Sb, and Zn are highly enriched (the average EF for As is 96,
close enough to 100 to be included in the highly enriched
elements). For Cu, Ni, Pb, and Zn, the EF's appear to follow the
line with slope -1, indicating a source (most likely atmospheric
pollution, Pacyna 1986) for those elements that is independent of
crustal rock or soil dust.
Lack of analytical precision for the elements As, Cd and Sb
may be responsible in part for the fact that they do not show a
definite slope of -1 in the enrichment factor plots despite their
obvious enrichment. Vanadium has a dual source in these samples,
(it is a component of mineral soil as well as a pollutant) and this
not only decreases the value of the enrichment factor, it may
decrease the tendency of the V data to show a clear slope in
enrichment factor plots as well.
Uptake of Mn by the moss may be responsible in part for the
enrichment of Mn in these samples, and the mobility of Mn in acid,
wet conditions at the bog surface make the behavior of Mn difficult
to interpret from concentration data alone.
105

-------
3.4 Utility of each species in monitoring atmospheric-deposition
Of the species studied here, Sphagnum fuscum, Cladina
stel laris, and C_s_ ranaif erina ¦ and Picea mariana twigs appear to
be the most useful species for monitoring atmospheric depostion of
trace elements in ombrotrophic bogs. Concentrations of trace
metals are correlated in these samples, and appear to accurately
reflect known patterns of atmospheric deposition of those elements.
S. rubellum appears to be less useful, perhaps because of greater
post-depositional mobility of trace elements in the wet hollow
microhabitat in which it grows, both from physical removal of
particles by water and cation exchange of1 adsorbed metal ions.
Species occurring in somewhat drier habitats thus seem to be most
appropriate for use as monitor species for atmospheric deposition.
Cladina stellaris and C^. ranaiferina are suggested for use in
monitoring because they are known to be present in the Arctic
(Thomson 1984) and because so many studies of atmospheric
deposition in natural vegetation have included these' species.
Sphagnum fuscum and Picea mariana, while useful in studies in the
sub-arctic and boreal regions, are not common above 60 0 N
latitude.
106

-------
4.0	Sources of variability in the data
4.1	Analytical variability
Coefficients of variation (C . V . = ( standard deviati on/mean) *100 )
for elements determined by ICPAES in the SMS standard were as
follows: C.V. < 5: Al, Mn, Zn; C.V. 6-10: Cr, Pb; C.V. 11-20: Cu,
Ni, Cd. Coefficients of variation for elements determined by NAA
(Univ. of Madison, Wisconsin) in the SMS standard were as follows:
As, 19; Hg, 67; Sb, 80; Th, 43; Ti, 59.
For the NAA analyses done at the University of Toronto,
insufficient data were obtained on the SMS standard to calculate
coeffients of variation, however, they provided estimates of
counting precision. Average counting precision data are presented
here as 1) a per cent of sample element concentration, and 2) the
range (in ppm) of the counting precision: As: 6.5 %, 0.02 to 0.1
ppm; Sb: 4.9 %, 0.01 to 0.04 ppm; Ti: 9.2 %, 8 to 10 ppm; and V:
5.4 %, 0.1 to 0.3 ppm.
4.2	Within-site variability
4.2.1 Between-sample variation
Estimates of between-sample variation for the four moss and
lichen species collected in this study are presented in Table 22.
Coefficients of variation for elements determined in this study
range from 15.5 (Cu) to 40.8 (Pb) for fuscum. from 21.2 (Zn)
to 66.4 (Ni) for S_;_ rubel lum, from 7.9 (Cu) to 37.1 (Cd) for C.
stel laris, and from 7.1 (Zn) to 41.5 (Cr) for C^. rangi f erina.
These are similar to the values found by other investigators.
107

-------
Table 22. Coefficients of variation (C.V.) (expressed as a per
cent) for element concentrations in moss and lichen samples, for
sites where at least three replicate samples were collected. The
C.V.'s listed from this study are calculated from log-transformed
data for 3 samples per site (except for Sphagnum rubellum and
Cladina ranoiferina. for which some sites had four samples)
averaged over all sites, according to the following formula for
pooling coefficients of variation:
V = ((n^ -l)var(xi) + (n2 - l)var(x2) + ...(n^ - l)var(X|j) )/N-k
Coefficient of variation = 230.26(V)
where N is the total number of observations from all sites, k is
the number of sites, n^ is the number of samples from site k, and
var(xb) is the variance of the log-transformed observations from
site k. For comparison, C.V.'s from three other studies and from
the samples collected in the study of seasonal variation in S.
fuscum from a single site are presented in this table as well, in
this case, the C.V. is calculated by dividing the mean by the
standard deviation.
Al „ Cd Cr Cu Mn Ni Pb Zn
S. fuscum3	26.7 37.9 34.2 15.5 40.8 26.5 38.7 18.5
7 sites
S. rubellum3 24.0 37.2 49.1 46.7 55.9 66.4 43.7 21.2
6 sites
C. stellaris3 10.9 37.1 29.3 7.9 21.2 * 11.0 8.6
2 sites
C. rangiferina3 17.4 13.5 41.5 9.4 23.2 30.3 15.7 7.1
2 sites
S. fuscum''	- - - 8 22 - 8 7
S. fuscum0	- - - 31.3 18.98 - - 34.0
S. fuscum1*	- - 61.1 36.1	- 38 8
Seasonal samples
S. fuscum3	14.9 67.8 15.6 14.6 28.6 16.2 14.5 8.2
n = 14
a this study
b Pakarinen 1981
c Aulio 1982
d Glooschenko 1986
* not. enough data to calculate c.v., because several samples were
below the detection limit
108

-------
4.2.2 Seasonal variability
Duplicate samples of Sphagnum fuscum were collected at two-
week intervals throughout the growing season at a site in
Minnesota (Toivola Bog), and analyzed by ICPES to determine if any
patterns of seasonal variation in element concentrations could be
detected. Figures 23-30 are plots of element concentrations vs.
collection date for these samples. No clear linear trend is
apparent for any of the elements except Mn. Manganese shows a
steady increase over the summer season, as would be expected if
this element (which is highly mobile under acid conditions) were
being transported by a "wicking" or capillary action as water
evaporated from the bog surface and moisture moved from the deeper
peat towards the surface. Additional samples and samples from more
than one site are necessary in order to rigorously test whether
seasonal trends are in fact present, however, at least these data
indicate that the range of seasonal variation in these elements is
within the range of between-sample variation for samples collected
at the same time for a given site (See Table 22).
109

-------
110

-------
Figure 23. Seasonal changes in Al concentrations in Sphagnum
fuscum collected from Toivola Bog, MN. Day 10 is June 16, 1983.
Ill

-------
900
800
700
600
500
400
300
200
100
0
Seasonal changes in S. fuscum
element concentrations
+
+
+
~
~
+
+
~
+
~
J	I	I	:	I	I	L:	I	
10	24	37	55	76	9B	130
Date of collection

-------
Figure 24. Seasonal changes in Cd concentrations in Sphagnum fuscum
collected from Toivola Bog, MN. Day 10 is June 16, 1983.
113

-------
0.5
0.4 -
0.3
0.2 -
0.1
Seasonal changes in S. fuscum
element concentrations
10	24	37	55	76	98	130
Date of collection

-------
Figure 25. Seasonal changes in Cr concentrations in Sphagnum fuscum
collected from Toivola Bog, MN. Day 10 is June 16, 1983.
115

-------
o>
\
D)
3
o
c
o
53
ra
>_
c
©
o
c
o
O
3.5
3 -
2.5
2 -
1.5 -
0.5
Seasonal changes in S. fuscum
element concentrations
10
24
37	55
Date of collection
76
96
130

-------
Figure 26. Seasonal changes in Cu concentrations in Sphagnum fuscum
collected from Toivola Bog, MN. Day 10 is June 16, 1983.
117

-------
Seasonal changes in S. fuscum
element concentrations
5 -
o>
\
o>
3
D
o
c
o
555
<0
**
c
o
u
c
o
o
3 -
2 -
1 -
10
24
37	55
Date of collection
76
96
130

-------
Figure 27. Seasonal changes in Mn concentrations in Sphagnum fuscum
collected from Toivola Bog, MN. Day 10 is June 16, 1983.
119

-------
700
600 -
500
400 -
300 -
200 -
100 -
10
Seasonal changes in S. fuscum
24
element concentrations
37	55
Date of collection
76
98
130

-------
Figure 28. Seasonal changes in Ni concentrations in Sphagnum fuscum
collected from Toivola Bog, MN. Day 10 is June 16, 1983.
121

-------
U)
\
O)
3
C
o
53
ra
•V*
c
©
o
c
o
O
Seasonal changes in S. fuscum
element concentrations
9
37	55
Date of collection

-------
Figure 29. Seasonal changes in Pb concentrations in Sphagnum fuscum
collected from Toivola Bog, MN. Day 10 is June 16, 1983.
123

-------
15
14
13
12
11
10
9
6
7
6
5
4
3
2
1
0
Seasonal changes in S. fuscum
element concentrations
~
+
~
+
j	i	i	i	i	i	i	
10	24	37	55	76	90	130
Date of collection
~
+
~
~
+
~
+
~

-------
Figure 30. Seasonal changes in Zn concentrations in Sphagnum fuscum
collected from Toivola Bog, MN. Day 10 is June 16, 1983.
125

-------
30
28
26
24
22
20
18
16
14
12
10
8
6
4
2
0
Seasonal changes in S. fuscum
element concentrations
~
~
+
+
~
+
~
+
~
0
J	I l l l I l I	I	I	I	I	I	L	I	|	I	I	I	L
20 40 60 80 100 120 140 160 180 200
Date of collection

-------
5.0 Recommendations
5.1 Site selection
Collection of samples from similar site types across the
entire region to be sampled is important, in order to minimize
variance due to differences among sites. For example, in the
arctic, different site types could include sedge tussock tundra,
sedge muskeg or meadows, ice-wedge polygons, talus slopes.
Collection of the species desired from the same site type in each
region is important. Collection should also be made from the same
microhabitat in each site. For example, the microtopography
associated with ice-wedge polygons results in several distinct
microhabitats separated by only a few decimeters, and plant growth
and species distributions can be reproducibly affected by this
microrelief (Britton 1957).
The use of pairs or groups of similar sites in each area
sampled is desirable in order to partition variance in element
concentrations accurately, and establish whether it is reasonable
to infer that patterns in the data are the result of real
differences in atmospheric deposition among regions. Because the
between-sample variation is relatively high for trace elements in
these types of samples, collection of at least 3 or 4 replicate
samples of each species from pairs or triplets of sites is
recommended. However, it is probably more useful to have twelve
samples collected as four replicates from three similar sites in
an area for estimating regional patterns of deposition than twelve
127

-------
samples from the same site, since for the same analytical expense
one can estimate both within- arid between-site variability.
In addition, it is important to follow the same sampling
procedures at all sites, rather than sampling one site intensively
and its pair less intensively (as sometimes occurred in this
study). In the arctic, where it may be difficult to determine
beforehand what types of site will be present in each area, it
would be helpful to: begin by sampling pairs or triplets of several
types of sites in each area visited with the expectation that in
other parts of the region some of those site types might not be
present. Similarly, it will be important to sample several species
from each site because not all species will be present at eiach site
type. Decisions about which suite of samples to analyze can be
made after sampling is completed and it is known which species were
present' at the most sites.
Consideration should be given from the start to the questions
or hypotheses that' need to be answered most, what statistical
analyses will be used to test them, and the sampling regime
designed accordingly. For example, one could use analysis of
variance to test the following hypotheses:
1) are there significant differences in the concentration of trace
elements in samples collected from different- regions (e.g. do
samples from the Toolik Lake region differ consistently from those
collected in ANWR and the Noatak W. R.?).
128

-------
2)	are there significant differences among samples collected at
different sites within each area sampled (e.g., do samples
collected from sedge meadows differ from those collected from bare
rock among ice-wedge polygons?).
3)	are there significant differences among the same site types
within the same sampling area (are samples collected from sedge
meadow A near Toolik Lake different from those collected from
sedge meadow B nearby?)
Grouping factors could be 1) area (Toolik Lake, ANWR, Noatak)
and 2) site type (sedge tussock tundra, exposed talus slope, trough
in ice-wedge polygon, etc.) with data from samples collected in
triplicate at each site type forming the repeated measures of each
element concentration. It would be important to sample site types
at least in duplicate for such an analysis.
If species such as C_^ stellaris and	rangif erina were
collected as part of the sampling, comparisons could be made with
studies done in sub-arctic and boreal regions such as the one
described here.
Concerns about the existence of chemical races of Cladina
lichens, which might differ in element accumulation, have been
expressed, particularly because it would be almost impossible to
distinguish such races in the field. According to Tomassini et al .
(1976), and Puckett and Finegan (1980), interspecies differences
among the Cladina lichens are very small, at least in the Northwest
129

-------
Territories of Canada. However, Pakarinen (1981a),, found
statistically significant differences between C. arbuscula and Cj_
stellaris collected in Finland for some elements. A practical
solution to this problem would be to collect these species,
identify and analyze them, and if chemical, reaces are -found,
construct a calibration table similar to that developed by Folkeson
(1979).
5.2 Sampling methods
Choosing a standard portion of the. plant to. sample is
important. Pakarinen (1981b) suggests collecting more than one
year's growth of Sphagnum moss in order to average out yearly
fluctuations in deposition patterns. He most commonly used
Sphagnum samples of the top 3 cm, including the living moss.
However, in some regions', such as the mid-continental U.S., moss
growth averages about 2 cm per year, so 3 cm increments average
only one and one-half years' growth. In regions where moss growth
is much slower, (for example,-maritime bogs where growth is onthe
order of 0.3 to 0.9 cm per year (Santelmann, unpublished data))
collecting to a depth of .3 cm averages several ^years. ^Collecting
a constant depth increment is thus most reasonable within a
geographic region where moss growth is fairly constant.
For monitoring fluxes of elements over time> it is desirable
to collect an increment of moss or lichen that represents a.
constant time interval at all sites sampled. Unfortunately,
little data is available on rates of growth of mosses and lichens
130

-------
in arctic regions, especially growth in length. Productivity data
could be combined with measurements of bulk density to estimate
the length of moss to collect, however, productivity data do not
always include measurements of bulk density. In practice, the most
efficient solution seems to be to set up observational studies at
sampling sites to measure the growth in length of mosses and
lichens over time, but to initially collect several samples of
constant depths among sites, archiving some of these samples until
more is known about growth rates of these plant species at each
site from direct measurements. According to Ruhling et al . (1987),
Hy1ocomium splendens produces easily distinguished annual growth
increments, however, there have been no studies to determine
whether this is so in the North American Arctic.
Even if the length of annual growth increments of a species
are not known, collection of a sample of a standard length can
provide useful information for comparison among sites. Such data
would at least establish a baseline for current element
concentrations in these remote regions, and information to be used
in estimating bioaccumulation of elements along the food chain.
For example, caribou and reindeer tend to eat only the top portion
of lichens (Nieboer and Richardson 1981). Collection and analysis
of the top portion of the lichen would provide information about
the intake of metals at this stage in the food chain.
Collection of samples in plastic bags using gloves is
recommended, so that collecting can be done without the use of
insect repellent by the collectors or contamination from their
131

-------
hands. If samples cannot be dried immediately, they should be
kept frozen or at least cold until they can be dried. Sample bags
should be double-packaged inside large plastic bags to prevent
contamination of the outsides of sample bags with dust etc., which
can be a problem when travelling on gravel or dirt roads common in
remote areas. This can also help in' keeping all samples from a
particular site together, and preventing confusion of samples.
Samples should be dried in the field if possible, because
transport of dried samples is simpler (less weight) and because
there will be less degradation of the samples en route to
analysis. Lichen samples in particular tend to mold rapidly in
plastic bags. Setting up a lightweight, portable field rack for
drying samples (without having them blow away) will probably be
necessary. Samples such as these cannot be dried using the
gasoline-fueled driers used commonly for drying taxonomic
specimens.
Although drying is faster in paper bags than in plastic bags,
drying wet plant samples in paper bags means risking contamination
of the sample from elements leached out of the paper or from the
glue holding the bag together. He found significantly elevated
concentrations of B (probably from the glue- in the bags) in
subsamples of a large bulk sample dried in paper bags compared to
subsamples of the same bulk collection dried in plastic bags.
Samples dried in paper bags were not significantly enriched in Al,
Cr, Cu, Mn, Ni, Pb, or Zn, however, it is not certain whether these
elements would be leached from paper bags from other sources.
132

-------
Samples were not analyzed for As, Hg, Sb, Ti, or V, so it is not
known whether these elements would be enriched in samples dried in
paper bags.
Drying should be done at moderate temperatures (25 0 C), if
the samples will be analyzed for Hg, which is volatile and will
be lost through evaporation at higher temperatures. It is
important to dry the samples at the same constant temperature, as
well. Dried samples should be kept in a desiccator until weighed,
and then weighed quickly, because moss and lichen samples will
rapidly take up moisture from the air, causing analytical error in
determination of the mass of sample used.
Voucher specimens should be collected from each sample, given
a sample collection number and code. Voucher specimens can and
should be placed in paper bags for more rapid drying.
Storing the samples (or at least, most of the samples) as
dried material is probably most desirable. Storage needs and
space are simpler (no energy requirement as there are with
freezers) and there are no problems with equipment failure or
power outages. In addition, as time goes on, money for processing
and drying the samples may become scarce, so it is useful to have
that done already. Perhaps a few replicates of each sample could
be archived as frozen material in case special processing methods
are needed at a later date, but most replicates could be preserved
dry. Samples to be analyzed immediately should be cleaned and
dried as soon as possible.
Grinding of the samples must be done carefully, and the type
133

-------
of blades used in grinding must be noted, because the production
of metal filings during the grinding process can enrich samples
unpredictably in trace elements such as Cr (Santelmann. and Gorham
1988, Munter et al. 1984). Grinding may not be necessary, and if
so, a source of contamination for trace metals can be eliminated.
Our Cj_ stellaris samples could be crushed to a fine powder when
dried and thus needed no grinding. The other plant samples which
were ground have much greater variation in Cr than the lichen
samples, possibly from metal filings produced during grinding.
Ross (1990) and Ruhling and Tyler (1987) used an acid digestion of
ungrouhd moss samples for their analyses. This adds some error due
to sample heterogeneity, but reduces the risk of contamination from
grinding.
Submission of internal standards with samples in a blind
manner is also important, as is ensuring that sufficient numbers
of standards are run with the samples. For example, in our study,
we submitted a bulk sample of the standard to be run at frequent
intervals among samples for NAA at the Univ. of Toronto. Owing to
lack of communication between investigators, it was treated as a
single sample and run only once. If, instead, splits of the
standard had been prepared along with the samples and submitted in
a blind fashion, this could have been avoided. Of course, it is
critical to keep careful track of sample codes when submitting
samples in such a manner.
Three major analytical problems were encountered in this
study. 1) Some of the analyses were extremely variable (C.V.-'s for
134

-------
standards > 0.50). 2) Some element concentrations were below the
detection limit in nearly all of the samples. 3) Detection limits
for some of the elements varied among the samples, making
comparison of data from different analytical runs difficult.
Coinvestigators at the Univ. of Wisconsin and Univ. of Minnesota
suggest that the source of these problems was most often lack of
sufficient sample for analysis. When sufficient sample was
available for ICPAES, detection limits were constant and higher
than for samples with larger dilution factors.
In addition, recent improvements in instrumentation for
ICPAES have lowered the detection limits for elements such as Ni
and Cd in these types of plant samples (R. Munter, personal
communication), improving analytical precision for internal
standards and samples.
For NAA, the following procedures were recommended for
improving analyses:
1)	Samples should be submitted in batches of similar mass, volume,
and composition. Including samples of leaves and twigs in the same
batch, for example, can cause analytical difficulties. This means
that sample type will be conffounded with batch (analytical run),
and thus care must be taken to provide sufficient standards in each
batch for calibration between batches.
2)	Irradiation time for short irradiation may need to be adjusted
to get appropriate counter dead time for standards and unknowns.
For example, in our analyses, irradiation time was set to a level
appropriate for the orchard leaf standard. This resulted in dead
135

-------
times on NBS pine needles and the SMS standard that were relatively
high, in some cases' too high for accurate results; (At high dead
times, decay events are occurring so rapidly that multiple events
occur at the same timem effectively removing counts from the
photopeak.)
Moss and lichen samples are not as dense as most other types
of plant materials, and element "concentrations in such samples can
be very low. This may necessitate special handling procedures for
these samples in order to obtain optimal analytical accuracy and
precision.
136

-------
6.0	Summary
6.1	Recommendations for sample collection, handling and analysis
In each area of the region to be sampled, several site types
should be chosen. Pairs or triplets of each of these site types
should be selected in each area in order to determine the between-
site component of variance in the data.
At each site, several species should be sampled; more species
than the research group intends to analyze, with the expectation
that not all species will be present at each site, and that this
will at least provide a subset of species that will be fairly
complete at the end of the sampling. It may be possible to also
construct a calibration matrix for estimating concentrations of
elements in missing species similar to that of Folkeson (1979).
Specimens should be collected in plastic specimen bags, using
powderless PVC gloves. Voucher specimens should be collected at
the same time from each sample. Specimens should be trimmed to the
desired length and dried in the field if possible, or frozen as
soon as possible if drying is not feasible. In the laboratory,
samples must be cleaned of other species or parts of vascular
plants, ground and homogenized for analysis. Further preparation
of the material will depend on the method of analysis chosen.
In addition to NBS or EPA standards used for calibrating
analyses, use of an internal standard of moss and/or lichen,
(collected in bulk and homogenized carefully) is recommended. Such
standards provide an independent estimate of analytical precision,
employing a matrix similar to that of the samples analyzed.
137

-------
6.2 Summary of data presented
Element concentrations in these samples are similar iri
magnitude to those found in Norway, Sweden, Finland, and other
studies in Canada (Glooschenko 1986, Ross 1990, Ruhling et al.
1987). Concentrations of metals such as As; Cd, Cu, Ni, Pb, V, and
Zn are highest in areas closest to sources of pollution, and lowest
iri areas remote from pollution sources.
Of the "elements investigated here, As, Cd, Cr, Cu, Ni, Pb, V,
and Zn appear to be the most useful for study. Mercury, Sb, Ti and
Th were too low in concentration in these samples to be detected
reliably. Manganese appears to be quite mobile in these acid, wet
environments, and concentrations of Mn in these samples may not
reflect deposition, or accumulation wel1. . In addition, Mn is the
only element that appears to show a significant seasonal trend in
concentration.
Element concentrations in moss,- lichen, and spruce twig
samples tend to be 'significantly correlated, as expected if they
are all sampling atmospheric deposition and accurately reflecting
relative deposition rates. Element concentrations tend to be
higher in Sphagnum fuscum samples as compared to £L_ rubel lum or
the Cladina lichens. - More data, especially more replication-, is
needed to determine whether significant differences exist between
the two lichen species studied here in their accumulation of trace
elements at the same site.
Data from Sphagnum rubellum and Picea needles give the poorest
138

-------
correlation with other species. Sphagnum fuscum moss, Pi cea
mariana twigs, and Cladina lichens thus appear to be most valuable
as indicators of atmospheric deposition of toxic trace metals.
Of these species, only Cladina lichens are commonly found in the
arctic.
Moss and lichen samples are useful in monitoring relative
levels of atmospheric deposition of some trace metal pollutants,
(Ross 1990, Ruhling et al., 1987, this study). Collection of moss
and lichen for analysis of trace metals in these species will
provide essential information on heavy metal deposition, surface
concentrations, and bioaccumulation of these elements in remote
arctic regions.
139

-------
Acknowledgements
The author wishes to thank Dr. Eville Gorham for generously
allowing data from his project to be used in this document, and to Drs.
Pekka Pakarinen and Paul Glaser for their help collecting the samples.
Jill Stefansen and Connie Osbeck provided field assistance. ^Drs. R.
C. Munter and R. J. Cashwell supervised the analyses and helped
interpret the analytical data. They also recommended methods to
improve analyses in thefuture. Thanks are also due to Drs. Jesse Ford
and George King for comments on the manuscript.
Although the research described in this report has been funded
by U.S. Environmental Protection Agency order OBO 348 NATA to Dr.
Mary V. Santelmann, it has not been subjected to the Agency's
review and therefore does not necessarily reflect the views of the
Agency, and no official endorsement should be inferred.
140

-------
Literature Cited
Aulio, K. 1982. Nutrient accumulation in Sphagnum mosses. II.
Intra- and interspecific variation of four species from
ombrotrophic and minerotrophic habitats. Annales Botanici Fennici
19: 93-101.
Barrie, L.A. 1986. Arctic air pollution: An overview of current
knowledge. Atmospheric Environment 20:643-663.
Britton, M. E. 1957. Vegetation of the Arctic tundra. In: Arctic
Biology, ed. H. P. Hanson, pp 67-130. Oregon State University
Press, Corvallis, Oregon, USA.
Chan, W.H., A. J. S. Tang, D. S. Chung, and M. S. Lusis. 1986.
Concentration and deposition of trace metals in Ontario, 1982.
Water, Air, and Soil Pollution 29:373-389.
Clymo, R. S. 1973. The growth of Sphagnum: Some effects of
environment. Journal of Ecology 61:849-869.
Damman, A. W. H. 1978. Distribution and movement of elements in
ombrotrophic peat bogs. Oikos 30: 480-495.
Eisenreich, S.J., N. A. Metzer, N. R. Urban, and J. A. Robbins.
1986. Response of atmospheric lead to decreased use of lead in
gasoline. Environmental Science and Technology 20:171-174.
Fernald, M. L. 1970. Gray's Manual of Botany, 8th ed. D. Van
Nostrand Co. New York, New York, USA. 1632 pp.
Folkeson, L. 1979. Interspecies calibration of heavy-metal
concentrations in nine mosses and lichens: applicability to
deposition measurements. Water, Air and Soil Pollution 11:253-260.
Galloway, J.N., J. D. Thornton, S. A. Norton, H. L. Volchok, and
R. A. N. McLean. 1982. Trace metals in atmospheric deposition:
A review and assessment. Atmospheric Environment 16:1677-1700.
Glaser, P. H. and J. A. Janssens. 1986. Raised bogs in eastern
North America: transitions in landforms and gross stratigraphy.
Canadian Journal of Botany 64: 395-415.
Glooschenko, W. A., R. Sims, M. Gregory, and T. Mayer. 1981. Use
of bog vegetation as a monitor of atmospheric input of metals,
In: "Atmospheric Pollutants in Natural Waters" ed. S. J. Eisenreich
pp. 389-399, Ann Arbor Science Publishing., Ann Arbor, MI, USA.
Glooschenko, W. A. 1986. Monitoring the atmospheric deposition of
metals by use of bog vegetation and peat profiles, pp. 507-534 in:
" Toxic Metals in the Atmosphere" eds. J. R. Nriagu and C. I.
141

-------
Davidson. John Wiley and Sons, New York, New York.
Hale, M.E. 1979. How to know the lichens. Wm. C. Brown Co.,
Dubuque Iowa, USA. 246 pp.
Heidam, N. Z. 1986. Trace metals in the Arctic aerosol, pp 267-
293 in: "Toxic Metals in the Atmosphere" eds. J. R. Nriagu and C.
I. Davidson. John Wiley and Sons, New York, New York.
Husain, L. 1986. Chemical elements as tracers of polllutant
transport to a rural area. pp. 295-333 in: "Toxic Metals in the
Atmosphere" eds. J. R. Nriagu and C. I. Davidson. John Wiley and
Sons, New York, New York.
Isoviita, P. 1966. Studies on Sphagnum. I. Nomenclatural revision
of the European taxa. Annales Botanici Fennici 3: 199-264.
Lazrus, A.L., E. Lorange, and J. P. Lodge,Jr. 1970. Lead and
other metals in atmospheric precipitation. Environmental Science
and Technology 4: 55-58.
Munter, R. C., T. C. Halverson, and R. D. Anderson. 1984. Quality
assurance for plant tissue analysis. Communications in Soil
Science and Plant Analysis 15: 1285-1322.
Mason, B. 1966. Principles of Geochemistry. John Wiley and Sons,
New York, New York, USA.
Nieboer, E. and D. H. S. Richardson. 1981. Lichens as monitors
of atmospheric deposition, In : "Atmospheric Pollutants in Natural
Waters" ed. S. J. Eisenreich pp. 339-388, Ann Arbor Science Publ.,
Ann Arbor, MI, USA.
Pakarinen, P. 1981a. Nutrient and trace metal content and
retention in reindeer lichen carpets of Finnish ombrotrophic bogs.
Annales Botanici Fennici 18: 265-274.
Pakarinen, P. 1981b. Metal content of ombrotrophic Sphagnum mosses
in NW Europe. Annales Botanici Fennici 18: 281-292.
Pakarinen, P. 1982. On the trace element and nutrient ecology of
the ground layer species of ombrotrophic bogs. Publications from
the Department of Botany, University of Helsinki, 10: 1-32.
Pakarinen, P. 1983 and E. Gorham. Mineral element compositiion of
Sphagnum fuscum peats collected from Minnesota, Manitoba, and
Ontario. Proc. Int. Symposium on Peat Utilization(C.H. Fuchsman
and S. A. Spigarelli, eds.) pp 417-429. Bemidji, Minnesota, USA.
Pakarinen, P. 1985. Mineral element accumulation in bog lichens.
In: Lichen Physiology and Cell Biology, ed. D. H. Brown, pp. 185-
192. Plenum Press, NY.
142

-------
Puckett, K. J., and E. J. Finegan. 1980. An analysis of the
element content of lichens from the Northwest Territories, Canada.
Canadian Journal of Botany 58: 2073-2089.
Rahn, K. A. 1976. The chemical composition of the atmospheric
aerosol. Technical Report to the Graduate School of Oceanography,
University of Rhode Island. Kingston, Rhode Island, USA. 265 pp.
Ross, H. B. 1990. On the use of mosses (Hylocomium splendens and
Pieurozium schreberi) for estimating atmospheric trace metal
deposition. Water, Air, and Soil Pollution 50:63-76.
Ruhling, A., L. Rasmussen, K. Pilegaard, A. Makinen, E. Steinnes.
1987. Survey of atmospheric heavy metal deposition in the Nordic
countries in 1985- monitored by moss analyses. Report of the
Steering Body of Environmental Monitoring in the Nordic Countries,
Copenhagen, Denmark. 44 pp.
Santelmann, M. V., and E. Gorham. 1988. The influence of airborne
road dust on the chemistry of Sphagnum mosses. Journal of Ecology
76: 1219-1231.
Smath, J. A. and T.L. Potter. 1984. Trace metals and organic
compounds in precipitation at Greenville, Maine, USA. U.S.
Geological Survey Water-Resources Investigations, prepared in
cooperation with the Maine Department of Environmental Protection.
52 pp.
Snedecor, G. W. and W. G. Cochran. 1980. Statistical Methods.
7th ed. Iowa State University Press, Ames, Iowa, USA. 507 pp.
Thomson, J. W. 1984. American Arctic Lichens. Columbia University
Press. New York, N. Y. 504 pp.
Tolonen, K., R. B. Davis, L. Widoff. 1988. Peat accumulation
rates in selected Maine peat deposits. Bulletin 33, Maine
Geological Survey, Department of Conservation.
Tomassini, F. D., K. J. Puckett, E. Nieboer, D. H. Richardson, and
B. Grace. 1976. Determination of copper, iron, nickel, and
sulphur by X-ray fluorescence in lichens from the Mackenzie Valley,
Northwest Territories, and the Sudbury District, Ontario. Canadian
Journal of Botany 54: 1591-1603.
Urban, N. R., S. J. Eisenreich, D. F. Grigal , and K. T. Schurr.
1990. Mobility and diagenesis of Pb and Pb-210 in peat. Submitted
to Geochimica Cosmochimica Acta.
Zoller, W.H., E. S. Gladney, R. A. Duce. 1974. Atmospheric
concentrations and sources of metals at the South Pole. Science
183:198-200 .
143

-------