Atmospheric metal deposition has become a major environmental problem in China due to its adverse effects on human and ecosystem health[@b1][@b2]. This is particularly true in Inner Mongolia, where frequent dust storms (due to steppe degradation and desertification) and air pollution (associated with the increasing urbanization and industrialization) have occurred in recent decades. However, there are insufficient data to fully evaluate this problem in the region. Although air pollution monitoring systems based on traditional (instrumental) methods have been established in Inner Mongolia, these methods have a low sampling density in space and only monitor a limited number of pollutants (mainly CO, SO~X~, NO~X~ and dust). Studies on the atmospheric deposition of elements in Inner Mongolia have mainly focused on nitrogen[@b3][@b4].

Lichens can be a complement, or to a lesser extent, an alternative to the traditional methods of studying atmospheric deposition from anthropogenic or natural sources and have been widely used outside of China in the past few decades[@b5][@b6]. These organisms are highly dependent on atmospheric deposition for mineral nutrients and have the extraordinary capability of accumulating metals far above their need. These features of lichens, combined with their widespread distribution and long lifespan, rank them among the best bioindicators and biomonitors of air pollution[@b5][@b6]. Although lichens are widespread in the diverse ecosystems of Inner Mongolia, they have not been applied to air quality assessment in the region.

Two questions are prerequisite to the assessment of air quality in Inner Mongolia using lichens. (1) Can lichens distinguish anthropogenic contribution from dust storm inputs? This question has rarely been addressed because most relevant studies have been performed in industrial/urban or remote sites without dust storms[@b7][@b8][@b9][@b10][@b11][@b12][@b13]. (2) Which lichen should be selected as a biomonitor? Species selection is necessary in such studies because the metal concentrations and enrichment capability are different among lichens[@b5][@b14][@b15][@b16].

We sampled six foliose lichens (*Physcia aipolia*, PA; *P. tribacia*, PT; *Xanthoria elegans*, XE; *X. mandschurica*, XM; *Xanthoparmelia camtschadalis*, XPC; and *Xp. tinctina*, XPT) from a remote region of the Xilin River Basin (XILRB), one of the most representative geographic areas of the Inner Mongolia steppe zone with frequent dust storms ([Fig. 1](#f1){ref-type="fig"}). Twenty-five elements (Al, Ba, Cd, Ce, Cr, Cs, Cu, Fe, K, La, Mn, Mo, Na, Ni, P, Pb, Sb, Sc, Sm, Tb, Th, Ti, Tl, V and Zn) were measured. The purposes of the present study were to quantify the concentration and identify the origin of elements in lichens and to select suitable lichens for monitoring atmospheric deposition of mineral elements in Inner Mongolia.

Results
=======

Six lichens were sampled from 15 sampling sites ([Fig. 1](#f1){ref-type="fig"}). There were no significant differences in the mean distance from the sampling sites to the national road between these lichens (XPC: 10.7 ± 5.3 km; PA: 10.6 ± 5.3; PT: 10.5 ± 6.4; XPT: 10.4 ± 6.4; XM: 10.4 ± 6.3; XE: 9.3 ± 6.3. All at p \> 0.10; One-way analyses of variance).

Element concentration and correlation
-------------------------------------

The concentrations of 25 elements in lichens and surface soil (SS) are given in [Table 1](#t1){ref-type="table"}. One-sample Kolmogorov-Smirnov tests show that the concentrations of each element are normally distributed across lichens and within each lichen species (all at p \> 0.05). The concentrations were distributed in the following order across all lichens: K \> Al \> Fe \> P \> Na \> Ti \> Mn \> Ba \> Zn \> Cr \> V \> Ce \> Pb \> Cu \> Ni \> La \> Cs \> Th \> Sc \> Sm \> Mo \> Sb \> Cd \> Tl \> Tb. This order is roughly followed in each lichen ([Table 1](#t1){ref-type="table"}).

Concentration correlations between elements across all lichens were tested using cluster analysis ([Fig. 2](#f2){ref-type="fig"}) and Pearson correlation tests. Cluster analysis preserved most of the pairwise distances between the original unmodelled data points (cophenetic correlation coefficient = 0.839) and distinguished six groups at a correlation similarity of 0.70. Group G1 contains 16 metals (Al, Ba, Cr, Cs, Cu, Fe, Mn, Mo, Na, Ni, Sb, Sc, Th, Ti, Tl and V). G2 contains 4 lanthanoids (Ce, La, Sm and Tb). G3 contains Pb. G4 contains K and P, which are strongly correlated (r = 0.89, p = 0.000; Pearson correlation test). Cd and Zn are not strongly correlated with other elements and formed G5 and G6, respectively ([Fig. 2](#f2){ref-type="fig"}).

Enrichment factor (EF)
----------------------

To assess the relative importance of crustal input in lichen elemental composition, element concentrations were normalized to Al in SS and in upper continental crust (UCC) to obtain EF~SS~ and EF~UCC~, respectively, according to [Eq. 1](#eq1){ref-type="disp-formula"}. The results are given in [Table 2](#t2){ref-type="table"}. Both EF~SS~ and EF~UCC~ were \>5 for three elements (Cd, P and Zn) across all lichens and in each lichen, as well as for Pb in XPT and XPC. Other metals were mostly \<5 in mean EF~SS~ ([Table 2](#t2){ref-type="table"}). Differences in the elemental ratios between SS and UCC resulted in marked differences between EF~SS~ and EF~UCC~ in some cases. For example, K (in PA and XPC) and Sb (in all lichens) had an EF~UCC~ of \>5 but an EF~SS~ of \<5 ([Table 2](#t2){ref-type="table"}).

Element concentration differences between lichens
-------------------------------------------------

One-way analyses of variance (ANOVA) based on the log10-transformed concentrations show that all elements were significantly different among lichens (all significant at p \< 0.05). *Post hoc* Student-Newman-Keuls (SNK) tests show that the element concentrations are dependent on lichen species and elements ([Table 1](#t1){ref-type="table"}). For the sake of clarity and simplicity, the SNK results were combined in [Fig. 2](#f2){ref-type="fig"}. [Figure 2](#f2){ref-type="fig"} shows that elements that showed strong positive correlations had similar lichen patterns; our results can therefore be generalized at the group scale.

The concentrations of the G1 metals (except Cu) were generally highest in PT, XE and XM, which were similar to XPT for 13 metals (Al, Ba, Cr, Cs, Mn, Mo, Na, Ni, Sb, Sc, Th, Ti and Tl) and to PA for 7 metals (Al, Ba, Mn, Sb, Sc, Th and Tl). PA was moderate in the concentrations of 8 metals (Cr, Cs, Fe, Mo, Na, Ni, Ti and V), among which Fe and V were also moderate in XPT. The Cu concentration was the highest in XM and was not significantly different between those of PA, PT, XE and XPT. The concentrations of all of the G1 metals were lowest in XPC ([Fig. 2](#f2){ref-type="fig"}, [Table 1](#t1){ref-type="table"}).

The concentrations of the G2 metals were highest in XPT, which was close to PT and XE for Ce, Sm and Tb. XM was lowest for lanthanoids, among which Sm and Tb were also lowest in XPC. The Pb concentrations were not significantly different among lichens, except XPT. The concentrations of the G4 elements were highest in XM, PT, XE and PA and were lowest in XPC. XM and XE were significantly lower in the concentration of Cd than other lichens. The Zn concentration was highest in PT, followed by PA, XM and XPT and was lowest in XE and XPC ([Fig. 2](#f2){ref-type="fig"}).

Comparison with the Taihang Mountains
-------------------------------------

A comparison of the element concentrations in XM between XILRB and the Taihang Mountains is presented in [Fig. 3](#f3){ref-type="fig"}. Compared with the Taihang Mountains, XILRB was significantly higher in concentrations for 4 elements (68--104% higher for Cs, K and P, and 65.6 times higher for Ti; all significant at p \< 0.05, one-way ANOVA) and lower in concentrations for 14 metals (33--88% lower for Cd, Ce, Cr, Cu, La, Pb, Sb, Sm, Tb, Th, Tl and Zn; 90% lower for Mo and 95% lower for V; all significant at p \< 0.05, one-way ANOVA). Seven metals (Al, Ba, Fe, Mn, Na, Ni and Sc) are not different in concentration between the two regions (all p \> 0.05, One-way ANOVA).

Discussion
==========

Elemental sources
-----------------

Generally, our results show that Cd, Pb and Zn are most likely of atmospheric origin, most likely from road traffic, whereas the other elements are mainly of crustal origin and are associated with dust storms.

The EF of an element provides information regarding its origin. An EF of \>5 often indicates a non-crustal or non-local source input, whereas an EF of \<5 is evidence of crustal input[@b17]. However, due to the different elemental ratios between SS and UCC, some metals had an EF~UCC~ of \>5 but an EF~SS~ of \<5, such as for K (in PA and XPC) and Sb (in all lichens; [Table 2](#t2){ref-type="table"}). We suggest that local SS is more applicable as a background reference than UCC because the suspension of SS is most likely the main source of atmospheric particulates due to frequent and severe dust storms in the Inner Mongolia steppe zone.

Both Cd and Zn were high in EFs (EF~SS~ and EF~UCC~ \> 10 across all lichens; EF~SS~ \> 5 in each lichen; [Table 2](#t2){ref-type="table"}), suggesting that other sources besides local crustal input can have a remarkable influence on the atmospheric deposition of both metals. This is also true for Pb, which had an EF~SS~ of \>5 in XPC and XPT. A large body of relevant literature has attributed the enrichment of these metals in lichens to anthropogenic pollutants released from industrial activities or traffic[@b5][@b9][@b11][@b13][@b17][@b18][@b19][@b20]. However, this region is a rural, pastoral area without intense industrial operations and is far from range fires and the application of chemical fertilizers and pesticides. The most possible source of these metals may be related to a national road crossing the study area ([Fig. 1](#f1){ref-type="fig"}). Lichens near roads often accumulate high levels of traffic-related metals, particularly Cd, Pb and Zn[@b5]. The Pb concentration in lichens has decreased as a result of declined vehicular Pb emissions due to the use of unleaded gasoline[@b5]. Accordingly, Pb was only slightly enriched in two lichens and the EF~SS~s (5.4--7.0) were much lower than those of Cd and Zn ([Table 2](#t2){ref-type="table"}). Resuspension of "old" Pb in soils may be an important source of Pb. Atmospheric pollutant transportation from the nearby city of Xilinhot (50 km away from our sites; [Fig. 1](#f1){ref-type="fig"}) may also be a source of these metals.

Although both the EF~SS~ and EF~UCC~ of P were \> 10 ([Table 2](#t2){ref-type="table"}), a strong positive correlation between P and K ([Fig. 2](#f2){ref-type="fig"}) suggests that the enrichment of P is not necessarily evidence of a non-crustal input but may be the result of active absorption and/or bio-regulation because both elements are essential nutrients for plants. The other metals are mainly of crustal origin (EF~SS~s of \<5), in strong agreement with many studies outside China[@b8][@b21][@b22][@b23][@b24][@b25].

Elemental concentration
-----------------------

Lichens in this study had higher concentrations of crustal elements but lower concentrations of atmospheric elements compared with relevant studies, particularly those performed in "polluted" regions. These results match well with the facts of frequent, heavy dust storms and low anthropogenic emissions in this remote steppe.

A comparison with values from different lichens in diverse ecosystems shows that our data are higher than or at the upper range of the literature values for 16 crustal metals (Al, Ba, Ce, Cs, Fe, K, La, Mn, Na, P, Sc, Sm, Tb, Th, Ti and V)[@b7][@b8][@b9][@b12][@b18][@b21][@b22][@b23][@b24][@b25][@b26][@b27][@b28][@b29][@b30][@b31][@b32]. To minimize species effects, XM was compared between XILRB and a region of the Taihang Mountains where the air quality has long been influenced by local anthropogenic emissions and heavy air pollution in the adjacent North China Plain[@b20]. The results also show higher or similar concentrations in XILRB for 11 crustal elements (Al, Ba, Cs, Fe, K, Mn, Na, Ni, P, Sc and Ti; [Fig. 3](#f3){ref-type="fig"}), clearly indicating a high level of crustal input in this region. By contrast, the literature records for 7 metals (Cd, Cu, Mo, Ni, Pb, Sb and Zn) are often 2 times to two orders of magnitude higher than our data, particularly at "polluted" sites where these metals were related to anthropogenic emissions[@b10][@b11][@b13][@b17][@b18][@b19][@b31][@b33][@b34][@b35]. Similarly, XM from the Taihang Mountains accumulated 1.5--10.3 times as much of these metals as XM from XILRB ([Fig. 3](#f3){ref-type="fig"}), indicating a much lower level of anthropogenic emissions in XILRB. In addition, XM had higher K and P concentrations in XILRB than in the Taihang Mountains, suggesting a better physiology of lichens because the K-P association is often related to the nutrient conditions in plants.

Species difference
------------------

It has been suggested that the response of lichen elemental composition to air pollution is different among lichen species and is dependent on the morphology and ecology of lichens[@b5][@b15][@b17]. This pattern is shown in our study, as indicated by the species- and element-specific concentrations ([Table 1](#t1){ref-type="table"}, [Fig. 2](#f2){ref-type="fig"}). Therefore, it is important to select lichens according to the elements of interest.

The higher concentrations of crustal elements indicate a greater efficiency of entrapment and/or retention of particulates derived from crustal input. In this case, the four epilithic lichens (PT, XE, XM and XPT) are suitable for the assessment of the crustal input, because they were at the upper range of concentrations for most crustal elements. The concentration of elements in lichens could be related to the substrate type and intimacy of connection between lichen thalli and the substrate[@b6][@b21]. Generally, the epiphytic lichen PA was lower in concentration of crustal elements than the four epilithic lichens (PT, XE, XM and XPT; [Table 1](#t1){ref-type="table"}, [Fig. 2](#f2){ref-type="fig"}), apparently due to the lower availability of aeolian particulates or soil/rock materials on bark relative to on rocks. Although it has been suggested that epigeal lichens are higher in crustal element concentrations than epiphytic lichens[@b7][@b30], we found that the epigeal lichen XPC had the lowest concentrations of all of the crustal elements ([Table 1](#t1){ref-type="table"}, [Fig. 2](#f2){ref-type="fig"}). The most possible explanation for these low concentrations is that the vagrant thalli of XPC are mostly free from the substrate and therefore have a lower degree of soil contact; by contrast, other lichens are closely adnate to the substrate.

Because Cd, Pb and Zn were mainly of atmospheric in origin, the higher values of EF~SS~ can be a measure of greater enrichment capability of lichens for these metals. XPT and XPC are the most suitable lichens for monitoring the atmospheric deposition of Pb. Pb was only enriched in these two lichens (EF~SS~ \> 5; [Table 2](#t2){ref-type="table"}), and was constant in concentration in both lichens (CV \< 20%; [Table 1](#t1){ref-type="table"}). Four lichens (PA, PT, XPC and XPT) are applicable for the monitoring of Cd. They had a greater enrichment capability of atmospheric Cd than other lichens, as indicated by the high concentration and EF~SS~ of Cd. PA is applicable to monitoring the atmospheric deposition of Zn. Although at the upper range of Zn concentration across all lichens, PT had a poor replicability in Zn concentration (CV = 50.3%) compared with PA (17.6%; [Table 1](#t1){ref-type="table"}). This could be explained by a higher degree of soil contamination in the thalli of the former lichen because the soils were spatially heterogeneous in Zn concentration (CV = 76.2% in SS; [Table 1](#t1){ref-type="table"}). Differences in accumulation of Cd, Pb and Zn between lichens are apparently not attributable to the location of sampling sites, because the mean distance from the sampling sites to the national road for each lichen ranged between 9.3 and 10.7 km and were not significantly different between lichens (All at p \> 0.10; One-way ANOVA).

Both XE and XM are less applicable to monitoring atmospheric deposition of Cd, Pb and Zn. They had a lower enrichment capability of atmospheric metals than other lichens, as indicated by the lower EF~SS~s and concentrations ([Tables 1](#t1){ref-type="table"} and [2](#t2){ref-type="table"}). Although the applicability of XM in the biomonitoring of natural and anthropogenic emissions has been reported in the Taihang Mountains[@b20], care should be taken in this region because the relative importance of anthropogenic contributions may be obscured by the high crustal input due to frequent dust storm events.

Our results show that anthropogenic emissions can be distinguished from the substantial dust storm input by analysis of the lichen elemental composition and therefore validate the applicability of lichens in monitoring atmospheric elemental deposition in ecosystems with prevailing dust storms. Different lichens should be selected according to the element of interest, for which a clear understanding of the species- and element-specific response of lichen elemental composition to atmospheric deposition is a prerequisite.

Methods
=======

Study area
----------

The study was conducted in the Inner Mongolia Grassland Ecosystem Research Station (IMGERS), the Chinese Academy of Sciences. The study area (43°32′--43°47′N, 116°33′--116°54′E) is located in the XILRB, Xilinhot, Inner Mongolia, China ([Fig. 1](#f1){ref-type="fig"}). The climate is continental, temperate and semi-arid, with rare annual precipitation (350 mm, mostly occurs as rainfall during May-September) and frequent drought and windy episodes during the whole winter-spring season. The area has undergone steppe degradation and frequent dust storms due to the continuous drought, overgrazing and heavy wind erosion of soil in the past decades[@b36]. The dominant vegetation is typical steppe of the Inner Mongolia Plateau, with chestnut soil as the dominant soil type, interspersed with sand dune complexes with sandy soils dominant. The landforms are hills, lava tablelands and sandy lands, with an average elevation of 1,350 m[@b36]. There are two small villages near IMGERS, with a population of \<100 inhabitants, and a national road crosses the area. The nearest city of Xilinhot is approximately 50 km northwest and has a population of 150,000 inhabitants ([Fig. 1](#f1){ref-type="fig"}). Livestock grazing is the predominant type of agricultural operation. There are few farms, and the use of chemical fertilizers and pesticides is absent. No industrial activity was found in the area.

Sampling sites
--------------

Fifteen sampling sites were selected at an interval of 4--8 km around IMGERS and covers approximately 260 km^2^ ([Fig. 1](#f1){ref-type="fig"}). To minimize the potential effects of local anthropogenic emissions on the lichen elemental composition, each site was \>1 km from major roads and settlements and \>0.5 km from farms. Vegetation was mainly semi-fixed sand dune steppe (dwarf shrub and grass complex) in three sites (S02, S05 and S06), predominantly typical steppes in four sites (S04, S08, S09 and S14), and both vegetation types in eight sites (S01, S03, S07, S10, S11, S12, S13 and S15). Six foliose lichens were sampled in these sites, including four epilithic lichens (PT, XE, XM and XPT), one epigeal lichen (XPC) and one epiphytic lichen (PA, on barks of *Ulmus pumila*).

Sampling strategies
-------------------

Lichens and soils were sampled over the course of 10 days in September 2013. At each site, in an area of 1 km^2^, \>50 mature individuals of each lichen and \>10 subsamples of SS (0--10 mm soil) were randomly collected from diverse microhabitats, and the composite samples were mixed to represent the average status of the elemental composition in the site. The purpose of these protocols was to minimize the effects of the microhabitat and individual differences. A total of 37 samples of lichens were sampled. PA was sampled in 6 sites (S02, S03, S05, S07, S11 and S12), PT in 5 sites (S01, S08, S13, S14 and S15), XE in 6 sites (S01, S04, S09, S13, S14 and S15), XM in 5 sites (S01, S04, S13, S14 and S15), XPC in 10 sites (S01, S03, S04, S05, S06, S08, S10, S11, S12 and S13), and XPT in 5 sites (S01, S04, S08, S13 and S14; [Fig. 1](#f1){ref-type="fig"}). Samples were transported to the laboratory in paper bags.

Sample preparation and chemical analysis
----------------------------------------

Lichen thalli were carefully cleaned, and the outermost part (1--1.5 cm) was detached for analysis. We think that these parts could allow for the comparison of recently accumulated elements by greatly minimizing the effects of age[@b14]. Lichen samples were not washed to avoid element leaching and were oven-dried at 70 °C for 72 h to a constant weight. SS samples were thoroughly cleaned and dried using the above method. All samples were ground and homogenized in a grinding mill equipped with Tungsten Carbide jars (Retsch MM400; Retsch GmbH, Haan, Germany).

Each sample (200--300 mg) was mineralized by microwaves in high pressure Teflon vessels in a mixture of HNO~3~ and H~2~O~2~ for lichens, as well as in a mixture of HNO~3~, HF, HCl, and HClO~4~ for SS samples. Twenty-five elements (Al, Ba, Cd, Ce, Cr, Cs, Cu, Fe, K, La, Mn, Mo, Na, Ni, P, Pb, Sb, Sc, Sm, Tb, Th, Ti, Tl, V and Zn) were analysed at Hebei Geological Laboratory by inductively coupled plasma mass spectrometry (ICP-MS; Agilent 7700X; Agilent Technologies, Tokyo, Japan). The analytical quality of the results was evaluated against the following reference materials: the national reference materials of GBW07451, GBW07452 and GBW07457 for SS, as well as GBW10014 (cabbage), GBW10015 (spinach), GBW10052 (green tea; all materials mentioned above were issued by the Institute of Geophysical and Geochemical Exploration, Chinese Academy of Geological Sciences) and IAEA-336 (lichen, issued by the International Atomic Energy Agency) for lichens. The measured element concentrations were within the confidence intervals of the certified/suggested values. Analytical precision was generally \<8% as judged from frequent, duplicate analyses.

Calculation of EF
-----------------

EF has been widely used in distinguishing element sources in lichens[@b8][@b17][@b20][@b25]. It is described in [Eq. 1](#eq1){ref-type="disp-formula"}.

where "Al" is the chosen reference element in accordance with most relevant studies[@b8][@b20][@b25]. "El" is the element under consideration. The square brackets denote concentrations. The subscripts denote the sample type. The natural abundance of elements for the UCC standard was adopted from data summarized by Rudnick and Gao[@b37].

Statistical analyses
--------------------

The normality of the data distribution was determined by the one-sample Kolmogorov-Smirnov test for the concentration of each element. CV was calculated as the standard deviation divided by the mean for each element and expressed as a percentage. Concentration correlations of lichen elements were tested by a Pearson correlation analysis and a cluster analysis. Cluster analysis was performed using the correlation distance to measure dissimilarities, and the UPGMA criterion was used to construct the hierarchical tree. All of the abovementioned analyses were performed using the Past 3.12 software (Ø. Hammer, Feb. 2016).

Concentration differences between lichens for each element were tested using one-way ANOVA based on the log10-transformed concentrations to satisfy the criteria of homogeneity and normality. *Post hoc* SNK tests were used for multicomparison. These analyses were performed using SPSS 13.0 (SPSS Inc., Chicago, IL, USA).

The maps in [Fig. 1](#f1){ref-type="fig"} were generated from the digital elevation model (DEM) data using ArcGIS 10.2 software (ESRI, Inc., Redlands, CA, USA; <http://www.esri.com>) for 3D visualization. The DEM data were obtained from the Geospatial Data Cloud (<http://www.gscloud.cn/>) and derived from the ASTER Global Digital Elevation Model (ASTER GDEM) with a horizontal accuracy of 30 m. The rivers and roads were drawn after Li *et al.*[@b36] by hand.

Additional Information
======================

**How to cite this article**: Liu, H.-J. *et al.* Lichen elemental composition distinguishes anthropogenic emissions from dust storm inputs and differs among species: Evidence from Xilinhot, Inner Mongolia, China. *Sci. Rep.* **6**, 34694; doi: 10.1038/srep34694 (2016).

The study was supported by the National Natural Science Foundation of China (Nos 31093440, 31000239), the Natural Science Foundation of Hebei Province (Nos C2014201032, C2010000268), the Key Bioengineering Discipline of Hebei Province (1050-5030023) and the Key Laboratory of Microbial Diversity Research and Application of Hebei Province. We are grateful to Prof. Ling-Hao Li (Institute of Botany, Chinese Academy of Sciences) for reading and improving the manuscript, and Zhen Wu for logistical support.

**Author Contributions** H.-J.L. and S.-B.F. designed this work and wrote the paper. X.-D.L. and J.-S.H. collected samples. S.-W.L. and Y.X. prepared samples. L.-C.Z., X.-P.G., Y.-J.J. and Y.-D.W. carried out the measurements. Q.-F.W. and S.-W.L. performed statistical analyses. J.-S.H. and S.-W.L. prepared Figures. All of the authors discussed the experiments and reviewed the manuscript.

![Location of the sampling sites.\
The black hollow circles denote the sampling sites. The red and blue lines represent main roads and rivers, respectively. The map was prepared using ArcGIS 10.2 software (ESRI, Inc., Redlands, CA, USA; <http://www.esri.com/>) with 3D visualization of the DEM data to illustrate the geomorphic features. The rivers and roads were drawn according to Li *et al.*[@b36] by hand. IMGERS denote Inner Mongolia Grassland Ecosystem Research Station, Chinese Academy of Sciences. For details of the DEM data, see the Methods section.](srep34694-f1){#f1}

![Dendrogram obtained by using UPGMA cluster analysis based on the correlation distance matrix (left panel) and the Table showing differences in the element concentrations between lichens (right panel).\
The broken line in the dendrogram shows a correlation similarity of 0.70. Different capitalized letters in each row of the table indicate a significant difference in element concentration between lichens (p ≤ 0.05). Cluster analysis was performed on the raw concentrations, and the resultant cophenetic correlation index was 0.839. Species differences were evaluated from the log10-transformed concentrations using one-way ANOVA followed by *post hoc* SNK tests. All tests were performed on 37 lichen samples from 15 sites in a remote region of Xilin River Basin, Xilinhot, Inner Mongolia, China. XM refers to *Xanthoria mandschurica* (n = 5). PT refers to *Physcia tribacia* (n = 5). XE refers to *Xanthoria elegans* (n = 6). XPT refers to *Xanthoparmelia tinctina* (n = 5). PA refers to *Physcia aipolia* (n = 6). XPC refers to *Xanthoparmelia camtschadalis* (n = 10).](srep34694-f2){#f2}

![Element concentrations in XM from XILRB and Taihang Mountains.\
Elements in red and in blue are of atmospheric origin in both regions and only in the Taihang Mountains, respectively. Elements in black are crustal elements in both regions. For detailed information on elemental concentrations in XM (*Xanthoria mandschurica*) from XILRB, see [Table 1](#t1){ref-type="table"}. Data from the Taihang Mountains were adopted from Liu *et al.*[@b20].](srep34694-f3){#f3}

###### Concentrations of 25 elements in lichens from Xilin River Basin, Xilinhot, Inner Mongolia, China.

  Element    Statistics   Concentration (μg·g^−1^)                                                           
  --------- ------------ -------------------------- -------- --------- --------- --------- -------- -------- -------
  Al            Mean                7293             9058A    11264A    10340A     8621A    6998A    3267B    42651
  CV(%)        53.12               18.11             33.18     32.17     34.91     29.97    38.96    18.95   
  Ba            Mean               79.15             127.8A   93.20A    95.18A    79.05A    116.5A   34.51B   625.2
  CV(%)        50.62               28.77             22.37     17.52     9.55      33.00    43.29     6.79   
  Cd            Mean                0.27             0.20B     0.33A     0.20B     0.35A    0.28A    0.27A    0.08
  CV(%)        25.41               10.00             12.12     15.00     25.71     21.43    11.11    45.92   
  Ce            Mean                9.64             3.33D    11.34AB   12.42AB   16.80A    8.58BC   6.67C    23.74
  CV(%)        49.65               27.03             24.78     33.33     31.55     15.50    27.14    56.44   
  Cr            Mean               14.15             25.39A   19.92A    17.77AB   16.41AB   12.71B   6.92C    337.5
  CV(%)        47.14               12.49             13.86     18.18     18.46     37.06    34.54    40.92   
  Cs            Mean                1.49             2.62A     2.30A    1.89AB    1.76AB    1.29B    0.66C    3.77
  CV(%)        53.71               39.31             16.96     22.22     30.11     28.68    37.88    65.29   
  Cu            Mean                8.84             15.25A   10.55B    10.20B     9.39B    9.52B    5.28C    19.31
  CV(%)        36.74               16.13             15.55     13.73     17.57     20.27    19.70    38.36   
  Fe            Mean                5926             11736A   8540AB    8226AB     6963B    5567B    1981C    11050
  CV(%)        58.50               17.24             23.83     22.88     23.61     31.39    30.47    66.15   
  K             Mean                8361             11981A   11596A    9374AB     6979B    11870A   4423C    23580
  CV(%)        44.77               25.99             20.97     29.97     9.20      24.06    23.69     3.62   
  La            Mean                5.08             1.22C     5.63B     6.23B     9.43A    4.29B    3.83B    12.90
  CV(%)        52.58               22.95             28.06     39.00     29.06     15.15    29.24    54.82   
  Mn            Mean               122.1             197.9A   176.2A    140.8A    133.3A    135.7A   59.82B   266.8
  CV(%)        47.75               25.45             32.16     17.99     29.47     34.08    23.24    90.61   
  Mo            Mean                0.31             0.47A    0.40AB    0.36AB    0.39AB    0.30B    0.18C    40.96
  CV(%)        39.67               21.28             35.00     25.00     12.82     23.33    22.22    20.84   
  Na            Mean                1650             3470A    2253AB    2404AB    1916AB    1437B    562.6C   12675
  CV(%)        60.82               23.24             20.05     23.36     16.43     31.94    57.14     7.72   
  Ni            Mean                5.90             10.32A   7.88AB    7.34AB    6.93AB    5.65B    2.93C    292.7
  CV(%)        46.41               19.86             30.08     24.52     15.73     22.12    28.67    19.26   
  P             Mean                1669             2297AB   2223AB    1799AB    1386BC    2511A    914.2C   258.7
  CV(%)        50.23               49.24             20.46     52.10     39.00     22.93    20.63    88.36   
  Pb            Mean                9.64             10.32B   11.07B     9.53B    14.85A    8.20B    7.47B    15.09
  CV(%)        31.12               18.22             13.46     16.05     17.44     29.27    19.54    29.70   
  Sb            Mean                0.30             0.48A     0.41A     0.34A     0.34A    0.36A    0.14B    0.60
  CV(%)        46.32               16.67             19.51     17.65     14.71     36.11    28.57    119.73  
  Sc            Mean                0.92             1.34A     1.37A     1.25A     1.07A    0.95A    0.39B    3.11
  CV(%)        53.87               22.39             40.15     33.60     33.64     23.16    41.03    80.67   
  Sm            Mean                0.76             0.41C    0.92AB     1.11A     1.22A    0.67B    0.47C    2.17
  CV(%)        48.18               14.63             23.91     30.63     29.51     14.93    27.66    59.06   
  Tb            Mean                0.10             0.07C    0.12AB     0.15A     0.16A    0.09BC   0.06C    0.30
  CV(%)        45.55               14.29             16.67     33.33     25.00     22.22    33.33    57.80   
  Th            Mean                1.30             0.98A     1.92A     2.19A     1.73A    1.29A    0.51B    3.85
  CV(%)        66.09               21.43             43.23     42.01     53.18     17.83    45.10    56.00   
  Ti            Mean               619.5             1232A    966.1A    876.3A    751.6AB   530.8B   182.9C   1241
  CV(%)        65.38               21.37             36.88     28.09     29.31     34.77    36.46    64.10   
  Tl            Mean                0.15             0.23A     0.21A     0.19A     0.17A    0.17A    0.08B    0.75
  CV(%)        44.23               34.78             23.81     31.58     11.76     23.53    12.50     9.09   
  V             Mean               13.11             25.61A   18.95AB   17.46AB   15.62BC   12.41C   4.69D    25.19
  CV(%)        56.04               15.62             20.63     20.33     20.17     34.09    28.14    78.52   
  Zn            Mean               56.28             51.96C   102.1A    39.28D    57.09BC   72.74B   38.19D   26.07
  CV(%)        51.22                4.93             50.26     7.03      8.15      17.60    18.83    76.21   

Different capitalized letters in each row indicate a significant difference in element concentration between lichens (p ≤ 0.05) based on one-way ANOVA performed on the log10-transformed concentrations followed by *post hoc* SNK tests. CV refers to the coefficient of variance (defined as the standard deviation divided by the mean). XM refers to *Xanthoria mandschurica* (n = 5). PT refers to *Physcia tribacia* (n = 5). XE refers to *Xanthoria elegans* (n = 6). XPT refers to *Xanthoparmelia tinctina* (n = 5). PA refers to *Physcia aipolia* (n = 6). XPC refers to *Xanthoparmelia camtschadalis* (n = 10). SS refers to surface soil (n = 15). n = 37 for all lichens.

###### EFs of 24 elements in lichens from Xilin River Basin, Xilinhot, Inner Mongolia, China.

  Element   EFs      Lichen species                                                                                                  
  --------- ------- ---------------- ------- ------- ------- ------- ------- ------- ------- ------- ------- ------- ------- ------- -------
  Ba        Mean          0.78        1.49    1.00    1.90    0.60    1.13    0.66    1.26    0.71    1.34    1.13    2.15    0.73    1.39
  CV(%)     32.79        43.01        27.33   19.35   42.23   9.75    18.69                                                          
  Cd        Mean         27.14        46.39   11.79   20.15   16.73   28.60   11.10   18.98   22.96   39.24   22.22   37.98   47.53   81.24
  CV(%)     61.57        11.10        27.96   35.96   30.70   32.81   23.75                                                          
  Ce        Mean          2.76        1.99    0.69    0.50    1.85    1.33    2.20    1.58    3.65    2.63    2.29    1.65    3.81    2.74
  CV(%)     42.63        38.56        8.22    22.49   31.63   19.56   17.13                                                          
  Cr        Mean          0.27        1.87    0.36    2.52    0.24    1.65    0.23    1.61    0.28    1.94    0.23    1.59    0.29    2.03
  CV(%)     36.11        16.81        21.35   23.46   47.80   19.82   42.42                                                          
  Cs        Mean          2.39        3.52    3.45    5.08    2.42    3.55    2.13    3.13    2.43    3.57    2.10    3.09    2.38    3.50
  CV(%)     32.94        55.15        16.77   13.41   24.54   12.32   35.77                                                          
  Cu        Mean          3.08        4.06    3.74    4.92    2.17    2.86    2.36    3.12    2.72    3.59    3.09    4.07    3.80    5.01
  CV(%)     31.32         8.23        18.86   32.16   44.67   19.27   20.59                                                          
  Fe        Mean          3.11        1.68    5.11    2.76    3.03    1.63    3.26    1.76    3.56    1.92    3.07    1.66    2.40    1.29
  CV(%)     35.93        26.81        19.04   30.60   51.27   14.20   14.03                                                          
  K         Mean          2.38        4.62    2.37    4.59    2.05    3.97    1.93    3.75    1.62    3.15    3.21    6.21    2.65    5.15
  CV(%)     40.28         8.68        44.95   62.12   36.61   29.19   30.24                                                          
  La        Mean          2.74        2.18    0.46    0.37    1.68    1.34    2.00    1.59    3.80    3.02    2.11    1.68    4.00    3.18
  CV(%)     49.19        35.65        10.58   26.15   32.49   21.58   17.54                                                          
  Mn        Mean          2.90        1.91    3.57    2.35    2.60    1.71    2.32    1.53    2.84    1.87    3.09    2.03    3.09    2.03
  CV(%)     29.91        33.08        29.02   26.78   56.32   14.44   20.61                                                          
  Mo        Mean          1.13        3.65    1.21    3.92    0.83    2.69    0.83    2.70    1.14    3.69    1.02    3.32    1.42    4.61
  CV(%)     40.63        31.38        16.70   24.51   38.82   28.97   40.51                                                          
  Na        Mean          0.74        0.74    1.33    1.32    0.72    0.72    0.81    0.81    0.84    0.84    0.69    0.69    0.56    0.55
  CV(%)     38.94        34.83        31.54   15.37   44.90   14.64   19.57                                                          
  Ni        Mean          0.13        1.55    0.17    2.03    0.10    1.25    0.11    1.32    0.13    1.59    0.12    1.43    0.14    1.70
  CV(%)     36.85        30.57        20.30   34.04   47.44   17.68   40.41                                                          
  P         Mean         44.54        33.63   40.40   30.51   35.32   26.67   36.41   27.50   29.97   22.63   62.17   46.95   50.73   38.31
  CV(%)     48.26        39.06        38.77   91.00   56.61   29.84   31.25                                                          
  Pb        Mean          4.65        7.88    3.34    5.67    2.93    4.97    2.82    4.79    5.36    9.10    3.38    5.74    6.94    11.77
  CV(%)     48.15        34.42        20.54   30.12   40.53   28.84   25.34                                                          
  Sb        Mean          3.10        8.87    3.85    11.01   2.70    7.73    2.50    7.16    3.08    8.81    3.70    10.58   3.08    8.82
  CV(%)     29.86        30.26        16.97   20.82   35.79   36.09   22.67                                                          
  Sc        Mean          1.74        0.74    2.06    0.88    1.65    0.70    1.66    0.71    1.73    0.74    1.89    0.80    1.66    0.71
  CV(%)     17.87        29.57        10.01   20.13   17.84   9.92    17.31                                                          
  Sm        Mean          2.32        2.04    0.92    0.81    1.67    1.47    2.16    1.90    2.88    2.54    1.95    1.72    2.96    2.61
  CV(%)     34.51        26.12        15.07   23.10   20.87   19.62   19.46                                                          
  Tb        Mean          2.24        1.86    1.09    0.91    1.56    1.29    2.11    1.75    2.64    2.20    1.88    1.56    2.90    2.41
  CV(%)     35.52        17.87        20.52   24.39   19.48   23.01   25.10                                                          
  Th        Mean          1.95        1.37    1.25    0.88    1.87    1.31    2.29    1.61    2.18    1.53    2.11    1.48    1.80    1.26
  CV(%)     31.85        38.35        16.11   21.30   40.37   19.56   37.34                                                          
  Ti        Mean          2.81        1.74    4.80    2.97    2.96    1.83    3.12    1.93    3.44    2.13    2.59    1.60    1.93    1.19
  CV(%)     43.74                     32.46   18.04   39.46   56.27   16.16   13.16                                                  
  Tl        Mean          1.32        2.11    1.50    2.40    1.11    1.78    1.11    1.78    1.24    1.99    1.39    2.22    1.45    2.32
  CV(%)     29.93        50.38        17.27   28.03   38.67   20.68   26.54                                                          
  V         Mean          3.07        1.53    4.86    2.41    2.98    1.48    3.03    1.50    3.54    1.76    2.99    1.49    2.53    1.26
  CV(%)     34.24        20.80        21.90   27.06   51.27   19.27   22.63                                                          
  Zn        Mean         15.20        11.30   9.55    7.10    14.85   11.04   6.85    5.09    11.97   8.90    17.60   13.08   21.07   15.67
  CV(%)     46.36        15.13        29.47   34.97   34.85   20.84   32.82                                                          

EF refers to enrichment factor and was calculated with Al as the reference element. UCC refers to the upper continental crust. SS refers to the local surface soil. CV refers to the coefficient of variance (defined as the standard deviation divided by the mean). EF~SS~ and EF~UCC~ had the same CV for each element in a lichen. Aluminium was not included because it is a reference element. XM refers to *Xanthoria mandschurica* (n = 5). PT refers to *Physcia tribacia* (n = 5). XE refers to *Xanthoria elegans* (n = 6). XPT refers to *Xanthoparmelia tinctina* (n = 5). PA refers to *Physcia aipolia* (n = 6). XPC refers to *Xanthoparmelia camtschadalis* (n = 10). n = 37 for all lichens.

[^1]: These authors contributed equally to this work.
