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. 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