Skip to main content

Sanionia uncinata and Salix polaris as bioindicators of trace element pollution in the High Arctic: a case study at Longyearbyen, Spitsbergen, Norway

Abstract

Longyearbyen (Spitsbergen) is influenced by local contamination sources, such as exhausts from power plants, traffic, coal mines, and industrial waste dumps subject to weathering, which threatens soil and living organisms. Therefore, the trace element level in this area needs to be evaluated. The moss Sanionia uncinata and prostrate dwarf-shrub Salix polaris were collected as contamination indicators. Concentrations of Cd, Co, Cr, Cu, Fe, Hg, Mn, Ni, Pb, and Zn in these species were measured. The tested hypotheses were: in Longyearbyen and its vicinity (1) the moss S. uncinata and the willow S. polaris may be used as phytoaccumulators and therefore as bioindicators and bioremediators of certain trace elements; (2) the moss S. uncinata contains higher concentrations of metals than the willow S. polaris. The soil of Longyearbyen was contaminated with Cd, Co, Cu, Ni, Pb, and Zn. The willow S. polaris may be used in phytoaccumulation and therefore in the bioremediation and bioindication of Cd and Zn from its environment. Stems of S. polaris from Longyearbyen are better bioindicators of Cr, Cu, Hg, Ni, and Pb and poorer bioindicators of Cd, Mn, and Zn than leaves of this species. S. polaris (both stems and leaves) was a better bioindicator of Cd and Zn concentrations than green gametophytes of S. uncinata. S. uncinata was a better bioindicator of Co, Cr, Cu, Fe, Hg, Mn, Ni, and Pb than S. polaris.

Introduction

Longyearbyen is the largest town in Spitsbergen, the largest island of the Svalbard archipelago, with about 2200 inhabitants and additionally with tourists visiting this area (Reimann et al. 2009). Longyearbyen is located in the Arctic, an area recognized as low polluted, but with a certain number of contamination sources (Johansen and Tømmervik 2014). These are a coal and diesel fuel power plant and transportation, e.g., snowmobiles, passenger cars, and heavy duty vehicles (Reimann et al. 2009; Aamaas et al. 2011). Coal mining in the Longyearbyen area started in 1906 and seven mines were established. Since 1961 the mines had been consecutively shut down up to 1996. Nowadays only one, Gruve 7, is active (Piepjohn et al. 2012). Although other coal mines are no longer active, the remains of the mines and heaps of industrial waste accumulated for decades still exist. They are subjected to weathering (especially thawing) and leaching of acid solutions (acid mine drainage) with metals being a threat to soil and living organisms (Holm et al. 2003; Elberling et al. 2007; Askaer et al. 2008; García-Moyano et al. 2015). In addition, airborne sediments of coal particles may be a source of pollution over broad areas (Holte et al. 1996). As well as local contamination also long-range transport from lower latitudes may supply agents, such as metals, to Spitsbergen (Rose et al. 2004; Samecka-Cymerman et al. 2011; Kozak et al. 2015). This area is considered heavily affected by specific atmospheric circulation patterns bringing various xenobiotics from Europe’s industrialized areas, especially in winter (Birks et al. 2004). According to Kłos et al. (2017) also sea aerosol is a source of anthropogenic Cs-137, Pb-210, Th-231, Pb, and Hg which affect the soil and biota near Longyearbyen. The same authors proved elevated levels of Ni in moss, lichen, and vascular plant samples (Salix polaris Wahlenb. and Cassiope tetragona L.D.Don.) as a result of factors, such as coal mining around Longyearbyen (Kłos et al. 2017). The biotas in Svalbard are very sensitive to any harmful human influence because of low productivity and a small number of species (Poikolainen et al. 2004). Xenobiotics accumulate and biomagnify at each trophic level and even small amounts influence considerable parts of the ecosystems (Gulińska et al. 2003; Birks et al. 2004; Wilkie and La Farge 2011). Therefore, examination of metal levels in the Arctic environment is very important for the safety of these special ecosystems (Askaer et al. 2008; Kozak et al. 2015; Halbach et al. 2017). These elements are particularly dangerous being non-degradable and they may be distributed throughout the ecosystem for many years once discharged into the environment (Kabata-Pendias 2011). Mosses are one of the most widespread plants with respect to phytomass productivity, and they have a crucial role in the function of polar terrestrial ecosystems (Smith 1982; Douma et al. 2007; Gornall et al. 2007; Longton 2008). According to Douma et al. (2007) especially their role of a discriminatory blanket for nutrient speciation is very important. These plants are able to continue growth at low temperatures in areas where the growing season is short. Additionally, they stabilize soil and release elements from rocks so their decomposed litter contributes to pedogenesis and nutrient cycling. After glacier retreat mosses are important pioneers for primary succession. Some of them are able to fix atmospheric nitrogen thanks to cooperation with cyanobacteria (Martin and Mallik 2017). Mosses accumulate elevated levels of xenobiotics, and therefore, since 1968 (Rühling and Tyler 1968), they have been commonly used as ecological indicators all over Europe (Kosior et al. 2010; Kłos et al. 2015). These plants have a high surface-to-volume ratio and immense exchange capacities for cations due to the absence of a well-developed cuticle, which simplifies their accumulation of trace elements (Gerdol et al. 2000; Zechmeister et al. 2003).

The aim of this study was to investigate the level of Cd, Co, Cr, Cu, Fe, Hg, Mn, Ni, Pb, and Zn in the representative Arctic moss Sanionia uncinata (Hedw.) Loeske and for comparison in the willow S. polaris collected in Longyearbyen and its vicinity. S. uncinata has already been used as an ecological indicator of pollution in Spitsbergen and Antarctica (Grodzińska and Godzik 1991; Yogui and Seicano 2008; Samecka-Cymerman et al. 2011; Kłos et al. 2015, 2017). Furthermore, S. polaris was reported by Wojtuń et al. (2013) as a bioindicator of metals in the Svalbard environment. The tested hypotheses were: in Longyearbyen and vicinity: (1) moss S. uncinata and the willow S. polaris may be used as phytoaccumulators and therefore as bioindicators and bioremediators of certain trace elements; (2) S. uncinata contains higher concentrations of metals than S. polaris.

Materials and methods

Sampling design

The study site, Longyearbyen (78°13′N, 15°38′E), and the vicinity were investigated in July 2016. Fifty-two sites (numbered 1–52) were selected within the city and 15 sites (Nos 53–67) in the neighboring mining areas (Fig. 1). The following sampling sites were situated on slopes: sites 53 and 54 on the abandoned Nye Gruve I mine; sites 62–64 on an abandoned mine without an established name; and sites 57–59 and 61 on the abandoned Nye Gruve II mine. Thus, these sites were at a particular risk of runoff from coal waste. The investigated area was divided into 30 m × 30 m2 of which sampling squares were selected by random sampling (each possible square was numbered and then three of them were drawn by a random number generator). In each sampling square gametophytes (green parts) of S. uncinata and above-ground parts of S. polaris were collected from 10 m × 10 m2 in three replicates. Each plant sample comprised a mixture of three subsamples. Because the goal of this study was to evaluate the ability of both species to reflect trace element deposition, plant samples were not washed (Čeburnis and Steinnes 2000). Also Kozlov et al. (2000) and Oliva and Valdés (2004) recommend that leaf samples should not be washed for bioindication processes in industrially polluted sites. Litter, dead material, and soil particles were manually removed from the moss and the willow. Additionally, topsoil samples (about 1 kg in weight) from a depth of 0–10 cm were collected using a plastic hand shovel and plastic bags from the S. uncinata and S. polaris collection sites, in five replicates from each square. Stones and plant remains were removed from the soil. The number of collected samples was based on preliminary determination to obtain reliable analytical results. All of the investigated topsoil layers were mineral layers with an average total organic carbon (TOC) content of 6.91%. TOC content in the topsoil layers ranged from 1.38 to 36.36%. It should be noted that the highest TOC contents were always related to the high content of fine coal fragments in the topsoil layer, and they were not related to the organic character of the soil. Most of the investigated topsoil layers exhibited sandy loam or silt loam texture. In some cases, loamy or loamy fine sand texture was present. Most of the investigated topsoil layers were characterized by a high content of SiO2, Al2O3, and Fe2O3 as well as a low content of K2O, Na2O, CaO, MgO, and P2O5. The most common minerals in the investigated topsoil layers were quartz, K-feldspar, plagioclase, mica, and chlorite.

Fig. 1
figure1

Location of the sampling sites

Soil and plant analysis

The willow Salix polaris was divided into leaves and stems. Soil and plant samples were dried at 50 °C to constant weight. This temperature was low enough to prevent mercury loss (Lodenius et al. 2003). A preliminary experiment proved that mercury did not evaporate at this temperature. Soil samples were sifted through a Morek Multiserw LPzE-2e 2 mm sieve shaker and then homogenized with a Fritsch Pulverisette 2 mortar grinder. 300 mg of dry weight (in triplicate) of soil and plant samples was digested with 3 mL of ultra-pure (65%) nitric acid and 2 mL of ultra-pure (70%) perchloric acid in a microwave oven (CEM Mars 5). The digests were diluted to 50 mL with deionized water. In these soil and plant digests, Fe, Mn, and Zn concentrations were analyzed using FAAS (Avanta PM from GBC) and Cd, Co, Cr, Cu, Ni, and Pb using GFAAS (PinAAcle 900Z from Perkin-Elmer). The elements were controlled against Atomic Absorption Standard Solutions from Sigma Chemical Co. and blanks which contained the same matrix as the samples and were processed as samples. Mercury was detected directly in powdered solid and plant samples using an AMA 254 Advanced Mercury Analyser. Results of metal concentrations for soil and plants were calculated on a dry weight basis. The accuracy of the methods employed for the evaluation of metal concentrations in soil and plant samples was controlled against Certified Reference Materials: moss M2 and M3 (Finnish Forest Research Institute) and Steinnes et al. (1997), and Chestnut Soil, Bainaimao and Bayan Obo, Neil Mongol in China GBW07402 (GSS-2). Coefficients of variance (CV) established for the measured metal concentrations in the reference materials are listed as Online Resources 1 and 2.

Statistical analysis

One-way ANOVA, combined with Tuckey’s post-hoc test, was used to test for the statistical significance of differences between 67 sites in metal concentrations in soil, and moss S. uncinata and the willow S. polaris stems and leaves. T tests were employed to analyze the differences between two groups of pooled samples: leaves versus mosses and leaves versus stems. Pearson correlations were calculated between trace element concentrations in soil and S. polaris stems and leaves. Data were log-transformed to obtain normal distribution (Zar 1999). Shapiro–Wilk’s W test was used for normality control and the Brown-Forsythe test for the evaluation of the homogeneity of variances (Brown and Forsythe 1974; Argaç 2004).

The concentrations of Cd, Co, Cr, Cu, Fe, Hg, Mn, Ni, Pb, and Zn in S. uncinata and S. polaris leaves from 67 sites were ordered to reveal possible gradients of metal levels through principal component and classification analysis (PCCA). Plots of PCCA ordination of S. uncinata and S. polaris leaves and projection of the metal concentrations on the factor plane provide information about similarities between samples and show relations between the original variables and the first two factors (Legendre and Legendre 1998). Subsequently, samples were divided into a city group including 52 sites (1–52) and into a mine group including 15 sites (53–67) in the neighboring mining areas (Fig. 1). PCCA analysis was performed for the concentrations of Cd, Co, Cr, Cu, Fe, Hg, Mn, Ni, Pb, and Zn in S. uncinata from the city group. Mn was excluded as a supplementary variable having the lowest correlation with factor 1 and 2. An exceptional feature of PCCA is the possibility to determine active and supplementary variables. The active variables are applied to derive principal components. The supplementary variables can be projected onto the factor space calculated from the active cases and variables. Therefore, conclusions may be made concerning these variables, even though the supplementary variables are not included in the analysis (Zuur et al. 2007). Another PCCA for S. uncinata from 15 mining group sites was performed for the concentrations of Cd, Co, Cr, Cu, Fe, Hg, Mn, Ni, Pb, and Zn.

The bioaccumulation factor (BF) is an important tool for the evaluation of the phytoremediation potential of a species. When higher than one, it indicates the ability of a plant to accumulate trace elements from soil and transport them to aerial parts (Galal and Shehata 2015). Thus, the Stem Bioaccumulation Factor, SBF (stems-to-soil ratio), Leaves Bioaccumulation Factor, LBF (leaves-to-soil ratio), and stem to leaves transfer factor, TF (leaves-to-stems ratio), were calculated for concentrations of metals in the willow S. polaris.

For the statistical calculations Dell Inc. software version 13 (2015) was used.

The spatial distribution of metals in S. uncinata in the study area was estimated by ordinary kriging using an exponential variogram model (Walter et al. 2001). The sample size (neighborhood search) was set globally, and all 67 data points were used to interpolate each trace variable into a regular 10 m resolution grid. The predicted surfaces were, respectively, classified using defined interspacing with the geometric intervals method of classification (Martín et al. 2007; Zamani-Ahmadmahmoodi et al. 2014). Geostatistical analysis was carried out using Geostatistical Analyst extension for ArcGIS for Desktop 10.2.2 (ESRI 2016).

Results

The soils and plants differed significantly between the sites with regard to the concentrations of the metals assessed for soil (all p < 0.001): Cd (F66,268 = 3.4), Co (F66,268 = 2.6), Cr (F66,268 = 3.4), Cu (F66,268 = 3.5), Fe (F66,268 = 3.1), Hg (F66,268 = 5.3), Mn (F66,268 = 3.4), Ni (F66,268 = 2.8), Pb (F66,268 = 2.9), Zn (F66,268 = 3.7). S. uncinata Cd (F66,134 = 4.8), Co (F66,134 = 3.5), Cr (F66,134 = 2.6), Cu (F66,134 = 3.7), Fe (F66,134 = 3.1), Hg (F66,134 = 4.5), Mn (F66,134 = 5.3), Ni (F66,134 = 2.5), Pb (F66,134 = 4.9), Zn (F66,134 = 4.1). S. polaris stems Cd (F66,134 = 5.8), Co (F66,134 = 20.4), Cr (F66,134 = 28.1), Cu (F66,134 = 23.5), Fe (F66,134 = 12.8), Hg (F66,134 = 8.9), Mn (F66,134 = 11.3), Ni (F66,134 = 6.1), Pb (F66,134 = 15.1), Zn (F66,134 = 15.9) and leaves Cd (F66,134 = 13.8), Co (F66,134 = 17.3), Cr (F66,134=13.9), Cu (F66,134 = 11.7), Fe (F66,134 = 27.4), Hg (F66,134 = 9.1), Mn (F66,134 = 13.1), Ni (F66,134 = 9.3), Pb (F66,134 = 10.1), Zn (F66,134 = 21.9). The concentrations of elements in soils were higher than those reported by Wojtuń et al. (2013) for Cd, Cu, Fe, Mn, Pb, Zn collected in Svalbard within up to a 3-km radius of the Polish Polar Station (77°00ʹN; 15°33ʹE) (Table 1). Maximum Cd, Co, Cu, Ni, Pb, and Zn concentrations were even higher than the admissible limits for soils in Poland (MŚ 2002), while those of Cr, Cu, Ni, Pb, and Zn were higher than the background values in Norwegian soils (Vik et al. 1999) (Table 1). The maximum concentration of Hg was higher than the average of unpolluted soil ( < 0.2 mg kg−1) Martín and Nanos (2016). Maximum concentrations of Cd, Co, Cr, Cu, Mn, Ni, and Zn in S. uncinata in this investigation (Table 2) were higher than those in the same species investigated in the southern part of Spitsbergen on Wedel Jarlsberg Land (Table 3) by Samecka-Cymerman et al. (2011) and Wojtuń et al. (2013). Comparable concentrations of Fe and Hg and lower concentration of Pb (Table 3) in S. uncinata in this investigation in comparison with S. uncinata reported by Samecka-Cymerman et al. (2011) and Wojtuń et al. (2013) were established. These concentrations in S. uncinata from Longyearbyen were also higher than in the same species from the Bellsund area reported as mean values (Table 3) investigated in 1987–1995 (Jóźwik 2000). Metal concentrations in stems and leaves of S. polaris in this investigation were also higher than in S. polaris examined by Wojtuń et al. (2013) in the less polluted southern part of Spitsbergen in the vicinity of the Polish Polar Station (Table 3). The maximum concentration of Cd in the willow S. polaris leaves and of Zn in S. polaris stems and leaves exceeded the toxicity threshold (mg kg−1) of > 5 and > 100, respectively, for the protection of food chains in ecosystems (Kabata-Pendias 2011). In addition, Bioaccumulation Factors (BFs, Table 4) calculated for S. polaris from soil to stems (SBF) and from soil to leaves (LBF) were the highest for Cd and Zn (higher than one) compared to the other metals. In addition, the t test revealed that S. polaris contained significantly higher concentrations of Cd (t132 = − 12.4, p < 0.001) and Zn (t132 = − 17.9, p < 0.001) in leaves than green parts of S. uncinata gametophytes. The concentration of all the other examined elements was significantly higher in the moss. The same pattern was observed for stems of S. polaris (Cd t132 = − 15.6, p < 0.001 and Zn t132 = − 17.5, p < 0.001) in comparison with green parts of moss gametophytes. T test (all p < 0.001) revealed that S. polaris leaves contained significantly lower concentrations of Cr (t132 = 12.6), Cu (t132 = 78.9), Ni (t132 = 3.2) and Pb (t132 = 6.7) than stems. The Translocation factor (TF) for S. polaris from stems to leaves was > 1 in the order of Mn > Co > Zn > Cd (Table 4).

Table 1 Minimum, maximum, median, and median average deviation (MAD) of the concentration (mg kg−1 dry weight) of metals in the soils of the investigated area (n = 335)
Table 2 Minimum, maximum, median, and median average deviation (MAD) of the concentration (mg kg−1 dry weight) of metals in Sanionia uncinata and Salix polaris stems and leaves (n = 201); significance level (p) for the t test for comparison of S. uncinata (S) and S. polaris stems (SSs), S. uncinata and S. polaris leaves (SSl) as well as S. polaris stems and S. polaris leaves (SsSl)
Table 3 Concentrations of metals (mg kg−1) in Sanionia uncinata from Svalbard established by Jóźwik (2000), Samecka-Cymerman et al. (2011), Wojtuń et al. (2013) as well as in stems and leaves of Salix polaris from Svalbard established by Wojtuń et al. (2013) and Krajcarová et al. (2016)
Table 4 Minimum, maximum, and median of the Stem Bioaccumulation Factor (SBF, stem-to-soil ratio), Leaf Bioaccumulation Factor (LBF, leaves-to-soil ratio), Transfer Factor (TF, leaves-to-stems ratio) of metals in Salix polaris

Discussion

Elevated metal levels in soils in Longyearbyen may point to the influence of local sources of pollution (Rose et al. 2004; Martín and Nanos 2016). These may be snow with carbon dust from a stockpile and power plant containing Hg in the amount 200-fold higher than the background as this element together with Cu, Zn, Pb, Mn, Cr, Ni, Cd, As are important constituents of coal and coal combustion products (Aamaas et al. 2011; Burmistrz and Kogut 2016; Shangguan et al. 2016). Elevated metal levels in S. uncinata may indicate that in Svalbard, not only local but also long-range airborne transport from lower latitudes may contribute to contamination (Rose et al. 2004; Samecka-Cymerman et al. 2011; Kozak et al. 2015). The highest levels of contaminants from coal combustion in sites near Longyearbyen may demonstrate that even low-level industry can be a significant source of pollution in such a vulnerable area with low deposition (Rose et al. 2004). The higher concentration of Pb in S. uncinata from the vicinity of the Polish Polar Station than in S. uncinata collected in Longyearbyen may be explained by the fact that this station is heated by oil burning and additionally equipped with a waste incinerator. Unleaded gasoline and diesel fuel contain certain quantities of Pb as crude oil is geogenically contaminated with lead (Kummer et al. 2009). The significantly higher concentrations of Cd and Zn in S. polaris leaves and stems than in the green parts of S. uncinata gametophytes may indicate that S. polaris is a good accumulator of Cd and Zn and a better bioindicator of the concentration of both elements in the environment in comparison with the moss species. Similar results of Cd in concentrations higher than the average values and Zn in concentrations exceeding the physiological needs for S. polaris in Longyearbyen and Barentsburg are reported by Jóźwik (2000) and Wojtuń et al. (2013). This resistance to elevated Cd levels may be caused by the apoplastic detoxification ability of Salix sp. for this metal (Harada et al. 2011). S. polaris leaves contained significantly lower concentrations of Cr, Cu, Hg, Ni, and Pb than stems. This may be explained by the fact that leaves are shed for winter and thus stems may indicate longer-term air pollution effects (Harju et al. 2002). However, atmospheric deposition or soil surface dust is more easily washed out from the leaf surface than from the outer bark surface. On the other hand, some trace elements show higher uptake in tree leaves than deposition, resulting in negative throughfall fluxes (Avila and Rodrigo 2004; Samecka-Cymerman et al. 2011). Furthermore, bark is a better pollution indicator than leaves due to longer exposure time (Reimann et al. 2007). Significantly higher Cd (t266 = − 6.4, p < 0.001), Mn (t266 = − 10.6, p < 0.001) and Zn (t266 = − 25.4, p < 0.001) concentrations in leaves than in stems are in agreement with Vandecasteele et al. (2005) who report that willows translocate Mn and Zn mainly to leaves. These authors also found higher Cd concentrations in leaves than in stems of this species (Vandecasteele et al. 2005). These results indicate that stems of S. polaris from Longyearbyen are a better bioindicator of Cr, Cu, Hg, Ni, and Pb and poorer bioindicators of Cd, Mn, and Zn than leaves.

S. polaris Bioaccumulation Factors (SBF and LBF, Table 4) are the highest for Cd and Zn compared to the other metals, which may indicate that both elements were most heavily accumulated by this species. Therefore, S. polaris could be used in the bioremediation of Cd and Zn toxicants from the environment, especially that this species accumulated Zn in leaves and stems proportionally to its concentration in soil with positive significant correlation (p < 0.01). Kabata-Pendias (2011) considers Cd as a metal which shows preferential accumulation by terrestrial plants with a BF of 10. The maximum values of this factor for Cd were much higher in S. polaris in this investigation: 55 in stems and 60 in leaves (Table 4). Kabata-Pendias (2011) shows Zn to undergo medium intensive accumulation in terrestrial plants with a BF of 0.6–0.8. The maximum values of this factor for Zn were also much higher in S. polaris from this investigation: 6.2 and 8.6 (Table 4). Unfortunately there are no data presenting Bioaccumulation Factors for Zn in the willow S. polaris from Arctic areas. Polygonum thunbergii from the industrial area of Korea (Kim et al. 2003) exhibits a higher BF for Zn: 28 as compared to S. polaris. The Translocation Factor (TF) from S. polaris was the highest for Mn, which indicates internal element transport where Mn seems to be the most effectively transported element from shoots to leaves. This is in agreement with Olivares et al. (2009) that Mn as an essential nutrient is actively transported to photosynthetic tissues. The lowest TF for Pb in S. polaris (Table 3) was probably caused by the fact that Pb as a toxic and non-essential metal exhibits low translocation within plants (Sultan 2000; Sharma and Dubey 2005).

PCCA ordination calculated for metal concentrations in moss S. uncinata and leaves of the willow S. polaris from 67 sites is presented in Fig. 2. The 1st principal component discriminates between polar willows (positive scores) and mosses (negative scores). The 2nd component is related (negative scores) to S. uncinata in site 10. Projection of the variables on the factor plane (Fig. 2) indicates that S. polaris was correlated with the highest concentrations of Cd and Zn in its tissues. Sanionia uncinata was correlated with the highest concentrations of Co, Cr, Cu, Fe, Hg, Ni, and Pb in its tissues. Sanionia uncinata from site 10 was correlated with the highest concentration of Mn. This site was situated within heath vegetation but in a close vicinity of wetland vegetation occupied by birds, mostly those feeding at sea. The highest amounts of Mn (compared to other metals) are transported by contaminated rivers to seas and oceans (Kabata-Pendias 2011). Seabirds are a crucial factor influencing the concentration of elements in the arctic soils (Ziółek et al. 2017). Birds which forage in the ocean accumulate metals, released via droppings on land and thus concentrating pollution to amounts that can be significant in the coastal ecosystem (Liu et al. 2006). Ziółek et al. (2017) found increased concentrations of Mn as well as Cu, Cd, and Zn in soils influenced by seabird colonies. In addition, Samecka-Cymerman et al. (2011) report the highest concentration of Mn in S. uncinata from sites closest to the shoreline and thus most influenced by sea spray as well as from sites influenced by birds. Because of their high position in the nutritional chain, seabirds concentrate high levels of trace elements in their tissues (Lucia et al. 2016).

Fig. 2
figure2

Ordination plot based on the concentrations of Cd, Co, Cr, Cu, Fe, Hg, Mn, Ni, Pb, and Zn in Sanionia uncinata and Salix polaris leaves and projection of element concentrations on the component plane; full triangles S. uncinata, full diamonds S. polaris, empty triangle S. uncinata in site 10

Ordination by PCCA calculated for 52 sites (Nos 1–52) of S. uncinata from Longyearbyen (Online Resource 3) shows that the first principal component discriminates mosses from sampling sites situated in the vicinity of streets, and vehicle and snowmobile parking places, e.g., 6, 9–11, 17–19, 29 (negative scores). Sanionia uncinata from sites closest to the power plant (sites 1–3) and in the vicinity of an abandoned station of the conveyor for coal transportation (sites 15, 20–21), all growing in soil covered with coal dust, show positive scores of the second principal component. Projection of the variables on the factor plane indicated that factor 1 was negatively related to Co, Cr, Cu, Fe, Ni, and Pb while factor 2 was positively related to Cd, Hg, and Zn. Similar distribution of metals may be observed on isoline plots presented in Online Resource 4 for metal concentrations (mg kg−1) measured in S. uncinata collected in Longyearbyen. Co, Cr, Cu, Fe, Ni, and Pb converge and form hotspots corresponding to the location of sites 6, 9–11, 17–19, 29, while Cd, Hg, and Zn converge and form hotspots corresponding to the location of sites 1–3 and sites 15, 20–21. It is difficult to explain the causes of distribution of this element in the examined bioindicators and, from a heuristic point of view, it is speculative. There are no data available concerning the element contents in emissions, concentration gradient analyses, isotopic ratio comparison, etc. These are all metals produced by transportation both by fuel exhausts and by abrasion in all types of vehicle parts (Kummer et al. 2009). However, coal mine residues as well as coal burning may be a significant source of Cd, Hg, and Zn (Askaer et al. 2008). For instance, elevated Hg levels of up to 1.5 mg kg−1 were found in coal waste deposited in the Nye Gruve I area. Ordination by PCCA calculated for 15 sites (Nos 53–67) of S. uncinata from the mine areas presented in Online Resource 5 shows that the first principal component discriminates mosses from sampling sites 53 and 54 (negative scores) situated on the slope of the abandoned Nye Gruve I mine. The second principal component discriminates S. uncinata from sites 62–64 (positive scores) also situated on the slope from the unnamed abandoned mine and S. uncinata from sites 57–59, 61 of the Nye Gruve II mine (negative scores). Projection of the variables on the factor plane indicated that S. uncinata collected from the Nye Gruve I mine was correlated with the highest concentrations of Co, Cr, Fe, Mn, Ni, and Pb in their tissues. Sanionia uncinata in sites 62–64 was correlated with the highest concentration of Cd and Zn. Mosses from sampling sites of the Nye Gruve II mine were positively correlated with the highest concentration of Hg in their tissues. Similar distribution of metals may be observed on isoline plots presented in Online Resource 5 for metal concentrations (mg kg−1) measured in S. uncinata collected in these mine areas. Co, Cr, Fe, Mn, Ni, and Pb converge and form hotspots corresponding to the location of sites 53 and 54, while Cd and Zn converge and form hotspots corresponding to the location of sites 62–64 and mercury converges and forms hotspots corresponding to the location of sites 57–59, 61. Elevated levels of these metals in mosses collected on the slopes of the mines may be explained by the fact that Fe, Mn and Ni are the most abundant constituents of runoff from coal waste at Svalbard (Sřndergaard et al. 2007). Furthermore, various sulfide minerals in the waste material of pyrite ore may be the source of Cd, Pb, and Zn (Sřndergaard et al. 2007). The results are in agreement with Askaer et al. (2008) that many of such mine waste dumps are hazardous to the environment and need permanent investigation.

Conclusions

The present investigation reveals local pollution affecting metal levels in common plant species used as bioindicators in part of Spitsbergen. This type of study helps to understand the biogeochemical processes of human-induced contamination and to protect unique places in this part of the Arctic.

The willow S. polaris may be used in phytoaccumulation and therefore in the bioremediation and bioindication of Cd and Zn from its environment.

Stems of S. polaris from Longyearbyen are better bioindicators of Cr, Cu, Hg, Ni, and Pb and poorer bioindicators of Cd, Mn, and Zn than leaves of this species.

S. polaris (both stems and leaves) was a better bioindicator of Cd and Zn concentrations than green gametophytes of S. uncinata.

S. uncinata was a better bioindicator of Co, Cr, Cu, Fe, Hg, Mn, Ni, and Pb than S. polaris.

References

  1. Aamaas B, Bøggild CE, Stordal F, Berntsen T, Holmén K, Ström J (2011) Elemental carbon deposition to Svalbard snow from Norwegian settlements and long-range transport. Tellus 63B:340–351

    Article  CAS  Google Scholar 

  2. Argaç D (2004) Testing for homogeneity in a general one-way classification with fixed effects: power simulations and comparative study. Comput Stat Data An 44:603–612

    Article  Google Scholar 

  3. Askaer L, Schmidt LB, Elberling B, Asmund G, Jónsdóttir IS (2008) Environmental impact on an Arctic soil-plant system resulting from metals released from coal mine waste in Svalbard (78° N). Water Air Soil Pollut 195:99–114

    Article  CAS  Google Scholar 

  4. Avila A, Rodrigo A (2004) Trace metal fluxes in bulk deposition, throughfall and stemflow at two evergreen oak stands in NE Spain subject to different exposure to the industrial environment. Atmos Environ 38:171–180

    Article  CAS  Google Scholar 

  5. Birks HJB, Jones VJ, Rose NL (2004) Recent environmental change and atmospheric contamination on Svalbard as recorded in lake sediments - an introduction. J Paleolimnol 31:403–410

    Article  Google Scholar 

  6. Brown MB, Forsythe AB (1974) Robust tests for the equality of variances. J Am Stat Assoc 69:364–367

    Article  Google Scholar 

  7. Burmistrz P, Kogut K (2016) Rtęć w węglach kamiennych spalanych w polskich elektrowniach i elektrociepłowniach [Mercury in bituminous coal used in polish power plants]. Arch Min Sci 61:473–488 [Engl sum]

  8. Čeburnis D, Steinnes E (2000) Conifer needles as biomonitors of atmospheric heavy metal deposition: comparison with mosses and precipitation role of the canopy. Atmos Environ 34:4265–4271

    Article  Google Scholar 

  9. Dell Inc. (2015) Dell Statistica (data analysis software system), version 13. software.dell.com

  10. Douma JC, van Wijk MT, Lang SI, Shaver GR (2007) The contribution of mosses to the carbon and water exchange of arctic ecosystems: quantification and relationships with system properties. Plant Cell Environ 30:1205–1215

    Article  CAS  PubMed  Google Scholar 

  11. Elberling B, Søndergaard J, Jensen LA, Schmidt LB, Hanse BU, Asmund G, Balić-Zunić T, Hollesen J, Hanson S, Jansson PE, Friborg T (2007) Arctic vegetation damage by winter-generated coal mining pollution released upon thawing. Environ Sci Technol 41:2407–2413

    Article  CAS  PubMed  Google Scholar 

  12. ESRI (2016) ArcGIS 10.4.1 for Desktop. ArcGIS Resource Center, Redlands, CA, USA 〈https://www.esri.com/en-us/home〉. 〈https://help.arcgis.com/en/arcgisdesktop/ 10.0/help/〉

  13. Galal TM, Shehata HS (2015) Bioaccumulation and translocation of heavy metals by Plantago major L. grown in contaminated soils under the effect of traffic pollution. Ecol Indic 48:244–251

    Article  CAS  Google Scholar 

  14. García-Moyano A, Austnes AE, Lanzén A, González-Toril E, Aguilera Á, Øvreås L (2015) Novel and unexpected microbial diversity in acid mine drainage in Svalbard (78° N), revealed by culture-independent approaches. Microorganisms 3:667–694

    Article  PubMed Central  PubMed  Google Scholar 

  15. Gerdol R, Bragazza L, Marchesini R, Alber R, Bonetti L, Lorenzoni G, Achilli M, Buffoni A, De Marco N, Franchi M, Pison S, Giaquinta S, Palmieri F, Spezzanto P (2000) Monitoring of heavy metal deposition in Northern Italy by moss analysis. Environ Pollut 108:201–208

    Article  CAS  PubMed  Google Scholar 

  16. Gornall JL, Jónsdóttir JS, Woodin SJ, Van der Wal R (2007) Arctic mosses govern below-ground environment and ecosystem processes. Oecologia 153:931–941

    Article  CAS  Google Scholar 

  17. Grodzińska K, Godzik B (1991) Heavy metals and sulphur in mosses from Southern Spitsbergen. Polar Res 9:133–140

    Article  Google Scholar 

  18. Gulińska J, Rachlewicz G, Szczuciński W, Barałkiewicz D, Kózka M, Bulska E, Burzyk M (2003) Soil contamination in High Arctic areas of human impact, Central Spitsbergen, Svalbard. Pol J Environ Stud 12:701–707

    Google Scholar 

  19. Halbach K, Mikkelsen O, Berg T, Steinnes E (2017) The presence of mercury and other trace metals in surface soils in the Norwegian Arctic. Chemosphere 188:567–574

    Article  CAS  PubMed  Google Scholar 

  20. Harada E, Hokura A, Nakai I, Terada Y, Baba K, Yazaki K, Shiono M, Mizunog N, Mizunoh T (2011) Assessment of willow (Salix sp.) as a woody heavy metal accumulator: field survey and in vivo X-ray analyses. Metallomics 3:1340–1346

    Article  CAS  PubMed  Google Scholar 

  21. Harju L, Saarela KE, Rajander J, Lil JO, Lindroos A, Heselius SJ (2002) Environmental monitoring of trace elements in bark of Scots pine by thick-target PIXE. Nucl Instrum Meth B 189:163–167

    Article  CAS  Google Scholar 

  22. Holm EB, Brandvik PJ, Steinnes E (2003) Pollution in acid mine drainage from mine tailings in Svalbard, Norwegian. Arctic J Phys IV France 107:625–628

    Article  CAS  Google Scholar 

  23. Holte B, Dahle S, Gulliksen B, Næs K (1996) Some macrofaunal effects of local pollution and glacier-induced sedimentation, with indicative chemical analyses, in the sediments of two Arctic fjords. Polar Biol 16:549–557

    Article  Google Scholar 

  24. Johansen B, Tømmervik H (2014) The relationship between phytomass, NDVI and vegetation communities on Svalbard. Int J Appl Earth Ob Geoinform 27:20–30

    Article  Google Scholar 

  25. Jóźwik Z (2000) Heavy metals in tundra plants of the Bellsund in West Spitsbergen, investigated in the years 1987–1995. Pol Polar Res 21:43–54

    Google Scholar 

  26. Kabata-Pendias A (2011) Trace elements in soils and plants. CRC Press, Boca Raton

    Google Scholar 

  27. Kim S, Kang KH, Johnson-Green P, Lee EJ (2003) Investigation of heavy metal accumulation in Polygonum thunbergii for phytoextraction. Environ Pollut 126:235–243

    Article  CAS  PubMed  Google Scholar 

  28. Kłos A, Bochenek Z, Bjerke JW, Zagajewski B, Ziółkowski D, Ziembik Z, Rajfur M, Dołhańczuk-Śródka A, Tømmervik H, Krems P, Jerz D, Zielińska M (2015) The use of mosses in biomonitoring of selected areas in Poland and Spitsbergen in the years from 1975 to 2014. Ecol Chem Eng S 22:201–218

    Google Scholar 

  29. Kłos A, Ziembik Z, Rajfur M, Dołhańczuk-Śródka A, Bochenek Z, Bjerke JW, Tømmervik H, Zagajewski B, Ziółkowski D, Jerz D, Zielińska M, Krems P, Godyń P (2017) The origin of heavy metals and radionuclides accumulated in the soil and biota samples collected in Svalbard, near Longyearbyen. Ecol Chem Eng S 24:223–238

    Google Scholar 

  30. Kosior G, Samecka-Cymerman A, Kolon K, Kempers AJ (2010) Bioindication capacity of metal pollution of native and transplanted Pleurozium schreberi under various levels of pollution. Chemosphere 81:321–326

    Article  CAS  PubMed  Google Scholar 

  31. Kozak K, Kozioł K, Luks B, Chmiel S, Ruman M, Marć M, Namieśnik J, Polkowska Ż (2015) The role of atmospheric precipitation in introducing contaminants to the surface waters of the Fuglebekken catchment Spitsbergen. Polar Res 34(1–10):24207. https://doi.org/10.3402/polar.v34.24207

    Article  CAS  Google Scholar 

  32. Kozlov MV, Haukioja E, Bakhtiarov AV, Stroganov DN, Zimna SN (2000) Root versus canopy uptake of heavy metals by birch in an industrial polluted area: contrasting behaviour of nickel and copper. Environ Pollut 107:413–420

    Article  CAS  PubMed  Google Scholar 

  33. Krajcarová L, Novotný K, Chattová B, Elster J (2016) Elemental analysis of soils and Salix polaris in the town of Pyramiden and its surroundings (Svalbard). Environ Sci Pollut Res 23:10124–10137

    Article  CAS  Google Scholar 

  34. Kummer U, Pacyna J, Pacyna E, Friedrich R (2009) Assessment of heavy metal releases from the use phase of road transport in Europe. Atmos Environ 43:640–647

    Article  CAS  Google Scholar 

  35. Legendre P, Legendre L (1998) Numerical ecology. In: Developments in Environmental Modelling, 2nd English edn. Elsevier, Amsterdam

    Google Scholar 

  36. Liu X, Zhao S, Sun L, Yin X, Xie Z, Honghao L, Wang Y (2006) P and trace metal contents in biomaterials, soils, sediments and plants in colony of red-footed booby (Sula sula) in the Dongdao Island of South China Sea. Chemosphere 65:707–715

    Article  CAS  PubMed  Google Scholar 

  37. Lodenius M, Tulisalo E, Soltanpour-Gargari A (2003) Exchange of mercury between atmosphere and vegetation under contaminated conditions. Sci Total Environ 304:169–174

    Article  CAS  PubMed  Google Scholar 

  38. Longton RE (2008) The biology of polar bryophytes and lichens. Cambridge University Press, Cambridge

    Google Scholar 

  39. Lucia M, Strøm H, Bustamante P, Herzke D, Gabrielsen GW (2016) Contamination of ivory gulls (Pagophila eburnea) at four colonies in Svalbard in relation to their trophic behaviour. Polar Biol 40:917–930

    Article  Google Scholar 

  40. Martín JAR, Nanos N (2016) Soil as an archive of coal-fired power plant mercury deposition. J Hazard Mater 308:131–138

    Article  CAS  Google Scholar 

  41. Martín JAR, de la Cueva AV, Corbí JMG, Arias ML (2007) Factors controlling the spatial variability of copper in topsoils of the northeastern region of the Iberian Peninsula, Spain. Water Air Soil Poll 186:311–321

    Article  CAS  Google Scholar 

  42. Martin PS, Mallik AU (2017) The status of non-vascular plants in trait-based ecosystem function studies. Perspect Plant Ecol Evol Syst 27:1–8

    Article  Google Scholar 

  43. MŚ (2002) Rozporządzenie Ministra Środowiska z dnia 9 września 2002 r w sprawie standardów jakości gleby oraz standardów jakości ziemi, (Dz. U. Nr 165, poz. 1359) [Regulations of the Ministry of Environment from 9 September 2002 concerning standards of soil quality (Journal of Laws No. 165 item 1359)]

  44. Oliva SR, Valdés B (2004) Influence of washing on metal concentration in leaf tissue. Commun Soil Sci Plant Anal 35:1543–1552

    Article  CAS  Google Scholar 

  45. Olivares E, Penã E, Marcano E, Mostacero J, Aguiar G, Benítez M, Rengifo E (2009) Aluminum accumulation and its relationship with mineral plant nutrients in 12 pteridophytes from Venezuela. Environ Exp Bot 65:132–141

    Article  CAS  Google Scholar 

  46. Piepjohn K, Stange R, Jochmann M, Hübner Ch (2012) The geology of Longyearbyen. Longyearbyen feltbiologiske forening, Longyearbyen

    Google Scholar 

  47. Poikolainen J, Kubin E, Piispanen J, Karhu J (2004) Estimation of the long-range transport of mercury, cadmium, and lead to Northern Finland on the basis of moss surveys. Arct Antarct Alp Res 36:292–297

    Article  Google Scholar 

  48. Reimann C, Arnoldussen A, Finne TE, Koller F, Nordgulen O, Englmaler P (2007) Element contents in mountain birch leaves, bark and wood under different anthropogenic and geogenic conditions. Appl Geochem 22:1549–1566

    Article  CAS  Google Scholar 

  49. Reimann S, Kallenborn R, Schmidbauer N (2009) Severe aromatic hydrocarbon pollution in the arctic town of Longyearbyen (Svalbard) caused by snowmobile emissions. Environ Sci Technol 43:4791–4795

    Article  CAS  PubMed  Google Scholar 

  50. Rose NL, Rose CL, Boyle JF, Appleby PG (2004) Lake-sediment evidence for local and remote sources of atmospherically deposited pollutants on Svalbard. J Paleolimnol 31:499–513

    Article  Google Scholar 

  51. Rühling A, Tyler G (1968) An ecological approach to the lead problem. Bot Not 121:321–342

    Google Scholar 

  52. Samecka-Cymerman A, Wojtuń B, Kolon K, Kempers AJ (2011) Sanionia uncinata (Hedw.) Loeske as bioindicator of metal pollution in polar regions. Polar Biol 34:381–388

    Article  Google Scholar 

  53. Shangguan Y, Wei Y, Wang L, Hou H (2016) Sources and distribution of trace elements in soils near coal-related industries. Arch Environ Contam Toxicol 70:439–451

    Article  CAS  PubMed  Google Scholar 

  54. Sharma P, Dubey RS (2005) Lead toxicity in plants. Braz J Plant Physiol 17:35–52

    Article  CAS  Google Scholar 

  55. Smith AJE (ed) (1982) Bryophyte ecology. Chapman and Hall Ltd., New York

    Google Scholar 

  56. Sřndergaard J, Elberling B, Asmund G, Gudum C, Iversen KM (2007) Temporal trends of dissolved weathering products released from a High Arctic coal mine waste rock pile in Svalbard (78oN). Appl Geochem 22:1025–1038

    Article  CAS  Google Scholar 

  57. Steinnes E, Rühling Å, Lippo H, Mäkinen A (1997) Reference materials for large-scale metal deposition surveys. Accredit Qual Assur 2:243–249

    Article  CAS  Google Scholar 

  58. Sultan SE (2000) Phenotypic plasticity for plant development, function and life history. Trends Plant Sci 5:537–542

    Article  CAS  PubMed  Google Scholar 

  59. Vandecasteele B, Meers E, Vervaeke P, De Vos B, Quataert P, Tack FMG (2005) Growth and trace metal accumulation of two Salix clones on sediment-derived soils with increasing contamination levels. Chemosphere 58:995–1002

    Article  CAS  PubMed  Google Scholar 

  60. Vik EA, Breedveld GD, Farestveit T (1999) Guidelines for the risk assessment of contaminated sites. SFT report: TA-1691/1999. Norwegian Pollution Control Authority, Oslo

  61. Walter Ch, McBratney AB, Douaoui A, Minasny B (2001) Spatial prediction of topsoil salinity in the Chelif Valley, Algeria, using local ordinary kriging with local variograms versus whole-area variogram. Aust J Soil Res 39:259–272

    Article  Google Scholar 

  62. Wilkie D, La Farge C (2011) Bryophytes as heavy metal biomonitors in the Canadian High Arctic. Arct Antarct Alp Res 43:289–300

    Article  Google Scholar 

  63. Wojtuń B, Samecka-Cymerman A, Kolon K, Kempers AJ, Skrzypek G (2013) Metals in some dominating vascular plants, mosses, lichens, algae and biological soil crust in various types of terrestrial tundra, SW Spitsbergen. Polar Biol 36:1799–1809

    Article  Google Scholar 

  64. Yogui JGT, Sericano L (2008) Polybrominated diphenyl ether flame retardants in lichens and mosses from King George Island, maritime Antarctica. Chemosphere 73:1589–1593

    Article  CAS  PubMed  Google Scholar 

  65. Zamani-Ahmadmahmoodi R, Bakhtiari AR, Rodríguez Martín JA (2014) Spatial relations of mercury contents in Pike (Esox lucius) and sediments concentration of the Anzali wetland, along the southern shores of the Caspian Sea Iran. Mar Pollut Bull 84:97–103

    Article  CAS  PubMed  Google Scholar 

  66. Zar H (1999) Biostatistical analysis. Prentice Hall, Upper Saddle River

    Google Scholar 

  67. Zechmeister HG, Hohenwallner D, Riss A, Hanus-Illnar A (2003) Variations in heavy metal concentrations in the moss species Abietinella abietina (Hedw.) Fleisch. According to sampling time, within site variability and increase in biomass. Sci Total Environ 301:55–65

    Article  CAS  PubMed  Google Scholar 

  68. Ziółek M, Bartmiński P, Stach A (2017) The influence of seabirds on the concentration of selected heavy metals in organic soil on the Bellsund coast, western Spitsbergen. Arct Antarct Alp Res 49:507–520

    Article  Google Scholar 

  69. Zuur A, Ieno EN, Smith GM (2007) Analysing ecological data. Springer Science, Business Media LLC

    Book  Google Scholar 

Download references

Acknowledgements

This research was supported by the University of Wrocław (1072/S/KEBOS/2017). According to the Act of 15 June 2001 No. 79 relating to the Protection of the Environment in Svalbard (the Svalbard Environmental Protection Act) the scientific activity as described did not require special permission. We thank Andrzej Leszek Rudecki and Teresa Łysiak for their assistance with chemical analyses.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Aleksandra Samecka-Cymerman.

Ethics declarations

Conflict of interest

The authors declare no conflict of interest.

Research involving human and animal rights

This article does not contain any studies with human participants or animals performed by any of the authors.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Wojtuń, B., Polechońska, L., Pech, P. et al. Sanionia uncinata and Salix polaris as bioindicators of trace element pollution in the High Arctic: a case study at Longyearbyen, Spitsbergen, Norway. Polar Biol 42, 1287–1297 (2019). https://doi.org/10.1007/s00300-019-02517-0

Download citation

Keywords

  • Moss
  • Arctic tundra
  • Coal mine
  • Bioaccumulation factor
  • Transfer factor