{"paper_id":"4e2f1c59-ab59-46ef-b1f7-2dfafb60d318","body_text":"Temporal and spatial characteristics of the composition of Hypogymnia physodes (Monk’s-hood lichen) from the Niepołomice Forest in Poland | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Temporal and spatial characteristics of the composition of Hypogymnia physodes (Monk’s-hood lichen) from the Niepołomice Forest in Poland Robert Kościelniak, Izabela Wiśniowska, Danuta Kadłub, Marzena Albrycht, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7719127/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 22 Dec, 2025 Read the published version in Scientific Reports → Version 1 posted 16 You are reading this latest preprint version Abstract The Niepołomice Forest, though relatively natural, is affected by air pollutants transported from nearby urban areas. To assess this impact, we examined the bioaccumulation of elements (Ca, Cd, Cu, Fe, Hg, Pb, S, Zn) in thalli of Hypogymnia physodes (L.) Nyl., together with oxidative stress biomarkers (SOD, TBARS) and thallus condition, at 15 sites. Samples were collected during both heating and non-heating seasons. Seasonal variability was observed: Cd, SOD, and TBARS were higher in the non-heating season, while S increased during the heating season, reflecting emissions from fuel combustion. Spatial differences were most pronounced for Cd, Zn, and TBARS. In the western part of the forest, H. physodes was absent at some sites, and lichens showed elevated Pb and Cu concentrations with increased SOD activity, indicating strong traffic-related pollution. In the east, thalli contained a high proportion of degenerated algae, associated with elevated Cd, Hg, and S, as well as other stressors. Overall, element concentrations were similar to those reported from other regions of Poland. The study highlights that even seemingly natural forests are subject to significant pollution pressure. Combining chemical data with biomarkers offers deeper insight into the effects of toxic elements on lichen bioindicators. Biological sciences/Ecology Earth and environmental sciences/Ecology Earth and environmental sciences/Environmental sciences Figures Figure 1 Figure 2 Figure 3 1. Introduction Since the mid-20th century, the Niepołomice Forest has been affected by incoming pollution, caused mainly by the development of the urban-industrial agglomeration of Kraków (Weiner et al., 1997 ) and other heavily polluted cities such as Tarnów and Nowy Sącz (Wojewódzki Inspektorat Ochrony Środowiska w Krakowie, 2017 ). The location of the pollution sources, together with the prevailing westerly winds carrying pollution from the Kraków agglomeration towards the forest, have created a pollution gradient in the area, intensifying the environmental pressure on this ecosystem (Kiszka, 1990 ; Kiszka and Grodzińska 2004 ). Therefore, the forest is a suitable place to study long-term ecological and environmental impacts of air pollution. These impacts have already been monitored using various groups of organisms, including mosses, trees and soil invertebrates (Grabowski, 1981 ; Grodzińska, 1981 ; Grodzińska et al., 1987 , 2005 ; Godzik and Szarek, 1993 ; Godzik and Szarek-Łukaszewska, 2005 ; Kapusta et al., 2019 ). One of the key bioindicator groups used to track environmental changes in the Niepołomice Forest has been lichens (Kiszka, 1977 , 1980 , 1990 ; Grodzińska, 2004; Kapusta et al., 2004 ). Due to the lack of a protective cuticle and roots, they are susceptible to disturbance, especially air pollution (Seaward, 1993 ; Purvis and Pawlik-Skowrońska, 2008 ). Widespread species such as Hypogymnia physodes (L.) Nyl. are excellent long-term indicators of air quality (Bąbelewska et al., 2018 ). Pollutants can disrupt the cellular homeostasis of lichens and induce the formation of reactive oxygen species (ROS), the excessive production of which can lead to cell damage, including damage to cell membranes. These changes may also be visible externally, as deformation of the thallus, such as darkening or bleaching of their fragments, and altered structures (Jóźwiak, 2007 ). In the long term, oxidative stress leads to cell death, which is signaled by an increase in the level of Thiobarbituric Acid Reactive Substances (TBARS) in the organism (Osyczka et al., 2023 ). As a consequence, lichen populations decline and species diversity of the polluted habitat decreases (Seaward, 1993 ; Kiszka and Grodzińska 2004 ; Maring et al., 2023 ). To prevent this, organisms activate defense mechanisms, such as enzymatic antioxidant systems neutralizing ROS. One of the key enzymes involved is Superoxide Dismutase (SOD), whose increased activity converts superoxide anions into less reactive oxygen species, thereby limiting cell damage (Bačkor and Fahselt 2008 ; Álvarez et al., 2015 ; Lucadamo et al., 2022 ). This enzymatic response plays an important role when lichens are exposed to environmental pollutants, such as chemical compounds and individual elements, particularly metals (Thakur et al., 2024 ). Metals, based on function, can be divided into those that are essential for life (e.g., calcium (Ca), copper (Cu), iron (Fe) and zinc (Zn)) and non-essential ones, which have no role in organisms (e.g., cadmium (Cd), lead (Pb) and mercury (Hg)) (Masindi et al., 2021 , Rucová et al., 2021, Matei et al., 2025 ). In addition to metals, sulfur and its oxides also exert harmful effect, especially during the heating season, when fuel combustion in households significantly increases their emissions into the atmosphere. Nowadays, in the environment concentrations of most of these pollutants stem from anthropogenic sources, such as traffic, industrial activities and domestic heating (Charlesworth et al., 2011 , Alloway, 2013 , Turhan et al., 2021 ), with their levels varying seasonally (Frati and Brunialti, 2023 ; Thakur et al., 2024 ). The heating season is characterized by increased emissions of particulate matter and heavy metals from domestic and industrial heating systems (Turhan et al., 2021 ). The distribution of these emission sources may cause site-specific differences in pollution levels, resulting in distinct spatial patterns of lichen pollution. Recognizing these patterns helps to identify the areas most vulnerable to harmful deposition, pinpoint the largest sources, and thus target potential protective measures. Research on lichens in the Niepołomice Forest began as early as the 1960s, leading to the classification of the larger part of the forest as moderately polluted, except for a stronger polluted small enclave in the western part of the southern complex (Kiszka, 1964 ; Kiszka, and Grodzińska, 2004 ). Since the 1970s, the extent of the moderately polluted zone has decreased as a result of increasing industrial emissions. Consequently, a decline in many sensitive species and noticeable damage to lichens were recorded (Kiszka, 1974 , 1978 , 1980 , 1981 ; Kiszka and Grodzińska, 2004 ). Lichen-based surveys conducted in the 1990s showed that the western part of the forest had shifted into the very heavily polluted zone, while the area classified as moderately polluted expanded at the expense of the strongly polluted zone (Kiszka, 1990 ; Kiszka and Grodzińska, 2004 ). The last lichen studies in the Niepołomice Forest were carried out 20 years ago (Kapusta et al., 2004 ). Since then, air protection policies, industrial activity, and transportation intensity have undergone significant changes. It remains unclear how these changes have influenced lichen condition and whether the current pollution levels are reflected in their physiological state. Additionally, until now, no measurements of TBARS levels or SOD activity have been performed for lichens in this area, limiting a more complete understanding of their exposure and responses in the Niepołomice Forest. In this context, we conducted the study to assess the impact of air pollution within the Niepołomice Forest on the monk's-hood lichen ( Hypogymnia physodes L. Nyl.). We measured concentrations of eight elements: Ca, Cd, Cu, Fe, Hg Pb, S and Zn in thalli sampled three times over a one year period: April 2018, October 2018 and April 2019, covering both heating and non-heating seasons. In addition to elements, we also measured the activity of SOD, TBARS level, as well as the proportion of dead algae in the thallus as markers of lichen condition. The data were analyzed using a multivariate approach and GIS visualization. Based on the collected information, we were able to address the following hypotheses: (1) the concentrations of elements, the activity of SOD and TBARS level depend on the season; (2) the above-mentioned parameters reveal spatial variability; (3) all the parameters are linked to the thallus condition. We expected both spatial and seasonal variability in the measured parameters, with a particular focus on the negative influence of non-essential elements (especially Cd, Hg, and Pb), associated with increased oxidative stress response and, consequently, deterioration of the condition of lichens. 2. Materials and methods 2.1 Study site The study was conducted in the area of the Niepołomice Forest (49°59′-50°07′N, 20°13′-20°28′E) in southern Poland, Europe (Fig. 1 ). It is a complex of several forest areas covering an area of 110 km 2 , located east of Kraków agglomeration in the western part of the Sandomierz Basin. It is dominated by pine and mixed oak-pine (Pino-Quercetum) as well as oak-hornbeam (Tilio-Carpinetum) forests (Kapusta et al. 2004 ), whose current stands have been shaped by human management (Gazda and Szlaga 2008 ). The area is characterized by little variation in relief (Godzik and Piechnik 2019 ). The highest temperatures in the area occur in July (average of 18.4°C) and the lowest (-2.6°C) are recorded in January (Climate-Data, 2025). Summer lasts up to 100 days andwinter up to 85 days. Average annual precipitation ranges from 560 to 700 mm, with rainfall recorded on 160–170 days per year. Snowfall occurs on about 45 days, and the average duration of snow cover is 110 to 120 days (Godzik, Piechnik 2019 ). The climate of the Niepołomice area is characterized by frequent occurrence of fog and temperature inversion, which significantly reduce the number of sunny days, especially in autumn and spring (Climate-Data, 2025). The research was conducted in the southern, largest part of the complex, covering an area of approximately 85 km 2 . In this area, 20 evenly distributed survey plots were initially selected, with their final location determined after field verification. In the western part of the Forest, representing about 20% of the planned study area, no H. physodes were found. Consequently, the number of study sites was reduced to 15 (Fig. 1 ). 2.2 Sampling Hypogymnia physodes thalli were sampled after the end of the heating season (April 2018 and 2019), and before the start of the heating season (October 2018). Considering the accumulation time of pollutants, we categorized these samplings as heating and non-heating seasons, respectively. Samples were collected from pine ( Pinus sylvestris L.) trunks at heights of 50 cm and 2 m above ground. Depending on the site and the collection period, the number of trees sampled ranged from 1 to 15. In total, 45 samples were collected in the whole study. After collection, the samples were dried at room temperature and stored in paper envelopes. 2.3 Algal condition The morpho-anatomical analysis of lichens was performed to determine the degree of thallus damage based on visible changes, according to the following criteria: 1) rosettes without disease damage, i.e. healthy, uniformly colored and morphologically intact; 2) rosettes with moderate damage, i.e. those with blackened or faded patches, excessive shrinkage, affecting no more than 50% of the rosette; 3) rosettes with severe damage, with more than 50% thallus degeneration (Betleja 1989 ). At most sites no thalli classified to the moderate damage group were found, therefore, two groups - healthy and severely damaged - were used. To study the internal thallus morphology, microscopic preparations were made from excised fragments of thalli with a specific and fixed diameter. From each site and damage group, three randomly selected thalli were sampled, and three preparations made from the middle part and both margins of each rosette. Using 40x magnification of the microscope (Delta Optical Genetic Pro), all algal cells were counted according to the following criteria: 1) healthy algae: all cells with uniformly green-colored chloroplast; 2) algal cells with damage, i.e., showing changes in chloroplast coloration (browning), degeneration in the form of shrinking, fragmentation, and with signs of plasmolysis; 3) dead algal cells lacking chloroplast content (Betleja 1989 ). The obtained numerical data on the external and internal morphology of the thalli were presented as percentages for each group (damaged and dead algal cells are grouped into one category). 2.4 Elemental analysis Air-dried samples were used in three separate protocols to measure Hg, other metals, and S consecutively. Hg concentrations were determined using a cold vapor atomic absorption spectrometer (MA-2, Nippon, Japan) in sub-samples of ca. 50 mg. Three, finally averaged replicates were performed for each lichen sample. During the measurements, quality control was performed using a standard solution of mercury (II) chloride (HgCl 2 , 100 ug/ml, Nippon, Japan) diluted to 0.01 ug/ml. If the RSD between results of triplicates was higher than 15%, the sample was reanalyzed. For quantification of other metals, air-dried samples were further dried (at 60°C for 72 hours) and aliquots of 2 g were mineralized in an open digestion system (Velp Scientifica, DK-20) using ultrapure nitric acid (Baker Instra, 65%) and ultrapure perchloric acid (Sigma-Aldrich, 70%) in a 4:1 volume ratio, kept first at 140°C (ca. 2 hours) and then at 160°C (ca. 20 hours). The mineralized solution was diluted with ultrapure water (Direct Q-3, Merck Millipore) to a volume of 10 ml and the concentration was measured in a flame atomic absorption spectrometer (AAnalyst 200, PerkinElmer, USA). Another part of the sample (approx. 80 mg) was used to measure sulfur concentrations using the modified Butters-Chenery method (Bielecki, Kulczycki 2012 ). Briefly, a sample was mineralized in the presence of an oxidizing agent, leading to the conversion of sulfur compounds into sulfates (SO₄²⁻), which are then, after reaction with barium chloride (BaCl₂), quantified turbidimetrically using a spectrophotometer (Evolution 260 Bio UV-Visible Spectrophotometer, Thermo Scientific, USA). The results were expressed as micrograms per gram of fresh weight of the lichen sample. For Cd, Cu, Hg, Pb and Zn, the accuracy of the method was tested against a Certified Reference Material (CRM; BCR 482, JRC, IRMM). Recoveries ranged from 97.16 for Cu to 104.65 for Zn, confirming the reliability of the analytical protocol (Table S1 ). The mean values and recoveries for the other elements are provided in the Supplementary materials (Table S1 ). Due to the lack of appropriate CRM available on the market, the accuracy of the method for Ca and Fe was tested using control solutions and spikes only. 2.5 Oxidative stress biomarkers Before the analyses, the lichens were placed into distilled water for 15 min to saturate. Next, they were acclimatized in a climate chamber for 48 hours (10°C, 60–70% RH, 12L:12D). Quantification of thiobarbituric acid-reactive substances (TBARS) as a proxy of the extent of lipid peroxidation was assessed according to Gawrońska et al. ( 2013 ). Briefly, lichen powder (0.2 g) was homogenized in 2 mL of 0.1% trichloroacetic acid (TCA, A.C.S., POCH). Homogenates were centrifuged at 10 000×g for 5 min at 4°C. The obtained supernatant was mixed 1:4 (v/v) with 0.5% barbituric acid solution (A.C.S., POCH) in 20% TCA, incubated at 95°C for 30 min, cooled on ice and centrifuged at 10 000×g for 5 min. The colored complexes of TBARS (products of lipid peroxidation) were determined at 532 nm, and the non-specific absorption at 600 nm was subtracted (Ultrospec 2100 pro-Classic, GE Healthcare, UK). An extinction coefficient of 1.56 × 105 M − 1 cm − 1 was used for TBARS concentration calculations. The results were expressed as mmol TBARS per gram of fresh weight of the lichen sample. To analyze the superoxide dismutase (SOD) activity, crude protein was extracted in accordance with the procedure described by Egger et al. ( 1994 ). Lichen powder (60 mg) was homogenized in 1 ml of 50 mM phosphate buffer (pH 7.5) containing 1 mM EDTA (99+%, Sigma-Aldrich), 1% PVP (99%, Sigma-Aldrich), 0.2% Tritone X-100 (99%, Sigma- Aldrich), and 5 mM 2-mercaptoethanol (99%, Sigma-Aldrich). The homogenate was centrifuged at 12 000×g for 5 min at 4°C, and supernatant was used for measuring antioxidant enzyme activity. Protein concentration was determined according to Bradford ( 1976 ). Separation of soluble protein fractions was performed according to the procedure described by Laemmli ( 1970 ) using native (without sodium dodecyl sulfate) PAGE at 4°C and 180 V. Visualization of SOD bands was performed on discontinuous 12% polyacrylamide gels in accordance with the method described by Beauchamp and Fridovich ( 1971 ). The gels were incubated in staining buffer for 30 min, in darkness, at room temperature and then exposed to white light until SOD activity bands became visible. Densitometric analysis of SODs bands was performed with ImageJ 2 (GPL license) and the results were expressed in activity units [AU]. 2.6 GIS and statistical analyses Based on the lichen sampling locations and values of each studied parameter, interpolation maps were created using the Inverse Distance Weighted (IDW) tool. Maps were prepared in QGIS ver. 3.2.2 Bonn. Coordinates were expressed in the EPSG: 2180 − 189 ETRS89/Poland CS92 system. For parameters which showed spatial differences, two maps for each season were created. Prior to the analysis, we plotted the data to identify the distribution and potential outliers. Since the element concentrations and dead algae fraction (DAF, hereafter) were log-normally distributed, further analysis was conducted on their logged data. Values of SOD and TBARS were normally distributed. The data from the measurements above were accompanied by the following variables: season (non-heating season vs heating season), and location (15 sampling points). The main analysis (factorial ANOVA) verified the variability of all element concentrations. For the metals, Principal Component Analysis (PCA) was performed to identify patterns of variation and relationships between the studied variables, and to prepare a PCA-derived metal concentration index. For DAF, SOD and TBARS, General Linear Models (GLM) were built to explain their variability using season, location, PCA-derived metal index, S, SOD (for DAF and TBARS models), TBARS (for DAF and SOD models) and DAF (for SOD and TBARS models). Model backward selection was used, starting with a full model and then dropping the consecutive variables until only significant ingredients remained. Finally, the AIC value corrected to the small sample size (AICc) was used to compare the final model with the full model. To assess potential multicollinearity effects on the models, correlations between all the numeric variables were examined (correlations were generally week, under r Pearson 0.7). Additionally, the strength and significance of potential correlations between elements were evaluated with r Pearson coefficient. Arithmetic mean, geometric mean, standard deviation, minimum, and maximum were calculated as descriptive statistics. Values were presented with at least three significant digits for the lowest value. In all the analyses, the significance level was set as 0.05. The data were compiled in Microsoft Excel (ver. 16). All the analyses were performed in R (ver. 4.0.2; R Core Team 2020 ) and R Studio (ver. 1.3). 3. Results All the measured element concentrations were higher than the quantification limits of the applied method (Table S1 ). Due to logistical constraints, SOD and TBARS activities could not be measured in the samples from April 2018. 3. 1 Concentrations of elements Elemental concentrations built the following order: Hg < Cd < Pb < Cu < Zn < Fe < S < Ca. The lowest concentration was noted for Hg (0.04 µg/g), while the highest was for Ca (7 569 µg/g). The lowest standard deviation was observed for Hg (0.040), and the highest for Ca (1762.054; Table 1 ). Table 1 Descriptive statistics (mean followed by geometric mean (in the bracket) and SD) of elements [µg/g], DAF (dead algae fraction) [%], SOD [AU] and TBARS mmol*g FM -1 in H. physodes thalli. Models Non-heating season Heating season Pooled Ca 1852 (1181) ± 1988 312–6112; n = 13 1706 (1230) ± 1687 280–7569; n = 29 1751 (1214) ± 1762 280–7569; n = 42 Cd 0.97 (0.96) ± 0.14 0.81–1.18; n = 13 0.87 (0.85) ± 0.17 0.61–1.29; n = 29 0.90 (0.88) ± 0.17 0.61–1.29; n = 42 Cu 5.72 (5.69) ± 0.67 4.35–6.44; n = 13 5.71 (5.65) ± 0.84 4.10–7.34; n = 29 5.71 (5.66) ± 0.78 4.10–7.34; n = 42 Fe 721 (709) ± 127 463–897; n = 13 648 (620) ± 211 343–1412; n = 29 671 (647) ± 191 343–1412; n = 42 Hg 0.10 (0.10) ± 0.02 0.07–0.13; n = 14 0.10 (0.09) ± 0.05 0.04–0.27; n = 30 0.10 (0.09) ± 0.04 0.04–0.27; n = 44 Pb 9.15 (8.90) ± 2.04 4.72–11.33; n = 13 9.13 (8.75) ± 2.46 3.46–13.20; n = 29 9.14 (8.80) ± 2.31 3.46–13.20; n = 42 S 917 (878) ± 236 348–1159; n = 14 1331 (1281) ± 376 784–2307; n = 30 1200 (1136) ± 388 348–2307; n = 44 Zn 108.1 (102.8) ± 39.2 69.5–197.6; n = 13 110.0 (105.2) ± 35.7 72.7–217.3; n = 29 109.4 (104.5) ± 36.3 69.5–217.3; n = 42 DAF 33.8 (33.4) ± 4.7 26.9–41.5; n = 15 34.0 (33.7) ± 5.0 26.3–46.5; n = 30 33.9 (33.6) ± 4.9 26.3–46.5; n = 45 SOD 23231 (22396) ± 6094 12463–32728; n = 15 19577 (19395) ± 2615 12996–22868; n = 15 21404 (20841) ± 4968 12463–32728; n = 30 TBARS 0.95 (0.95) ± 0.07 0.89–1.14; n = 15 0.88 (0.88) ± 0.04 0.80–0.96; n = 15 0.91 (0.91) ± 0.07 0.80–1.14; n = 30 Concentrations of Cd and S differed between seasons, in contrast to other elements (Table 2 ). The influence of location was significant only for Cd and Zn concentrations. No interaction was observed between season and location for any of the elements (Table 2 ). Cd concentrations were higher in the non-heating season, while S concentrations were higher during the heating season (Table 1 ). For Cd, the highest concentrations were found in the north-eastern part of the forest (sites 2, 6 and 7), while the lowest concentrations were observed in the central-western part (sites 8, 9, 12 and 15). For Zn, the highest concentrations were recorded in the northern and western parts of the forest (sites 6 and 15), while the lowest concentrations were in the central part (sites 7, 9, 12 and 14) (Fig. 3 ). Table 2 ANOVA models testing the influence of season, location and their interaction on element concentrations in H. physodes thalli collected in the Niepołomice Forest Variables Season Location Interaction Ca F 1, 14 = 0.034, p = 0.856 F 14, 14 = 2.212, p = 0.075 F 12, 14 = 1.631, p = 0.190 Cd F 1, 14 = 6.340, p = 0.025 F 14, 14 = 2.787, p = 0.032 F 12, 14 = 0.558, p = 0.842 Cu F 1, 14 = 0.023, p = 0.882 F 14, 14 = 1.869, p = 0.127 F 12, 14 = 0.675, p = 0.750 Fe F 1, 14 = 1.915, p = 0.188 F 14, 14 = 0.969, p = 0.523 F 12, 14 = 0.525, p = 0.865 Hg F 1, 15 = 1.035, p = 0.325 F 14, 15 = 1.179, p = 0.377 F 13, 15 = 0.285, p = 0.986 Pb F 1, 14 = 0.026, p = 0.875 F 14, 14 = 1.387, p = 0.274 F 12, 14 = 0.343, p = 0.965 Zn F 1, 14 = 0.152, p = 0.703 F 14, 14 = 5.512, p = 0.001 F 12, 14 = 2.397, p = 0.061 S F 1, 15 = 18.579, p = 0.001 F 14, 15 = 1.529, p = 0.212 F 13, 15 = 1.121, p = 0.412 Bold indicates significant differences (p < 0.05). Relationships between elements were generally weak (r Pearson below 0.6), with the strongest observed between Cu and Pb (r Pearson 0.505), followed by Fe and Pb (r Pearson 0.486), and Zn and Pb (r Pearson 0.436) (Figure S3). Other potential correlations were statistically insignificant. PCA analysis of metals showed that the first two principal components (PC1 and PC2) explain 52.8% of the total variability (PC1: 33.1%, PC2: 19.7%, respectively) (Figure S2). 3.2 Oxidative stress biomarkers The best-fitting GLM model explaining SOD values was the one including season only (Table 3 ) and revealing the negative relationship between both variables (Table S2). For TBARS, the final model included season and location (Table 3 ), indicating a negative relationship with season but a positive relationship with location for TBARS (Table S2). Table 3 Corrected for small sample size Akaike Information Criterion (AICc) for GLM models explaining the condition parameters of H. physodes thalli collected in the Niepołomice Forest. The model with the lowest AICc was considered the best-fitting explanatory model Variables Full model * AICc Final model (backward selection) Final model AICc DAF 127.93 null model -45.94 SOD 700.05 Season 597.17 TBARS 58.14 Season + Localization -36.75 * Full model included the PCA-derived variable for metals (Figure S2), logged sulfur, logged DAF (dead algae fraction; for SOD and TBARS models), SOD (for DAF and TBARS models) and TBARS (for DAF and SOD models). Values of SOD reached higher concentrations in the non-heating season than the heating season (23231 [AU] and 19577 [AU], respectively; Table 1 ). TBARS mean values were also higher in the non-heating season (0.95 mmol*g FM -1 and 0.88 mmol*g FM -1 , respectively; Table 1 ). The highest TBARS values were observed at sites 5, 8 and 11, the lowest were noted at sites 1, 2 and 3 (Fig. 3 ). 3.3 Algal condition The examined preparations showed the presence of healthy algal cells, algal cells with severe damage involving more than 90% of chloroplast content, and dead cells devoid of chloroplast content. At most sites, both healthy and severely damaged thalli were observed; however, no thalli with moderate damage were detected. In samples collected during the heating season, the proportion of dead algal cells ranged from 26.3% to 46.5%, while in the non-heating season, it ranged from 26.9% to 41.5% of all algal cells and was not influenced by the parameters examined in this study (Table 3 ). 4. Discussion We found that only Cd and S concentrations showed seasonal variation, while Cd and Zn concentrations varied spatially. SOD and TBARS also revealed seasonality, although their values were partially explained by season but only TBARS by location. The condition of algae was not influenced by any parameters analyzed in the study. Over the past 40 years of research in the area, it has been shown how the number of lichen species (lichenized fungi), site frequency and abundance have changed, as well as the strong response to air pollution in the form of damage or even degeneration of entire thalli. Our research showed that the average concentrations of elements in H. physodes thalli were comparable to those reported from other parts of Poland (Białońska, 2005; Bąbelewska et al., 2018 ; Białońska and Dayan, 2005; Sawicka-Kapusta et al., 2014 ). According to the classification of Nimis et al. ( 2000 ), only the average concentrations of Cd and Zn reached values indicating potential negative impacts on the natural environment. This shows fairly significant environmental changes that, if they continue to increase, could pose a serious threat to the natural environment. 4. 1 Seasonal differences Many studies indicate that the process of metal accumulation by lichens is closely related to seasonality, with higher concentrations of certain elements typically occurring during the heating season (Bąbelewska et al., 2018 ). Literature also reports increased emissions of Cd and S during the combustion of coal and wood (Johansson et al., 2003 ; Sippula et al., 2009 ; Świetlik et al., 2012 ; Cui et al., 2019 ). In our study, however, the higher concentration of Cd was observed outside the heating season (Table 1 ), suggesting that other sources may contribute to its elevated levels. Cd is released not only in combustion processes, but also through industrial activity, waste disposal (Hutton 1983 ; Nzihou and Stanmore 2013 ), and fuel combustion (Ciężka et al., 2018 ). Therefore, we suggest that these sources may be responsible for the higher Cd emissions during the non-heating season compared to the heating season. In the study, we also observed seasonality of S concentrations (Table 2 ). In the environment, S occurs mainly as sulfur oxides, which are released, particularly by thermal power plants (Wiseman and Wadleigh, 2002 ; Lin et al., 2018 , Shikhovtsev et al., 2024 ). Research conducted in the Świętokrzyski National Park on H. physodes pollution showed that the concentration of sulfur (IV) oxides (SO 2 ) increases significantly during the heating season (Ciężka et al., 2018 ; Ciężka et al., 2022 ), which supports our findings. In Kraków, located in the vicinity of the western part of the forest, the observed concentrations are lower (Fig. 2 ). This may be related to the anti-smog resolution enacted in 2019, which introduced a legal ban on burning coal and wood for residential heating within the city boundaries In contrast, sites located in the western part of the forest are near Tarnów and smaller towns, where no such ban has been implemented (Sejmik Województwa Małopolskiego, 2016; Wojewódzki Inspektorat Ochrony Środowiska w Krakowie, 2017 ). Our results indicate seasonal differences in oxidative stress biomarkers (Table 3 ). Besides air pollution, their activity is influenced by environmental conditions. During the non-heating season, lichens are exposed to increased UV radiation and low humidity, which disrupt homeostasis and promote ROS production (Mittler, 2002 ; Bačkor and Loppi, 2009 ), indicating oxidative stress. We suggest that increased SOD activity observed in the non-heating season was influenced by the above mentioned factors. However, in relation to TBARS, although its higher average concentration was observed during the non-heating season, its spatial distribution (Figure S2) indicates its increased concentration during the heating season in the western part of the forest. Both SOD and TBARS can serve as indicators of environmental pollution, as their levels increase in response to metal pollution (Santos et al., 2022 ; Osyczka et al., 2023 ), which is higher during the heating season. Although our study does not show a clear impact of the measured elements, we suggest that pollution from Kraków may contribute to their higher levels at those sites. 4. 2 Spatial differences The spatial distribution of Cd is diversified, with the highest values recorded in the middle-eastern part of the forest (Fig. 3 ). Cd is released in combustion processes, as a result of industrial activity and waste disposal, as discussed in the previous subsection. It is worth noting, however, that less urbanized areas may also contribute significantly to emission of this metal - for example, through waste burning, agricultural practices, or local transport. This indicates a real threat of metal pollution even in areas considered to be more natural (Hutton et al., 1983; Aslan et al., 2011 ; Gómez et al., 2024 ). Over the years, studies conducted in the Niepołomice Forest have consistently reported higher Zn pollution in its western part (Szarek-Łukaszewska et al., 2002 ; Kapusta et al., 2004 ), suggesting a significant impact of the Kraków agglomeration. Our results confirmed this pattern, with the highest concentrations observed in the western part (site 15; Fig. 3 ), where Zn coincided with Pb and Cu (Figure S1 ), supporting the hypothesis that road transport is a major source (Oliva and Rautio, 2004; Hjortenkrans et al., 2007 ; Jeong, 2022 ). In contrast, an additional Zn maximum was recorded at a northern site located near the village of Olszyny, adjacent to agricultural fields. This pattern cannot be explained by traffic and, together with elevated Cd and Ca concentrations and the highest percentage of damaged thalli, it strongly suggests the contribution of agricultural activities. On the other hand, Pb pollution can also be linked to incomplete fuel and oil combustion as well as the legacy of leaded gasoline use (Al-Sabbagh and Shreaz, 2025 ). We also observed an antagonistic spatial relationship between Pb and Cu versus Ca. The highest Ca concentrations were found at eastern sites, where Pb and Cu levels were relatively low. compared to the western part, of the forest, where the opposite trend occurred. We suggest that this may be related to the protective role of Ca as a competitor for binding sites with toxic metals such as Cd (Branquinho et al., 1997 ; Kováčik et al., 2020 ). In contrast, in the eastern part, higher concentrations of S, Cd, Hg, and Ca, as well as greater damage to lichens were observed. This suggests a stronger impact of local emission sources, such as the energy industry, municipal and domestic combustion, and emissions related to agricultural activities (Ministerstwo Klimatu i Środowiska 2020). Additionally, for Hg and S, long-range transport from small towns and surrounding agricultural areas located in the immediate vicinity of this region cannot be ruled out (Zeedijk and Velds, 1973 ; Marumoto et al., 2015 ). Unlike most metals, which tend to deposit relatively close to their emission sources, elemental Hg and sulfur oxides can remain airborne for extended periods, allowing them to disperse and deposit far from their origin (Jackson, 1997 ; Xiao et al., 1997 ; Sigler et al., 2003 ; Qu et al., 2016 ). The concentration of elements in the air is mainly influenced by local sources of their release, as well as meteorological conditions in a given area, such as wind speed, temperature and precipitation. In addition, rainfall favors pollutant leaching, while strong winds and low temperatures promote their spread (Inspektorat Ochrony Środowiska, 2007 ). According to the emission balance for 2018 and 2019 in Poland (Ministerstwo Klimatu i Środowiska, 2020, 2021), industrial processes were the main source of Cd in the environment, with emissions related to energy production also playing a significant role. Therefore, the high concentrations recorded in our study may have been caused by weather conditions, as - according to the thermal classification made by the Institute of Meteorology and Water Management (GIOŚ 2020) − 2018 and 2019 were classified as extremely warm, characterized by low rainfall, which might have favored accumulation of pollutants in H. physodes thalli. Although, our study did not indicate a connection between lichen damage and oxidative stress biomarkers, we observed that increased TBARS levels and SOD activity were noted in the western part of the forest. ROS are mainly produced in the mitochondria of living cells (Hernansanz-Agustín and Enríquez, 2021 ), so their low concentrations in the eastern part of the forest may be related to reduced metabolic activity caused by higher cell degeneration that indicates lower activity of SOD and TBARS levels. Thus, stressors present in the eastern part of the forest may be responsible for the condition of lichens. However, for sites 5, 8 and 11 TBARS values were significant but could not be explained by the studied factors. Therefore, we suggest the impact of other environmental factors. 5. Conclusions The concentrations of metals and S in H. physoides thalli from the Niepołomice Forest were comparable to those reported from other parts of Poland. The study confirmed that Cd and S concentrations varied depending on the season. S concentrations were higher during the heating season, suggesting a significant impact of domestic heating. In contrast, Cd concentrations were higher in the non-heating season, suggesting a significant impact of other factors, such as industrial activity, waste disposal, agricultural practices or local transport. SOD and TBARS values were also found to be higher in the non-heating season, which may be linked to increased UV radiation and low humidity, indicating oxidative stress. Location was only significant for Cd, Zn and TBARS. For Cd, the highest values were recorded in the central-eastern part of the forest, suggesting sources similar to those responsible for the seasonal differences mentioned above. The highest Zn values were found in the western and northern parts of the forest, which may indicate a strong impact of transport and agricultural acitivity. TBARS was significant only at three locations, which suggests the influence of the other environmental factors. At the westernmost sites, H. physodes was absent, whereas in other western locations, lichens exhibited elevated Pb and Cu concentrations. This indicates a significant impact of traffic-related emissions, which may also explain the high SOD activity observed there. Moreover, similar distribution of Pb and Cu indicates the influence of road transport, as well as incomplete fuel and oil combustion and the legacy of leaded gasoline use. An antagonistic spatial distribution between Pb and Cu in relation to Ca was also observed, which may reflect the protective function of its element. Higher concentrations of S, Cd and Hg as well as greater damage to lichens, were observed in the eastern part of the forest, which might be caused by local emission sources such as the energy industry, municipal and domestic combustion, or emissions related to agricultural activities. Declarations Funding The study was founded through the statutory research subvention of UKEN: BS-472/G/2018 “Ocena stanu środowiska naturalnego Puszczy Niepołomickiej w oparciu o porost Hypogymnia physodes (Nyl)”. [Assessment of the natural environment of the Niepołomice Forest based on the lichen Hypogymnia physodes (Nyl.)]. Author Contribution RK: Conceptualization, Funding acquisition, Investigation, Methodology, Writing – review & editing,IW: Formal analysis, Validation, Visualization, Writing – original draft.DK: Validation, Visualization, Writing – original draft.MA: Methodology, Writing – review & editing.LB: Methodology, Writing – review & editing.KG: Methodology, Writing – review & editing.KK: Visualization, Writing – review & editing.ŁJB: Data curation, Formal analysis, Project administration, Supervision, Writing – review & editing. Acknowledgement The study was founded through the statutory research subvention of UKEN: BS-472/G/2018 “Ocena stanu środowiska naturalnego Puszczy Niepołomickiej w oparciu o porost Hypogymnia physodes (Nyl)”. [Assessment of the natural environment of the Niepołomice Forest based on the lichen Hypogymnia physodes (Nyl.)]. Data Availability Data will be made available on request. References Alloway, B. J. Heavy metals in soils: Trace metals and metalloids in soils and their bioavailability, Environmental Pollution 22. Dordrecht, The Netherlands: Springer. (2013). Almeida, S. et al. Ambient particulate matter source apportionment using receptor modelling in European and Central Asia urban areas. Environ. Pollut. 266 (3), 115199. https://doi.org/10.1016/j.envpol.2020.115199 (2020). Al-Sabbagh, T. A. & Shreaz, S. Impact of lead pollution from vehicular traffic on highway-side grazing areas: challenges and mitigation policies. Int. J. Environ. Res. Public Health . 22 (2). https://doi.org/10.3390/ijerph22020311 (2025). Álvarez, R. et al. Lichen rehydration in heavy metal-polluted environments: Pb modulates the oxidative response of both Ramalina farinacea thalli and its isolated microalgae. Microb. Ecol. 69 , 698–709. https://doi.org/10.1007/s00248-014-0524-0 (2015). Aslan, A. et al. The assessment of lichens as bioindicator of heavy metal pollution from motor vehicles activites. Afr. J. Agric. Res. 6 (7), 1698–1706. https://doi.org/10.5897/AJAR10.331 (2011). Bačkor, M. & Fahselt, D. Lichen photobionts and metal toxicity. Symbiosis (Rehovot) . 46 (1), 1–10 (2008). Bačkor, M. & Loppi, S. Interactions of lichens with heavy metals. Biol. Plantetarum . 53 , 214–222. https://doi.org/10.1007/s10535-009-0042-y (2009). Bąbelewska, A., Musielińska, R. & Ciesielski, W. Bioindykacyjna ocena stopnia zagrożenia metalami ciężkimi zbiorowisk leśnych Załęczańskiego Parku Krajobrazowego przy wykorzystaniu zdolności kumulacji plech porostu Hypogymnia physodes L. [Bioindically rating of heavy metals hazard association for land forests of the załęcze landscape park with the use of cumulation capacity of the Hypogymnia physodes L]. Prace Naukowe Akademii im Jana Długosza w Częstochowie: Technika Informatyka Inżynieria Bezpieczeństwa . 6 , 279–496. https://doi.org/10.16926/tiib.2018.06.35 (2018). Beauchamp, C. & Fridovich, I. Superoxide dismutase: improved assays and an assay applicable to acrylamide gels. Anal. Biochem. 44 (1), 276–287. https://doi.org/10.1016/0003-2697(71)90370-8 (1971). Betleja, L. & Badania morfologii plech Hypogymnia physodes (L.) Nyl. w płatach pni sosny ( Pinus silvestris ) w borach woj. Katowickiego. [Studies on the morphology of Hypogymnia physodes (L.) Nyl. thalli in pine ( Pinus silvestris ) trunk sections in forests in the Katowice Province]. In: Lipnicki L. (Ed.). V Zjazd Lichenologów Polskich, Porosty ( Lichenes ) Pszczewskiego PK. [5th Congress of Polish Lichenologists, Lichens Pszczewski PK]. Instytut Badań i Ekspertyz Naukowych, Gorzów Wielkopolski : 95–101. (1989). Bielecki, K. & Kulczycki, G. Modyfikacja metody Buttersa i Chenery’ego oznaczenia siarki ogólnej w roślinach i glebie. [Modification of Butters-Chenery method for determination of total sulfur in plants and soil]. Przemysł Chemiczny . 91 (5), 688–691 (2012). Bradford, M. M. A rapid sensitive method for the quantification of microgram quantities of protein utilizing the principle of protein-dye binding. Anal. Biochem. 72 (1–2), 248–254. https://doi.org/10.1016/0003-2697(76)90527-3 (1976). Branquinho, C., Brown, D. H., Máguas, C. & Catarino, F. Lead (Pb) uptake and its effects on membrane integrity and chlorophyll fluorescence in different lichen species. Environ. Exp. Bot. 37 (2–3), 95–105. https://doi.org/10.1016/S0098-8472(96)01038-6 (1997). Charlesworth, S., De Miguel, E. & Ordóñez, A. A review of the distribution of particulate trace elements in urban terrestrial environments and its application to considerations of risk. Environ. Geochem. Health . 33 , 103–123. https://doi.org/10.1007/s10653-010-9325-7 (2011). Ciężka, M. M. et al. The coupled study of metal concentrations and electron paramagnetic resonance (EPR) of lichens ( Hypogymnia physodes ) from the Świętokrzyski National Park—environmental implications. Environ. Sci. Pollut. Res. 25 , 25348–25362. https://doi.org/10.1007/s11356-018-2586-x (2018). Ciężka, M. M. et al. The multi-isotope biogeochemistry (S, C, N and Pb) of Hypogymnia physodes lichens: air quality approach in the Świętokrzyski National Park, Poland. Isot. Environ. Health Stud. 58 (4–6), 340–362. https://doi.org/10.1080/10256016.2022.2110591 (2022). Cui, W. et al. Occurrence and release of cadmium, chromium, and lead from stone coal combustion. Int. J. Coal Sci. Technol. 6 , 586–594. https://doi.org/10.1007/s40789-019-00281-4 (2019). Egger, R., Schlee, D. & Turk, R. Changes of physiologicaland biochemical parameters in the lichen Hypogymnia physodes (L) Nyl. due to the action of air pollutants—a field study. Phyton 34 , 229–242 (1994). Frati, L. & Brunialti, G. Recent trends and future challenges for lichen biomonitoring in forests. Forests 14 (1), 647. https://doi.org/10.3390/f14030647 (2023). Hernansanz-Agustín, P. & Enríquez, J. A. Generation of Reactive Oxygen Species by Mitochondria. Antioxidants 10 , 415. https://doi.org/10.3390/antiox10030415 (2021). Gawrońska, K. & Gołębiowska-Pikania, G. The effects of cold-hardening and Microdochium nivale infection on oxidative stress and antioxidative protection of the two contrasting genotypes of winter triticale. Eur. Food Res. Technol. 242 , 1267–1276. https://doi.org/10.1007/s00217-015-2630-8 (2016). Gawrońska, K., Romanowska, E., Miszalski, Z. & Niewiadomska, E. Limitation of C3–CAM shift in the common ice plant under high irradiance. J. Plant Physiol. 170 (2), 129–135. https://doi.org/10.1016/j.jplph.2012.09.019 (2013). Gazda, A. & Szlaga, A. Obce gatunki drzewiaste w północnym kompleksie Puszczy Niepołomickiej [Alien tree species in the northern part of the Niepołomice Forest]. Sylwan 152 (4), 58–67 (2008). Główny Inspektorat Ochrony Środowiska. Regionalny Wydział Monitoringu Środowiska w Krakowie, Departament Monitoringu Środowiska. Roczna ocena jakości powietrza w województwie małopolskim: Raport wojewódzki za rok 2019. [Annual air quality assessment in the Małopolska Province: Provincial report for 2019]. Główny Inspektorat Ochrony Środowiska (2020). Godzik, B. & Piechnik, Ł. Puszcza Niepołomicka – zrównoważona gospodarka leśna a ochrona bogactwa przyrodniczego. [The Niepołomice Forest – sustainable Forest management and protection of natural wealth]. Zjazd Polskiego Towarzystwa Botanicznego Przewodnik sesji terenowych : 183–213 (2019). Godzik, B. & Szarek, G. Heavy metals in mosses from the Niepołomice Forest, southern Poland – changes in 1975–1992. Fragmenta Floristica et Geobotanica . 38 (1), 199–208 (1993). Godzik, B. & Szarek-Łukaszewska, G. Concentrations of heavy metals in Moehringia trinervia (Caryophyllaceae) in the Niepołomice Forest (S Poland) – changes from 1984 to 1999. Pol. Bot. Stud. 19 , 43–47 (2005). Gómez, S., Vergara, M., Rivadeneira, B., Rodríguez, J. & Carpio, A. Use of lichens as bioindicators of contamination by agrochemicals and metals. Environ. Sci. Pollut. Res. 31 , 49214–49226. https://doi.org/10.1007/s11356-024-34450-z (2024). Grabowski, A. Zmiany morfologiczne koron sosny w Puszczy Niepołomickiej. [Morphological changes of pine crowns in the Niepołomice Forest]. Studia Ośrodka Dokumentacji Fizjograficznej . 9 , 357–367 (1981). Grodzińska, K. Zawartość siarki w ogólnej w szpilkach sosny zwyczajnej ( Pinus silvestris ) z Puszczy Niepołomickiej. [Total sulphur content of Scots pine ( Pinus silvestris ) pins from the Niepołomice Forest]. Studia Ośrodka Dokumentacji Fizjograficznej . 9 , 293–301 (1981). Grodzińska, K., Godzik, B., Darowska, E. & Pawłowska, B. Concentration of heavy metals in trophic chains of Niepołomice Forest. S Pol. Ekologia Polska . 35 (2), 327–344 (1987). Grodzińska, K., Szarek-Łukaszewska, G., Frontasyeva, M., Pavlov, S. S. & Gudorina, S. F. Multielement concentration in mosses in the forest influenced by industrial emissions (Niepołomice Forest, S Poland) at the end of the 20th century. Pol. J. Environ. Stud. 14 (2), 165–172 (2005). Hjortenkrans, D. S., Bergbäck, B. G. & Häggerud, A. V. Metal emissions from brake linings and tires: case studies of Stockholm, Sweden 1995/1998 and 2005. Environ. Sci. Technol. 41 (15), 5224–5230. https://doi.org/10.1021/es070198o (2007). Huang, D. et al. Effects of calcium at toxic concentrations of cadmium in plants. Planta 245 , 863–873. https://doi.org/10.1007/s00425-017-2664-1 (2017). Hutton, M. Sources of cadmium in the environment. Ecotoxicol. Environ. Saf. 7 (1), 9–24. https://doi.org/10.1016/0147-6513(83)90044-1 (1983). Inspektorat Ochrony & Środowiska Krajowy raport mozaikowy o stanie środowiska. [National mosaic report on the state of the environment.] Wojewódzki Inspektorat Ochrony Środowiska Kraków , Kraków. (2007). Jackson, T. A. Long-range atmospheric transport of mercury to ecosystems, and the importance of anthropogenic emissions—a critical review and evaluation of the published evidence. Environ. Reviews . 5 (2). https://doi.org/10.1139/a97-005 (1997). Jeong, H. Toxic metal concentrations and Cu–Zn–Pb isotopic compositions in tires. J. Anal. Sci. Technol. 13 (2). https://doi.org/10.1186/s40543-021-00312-3 (2022). Johansson, L. S., Tullin, C., Leckner, B. & Sjövall, P. Particle emissions from biomass combustion in small combustors. Biomass Bioenerg. 25 (4), 435–446. https://doi.org/10.1016/S0961-9534(03)00036-9 (2003). Jóźwiak, M. Kumulacja metali ciężkich i zmiany morfologiczne w plechach porostu Hypogymnia physodes (L.)Nyl. [Accumulation of heavy metals and morphological changes in thalli of Hypogymnia physodes (L.)Nyl.) lichen]. Monit. Środowiska Przyrodniczego . 8 , 51–56 (2007). Kapusta, P., Stanek, M., Szarek-Łukaszewska, G. & Godzik, B. Long-term moss monitoring of atmospheric deposition near a large steelworks reveals the growing importance of local non-industrial sources of pollution. Chemosphere 230 , 29–39 (2019). Kapusta, P., Szarek-Łukaszewska, G. & Kiszka, J. Spatial analysis of lichen species richness in a disturbed ecosystem (Niepołomice Forest, S Poland). Lichenologist 36 (3–4), 249–260 (2004). Kiszka, J. Porosty Kotliny Sandomierskiej. Część I. Porosty Okręgu Puszczy Niepołomickiej [The lichens of the Sandomierz Lowland. Part I: Lichens of Niepołomice Forest district]. Fragmenta Floristica et Geobotanica . 10 (4), 527–564 (1964). Kiszka, J. Bioindykacja środowiska przyrodniczego na przykładzie porostów w Krakowie i Puszczy Niepołomickiej. [Bioindication of the natural environment on the example of lichens of Cracow and the Niepołomice Forest]. In: W. Grodziński, W. Juszczyk, J. Kiszka, A. Medwecka-Kornaś (Ed.). Problemy ekologiczne i fizjologiczne w ochronie środowiska makroregionu Południowego. [Ecological and physiological problems in the protection of the environment of the Southern macro-region]. Sympozjum „Człowiek i Środowisko, Sesja XXX-lecia PRL : 11–17. (1974). Kiszka, J. Wpływ emisji miejskich i przemysłowych na florę porostów (Lichenes) Krakowa i Puszczy Niepołomickiej. [Influence of urban and industrial emissions on the lichen flora (Lichenes) of Kraków and the Niepołomice Forest]. Prace Monograficzne Wyższej Szkoły Pedagogicznej w Krakowie . 19 , 5–32 (1977). Kiszka, J. Porosty rezerwatu Lipówka w Puszczy Niepołomickiej [The lichens in the forest reserve of Lipówka in the Niepołomice Forest]. Studia Nat. Seria A . 17 , 149–158 (1978). Kiszka, J. Lichens. In: K. Grodzińska (Ed.). Acidification of forest environment (Niepołomice Forest) caused by SO2 emissions from steel mills (Final report on investigations from the period July 1.1976-June 30.). Institute of Botany Polish Academy of Sciences, Cracow : 86–89. (1980). Kiszka, J. Flora porostów (Lichenes) Puszczy Niepołomickiej. [Flora of lichens (Lichenes) of the Niepołomice Forest]. Studia Ośrodka Dokumentacji Fizjograficznej . 9 , 335–356 (1981). Kiszka, J. Lichenoindykacja obszaru województwa krakowskiego. [Licheno-indication of the area of the Cracow voivodeship]. Studia Ośrodka Dokumentacji Fizjograficznej . 18 , 201–212 (1990). Kiszka, J. & Grodzińska, K. Lichen flora and air pollution in the Niepolomice Forest (S Poland) in 1960 – 200. Biol. (Bratislava) . 59 (1), 25–37 (2004). ISSN 0006-3088. Kováčik, J., Dresler, S., Babula, P. & HladkýJ., Sowa, I. Calcium has protective impact on cadmium-induced toxicity in lichens. Plant Physiol. Biochem. 156 , 591–599. https://doi.org/10.1016/j.plaphy.2020.10.007 (2020). Laemmli, U. K. Cleavage of structural proteins during the assembly of the head of bacteriophage T4. Nature 227 , 680–685. https://doi.org/10.1038/227680a0 (1970). Lin, C. K. et al. A Global Perspective on Sulfur Oxide Controls in Coal-Fired Power Plants and Cardiovascular Disease. Sci. Rep. 8 , 2611. https://doi.org/10.1038/s41598-018-20404-2 (2018). Lucadamo, L., Gallo, L. & Corapi, A. Detection of air quality improvement within a suburban district (southern Italy) by means of lichen biomonitoring. Atmospheric Pollution Res. 13 (3), 101346. https://doi.org/10.1016/j.apr.2022.101346 (2022). Maring, T., Kumar, S., Jha, A. K., Kumar, N. & Pandey, S. P. Airborne Particulate Matter and Associated Heavy Metals: A Review. Macromolecular Symposia . 407 , 2100487. https://doi.org/10.1002/masy.202100487 (2023). Marumoto, K., Hayashi, M. & Takami, A. Atmospheric mercury concentrations at two sites in the Kyushu Islands, Japan, and evidence of long-range transport from East Asia. Atmos. Environ. 117 , 147–155. https://doi.org/10.1016/j.atmosenv.2015.07.019 (2015). Masindi, V., Mkhonza, P. & Tekere, M. Sources of heavy metals pollution. In: Inamuddin, Ahamed M.I., Lichtfouse E., Altalhi T. (Ed.). Remediation of heavy metals. environmental chemistry for a sustainable world 70. Springer , Cham: 419–454. (2021). https://doi.org/10.1007/978-3-030-80334-6_17 Matei, E. et al. Covaliu-Mierlă C.I. Heavy metals in particulate matter—trends and impacts on environment. Molecules 30 (7), 1455. https://doi.org/10.3390/molecules30071455 (2025). Ministerstwo Klimatu i Środowiska. Krajowy bilans emisji SO2, NOX, CO, NH3, NMLZO, pyłów, metali ciężkich i TZO za lata 1990–2018. Raport syntetyczny. [National emissions balance of SO2, NOX, CO, NH3, NMLZO, dust, heavy metals and TZO for the period 1990–2018. Synthesis report]. Krajowy Ośrodek Inwentaryzacji i Raportowania Emisji, Instytut Ochrony Środowiska – Państwowy Instytut Badawczy, Warszawa. (2020). Ministerstwo Klimatu i Środowiska. Krajowy bilans emisji SO2, NOX, CO, NH3, NMLZO, pyłów, metali ciężkich i TZO za lata 1990–2019. Raport syntetyczny. [National emissions balance of SO2, NOX, CO, NH3, NMLZO, dust, heavy metals and TZO for the period 1990–2019. Synthesis report]. Krajowy Ośrodek Inwentaryzacji i Raportowania Emisji, Instytut Ochrony Środowiska – Państwowy Instytut Badawczy, Warszawa. (2021). Mittler, R. Oxidative stress, antioxidants and stress tolerance. Trends Plant Sci. 7 (9), 405–410. https://doi.org/10.1016/S1360-1385(02)02312-9 (2002). Nimis, P. L., Lazzarin, G., Lazzarin, A. & Skert, N. Biomonitoring of trace elements with lichens in Veneto (NE Italy). Sci. Total Environ. 255 (1–3), 97–111. https://doi.org/10.1016/S0048-9697(00)00454-X (2000). Nzihou, A. & Stanmore, B. The fate of heavy metals during combustion and gasification of contaminated biomass - A brief review. J. Hazard. Mater. 256–257 , 56–66. https://doi.org/10.1016/j.jhazmat.2013.02.050 (2013). Olivia, S. R. & Rautio, P. Could ornamental plants serve as passive biomonitors in urban area? J. Atmos. Chem. 49 , 137–148. https://doi.org/10.1007/s10874-004-1220-0 (2004). Osyczka, P., Chowaniec, K. & Skubała, K. Membrane lipid peroxidation in lichens determined by the TBARS assay as a suitable biomarker for the prediction of elevated level of potentially toxic trace elements in soil. Ecol. Ind. 146 , 109910. https://doi.org/10.1016/j.ecolind.2023.109910 (2023). Purvis, O. W. & Pawlik-Skowrońska, B. Lichens and metals. Br. Mycological Soc. Symposia Ser. 27 , 175–200. https://doi.org/10.1016/S0275-0287(08)80054-9 (2008). Qu, Y., An, J., He, Y. & Zheng, J. An overview of emissions of SO2 and NOx and the long-range transport of oxidized sulfur and nitrogen pollutants in East Asia. J. Environ. Sci. 44 , 13–25. https://doi.org/10.1016/j.jes.2015.08.028 (2016). R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL (2020). https://www.R-project.org/ Ručová, D. et al. Investigation of Calcium Forms in Lichens from Travertine Sites. Plants 11, 620. (2022). https://doi.org/10.3390/plants11050620 Santos, A. M. D. et al. Impacts of Cd Pollution on the Vitality, Anatomy and Physiology of Two Morphologically Different Lichen Species of the Genera Parmotrema and Usnea. Evaluated under Experimental Conditions Divers. 14 , 926. https://doi.org/10.3390/d14110926 (2022). Sawicka-Kapusta, K., Zakrzewska, M., Dudzik, P. & Gołuszka, K. Zanieczyszczenia powietrza Stacji Bazowych ZMSP w 2011 roku na podstawie koncentracji metali ciężkich i siarki w plechach porostu Hypogymnia physodes zebranych z naturalnego środowiska. [Air pollution of the base stations of the Integrated Monitoring of Natural Environment in 2011 on the basis of heavy metals and sulphur concentration in lichen Hypogymnia physodes collected from natural environment]. Monit. Środowiska Przyrodniczego . 16 , 49–57 (2014). Sawicka-Kapusta, K., Zakrzewska, M., Gdula-Argasińska, J. & Bydłoń, G. Air pollution in the base stations of the environmental integrated monitoring system in Poland. In: Brebbia C.A. (Ed.) Air Pollution XIII. WIT Transaction on Ecology and the Environment 82: 465–475. ISSN 1743–3541. (2005). Seaward, M. R. D. Lichens and sulphur dioxide air pollution: field studies. Environ. Reviews . 1 (2). https://doi.org/10.1139/a93-007 (1993). Shikhovtsev, M. Y. et al. Features of temporal variability of the concentrations of gaseous trace pollutants in the air of the urban and rural areas in the Southern Baikal region (East Siberia, Russia). Appl. Sci. 14 (18), 8327. https://doi.org/10.3390/app14188327 (2024). Sigler, J. M., Lee, X. & Munger, W. Emission and long-range transport of gaseous mercury from a large-scale Canadian boreal forest fire. Environ. Sci. Technol. 37 (19), 4343–4347. https://doi.org/10.1021/es026401r (2003). Sippula, O., Hokkinen, J., Puustinen, H., Yli-Pirilä, P. & Jokiniemi, J. Comparison of particle emissions from small heavy fuel oil and wood-fired boilers. Atmospheric Environ. 43 (32), 4855–4864. https://doi.org/10.1016/j.atmosenv.2009.07.022 (2009). Szarek-Łukaszewska, G., Grodzińska, K. & Braniewski, S. Heavy metal concentration in the moss Pleurozium Schreberi in the Niepołomice Forest, Poland: changes during 20 years. Environ. Monit. Assess. 79 , 231–237. https://doi.org/10.1023/A:1020226526451 (2002). Świetlik, R., Trojanowska, M. & Rabek, P. Distribution patterns of Cd, Cu, Mn, Pb and Zn in wood fly ash emitted from domestic boilers. Chem. Speciat. Bioavailab. 35 (1), 63–70. https://doi.org/10.3184/095422912X13497968675047 (2012). Thakur, M., Bhardwaj, S., Kumar, V. & Rodrigo-Comino, J. Lichens as effective bioindicators for monitoring environmental changes: A comprehensive review. Total Environ. Adv. 9 , 200085. https://doi.org/10.1016/j.teadva.2023.200085 (2024). Turhan, S. B., Oruc, I. & Ozdemir, H. Impact of heating season on the soil pollution in Kirklareli province of Turkey. Environ. Monit. Assess. 193 , 209. https://doi.org/10.1007/s10661-021-09002-4 (2021). Uchwała nr XVIII/243/16 Sejmiku. XVIII/243/16 of the Sejmik of the Małopolskie Voivodeship of 15.01.2016. On the introduction in the area of the Municipality of Krakow of restrictions on the operation of installations in which fuel is burned] (Poland, 2016). Województwa Małopolskiego z dnia 15.01.2016. W sprawie wprowadzenia na obszarze Gminy Miejskiej Kraków ograniczeń w zakresie ekspoatacji instalacji, w których następuje spalanie paliw. [Resolution No. Weiner, J., Fredro-Boniecki, S., Reed, D., Maclean, A. & Strong, M. Niepołomice Forest - a GIS analysis of ecosystem response to industrial pollution. Environ. Pollut. 98 (3), 381–388. https://doi.org/10.1016/S0269-7491(97)00152-8 (1997). Wiseman, R. D. & Wadleigh, M. A. Lichen response to changes in atmospheric sulphur: isotopic evidence. Environmental Pollution 116(2): 235–241. (2002). https://doi.org/10.1016/S0269-7491(01)00133-6 (2002). Wojewódzki Inspektorat Ochrony Środowiska w Krakowie. Raport o stanie środowiska w województwie małopolskim w 2016 roku. [Report on the state of the environment in the Małopolskie Voivodeship in 2016] (Wojewódzki Inspektorat Ochrony Środowiska w Krakowie, 2017). Xiao, H., Carmichael, G. R., Durchenwald, J., Thornton, D. & Bandy, A. Long-range transport of SOx and dust in East Asia during the PEM B Experiment. J. Geophys. Research: Atmos. 102 (D23), 28589–28612. https://doi.org/10.1029/96JD03782 (1997). Zeedijk, H. & Velds, C. A. The transport of sulphur dioxide over a long distance. Atmospheric Environ. 7 (9), 849–862. https://doi.org/10.1016/0004-6981(73)90107-8 (1973). Climate-Data.org. Klimat: Niepołomice . Climate-Data.org. (2025). https://pl.climate-data.org/europa/polska/lesser-poland-voivodeship/niepołomice-10403/ . [access 10-05-2025]. Additional Declarations No competing interests reported. Supplementary Files Supplementarymaterials.pdf Cite Share Download PDF Status: Published Journal Publication published 22 Dec, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 04 Nov, 2025 Reviews received at journal 29 Oct, 2025 Reviews received at journal 27 Oct, 2025 Reviewers agreed at journal 24 Oct, 2025 Reviewers agreed at journal 24 Oct, 2025 Reviewers agreed at journal 22 Oct, 2025 Reviewers agreed at journal 22 Oct, 2025 Reviewers agreed at journal 21 Oct, 2025 Reviewers agreed at journal 21 Oct, 2025 Reviewers agreed at journal 21 Oct, 2025 Reviewers agreed at journal 21 Oct, 2025 Reviewers invited by journal 21 Oct, 2025 Editor invited by journal 30 Sep, 2025 Editor assigned by journal 29 Sep, 2025 Submission checks completed at journal 26 Sep, 2025 First submitted to journal 26 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-7719127\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Article\",\"associatedPublications\":[],\"authors\":[{\"id\":536849720,\"identity\":\"23b7b6d7-b0db-4888-a8e2-0f66209f906c\",\"order_by\":0,\"name\":\"Robert Kościelniak\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of the National Education Commission\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Robert\",\"middleName\":\"\",\"lastName\":\"Kościelniak\",\"suffix\":\"\"},{\"id\":536849722,\"identity\":\"7cd0a50b-5c88-4cfa-a475-eba31a7af411\",\"order_by\":1,\"name\":\"Izabela Wiśniowska\",\"email\":\"data:image/png;base64,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\",\"orcid\":\"\",\"institution\":\"University of the National Education Commission\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Izabela\",\"middleName\":\"\",\"lastName\":\"Wiśniowska\",\"suffix\":\"\"},{\"id\":536849723,\"identity\":\"4ce0c6d2-7cfd-49fa-a449-3aebf9a4001e\",\"order_by\":2,\"name\":\"Danuta Kadłub\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of the National Education Commission\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Danuta\",\"middleName\":\"\",\"lastName\":\"Kadłub\",\"suffix\":\"\"},{\"id\":536849725,\"identity\":\"340884d2-90c7-41e9-9f97-c448762e8b3b\",\"order_by\":3,\"name\":\"Marzena Albrycht\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of the National Education Commission\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Marzena\",\"middleName\":\"\",\"lastName\":\"Albrycht\",\"suffix\":\"\"},{\"id\":536849727,\"identity\":\"1168491d-a15f-49b4-b8a1-3c8e84f1f314\",\"order_by\":4,\"name\":\"Laura Betleja\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of the National Education Commission\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Laura\",\"middleName\":\"\",\"lastName\":\"Betleja\",\"suffix\":\"\"},{\"id\":536849731,\"identity\":\"f4d60878-d0f1-4dbb-815c-38341620907b\",\"order_by\":5,\"name\":\"Katarzyna Gawrońska\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of the National Education Commission\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Katarzyna\",\"middleName\":\"\",\"lastName\":\"Gawrońska\",\"suffix\":\"\"},{\"id\":536849735,\"identity\":\"54cbb812-636b-42ef-9fb6-75c2e17fd059\",\"order_by\":6,\"name\":\"Katarzyna Kucharska\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of the National Education Commission\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Katarzyna\",\"middleName\":\"\",\"lastName\":\"Kucharska\",\"suffix\":\"\"},{\"id\":536849741,\"identity\":\"6291fb75-ce01-4450-bcdf-96cdd359639e\",\"order_by\":7,\"name\":\"Łukasz J. Binkowski\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of the National Education Commission\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Łukasz\",\"middleName\":\"J.\",\"lastName\":\"Binkowski\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2025-09-26 07:53:26\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-7719127/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-7719127/v1\",\"draftVersion\":[],\"editorialEvents\":[{\"content\":\"https://doi.org/10.1038/s41598-025-31463-7\",\"type\":\"published\",\"date\":\"2025-12-22T15:57:46+00:00\"}],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":94986113,\"identity\":\"9606b30a-786f-49a1-a0ab-9badf985ff45\",\"added_by\":\"auto\",\"created_at\":\"2025-11-03 06:59:47\",\"extension\":\"docx\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"acdc-reference\",\"size\":789940,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"20250926Manuscript.docx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7719127/v1/03b9eb436bbac462006db405.docx\"},{\"id\":94881567,\"identity\":\"f8330261-6aeb-4752-96dd-626652b4cecf\",\"added_by\":\"auto\",\"created_at\":\"2025-10-31 17:04:30\",\"extension\":\"json\",\"order_by\":1,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"acdc-reference\",\"size\":9260,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"ad4274b7308e484ca892a1785df8c10c.json\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7719127/v1/108462cc97d5f63f658df380.json\"},{\"id\":94881568,\"identity\":\"52b51f10-286f-47d2-bc7f-db107d8f4d5e\",\"added_by\":\"auto\",\"created_at\":\"2025-10-31 17:04:30\",\"extension\":\"pdf\",\"order_by\":2,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"acdc-reference\",\"size\":305792,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"Supplementarymaterials.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7719127/v1/f1b1f6f17b9fe290ac64b4d4.pdf\"},{\"id\":94881570,\"identity\":\"dd9cf5ac-5285-420b-96ef-bb203a233701\",\"added_by\":\"auto\",\"created_at\":\"2025-10-31 17:04:30\",\"extension\":\"xml\",\"order_by\":3,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"acdc-reference\",\"size\":188885,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"ad4274b7308e484ca892a1785df8c10c1enriched.xml\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7719127/v1/bf5c59fe87bad9d2a6bbd572.xml\"},{\"id\":94986729,\"identity\":\"e6971781-179d-4406-b695-381e296153b8\",\"added_by\":\"auto\",\"created_at\":\"2025-11-03 07:00:41\",\"extension\":\"png\",\"order_by\":7,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"acdc-reference\",\"size\":182436,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"Onlinefloatimage1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7719127/v1/a6d345d0293d653529099afd.png\"},{\"id\":94881576,\"identity\":\"661d9a4f-7924-40f9-be5f-f8c360ee6705\",\"added_by\":\"auto\",\"created_at\":\"2025-10-31 17:04:30\",\"extension\":\"png\",\"order_by\":8,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"acdc-reference\",\"size\":85674,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"Onlinefloatimage2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7719127/v1/1db12b6c9981e573a581f08c.png\"},{\"id\":94881571,\"identity\":\"9c51d6ad-0573-4539-b8e5-5db2fc9b0be9\",\"added_by\":\"auto\",\"created_at\":\"2025-10-31 17:04:30\",\"extension\":\"png\",\"order_by\":9,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"acdc-reference\",\"size\":71152,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"Onlinefloatimage3.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7719127/v1/f63bd0c44ef402b8d6176e8c.png\"},{\"id\":94881575,\"identity\":\"b0616ebd-0f5b-4eca-9630-a7ee4701606e\",\"added_by\":\"auto\",\"created_at\":\"2025-10-31 17:04:30\",\"extension\":\"xml\",\"order_by\":10,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"acdc-reference\",\"size\":191087,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"ad4274b7308e484ca892a1785df8c10c1structuring.xml\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7719127/v1/95e00007d0037090cb2e8e43.xml\"},{\"id\":94986833,\"identity\":\"da29d462-be81-4ac6-ade5-5aef0c174cec\",\"added_by\":\"auto\",\"created_at\":\"2025-11-03 07:00:51\",\"extension\":\"html\",\"order_by\":11,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"acdc-reference\",\"size\":203863,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"earlyproof.html\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7719127/v1/6c208ac77e3c04ca722fdcb7.html\"},{\"id\":94881565,\"identity\":\"315abb02-8ec6-4976-9e38-44e67317c456\",\"added_by\":\"auto\",\"created_at\":\"2025-10-31 17:04:29\",\"extension\":\"jpeg\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":241839,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eThe Niepołomice Forest (southern Poland, Europe) with sampling sites of \\u003cem\\u003eH. physodes\\u003c/em\\u003e.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage1.jpeg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7719127/v1/748b7481f61038142de451c4.jpeg\"},{\"id\":94986004,\"identity\":\"8d059814-46fb-42ac-a6df-4cfe99b62aec\",\"added_by\":\"auto\",\"created_at\":\"2025-11-03 06:59:32\",\"extension\":\"jpeg\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":137582,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eSpatial distribution of Cd, S, SOD and TBARS in \\u003cem\\u003eH. physodes\\u003c/em\\u003e showing statistically significant seasonal differences in the Niepołomice Forest.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage2.jpeg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7719127/v1/0e2e9b93aaa0f08ccdedee77.jpeg\"},{\"id\":94881573,\"identity\":\"2845cac9-4a12-4519-8b7f-e91a3e10347a\",\"added_by\":\"auto\",\"created_at\":\"2025-10-31 17:04:30\",\"extension\":\"jpeg\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":258036,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eSpatial distribution of Cd and Zn concentrations and TBARS in \\u003cem\\u003eH. physodes\\u003c/em\\u003e, the only elements showing statistically significant spatial variation in the Niepołomice Forest.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage3.jpeg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7719127/v1/a2801b3dbb941e8d6a5e819d.jpeg\"},{\"id\":99172313,\"identity\":\"50bfd9af-9fe0-4c4c-8c32-6bc6e15beeb1\",\"added_by\":\"auto\",\"created_at\":\"2025-12-29 16:07:41\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":1693209,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7719127/v1/68e329ef-050c-4a52-8b99-7dc6a9c0cc89.pdf\"},{\"id\":94881564,\"identity\":\"8d645bb6-b29b-419f-9c11-efd60d7a245f\",\"added_by\":\"auto\",\"created_at\":\"2025-10-31 17:04:29\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":305792,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"Supplementarymaterials.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7719127/v1/d29e71949034c24e0fa65497.pdf\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Temporal and spatial characteristics of the composition of Hypogymnia physodes (Monk’s-hood lichen) from the Niepołomice Forest in Poland\",\"fulltext\":[{\"header\":\"1. Introduction\",\"content\":\"\\u003cp\\u003eSince the mid-20th century, the Niepołomice Forest has been affected by incoming pollution, caused mainly by the development of the urban-industrial agglomeration of Krak\\u0026oacute;w (Weiner et al., \\u003cspan citationid=\\\"CR82\\\" class=\\\"CitationRef\\\"\\u003e1997\\u003c/span\\u003e) and other heavily polluted cities such as Tarn\\u0026oacute;w and Nowy Sącz (Wojew\\u0026oacute;dzki Inspektorat Ochrony Środowiska w Krakowie, \\u003cspan citationid=\\\"CR84\\\" class=\\\"CitationRef\\\"\\u003e2017\\u003c/span\\u003e). The location of the pollution sources, together with the prevailing westerly winds carrying pollution from the Krak\\u0026oacute;w agglomeration towards the forest, have created a pollution gradient in the area, intensifying the environmental pressure on this ecosystem (Kiszka, \\u003cspan citationid=\\\"CR49\\\" class=\\\"CitationRef\\\"\\u003e1990\\u003c/span\\u003e; Kiszka and Grodzińska \\u003cspan citationid=\\\"CR50\\\" class=\\\"CitationRef\\\"\\u003e2004\\u003c/span\\u003e). Therefore, the forest is a suitable place to study long-term ecological and environmental impacts of air pollution. These impacts have already been monitored using various groups of organisms, including mosses, trees and soil invertebrates (Grabowski, \\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e1981\\u003c/span\\u003e; Grodzińska, \\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e1981\\u003c/span\\u003e; Grodzińska et al., \\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e1987\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e2005\\u003c/span\\u003e; Godzik and Szarek, \\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e1993\\u003c/span\\u003e; Godzik and Szarek-Łukaszewska, \\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e2005\\u003c/span\\u003e; Kapusta et al., \\u003cspan citationid=\\\"CR41\\\" class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e). One of the key bioindicator groups used to track environmental changes in the Niepołomice Forest has been lichens (Kiszka, \\u003cspan citationid=\\\"CR45\\\" class=\\\"CitationRef\\\"\\u003e1977\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR47\\\" class=\\\"CitationRef\\\"\\u003e1980\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR49\\\" class=\\\"CitationRef\\\"\\u003e1990\\u003c/span\\u003e; Grodzińska, 2004; Kapusta et al., \\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e2004\\u003c/span\\u003e). Due to the lack of a protective cuticle and roots, they are susceptible to disturbance, especially air pollution (Seaward, \\u003cspan citationid=\\\"CR73\\\" class=\\\"CitationRef\\\"\\u003e1993\\u003c/span\\u003e; Purvis and Pawlik-Skowrońska, \\u003cspan citationid=\\\"CR66\\\" class=\\\"CitationRef\\\"\\u003e2008\\u003c/span\\u003e). Widespread species such as \\u003cem\\u003eHypogymnia physodes\\u003c/em\\u003e (L.) Nyl. are excellent long-term indicators of air quality (Bąbelewska et al., \\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003ePollutants can disrupt the cellular homeostasis of lichens and induce the formation of reactive oxygen species (ROS), the excessive production of which can lead to cell damage, including damage to cell membranes. These changes may also be visible externally, as deformation of the thallus, such as darkening or bleaching of their fragments, and altered structures (J\\u0026oacute;źwiak, \\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e2007\\u003c/span\\u003e). In the long term, oxidative stress leads to cell death, which is signaled by an increase in the level of Thiobarbituric Acid Reactive Substances (TBARS) in the organism (Osyczka et al., \\u003cspan citationid=\\\"CR65\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e). As a consequence, lichen populations decline and species diversity of the polluted habitat decreases (Seaward, \\u003cspan citationid=\\\"CR73\\\" class=\\\"CitationRef\\\"\\u003e1993\\u003c/span\\u003e; Kiszka and Grodzińska \\u003cspan citationid=\\\"CR50\\\" class=\\\"CitationRef\\\"\\u003e2004\\u003c/span\\u003e; Maring et al., \\u003cspan citationid=\\\"CR55\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e). To prevent this, organisms activate defense mechanisms, such as enzymatic antioxidant systems neutralizing ROS. One of the key enzymes involved is Superoxide Dismutase (SOD), whose increased activity converts superoxide anions into less reactive oxygen species, thereby limiting cell damage (Bačkor and Fahselt \\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e2008\\u003c/span\\u003e; \\u0026Aacute;lvarez et al., \\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e2015\\u003c/span\\u003e; Lucadamo et al., \\u003cspan citationid=\\\"CR54\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e). This enzymatic response plays an important role when lichens are exposed to environmental pollutants, such as chemical compounds and individual elements, particularly metals (Thakur et al., \\u003cspan citationid=\\\"CR79\\\" class=\\\"CitationRef\\\"\\u003e2024\\u003c/span\\u003e). Metals, based on function, can be divided into those that are essential for life (e.g., calcium (Ca), copper (Cu), iron (Fe) and zinc (Zn)) and non-essential ones, which have no role in organisms (e.g., cadmium (Cd), lead (Pb) and mercury (Hg)) (Masindi et al., \\u003cspan citationid=\\\"CR57\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e, Rucov\\u0026aacute; et al., 2021, Matei et al., \\u003cspan citationid=\\\"CR58\\\" class=\\\"CitationRef\\\"\\u003e2025\\u003c/span\\u003e). In addition to metals, sulfur and its oxides also exert harmful effect, especially during the heating season, when fuel combustion in households significantly increases their emissions into the atmosphere. Nowadays, in the environment concentrations of most of these pollutants stem from anthropogenic sources, such as traffic, industrial activities and domestic heating (Charlesworth et al., \\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e2011\\u003c/span\\u003e, Alloway, \\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e2013\\u003c/span\\u003e, Turhan et al., \\u003cspan citationid=\\\"CR80\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e), with their levels varying seasonally (Frati and Brunialti, \\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e; Thakur et al., \\u003cspan citationid=\\\"CR79\\\" class=\\\"CitationRef\\\"\\u003e2024\\u003c/span\\u003e). The heating season is characterized by increased emissions of particulate matter and heavy metals from domestic and industrial heating systems (Turhan et al., \\u003cspan citationid=\\\"CR80\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e). The distribution of these emission sources may cause site-specific differences in pollution levels, resulting in distinct spatial patterns of lichen pollution. Recognizing these patterns helps to identify the areas most vulnerable to harmful deposition, pinpoint the largest sources, and thus target potential protective measures.\\u003c/p\\u003e\\u003cp\\u003eResearch on lichens in the Niepołomice Forest began as early as the 1960s, leading to the classification of the larger part of the forest as moderately polluted, except for a stronger polluted small enclave in the western part of the southern complex (Kiszka, \\u003cspan citationid=\\\"CR43\\\" class=\\\"CitationRef\\\"\\u003e1964\\u003c/span\\u003e; Kiszka, and Grodzińska, \\u003cspan citationid=\\\"CR50\\\" class=\\\"CitationRef\\\"\\u003e2004\\u003c/span\\u003e). Since the 1970s, the extent of the moderately polluted zone has decreased as a result of increasing industrial emissions. Consequently, a decline in many sensitive species and noticeable damage to lichens were recorded (Kiszka, \\u003cspan citationid=\\\"CR44\\\" class=\\\"CitationRef\\\"\\u003e1974\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR46\\\" class=\\\"CitationRef\\\"\\u003e1978\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR47\\\" class=\\\"CitationRef\\\"\\u003e1980\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR48\\\" class=\\\"CitationRef\\\"\\u003e1981\\u003c/span\\u003e; Kiszka and Grodzińska, \\u003cspan citationid=\\\"CR50\\\" class=\\\"CitationRef\\\"\\u003e2004\\u003c/span\\u003e). Lichen-based surveys conducted in the 1990s showed that the western part of the forest had shifted into the very heavily polluted zone, while the area classified as moderately polluted expanded at the expense of the strongly polluted zone (Kiszka, \\u003cspan citationid=\\\"CR49\\\" class=\\\"CitationRef\\\"\\u003e1990\\u003c/span\\u003e; Kiszka and Grodzińska, \\u003cspan citationid=\\\"CR50\\\" class=\\\"CitationRef\\\"\\u003e2004\\u003c/span\\u003e). The last lichen studies in the Niepołomice Forest were carried out 20 years ago (Kapusta et al., \\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e2004\\u003c/span\\u003e). Since then, air protection policies, industrial activity, and transportation intensity have undergone significant changes. It remains unclear how these changes have influenced lichen condition and whether the current pollution levels are reflected in their physiological state. Additionally, until now, no measurements of TBARS levels or SOD activity have been performed for lichens in this area, limiting a more complete understanding of their exposure and responses in the Niepołomice Forest.\\u003c/p\\u003e\\u003cp\\u003eIn this context, we conducted the study to assess the impact of air pollution within the Niepołomice Forest on the monk's-hood lichen (\\u003cem\\u003eHypogymnia physodes\\u003c/em\\u003e L. Nyl.). We measured concentrations of eight elements: Ca, Cd, Cu, Fe, Hg Pb, S and Zn in thalli sampled three times over a one year period: April 2018, October 2018 and April 2019, covering both heating and non-heating seasons. In addition to elements, we also measured the activity of SOD, TBARS level, as well as the proportion of dead algae in the thallus as markers of lichen condition. The data were analyzed using a multivariate approach and GIS visualization. Based on the collected information, we were able to address the following hypotheses: (1) the concentrations of elements, the activity of SOD and TBARS level depend on the season; (2) the above-mentioned parameters reveal spatial variability; (3) all the parameters are linked to the thallus condition. We expected both spatial and seasonal variability in the measured parameters, with a particular focus on the negative influence of non-essential elements (especially Cd, Hg, and Pb), associated with increased oxidative stress response and, consequently, deterioration of the condition of lichens.\\u003c/p\\u003e\"},{\"header\":\"2. Materials and methods\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003e2.1 Study site\\u003c/h2\\u003e\\u003cp\\u003eThe study was conducted in the area of the Niepołomice Forest (49\\u0026deg;59\\u0026prime;-50\\u0026deg;07\\u0026prime;N, 20\\u0026deg;13\\u0026prime;-20\\u0026deg;28\\u0026prime;E) in southern Poland, Europe (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). It is a complex of several forest areas covering an area of 110 km\\u003csup\\u003e2\\u003c/sup\\u003e, located east of Krak\\u0026oacute;w agglomeration in the western part of the Sandomierz Basin. It is dominated by pine and mixed oak-pine (Pino-Quercetum) as well as oak-hornbeam (Tilio-Carpinetum) forests (Kapusta et al. \\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e2004\\u003c/span\\u003e), whose current stands have been shaped by human management (Gazda and Szlaga \\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e2008\\u003c/span\\u003e). The area is characterized by little variation in relief (Godzik and Piechnik \\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003e\\u003c/p\\u003e\\u003cp\\u003eThe highest temperatures in the area occur in July (average of 18.4\\u0026deg;C) and the lowest (-2.6\\u0026deg;C) are recorded in January (Climate-Data, 2025). Summer lasts up to 100 days andwinter up to 85 days. Average annual precipitation ranges from 560 to 700 mm, with rainfall recorded on 160\\u0026ndash;170 days per year. Snowfall occurs on about 45 days, and the average duration of snow cover is 110 to 120 days (Godzik, Piechnik \\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e). The climate of the Niepołomice area is characterized by frequent occurrence of fog and temperature inversion, which significantly reduce the number of sunny days, especially in autumn and spring (Climate-Data, 2025).\\u003c/p\\u003e\\u003cp\\u003eThe research was conducted in the southern, largest part of the complex, covering an area of approximately 85 km\\u003csup\\u003e2\\u003c/sup\\u003e. In this area, 20 evenly distributed survey plots were initially selected, with their final location determined after field verification. In the western part of the Forest, representing about 20% of the planned study area, no \\u003cem\\u003eH. physodes\\u003c/em\\u003e were found. Consequently, the number of study sites was reduced to 15 (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e).\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec4\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003e2.2 Sampling\\u003c/h2\\u003e\\u003cp\\u003e\\u003cem\\u003eHypogymnia physodes\\u003c/em\\u003e thalli were sampled after the end of the heating season (April 2018 and 2019), and before the start of the heating season (October 2018). Considering the accumulation time of pollutants, we categorized these samplings as heating and non-heating seasons, respectively. Samples were collected from pine (\\u003cem\\u003ePinus sylvestris\\u003c/em\\u003e L.) trunks at heights of 50 cm and 2 m above ground. Depending on the site and the collection period, the number of trees sampled ranged from 1 to 15. In total, 45 samples were collected in the whole study. After collection, the samples were dried at room temperature and stored in paper envelopes.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec5\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003e2.3 Algal condition\\u003c/h2\\u003e\\u003cp\\u003eThe morpho-anatomical analysis of lichens was performed to determine the degree of thallus damage based on visible changes, according to the following criteria: 1) rosettes without disease damage, i.e. healthy, uniformly colored and morphologically intact; 2) rosettes with moderate damage, i.e. those with blackened or faded patches, excessive shrinkage, affecting no more than 50% of the rosette; 3) rosettes with severe damage, with more than 50% thallus degeneration (Betleja \\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e1989\\u003c/span\\u003e). At most sites no thalli classified to the moderate damage group were found, therefore, two groups - healthy and severely damaged - were used.\\u003c/p\\u003e\\u003cp\\u003eTo study the internal thallus morphology, microscopic preparations were made from excised fragments of thalli with a specific and fixed diameter. From each site and damage group, three randomly selected thalli were sampled, and three preparations made from the middle part and both margins of each rosette. Using 40x magnification of the microscope (Delta Optical Genetic Pro), all algal cells were counted according to the following criteria: 1) healthy algae: all cells with uniformly green-colored chloroplast; 2) algal cells with damage, i.e., showing changes in chloroplast coloration (browning), degeneration in the form of shrinking, fragmentation, and with signs of plasmolysis; 3) dead algal cells lacking chloroplast content (Betleja \\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e1989\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003eThe obtained numerical data on the external and internal morphology of the thalli were presented as percentages for each group (damaged and dead algal cells are grouped into one category).\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec6\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003e2.4 Elemental analysis\\u003c/h2\\u003e\\u003cp\\u003eAir-dried samples were used in three separate protocols to measure Hg, other metals, and S consecutively. Hg concentrations were determined using a cold vapor atomic absorption spectrometer (MA-2, Nippon, Japan) in sub-samples of ca. 50 mg. Three, finally averaged replicates were performed for each lichen sample. During the measurements, quality control was performed using a standard solution of mercury (II) chloride (HgCl\\u003csub\\u003e2\\u003c/sub\\u003e, 100 ug/ml, Nippon, Japan) diluted to 0.01 ug/ml. If the RSD between results of triplicates was higher than 15%, the sample was reanalyzed.\\u003c/p\\u003e\\u003cp\\u003eFor quantification of other metals, air-dried samples were further dried (at 60\\u0026deg;C for 72 hours) and aliquots of 2 g were mineralized in an open digestion system (Velp Scientifica, DK-20) using ultrapure nitric acid (Baker Instra, 65%) and ultrapure perchloric acid (Sigma-Aldrich, 70%) in a 4:1 volume ratio, kept first at 140\\u0026deg;C (ca. 2 hours) and then at 160\\u0026deg;C (ca. 20 hours). The mineralized solution was diluted with ultrapure water (Direct Q-3, Merck Millipore) to a volume of 10 ml and the concentration was measured in a flame atomic absorption spectrometer (AAnalyst 200, PerkinElmer, USA).\\u003c/p\\u003e\\u003cp\\u003eAnother part of the sample (approx. 80 mg) was used to measure sulfur concentrations using the modified Butters-Chenery method (Bielecki, Kulczycki \\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e2012\\u003c/span\\u003e). Briefly, a sample was mineralized in the presence of an oxidizing agent, leading to the conversion of sulfur compounds into sulfates (SO₄\\u0026sup2;⁻), which are then, after reaction with barium chloride (BaCl₂), quantified turbidimetrically using a spectrophotometer (Evolution 260 Bio UV-Visible Spectrophotometer, Thermo Scientific, USA). The results were expressed as micrograms per gram of fresh weight of the lichen sample.\\u003c/p\\u003e\\u003cp\\u003eFor Cd, Cu, Hg, Pb and Zn, the accuracy of the method was tested against a Certified Reference Material (CRM; BCR 482, JRC, IRMM). Recoveries ranged from 97.16 for Cu to 104.65 for Zn, confirming the reliability of the analytical protocol (Table \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003e). The mean values and recoveries for the other elements are provided in the Supplementary materials (Table \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003e). Due to the lack of appropriate CRM available on the market, the accuracy of the method for Ca and Fe was tested using control solutions and spikes only.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec7\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003e2.5 Oxidative stress biomarkers\\u003c/h2\\u003e\\u003cp\\u003eBefore the analyses, the lichens were placed into distilled water for 15 min to saturate. Next, they were acclimatized in a climate chamber for 48 hours (10\\u0026deg;C, 60\\u0026ndash;70% RH, 12L:12D).\\u003c/p\\u003e\\u003cp\\u003eQuantification of thiobarbituric acid-reactive substances (TBARS) as a proxy of the extent of lipid peroxidation was assessed according to Gawrońska et al. (\\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e2013\\u003c/span\\u003e). Briefly, lichen powder (0.2 g) was homogenized in 2 mL of 0.1% trichloroacetic acid (TCA, A.C.S., POCH). Homogenates were centrifuged at 10 000\\u0026times;g for 5 min at 4\\u0026deg;C. The obtained supernatant was mixed 1:4 (v/v) with 0.5% barbituric acid solution (A.C.S., POCH) in 20% TCA, incubated at 95\\u0026deg;C for 30 min, cooled on ice and centrifuged at 10 000\\u0026times;g for 5 min. The colored complexes of TBARS (products of lipid peroxidation) were determined at 532 nm, and the non-specific absorption at 600 nm was subtracted (Ultrospec 2100 pro-Classic, GE Healthcare, UK). An extinction coefficient of 1.56 \\u0026times; 105 M\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e cm\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e was used for TBARS concentration calculations. The results were expressed as mmol TBARS per gram of fresh weight of the lichen sample.\\u003c/p\\u003e\\u003cp\\u003eTo analyze the superoxide dismutase (SOD) activity, crude protein was extracted in accordance with the procedure described by Egger et al. (\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e1994\\u003c/span\\u003e). Lichen powder (60 mg) was homogenized in 1 ml of 50 mM phosphate buffer (pH 7.5) containing 1 mM EDTA (99+%, Sigma-Aldrich), 1% PVP (99%, Sigma-Aldrich), 0.2% Tritone X-100 (99%, Sigma- Aldrich), and 5 mM 2-mercaptoethanol (99%, Sigma-Aldrich). The homogenate was centrifuged at 12 000\\u0026times;g for 5 min at 4\\u0026deg;C, and supernatant was used for measuring antioxidant enzyme activity. Protein concentration was determined according to Bradford (\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e1976\\u003c/span\\u003e). Separation of soluble protein fractions was performed according to the procedure described by Laemmli (\\u003cspan citationid=\\\"CR52\\\" class=\\\"CitationRef\\\"\\u003e1970\\u003c/span\\u003e) using native (without sodium dodecyl sulfate) PAGE at 4\\u0026deg;C and 180 V. Visualization of SOD bands was performed on discontinuous 12% polyacrylamide gels in accordance with the method described by Beauchamp and Fridovich (\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e1971\\u003c/span\\u003e). The gels were incubated in staining buffer for 30 min, in darkness, at room temperature and then exposed to white light until SOD activity bands became visible. Densitometric analysis of SODs bands was performed with ImageJ 2 (GPL license) and the results were expressed in activity units [AU].\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec8\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003e2.6 GIS and statistical analyses\\u003c/h2\\u003e\\u003cp\\u003eBased on the lichen sampling locations and values of each studied parameter, interpolation maps were created using the Inverse Distance Weighted (IDW) tool. Maps were prepared in QGIS ver. 3.2.2 Bonn. Coordinates were expressed in the EPSG: 2180\\u0026thinsp;\\u0026minus;\\u0026thinsp;189 ETRS89/Poland CS92 system. For parameters which showed spatial differences, two maps for each season were created.\\u003c/p\\u003e\\u003cp\\u003ePrior to the analysis, we plotted the data to identify the distribution and potential outliers. Since the element concentrations and dead algae fraction (DAF, hereafter) were log-normally distributed, further analysis was conducted on their logged data. Values of SOD and TBARS were normally distributed. The data from the measurements above were accompanied by the following variables: season (non-heating season vs heating season), and location (15 sampling points).\\u003c/p\\u003e\\u003cp\\u003eThe main analysis (factorial ANOVA) verified the variability of all element concentrations. For the metals, Principal Component Analysis (PCA) was performed to identify patterns of variation and relationships between the studied variables, and to prepare a PCA-derived metal concentration index. For DAF, SOD and TBARS, General Linear Models (GLM) were built to explain their variability using season, location, PCA-derived metal index, S, SOD (for DAF and TBARS models), TBARS (for DAF and SOD models) and DAF (for SOD and TBARS models). Model backward selection was used, starting with a full model and then dropping the consecutive variables until only significant ingredients remained. Finally, the AIC value corrected to the small sample size (AICc) was used to compare the final model with the full model. To assess potential multicollinearity effects on the models, correlations between all the numeric variables were examined (correlations were generally week, under r Pearson 0.7).\\u003c/p\\u003e\\u003cp\\u003eAdditionally, the strength and significance of potential correlations between elements were evaluated with r Pearson coefficient. Arithmetic mean, geometric mean, standard deviation, minimum, and maximum were calculated as descriptive statistics. Values were presented with at least three significant digits for the lowest value. In all the analyses, the significance level was set as 0.05. The data were compiled in Microsoft Excel (ver. 16). All the analyses were performed in R (ver. 4.0.2; R Core Team \\u003cspan citationid=\\\"CR68\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e) and R Studio (ver. 1.3).\\u003c/p\\u003e\\u003c/div\\u003e\"},{\"header\":\"3. Results\",\"content\":\"\\u003cp\\u003eAll the measured element concentrations were higher than the quantification limits of the applied method (Table \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003e). Due to logistical constraints, SOD and TBARS activities could not be measured in the samples from April 2018.\\u003c/p\\u003e\\n\\u003ch3\\u003e3. 1 Concentrations of elements\\u003c/h3\\u003e\\n\\u003cp\\u003eElemental concentrations built the following order: Hg\\u0026thinsp;\\u0026lt;\\u0026thinsp;Cd\\u0026thinsp;\\u0026lt;\\u0026thinsp;Pb\\u0026thinsp;\\u0026lt;\\u0026thinsp;Cu\\u0026thinsp;\\u0026lt;\\u0026thinsp;Zn\\u0026thinsp;\\u0026lt;\\u0026thinsp;Fe\\u0026thinsp;\\u0026lt;\\u0026thinsp;S\\u0026thinsp;\\u0026lt;\\u0026thinsp;Ca. The lowest concentration was noted for Hg (0.04 \\u0026micro;g/g), while the highest was for Ca (7 569 \\u0026micro;g/g). The lowest standard deviation was observed for Hg (0.040), and the highest for Ca (1762.054; Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003e\\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e\\u003ccaption language=\\\"En\\\"\\u003e\\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e\\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\u003cp\\u003eDescriptive statistics (mean followed by geometric mean (in the bracket) and SD) of elements [\\u0026micro;g/g], DAF (dead algae fraction) [%], SOD [AU] and TBARS mmol*g\\u003csub\\u003eFM\\u003c/sub\\u003e \\u003csup\\u003e-1\\u003c/sup\\u003e in \\u003cem\\u003eH. physodes\\u003c/em\\u003e thalli.\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/caption\\u003e\\u003ccolgroup cols=\\\"4\\\"\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e\\u003cthead\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eModels\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eNon-heating season\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eHeating season\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003ePooled\\u003c/p\\u003e\\u003c/th\\u003e\\u003c/tr\\u003e\\u003c/thead\\u003e\\u003ctbody\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eCa\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e1852 (1181)\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1988\\u003c/p\\u003e\\u003cp\\u003e312\\u0026ndash;6112; n\\u0026thinsp;=\\u0026thinsp;13\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e1706 (1230)\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1687\\u003c/p\\u003e\\u003cp\\u003e280\\u0026ndash;7569; n\\u0026thinsp;=\\u0026thinsp;29\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e1751 (1214)\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1762\\u003c/p\\u003e\\u003cp\\u003e280\\u0026ndash;7569; n\\u0026thinsp;=\\u0026thinsp;42\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eCd\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e0.97 (0.96)\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.14\\u003c/p\\u003e\\u003cp\\u003e0.81\\u0026ndash;1.18; n\\u0026thinsp;=\\u0026thinsp;13\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.87 (0.85)\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.17\\u003c/p\\u003e\\u003cp\\u003e0.61\\u0026ndash;1.29; n\\u0026thinsp;=\\u0026thinsp;29\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.90 (0.88)\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.17\\u003c/p\\u003e\\u003cp\\u003e0.61\\u0026ndash;1.29; n\\u0026thinsp;=\\u0026thinsp;42\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eCu\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e5.72 (5.69)\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.67\\u003c/p\\u003e\\u003cp\\u003e4.35\\u0026ndash;6.44; n\\u0026thinsp;=\\u0026thinsp;13\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e5.71 (5.65)\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.84\\u003c/p\\u003e\\u003cp\\u003e4.10\\u0026ndash;7.34; n\\u0026thinsp;=\\u0026thinsp;29\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e5.71 (5.66)\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.78\\u003c/p\\u003e\\u003cp\\u003e4.10\\u0026ndash;7.34; n\\u0026thinsp;=\\u0026thinsp;42\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eFe\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e721 (709)\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;127\\u003c/p\\u003e\\u003cp\\u003e463\\u0026ndash;897; n\\u0026thinsp;=\\u0026thinsp;13\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e648 (620)\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;211\\u003c/p\\u003e\\u003cp\\u003e343\\u0026ndash;1412; n\\u0026thinsp;=\\u0026thinsp;29\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e671 (647)\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;191\\u003c/p\\u003e\\u003cp\\u003e343\\u0026ndash;1412; n\\u0026thinsp;=\\u0026thinsp;42\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eHg\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e0.10 (0.10)\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.02\\u003c/p\\u003e\\u003cp\\u003e0.07\\u0026ndash;0.13; n\\u0026thinsp;=\\u0026thinsp;14\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.10 (0.09)\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.05\\u003c/p\\u003e\\u003cp\\u003e0.04\\u0026ndash;0.27; n\\u0026thinsp;=\\u0026thinsp;30\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.10 (0.09)\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.04\\u003c/p\\u003e\\u003cp\\u003e0.04\\u0026ndash;0.27; n\\u0026thinsp;=\\u0026thinsp;44\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003ePb\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e9.15 (8.90)\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.04\\u003c/p\\u003e\\u003cp\\u003e4.72\\u0026ndash;11.33; n\\u0026thinsp;=\\u0026thinsp;13\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e9.13 (8.75)\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.46\\u003c/p\\u003e\\u003cp\\u003e3.46\\u0026ndash;13.20; n\\u0026thinsp;=\\u0026thinsp;29\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e9.14 (8.80)\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.31\\u003c/p\\u003e\\u003cp\\u003e3.46\\u0026ndash;13.20; n\\u0026thinsp;=\\u0026thinsp;42\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eS\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e917 (878)\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;236\\u003c/p\\u003e\\u003cp\\u003e348\\u0026ndash;1159; n\\u0026thinsp;=\\u0026thinsp;14\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e1331 (1281)\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;376\\u003c/p\\u003e\\u003cp\\u003e784\\u0026ndash;2307; n\\u0026thinsp;=\\u0026thinsp;30\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e1200 (1136)\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;388\\u003c/p\\u003e\\u003cp\\u003e348\\u0026ndash;2307; n\\u0026thinsp;=\\u0026thinsp;44\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eZn\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e108.1 (102.8)\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;39.2\\u003c/p\\u003e\\u003cp\\u003e69.5\\u0026ndash;197.6; n\\u0026thinsp;=\\u0026thinsp;13\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e110.0 (105.2)\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;35.7\\u003c/p\\u003e\\u003cp\\u003e72.7\\u0026ndash;217.3; n\\u0026thinsp;=\\u0026thinsp;29\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e109.4 (104.5)\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;36.3\\u003c/p\\u003e\\u003cp\\u003e69.5\\u0026ndash;217.3; n\\u0026thinsp;=\\u0026thinsp;42\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eDAF\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e33.8 (33.4)\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;4.7\\u003c/p\\u003e\\u003cp\\u003e26.9\\u0026ndash;41.5; n\\u0026thinsp;=\\u0026thinsp;15\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e34.0 (33.7)\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;5.0\\u003c/p\\u003e\\u003cp\\u003e26.3\\u0026ndash;46.5; n\\u0026thinsp;=\\u0026thinsp;30\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e33.9 (33.6)\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;4.9\\u003c/p\\u003e\\u003cp\\u003e26.3\\u0026ndash;46.5; n\\u0026thinsp;=\\u0026thinsp;45\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eSOD\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e23231 (22396)\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;6094\\u003c/p\\u003e\\u003cp\\u003e12463\\u0026ndash;32728; n\\u0026thinsp;=\\u0026thinsp;15\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e19577 (19395)\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2615\\u003c/p\\u003e\\u003cp\\u003e12996\\u0026ndash;22868; n\\u0026thinsp;=\\u0026thinsp;15\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e21404 (20841)\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;4968\\u003c/p\\u003e\\u003cp\\u003e12463\\u0026ndash;32728; n\\u0026thinsp;=\\u0026thinsp;30\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eTBARS\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e0.95 (0.95)\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.07\\u003c/p\\u003e\\u003cp\\u003e0.89\\u0026ndash;1.14; n\\u0026thinsp;=\\u0026thinsp;15\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.88 (0.88)\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.04\\u003c/p\\u003e\\u003cp\\u003e0.80\\u0026ndash;0.96; n\\u0026thinsp;=\\u0026thinsp;15\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.91 (0.91)\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.07\\u003c/p\\u003e\\u003cp\\u003e0.80\\u0026ndash;1.14; n\\u0026thinsp;=\\u0026thinsp;30\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tbody\\u003e\\u003c/colgroup\\u003e\\u003c/table\\u003e\\u003c/div\\u003e\\u003c/p\\u003e\\u003cp\\u003eConcentrations of Cd and S differed between seasons, in contrast to other elements (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e). The influence of location was significant only for Cd and Zn concentrations. No interaction was observed between season and location for any of the elements (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e). Cd concentrations were higher in the non-heating season, while S concentrations were higher during the heating season (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). For Cd, the highest concentrations were found in the north-eastern part of the forest (sites 2, 6 and 7), while the lowest concentrations were observed in the central-western part (sites 8, 9, 12 and 15). For Zn, the highest concentrations were recorded in the northern and western parts of the forest (sites 6 and 15), while the lowest concentrations were in the central part (sites 7, 9, 12 and 14) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003e\\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab2\\\" border=\\\"1\\\"\\u003e\\u003ccaption language=\\\"En\\\"\\u003e\\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 2\\u003c/div\\u003e\\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\u003cp\\u003eANOVA models testing the influence of season, location and their interaction on element concentrations in \\u003cem\\u003eH. physodes\\u003c/em\\u003e thalli collected in the Niepołomice Forest\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/caption\\u003e\\u003ccolgroup cols=\\\"4\\\"\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e\\u003cthead\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eVariables\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eSeason\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eLocation\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eInteraction\\u003c/p\\u003e\\u003c/th\\u003e\\u003c/tr\\u003e\\u003c/thead\\u003e\\u003ctbody\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eCa\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eF\\u003csub\\u003e1, 14\\u003c/sub\\u003e = 0.034, p\\u0026thinsp;=\\u0026thinsp;0.856\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eF\\u003csub\\u003e14, 14\\u003c/sub\\u003e = 2.212, p\\u0026thinsp;=\\u0026thinsp;0.075\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eF\\u003csub\\u003e12, 14\\u003c/sub\\u003e = 1.631, p\\u0026thinsp;=\\u0026thinsp;0.190\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eCd\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eF\\u003c/b\\u003e\\u003csub\\u003e\\u003cb\\u003e1, 14\\u003c/b\\u003e\\u003c/sub\\u003e \\u003cb\\u003e= 6.340, p\\u0026thinsp;=\\u0026thinsp;0.025\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eF\\u003c/b\\u003e\\u003csub\\u003e\\u003cb\\u003e14, 14\\u003c/b\\u003e\\u003c/sub\\u003e \\u003cb\\u003e= 2.787, p\\u0026thinsp;=\\u0026thinsp;0.032\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eF\\u003csub\\u003e12, 14\\u003c/sub\\u003e = 0.558, p\\u0026thinsp;=\\u0026thinsp;0.842\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eCu\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eF\\u003csub\\u003e1, 14\\u003c/sub\\u003e = 0.023, p\\u0026thinsp;=\\u0026thinsp;0.882\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eF\\u003csub\\u003e14, 14\\u003c/sub\\u003e = 1.869, p\\u0026thinsp;=\\u0026thinsp;0.127\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eF\\u003csub\\u003e12, 14\\u003c/sub\\u003e = 0.675, p\\u0026thinsp;=\\u0026thinsp;0.750\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eFe\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eF\\u003csub\\u003e1, 14\\u003c/sub\\u003e = 1.915, p\\u0026thinsp;=\\u0026thinsp;0.188\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eF\\u003csub\\u003e14, 14\\u003c/sub\\u003e = 0.969, p\\u0026thinsp;=\\u0026thinsp;0.523\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eF\\u003csub\\u003e12, 14\\u003c/sub\\u003e = 0.525, p\\u0026thinsp;=\\u0026thinsp;0.865\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eHg\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eF\\u003csub\\u003e1, 15\\u003c/sub\\u003e = 1.035, p\\u0026thinsp;=\\u0026thinsp;0.325\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eF\\u003csub\\u003e14, 15\\u003c/sub\\u003e = 1.179, p\\u0026thinsp;=\\u0026thinsp;0.377\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eF\\u003csub\\u003e13, 15\\u003c/sub\\u003e = 0.285, p\\u0026thinsp;=\\u0026thinsp;0.986\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003ePb\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eF\\u003csub\\u003e1, 14\\u003c/sub\\u003e = 0.026, p\\u0026thinsp;=\\u0026thinsp;0.875\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eF\\u003csub\\u003e14, 14\\u003c/sub\\u003e = 1.387, p\\u0026thinsp;=\\u0026thinsp;0.274\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eF\\u003csub\\u003e12, 14\\u003c/sub\\u003e = 0.343, p\\u0026thinsp;=\\u0026thinsp;0.965\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eZn\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eF\\u003csub\\u003e1, 14\\u003c/sub\\u003e = 0.152, p\\u0026thinsp;=\\u0026thinsp;0.703\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eF\\u003c/b\\u003e\\u003csub\\u003e\\u003cb\\u003e14, 14\\u003c/b\\u003e\\u003c/sub\\u003e \\u003cb\\u003e= 5.512, p\\u0026thinsp;=\\u0026thinsp;0.001\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eF\\u003csub\\u003e12, 14\\u003c/sub\\u003e = 2.397, p\\u0026thinsp;=\\u0026thinsp;0.061\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eS\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eF\\u003c/b\\u003e\\u003csub\\u003e\\u003cb\\u003e1, 15\\u003c/b\\u003e\\u003c/sub\\u003e \\u003cb\\u003e=\\u003c/b\\u003e \\u003cb\\u003e18.579, p\\u0026thinsp;=\\u0026thinsp;0.001\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eF\\u003csub\\u003e14, 15\\u003c/sub\\u003e = 1.529, p\\u0026thinsp;=\\u0026thinsp;0.212\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eF\\u003csub\\u003e13, 15\\u003c/sub\\u003e = 1.121, p\\u0026thinsp;=\\u0026thinsp;0.412\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tbody\\u003e\\u003c/colgroup\\u003e\\u003ctfoot\\u003e\\u003ctr\\u003e\\u003ctd colspan=\\\"4\\\"\\u003eBold indicates significant differences (p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05).\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tfoot\\u003e\\u003c/table\\u003e\\u003c/div\\u003e\\u003c/p\\u003e\\u003cp\\u003e\\u003c/p\\u003e\\u003cp\\u003eRelationships between elements were generally weak (r Pearson below 0.6), with the strongest observed between Cu and Pb (r Pearson 0.505), followed by Fe and Pb (r Pearson 0.486), and Zn and Pb (r Pearson 0.436) (Figure S3). Other potential correlations were statistically insignificant. PCA analysis of metals showed that the first two principal components (PC1 and PC2) explain 52.8% of the total variability (PC1: 33.1%, PC2: 19.7%, respectively) (Figure S2).\\u003c/p\\u003e\\u003cdiv id=\\\"Sec11\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003e3.2 Oxidative stress biomarkers\\u003c/h2\\u003e\\u003cp\\u003eThe best-fitting GLM model explaining SOD values was the one including season only (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e) and revealing the negative relationship between both variables (Table S2). For TBARS, the final model included season and location (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e), indicating a negative relationship with season but a positive relationship with location for TBARS (Table S2).\\u003c/p\\u003e\\u003cp\\u003e\\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab3\\\" border=\\\"1\\\"\\u003e\\u003ccaption language=\\\"En\\\"\\u003e\\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 3\\u003c/div\\u003e\\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\u003cp\\u003eCorrected for small sample size Akaike Information Criterion (AICc) for GLM models explaining the condition parameters of \\u003cem\\u003eH. physodes\\u003c/em\\u003e thalli collected in the Niepołomice Forest. The model with the lowest AICc was considered the best-fitting explanatory model\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/caption\\u003e\\u003ccolgroup cols=\\\"4\\\"\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e\\u003cthead\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eVariables\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eFull model\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\u003cp\\u003eAICc\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eFinal model \\u003c/p\\u003e\\u003cp\\u003e(backward selection)\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eFinal model\\u003c/p\\u003e\\u003cp\\u003eAICc\\u003c/p\\u003e\\u003c/th\\u003e\\u003c/tr\\u003e\\u003c/thead\\u003e\\u003ctbody\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eDAF\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e127.93\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003enull model\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e-45.94\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eSOD\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e700.05\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eSeason\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e597.17\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eTBARS\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e58.14\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eSeason\\u0026thinsp;+\\u0026thinsp;Localization\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e-36.75\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tbody\\u003e\\u003c/colgroup\\u003e\\u003ctfoot\\u003e\\u003ctr\\u003e\\u003ctd colspan=\\\"4\\\"\\u003e\\u003csup\\u003e*\\u003c/sup\\u003eFull model included the PCA-derived variable for metals (Figure S2), logged sulfur, logged DAF (dead algae fraction; for SOD and TBARS models), SOD (for DAF and TBARS models) and TBARS (for DAF and SOD models).\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tfoot\\u003e\\u003c/table\\u003e\\u003c/div\\u003e\\u003c/p\\u003e\\u003cp\\u003eValues of SOD reached higher concentrations in the non-heating season than the heating season (23231 [AU] and 19577 [AU], respectively; Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). TBARS mean values were also higher in the non-heating season (0.95 mmol*g\\u003csub\\u003eFM\\u003c/sub\\u003e \\u003csup\\u003e-1\\u003c/sup\\u003e and 0.88 mmol*g\\u003csub\\u003eFM\\u003c/sub\\u003e \\u003csup\\u003e-1\\u003c/sup\\u003e, respectively; Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). The highest TBARS values were observed at sites 5, 8 and 11, the lowest were noted at sites 1, 2 and 3 (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e).\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec12\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003e3.3 Algal condition\\u003c/h2\\u003e\\u003cp\\u003eThe examined preparations showed the presence of healthy algal cells, algal cells with severe damage involving more than 90% of chloroplast content, and dead cells devoid of chloroplast content. At most sites, both healthy and severely damaged thalli were observed; however, no thalli with moderate damage were detected.\\u003c/p\\u003e\\u003cp\\u003eIn samples collected during the heating season, the proportion of dead algal cells ranged from 26.3% to 46.5%, while in the non-heating season, it ranged from 26.9% to 41.5% of all algal cells and was not influenced by the parameters examined in this study (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e).\\u003c/p\\u003e\\u003c/div\\u003e\"},{\"header\":\"4. Discussion\",\"content\":\"\\u003cp\\u003eWe found that only Cd and S concentrations showed seasonal variation, while Cd and Zn concentrations varied spatially. SOD and TBARS also revealed seasonality, although their values were partially explained by season but only TBARS by location. The condition of algae was not influenced by any parameters analyzed in the study.\\u003c/p\\u003e\\u003cp\\u003e\\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003eOver the past 40 years of research in the area, it has been shown how the number of lichen species (lichenized fungi), site frequency and abundance have changed, as well as the strong response to air pollution in the form of damage or even degeneration of entire thalli. Our research showed that the average concentrations of elements in\\u003c/span\\u003e \\u003cspan type=\\\"ItalicUnderline\\\" class=\\\"ItalicUnderline\\\" name=\\\"Emphasis\\\"\\u003eH. physodes\\u003c/span\\u003e \\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003ethalli were comparable to those reported from other parts of Poland (Białońska, 2005;\\u003c/span\\u003e Bąbelewska et al., \\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e; \\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003eBiałońska and Dayan, 2005;\\u003c/span\\u003e Sawicka-Kapusta et al., \\u003cspan citationid=\\\"CR71\\\" class=\\\"CitationRef\\\"\\u003e2014\\u003c/span\\u003e). \\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003eAccording to the classification of\\u003c/span\\u003e Nimis et al. (\\u003cspan citationid=\\\"CR62\\\" class=\\\"CitationRef\\\"\\u003e2000\\u003c/span\\u003e), \\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003eonly the average concentrations of Cd and Zn reached values indicating potential negative impacts on the natural environment. This shows fairly significant environmental changes that, if they continue to increase, could pose a serious threat to the natural environment.\\u003c/span\\u003e\\u003c/p\\u003e\\n\\u003ch3\\u003e4. 1 Seasonal differences\\u003c/h3\\u003e\\n\\u003cp\\u003eMany studies indicate that the process of metal accumulation by lichens is closely related to seasonality, with higher concentrations of certain elements typically occurring during the heating season (Bąbelewska et al., \\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e). Literature also reports increased emissions of Cd and S during the combustion of coal and wood (Johansson et al., \\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e2003\\u003c/span\\u003e; Sippula et al., \\u003cspan citationid=\\\"CR76\\\" class=\\\"CitationRef\\\"\\u003e2009\\u003c/span\\u003e; Świetlik et al., \\u003cspan citationid=\\\"CR78\\\" class=\\\"CitationRef\\\"\\u003e2012\\u003c/span\\u003e; Cui et al., \\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e). In our study, however, the higher concentration of Cd was observed outside the heating season (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e), suggesting that other sources may contribute to its elevated levels. Cd is released not only in combustion processes, but also through industrial activity, waste disposal (Hutton \\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e1983\\u003c/span\\u003e; Nzihou and Stanmore \\u003cspan citationid=\\\"CR63\\\" class=\\\"CitationRef\\\"\\u003e2013\\u003c/span\\u003e), and fuel combustion (Ciężka et al., \\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e). Therefore, we suggest that these sources may be responsible for the higher Cd emissions during the non-heating season compared to the heating season.\\u003c/p\\u003e\\u003cp\\u003eIn the study, we also observed seasonality of S concentrations (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e). In the environment, S occurs mainly as sulfur oxides, which are released, particularly by thermal power plants (Wiseman and Wadleigh, \\u003cspan citationid=\\\"CR83\\\" class=\\\"CitationRef\\\"\\u003e2002\\u003c/span\\u003e; Lin et al., \\u003cspan citationid=\\\"CR53\\\" class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e, Shikhovtsev et al., \\u003cspan citationid=\\\"CR74\\\" class=\\\"CitationRef\\\"\\u003e2024\\u003c/span\\u003e). Research conducted in the Świętokrzyski National Park on \\u003cem\\u003eH. physodes\\u003c/em\\u003e pollution showed that the concentration of sulfur (IV) oxides (SO\\u003csub\\u003e2\\u003c/sub\\u003e) increases significantly during the heating season (Ciężka et al., \\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e; Ciężka et al., \\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e), which supports our findings. In Krak\\u0026oacute;w, located in the vicinity of the western part of the forest, the observed concentrations are lower (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e). This may be related to the anti-smog resolution enacted in 2019, which introduced a legal ban on burning coal and wood for residential heating within the city boundaries In contrast, sites located in the western part of the forest are near Tarn\\u0026oacute;w and smaller towns, where no such ban has been implemented (Sejmik Wojew\\u0026oacute;dztwa Małopolskiego, 2016; Wojew\\u0026oacute;dzki Inspektorat Ochrony Środowiska w Krakowie, \\u003cspan citationid=\\\"CR84\\\" class=\\\"CitationRef\\\"\\u003e2017\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003e\\u003c/p\\u003e\\u003cp\\u003eOur results indicate seasonal differences in oxidative stress biomarkers (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e). Besides air pollution, their activity is influenced by environmental conditions. During the non-heating season, lichens are exposed to increased UV radiation and low humidity, which disrupt homeostasis and promote ROS production (Mittler, \\u003cspan citationid=\\\"CR61\\\" class=\\\"CitationRef\\\"\\u003e2002\\u003c/span\\u003e; Bačkor and Loppi, \\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e2009\\u003c/span\\u003e), indicating oxidative stress. We suggest that increased SOD activity observed in the non-heating season was influenced by the above mentioned factors. However, in relation to TBARS, although its higher average concentration was observed during the non-heating season, its spatial distribution (Figure S2) indicates its increased concentration during the heating season in the western part of the forest. Both SOD and TBARS can serve as indicators of environmental pollution, as their levels increase in response to metal pollution (Santos et al., \\u003cspan citationid=\\\"CR70\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e; Osyczka et al., \\u003cspan citationid=\\\"CR65\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e), which is higher during the heating season. Although our study does not show a clear impact of the measured elements, we suggest that pollution from Krak\\u0026oacute;w may contribute to their higher levels at those sites.\\u003c/p\\u003e\\n\\u003ch3\\u003e4. 2 Spatial differences\\u003c/h3\\u003e\\n\\u003cp\\u003eThe spatial distribution of Cd is diversified, with the highest values recorded in the middle-eastern part of the forest (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e). Cd is released in combustion processes, as a result of industrial activity and waste disposal, as discussed in the previous subsection. It is worth noting, however, that less urbanized areas may also contribute significantly to emission of this metal - for example, through waste burning, agricultural practices, or local transport. This indicates a real threat of metal pollution even in areas considered to be more natural (Hutton et al., 1983; Aslan et al., \\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e2011\\u003c/span\\u003e; G\\u0026oacute;mez et al., \\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e2024\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003eOver the years, studies conducted in the Niepołomice Forest have consistently reported higher Zn pollution in its western part (Szarek-Łukaszewska et al., \\u003cspan citationid=\\\"CR77\\\" class=\\\"CitationRef\\\"\\u003e2002\\u003c/span\\u003e; Kapusta et al., \\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e2004\\u003c/span\\u003e), suggesting a significant impact of the Krak\\u0026oacute;w agglomeration. Our results confirmed this pattern, with the highest concentrations observed in the western part (site 15; Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e), where Zn coincided with Pb and Cu (Figure \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003e), supporting the hypothesis that road transport is a major source (Oliva and Rautio, 2004; Hjortenkrans et al., \\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e2007\\u003c/span\\u003e; Jeong, \\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e). In contrast, an additional Zn maximum was recorded at a northern site located near the village of Olszyny, adjacent to agricultural fields. This pattern cannot be explained by traffic and, together with elevated Cd and Ca concentrations and the highest percentage of damaged thalli, it strongly suggests the contribution of agricultural activities. On the other hand, Pb pollution can also be linked to incomplete fuel and oil combustion as well as the legacy of leaded gasoline use (Al-Sabbagh and Shreaz, \\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e2025\\u003c/span\\u003e). We also observed an antagonistic spatial relationship between Pb and Cu versus Ca. The highest Ca concentrations were found at eastern sites, where Pb and Cu levels were relatively low. compared to the western part, of the forest, where the opposite trend occurred. We suggest that this may be related to the protective role of Ca as a competitor for binding sites with toxic metals such as Cd (Branquinho et al., \\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e1997\\u003c/span\\u003e; Kov\\u0026aacute;čik et al., \\u003cspan citationid=\\\"CR51\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e). In contrast, in the eastern part, higher concentrations of S, Cd, Hg, and Ca, as well as greater damage to lichens were observed. This suggests a stronger impact of local emission sources, such as the energy industry, municipal and domestic combustion, and emissions related to agricultural activities (Ministerstwo Klimatu i Środowiska 2020). Additionally, for Hg and S, long-range transport from small towns and surrounding agricultural areas located in the immediate vicinity of this region cannot be ruled out (Zeedijk and Velds, \\u003cspan citationid=\\\"CR86\\\" class=\\\"CitationRef\\\"\\u003e1973\\u003c/span\\u003e; Marumoto et al., \\u003cspan citationid=\\\"CR56\\\" class=\\\"CitationRef\\\"\\u003e2015\\u003c/span\\u003e). Unlike most metals, which tend to deposit relatively close to their emission sources, elemental Hg and sulfur oxides can remain airborne for extended periods, allowing them to disperse and deposit far from their origin (Jackson, \\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e1997\\u003c/span\\u003e; Xiao et al., \\u003cspan citationid=\\\"CR85\\\" class=\\\"CitationRef\\\"\\u003e1997\\u003c/span\\u003e; Sigler et al., \\u003cspan citationid=\\\"CR75\\\" class=\\\"CitationRef\\\"\\u003e2003\\u003c/span\\u003e; Qu et al., \\u003cspan citationid=\\\"CR67\\\" class=\\\"CitationRef\\\"\\u003e2016\\u003c/span\\u003e). The concentration of elements in the air is mainly influenced by local sources of their release, as well as meteorological conditions in a given area, such as wind speed, temperature and precipitation. In addition, rainfall favors pollutant leaching, while strong winds and low temperatures promote their spread (Inspektorat Ochrony Środowiska, \\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e2007\\u003c/span\\u003e). According to the emission balance for 2018 and 2019 in Poland (Ministerstwo Klimatu i Środowiska, 2020, 2021), industrial processes were the main source of Cd in the environment, with emissions related to energy production also playing a significant role. Therefore, the high concentrations recorded in our study may have been caused by weather conditions, as - according to the thermal classification made by the Institute of Meteorology and Water Management (GIOŚ 2020) \\u0026minus;\\u0026thinsp;2018 and 2019 were classified as extremely warm, characterized by low rainfall, which might have favored accumulation of pollutants in \\u003cem\\u003eH. physodes\\u003c/em\\u003e thalli.\\u003c/p\\u003e\\u003cp\\u003eAlthough, our study did not indicate a connection between lichen damage and oxidative stress biomarkers, we observed that increased TBARS levels and SOD activity were noted in the western part of the forest. ROS are mainly produced in the mitochondria of living cells (Hernansanz-Agust\\u0026iacute;n and Enr\\u0026iacute;quez, \\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e), so their low concentrations in the eastern part of the forest may be related to reduced metabolic activity caused by higher cell degeneration that indicates lower activity of SOD and TBARS levels. Thus, stressors present in the eastern part of the forest may be responsible for the condition of lichens. However, for sites 5, 8 and 11 TBARS values were significant but could not be explained by the studied factors. Therefore, we suggest the impact of other environmental factors.\\u003c/p\\u003e\"},{\"header\":\"5. Conclusions\",\"content\":\"\\u003cp\\u003eThe concentrations of metals and S in \\u003cem\\u003eH. physoides\\u003c/em\\u003e thalli from the Niepołomice Forest were comparable to those reported from other parts of Poland. The study confirmed that Cd and S concentrations varied depending on the season. S concentrations were higher during the heating season, suggesting a significant impact of domestic heating. In contrast, Cd concentrations were higher in the non-heating season, suggesting a significant impact of other factors, such as industrial activity, waste disposal, agricultural practices or local transport. SOD and TBARS values were also found to be higher in the non-heating season, which may be linked to increased UV radiation and low humidity, indicating oxidative stress.\\u003c/p\\u003e\\u003cp\\u003eLocation was only significant for Cd, Zn and TBARS. For Cd, the highest values were recorded in the central-eastern part of the forest, suggesting sources similar to those responsible for the seasonal differences mentioned above. The highest Zn values were found in the western and northern parts of the forest, which may indicate a strong impact of transport and agricultural acitivity. TBARS was significant only at three locations, which suggests the influence of the other environmental factors. At the westernmost sites, \\u003cem\\u003eH. physodes\\u003c/em\\u003e was absent, whereas in other western locations, lichens exhibited elevated Pb and Cu concentrations. This indicates a significant impact of traffic-related emissions, which may also explain the high SOD activity observed there. Moreover, similar distribution of Pb and Cu indicates the influence of road transport, as well as incomplete fuel and oil combustion and the legacy of leaded gasoline use. An antagonistic spatial distribution between Pb and Cu in relation to Ca was also observed, which may reflect the protective function of its element. Higher concentrations of S, Cd and Hg as well as greater damage to lichens, were observed in the eastern part of the forest, which might be caused by local emission sources such as the energy industry, municipal and domestic combustion, or emissions related to agricultural activities.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003ch2\\u003eFunding\\u003c/h2\\u003e\\u003cp\\u003eThe study was founded through the statutory research subvention of UKEN: BS-472/G/2018 \\u0026ldquo;Ocena stanu środowiska naturalnego Puszczy Niepołomickiej w oparciu o porost \\u003cem\\u003eHypogymnia physodes\\u003c/em\\u003e (Nyl)\\u0026rdquo;. [Assessment of the natural environment of the Niepołomice Forest based on the lichen \\u003cem\\u003eHypogymnia physodes\\u003c/em\\u003e (Nyl.)].\\u003c/p\\u003e\\u003ch2\\u003eAuthor Contribution\\u003c/h2\\u003e\\u003cp\\u003eRK: Conceptualization, Funding acquisition, Investigation, Methodology, Writing \\u0026ndash; review \\u0026amp; editing,IW: Formal analysis, Validation, Visualization, Writing \\u0026ndash; original draft.DK: Validation, Visualization, Writing \\u0026ndash; original draft.MA: Methodology, Writing \\u0026ndash; review \\u0026amp; editing.LB: Methodology, Writing \\u0026ndash; review \\u0026amp; editing.KG: Methodology, Writing \\u0026ndash; review \\u0026amp; editing.KK: Visualization, Writing \\u0026ndash; review \\u0026amp; editing.ŁJB: Data curation, Formal analysis, Project administration, Supervision, Writing \\u0026ndash; review \\u0026amp; editing.\\u003c/p\\u003e\\u003ch2\\u003eAcknowledgement\\u003c/h2\\u003e\\u003cp\\u003eThe study was founded through the statutory research subvention of UKEN: BS-472/G/2018 \\u0026ldquo;Ocena stanu środowiska naturalnego Puszczy Niepołomickiej w oparciu o porost Hypogymnia physodes (Nyl)\\u0026rdquo;. [Assessment of the natural environment of the Niepołomice Forest based on the lichen Hypogymnia physodes (Nyl.)].\\u003c/p\\u003e\\u003ch2\\u003eData Availability\\u003c/h2\\u003e\\u003cp\\u003eData will be made available on request.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\u003cli\\u003e\\u003cspan\\u003eAlloway, B. J. Heavy metals in soils: Trace metals and metalloids in soils and their bioavailability, \\u003cem\\u003eEnvironmental Pollution\\u003c/em\\u003e 22. Dordrecht, The Netherlands: Springer. (2013).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eAlmeida, S. et al. Ambient particulate matter source apportionment using receptor modelling in European and Central Asia urban areas. \\u003cem\\u003eEnviron. Pollut.\\u003c/em\\u003e \\u003cb\\u003e266\\u003c/b\\u003e (3), 115199. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1016/j.envpol.2020.115199\\u003c/span\\u003e\\u003cspan address=\\\"10.1016/j.envpol.2020.115199\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2020).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eAl-Sabbagh, T. A. \\u0026amp; Shreaz, S. Impact of lead pollution from vehicular traffic on highway-side grazing areas: challenges and mitigation policies. \\u003cem\\u003eInt. J. Environ. Res. Public Health\\u003c/em\\u003e. \\u003cb\\u003e22\\u003c/b\\u003e (2). \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.3390/ijerph22020311\\u003c/span\\u003e\\u003cspan address=\\\"10.3390/ijerph22020311\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2025).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003e\\u0026Aacute;lvarez, R. et al. Lichen rehydration in heavy metal-polluted environments: Pb modulates the oxidative response of both \\u003cem\\u003eRamalina farinacea\\u003c/em\\u003e thalli and its isolated microalgae. \\u003cem\\u003eMicrob. Ecol.\\u003c/em\\u003e \\u003cb\\u003e69\\u003c/b\\u003e, 698\\u0026ndash;709. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1007/s00248-014-0524-0\\u003c/span\\u003e\\u003cspan address=\\\"10.1007/s00248-014-0524-0\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2015).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eAslan, A. et al. The assessment of lichens as bioindicator of heavy metal pollution from motor vehicles activites. \\u003cem\\u003eAfr. J. Agric. Res.\\u003c/em\\u003e \\u003cb\\u003e6\\u003c/b\\u003e (7), 1698\\u0026ndash;1706. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.5897/AJAR10.331\\u003c/span\\u003e\\u003cspan address=\\\"10.5897/AJAR10.331\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2011).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eBačkor, M. \\u0026amp; Fahselt, D. Lichen photobionts and metal toxicity. \\u003cem\\u003eSymbiosis (Rehovot)\\u003c/em\\u003e. \\u003cb\\u003e46\\u003c/b\\u003e (1), 1\\u0026ndash;10 (2008).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eBačkor, M. \\u0026amp; Loppi, S. Interactions of lichens with heavy metals. \\u003cem\\u003eBiol. Plantetarum\\u003c/em\\u003e. \\u003cb\\u003e53\\u003c/b\\u003e, 214\\u0026ndash;222. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1007/s10535-009-0042-y\\u003c/span\\u003e\\u003cspan address=\\\"10.1007/s10535-009-0042-y\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2009).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eBąbelewska, A., Musielińska, R. \\u0026amp; Ciesielski, W. Bioindykacyjna ocena stopnia zagrożenia metalami ciężkimi zbiorowisk leśnych Załęczańskiego Parku Krajobrazowego przy wykorzystaniu zdolności kumulacji plech porostu \\u003cem\\u003eHypogymnia physodes\\u003c/em\\u003e L. [Bioindically rating of heavy metals hazard association for land forests of the załęcze landscape park with the use of cumulation capacity of the \\u003cem\\u003eHypogymnia physodes\\u003c/em\\u003e L]. \\u003cem\\u003ePrace Naukowe Akademii im Jana Długosza w Częstochowie: Technika Informatyka Inżynieria Bezpieczeństwa\\u003c/em\\u003e. \\u003cb\\u003e6\\u003c/b\\u003e, 279\\u0026ndash;496. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.16926/tiib.2018.06.35\\u003c/span\\u003e\\u003cspan address=\\\"10.16926/tiib.2018.06.35\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2018).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eBeauchamp, C. \\u0026amp; Fridovich, I. Superoxide dismutase: improved assays and an assay applicable to acrylamide gels. \\u003cem\\u003eAnal. Biochem.\\u003c/em\\u003e \\u003cb\\u003e44\\u003c/b\\u003e (1), 276\\u0026ndash;287. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1016/0003-2697(71)90370-8\\u003c/span\\u003e\\u003cspan address=\\\"10.1016/0003-2697(71)90370-8\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (1971).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eBetleja, L. \\u0026amp; Badania morfologii plech \\u003cem\\u003eHypogymnia physodes\\u003c/em\\u003e (L.) Nyl. w płatach pni sosny (\\u003cem\\u003ePinus silvestris\\u003c/em\\u003e) w borach woj. Katowickiego. [Studies on the morphology of \\u003cem\\u003eHypogymnia physodes\\u003c/em\\u003e (L.) Nyl. thalli in pine (\\u003cem\\u003ePinus silvestris\\u003c/em\\u003e) trunk sections in forests in the Katowice Province]. In: Lipnicki L. (Ed.). V Zjazd Lichenolog\\u0026oacute;w Polskich, Porosty (\\u003cem\\u003eLichenes\\u003c/em\\u003e) Pszczewskiego PK. [5th Congress of Polish Lichenologists, Lichens Pszczewski PK]. \\u003cem\\u003eInstytut Badań i Ekspertyz Naukowych, Gorz\\u0026oacute;w Wielkopolski\\u003c/em\\u003e: 95\\u0026ndash;101. (1989).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eBielecki, K. \\u0026amp; Kulczycki, G. Modyfikacja metody Buttersa i Chenery\\u0026rsquo;ego oznaczenia siarki og\\u0026oacute;lnej w roślinach i glebie. [Modification of Butters-Chenery method for determination of total sulfur in plants and soil]. \\u003cem\\u003ePrzemysł Chemiczny\\u003c/em\\u003e. \\u003cb\\u003e91\\u003c/b\\u003e (5), 688\\u0026ndash;691 (2012).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eBradford, M. M. A rapid sensitive method for the quantification of microgram quantities of protein utilizing the principle of protein-dye binding. \\u003cem\\u003eAnal. Biochem.\\u003c/em\\u003e \\u003cb\\u003e72\\u003c/b\\u003e (1\\u0026ndash;2), 248\\u0026ndash;254. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1016/0003-2697(76)90527-3\\u003c/span\\u003e\\u003cspan address=\\\"10.1016/0003-2697(76)90527-3\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (1976).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eBranquinho, C., Brown, D. H., M\\u0026aacute;guas, C. \\u0026amp; Catarino, F. Lead (Pb) uptake and its effects on membrane integrity and chlorophyll fluorescence in different lichen species. \\u003cem\\u003eEnviron. Exp. Bot.\\u003c/em\\u003e \\u003cb\\u003e37\\u003c/b\\u003e (2\\u0026ndash;3), 95\\u0026ndash;105. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1016/S0098-8472(96)01038-6\\u003c/span\\u003e\\u003cspan address=\\\"10.1016/S0098-8472(96)01038-6\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (1997).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eCharlesworth, S., De Miguel, E. \\u0026amp; Ord\\u0026oacute;\\u0026ntilde;ez, A. A review of the distribution of particulate trace elements in urban terrestrial environments and its application to considerations of risk. \\u003cem\\u003eEnviron. Geochem. Health\\u003c/em\\u003e. \\u003cb\\u003e33\\u003c/b\\u003e, 103\\u0026ndash;123. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1007/s10653-010-9325-7\\u003c/span\\u003e\\u003cspan address=\\\"10.1007/s10653-010-9325-7\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2011).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eCiężka, M. M. et al. The coupled study of metal concentrations and electron paramagnetic resonance (EPR) of lichens (\\u003cem\\u003eHypogymnia physodes\\u003c/em\\u003e) from the Świętokrzyski National Park\\u0026mdash;environmental implications. \\u003cem\\u003eEnviron. Sci. Pollut. Res.\\u003c/em\\u003e \\u003cb\\u003e25\\u003c/b\\u003e, 25348\\u0026ndash;25362. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1007/s11356-018-2586-x\\u003c/span\\u003e\\u003cspan address=\\\"10.1007/s11356-018-2586-x\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2018).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eCiężka, M. M. et al. The multi-isotope biogeochemistry (S, C, N and Pb) of \\u003cem\\u003eHypogymnia physodes\\u003c/em\\u003e lichens: air quality approach in the Świętokrzyski National Park, Poland. \\u003cem\\u003eIsot. Environ. Health Stud.\\u003c/em\\u003e \\u003cb\\u003e58\\u003c/b\\u003e (4\\u0026ndash;6), 340\\u0026ndash;362. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1080/10256016.2022.2110591\\u003c/span\\u003e\\u003cspan address=\\\"10.1080/10256016.2022.2110591\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2022).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eCui, W. et al. Occurrence and release of cadmium, chromium, and lead from stone coal combustion. \\u003cem\\u003eInt. J. Coal Sci. Technol.\\u003c/em\\u003e \\u003cb\\u003e6\\u003c/b\\u003e, 586\\u0026ndash;594. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1007/s40789-019-00281-4\\u003c/span\\u003e\\u003cspan address=\\\"10.1007/s40789-019-00281-4\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2019).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eEgger, R., Schlee, D. \\u0026amp; Turk, R. Changes of physiologicaland biochemical parameters in the lichen \\u003cem\\u003eHypogymnia physodes\\u003c/em\\u003e (L) Nyl. due to the action of air pollutants\\u0026mdash;a field study. \\u003cem\\u003ePhyton\\u003c/em\\u003e \\u003cb\\u003e34\\u003c/b\\u003e, 229\\u0026ndash;242 (1994).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eFrati, L. \\u0026amp; Brunialti, G. Recent trends and future challenges for lichen biomonitoring in forests. \\u003cem\\u003eForests\\u003c/em\\u003e \\u003cb\\u003e14\\u003c/b\\u003e (1), 647. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.3390/f14030647\\u003c/span\\u003e\\u003cspan address=\\\"10.3390/f14030647\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2023).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eHernansanz-Agust\\u0026iacute;n, P. \\u0026amp; Enr\\u0026iacute;quez, J. A. Generation of Reactive Oxygen Species by Mitochondria. \\u003cem\\u003eAntioxidants\\u003c/em\\u003e \\u003cb\\u003e10\\u003c/b\\u003e, 415. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.3390/antiox10030415\\u003c/span\\u003e\\u003cspan address=\\\"10.3390/antiox10030415\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2021).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eGawrońska, K. \\u0026amp; Gołębiowska-Pikania, G. The effects of cold-hardening and Microdochium nivale infection on oxidative stress and antioxidative protection of the two contrasting genotypes of winter triticale. \\u003cem\\u003eEur. Food Res. Technol.\\u003c/em\\u003e \\u003cb\\u003e242\\u003c/b\\u003e, 1267\\u0026ndash;1276. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1007/s00217-015-2630-8\\u003c/span\\u003e\\u003cspan address=\\\"10.1007/s00217-015-2630-8\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2016).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eGawrońska, K., Romanowska, E., Miszalski, Z. \\u0026amp; Niewiadomska, E. Limitation of C3\\u0026ndash;CAM shift in the common ice plant under high irradiance. \\u003cem\\u003eJ. Plant Physiol.\\u003c/em\\u003e \\u003cb\\u003e170\\u003c/b\\u003e (2), 129\\u0026ndash;135. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1016/j.jplph.2012.09.019\\u003c/span\\u003e\\u003cspan address=\\\"10.1016/j.jplph.2012.09.019\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2013).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eGazda, A. \\u0026amp; Szlaga, A. Obce gatunki drzewiaste w p\\u0026oacute;łnocnym kompleksie Puszczy Niepołomickiej [Alien tree species in the northern part of the Niepołomice Forest]. \\u003cem\\u003eSylwan\\u003c/em\\u003e \\u003cb\\u003e152\\u003c/b\\u003e (4), 58\\u0026ndash;67 (2008).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eGł\\u0026oacute;wny Inspektorat Ochrony Środowiska. Regionalny Wydział Monitoringu Środowiska w Krakowie, Departament Monitoringu Środowiska. Roczna ocena jakości powietrza w wojew\\u0026oacute;dztwie małopolskim: Raport wojew\\u0026oacute;dzki za rok 2019. [Annual air quality assessment in the Małopolska Province: Provincial report for 2019]. \\u003cem\\u003eGł\\u0026oacute;wny Inspektorat Ochrony Środowiska\\u003c/em\\u003e (2020).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eGodzik, B. \\u0026amp; Piechnik, Ł. Puszcza Niepołomicka \\u0026ndash; zr\\u0026oacute;wnoważona gospodarka leśna a ochrona bogactwa przyrodniczego. [The Niepołomice Forest \\u0026ndash; sustainable Forest management and protection of natural wealth]. \\u003cem\\u003eZjazd Polskiego Towarzystwa Botanicznego Przewodnik sesji terenowych\\u003c/em\\u003e : 183\\u0026ndash;213 (2019).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eGodzik, B. \\u0026amp; Szarek, G. Heavy metals in mosses from the Niepołomice Forest, southern Poland \\u0026ndash; changes in 1975\\u0026ndash;1992. \\u003cem\\u003eFragmenta Floristica et Geobotanica\\u003c/em\\u003e. \\u003cb\\u003e38\\u003c/b\\u003e (1), 199\\u0026ndash;208 (1993).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eGodzik, B. \\u0026amp; Szarek-Łukaszewska, G. Concentrations of heavy metals in \\u003cem\\u003eMoehringia trinervia\\u003c/em\\u003e (Caryophyllaceae) in the Niepołomice Forest (S Poland) \\u0026ndash; changes from 1984 to 1999. \\u003cem\\u003ePol. Bot. Stud.\\u003c/em\\u003e \\u003cb\\u003e19\\u003c/b\\u003e, 43\\u0026ndash;47 (2005).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eG\\u0026oacute;mez, S., Vergara, M., Rivadeneira, B., Rodr\\u0026iacute;guez, J. \\u0026amp; Carpio, A. Use of lichens as bioindicators of contamination by agrochemicals and metals. \\u003cem\\u003eEnviron. Sci. Pollut. Res.\\u003c/em\\u003e \\u003cb\\u003e31\\u003c/b\\u003e, 49214\\u0026ndash;49226. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1007/s11356-024-34450-z\\u003c/span\\u003e\\u003cspan address=\\\"10.1007/s11356-024-34450-z\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2024).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eGrabowski, A. Zmiany morfologiczne koron sosny w Puszczy Niepołomickiej. [Morphological changes of pine crowns in the Niepołomice Forest]. \\u003cem\\u003eStudia Ośrodka Dokumentacji Fizjograficznej\\u003c/em\\u003e. \\u003cb\\u003e9\\u003c/b\\u003e, 357\\u0026ndash;367 (1981).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eGrodzińska, K. Zawartość siarki w og\\u0026oacute;lnej w szpilkach sosny zwyczajnej (\\u003cem\\u003ePinus silvestris\\u003c/em\\u003e) z Puszczy Niepołomickiej. [Total sulphur content of Scots pine (\\u003cem\\u003ePinus silvestris\\u003c/em\\u003e) pins from the Niepołomice Forest]. \\u003cem\\u003eStudia Ośrodka Dokumentacji Fizjograficznej\\u003c/em\\u003e. \\u003cb\\u003e9\\u003c/b\\u003e, 293\\u0026ndash;301 (1981).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eGrodzińska, K., Godzik, B., Darowska, E. \\u0026amp; Pawłowska, B. Concentration of heavy metals in trophic chains of Niepołomice Forest. \\u003cem\\u003eS Pol. Ekologia Polska\\u003c/em\\u003e. \\u003cb\\u003e35\\u003c/b\\u003e (2), 327\\u0026ndash;344 (1987).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eGrodzińska, K., Szarek-Łukaszewska, G., Frontasyeva, M., Pavlov, S. S. \\u0026amp; Gudorina, S. F. Multielement concentration in mosses in the forest influenced by industrial emissions (Niepołomice Forest, S Poland) at the end of the 20th century. \\u003cem\\u003ePol. J. Environ. Stud.\\u003c/em\\u003e \\u003cb\\u003e14\\u003c/b\\u003e (2), 165\\u0026ndash;172 (2005).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eHjortenkrans, D. S., Bergb\\u0026auml;ck, B. G. \\u0026amp; H\\u0026auml;ggerud, A. V. Metal emissions from brake linings and tires: case studies of Stockholm, Sweden 1995/1998 and 2005. \\u003cem\\u003eEnviron. Sci. Technol.\\u003c/em\\u003e \\u003cb\\u003e41\\u003c/b\\u003e (15), 5224\\u0026ndash;5230. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1021/es070198o\\u003c/span\\u003e\\u003cspan address=\\\"10.1021/es070198o\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2007).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eHuang, D. et al. Effects of calcium at toxic concentrations of cadmium in plants. \\u003cem\\u003ePlanta\\u003c/em\\u003e \\u003cb\\u003e245\\u003c/b\\u003e, 863\\u0026ndash;873. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1007/s00425-017-2664-1\\u003c/span\\u003e\\u003cspan address=\\\"10.1007/s00425-017-2664-1\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2017).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eHutton, M. Sources of cadmium in the environment. \\u003cem\\u003eEcotoxicol. Environ. Saf.\\u003c/em\\u003e \\u003cb\\u003e7\\u003c/b\\u003e (1), 9\\u0026ndash;24. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1016/0147-6513(83)90044-1\\u003c/span\\u003e\\u003cspan address=\\\"10.1016/0147-6513(83)90044-1\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (1983).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eInspektorat Ochrony \\u0026amp; Środowiska Krajowy raport mozaikowy o stanie środowiska. [National mosaic report on the state of the environment.] \\u003cem\\u003eWojew\\u0026oacute;dzki Inspektorat Ochrony Środowiska Krak\\u0026oacute;w\\u003c/em\\u003e, Krak\\u0026oacute;w. (2007).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eJackson, T. A. Long-range atmospheric transport of mercury to ecosystems, and the importance of anthropogenic emissions\\u0026mdash;a critical review and evaluation of the published evidence. \\u003cem\\u003eEnviron. Reviews\\u003c/em\\u003e. \\u003cb\\u003e5\\u003c/b\\u003e (2). \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1139/a97-005\\u003c/span\\u003e\\u003cspan address=\\\"10.1139/a97-005\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (1997).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eJeong, H. Toxic metal concentrations and Cu\\u0026ndash;Zn\\u0026ndash;Pb isotopic compositions in tires. \\u003cem\\u003eJ. Anal. Sci. Technol.\\u003c/em\\u003e \\u003cb\\u003e13\\u003c/b\\u003e (2). \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1186/s40543-021-00312-3\\u003c/span\\u003e\\u003cspan address=\\\"10.1186/s40543-021-00312-3\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2022).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eJohansson, L. S., Tullin, C., Leckner, B. \\u0026amp; Sj\\u0026ouml;vall, P. Particle emissions from biomass combustion in small combustors. \\u003cem\\u003eBiomass Bioenerg.\\u003c/em\\u003e \\u003cb\\u003e25\\u003c/b\\u003e (4), 435\\u0026ndash;446. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1016/S0961-9534(03)00036-9\\u003c/span\\u003e\\u003cspan address=\\\"10.1016/S0961-9534(03)00036-9\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2003).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eJ\\u0026oacute;źwiak, M. Kumulacja metali ciężkich i zmiany morfologiczne w plechach porostu \\u003cem\\u003eHypogymnia physodes\\u003c/em\\u003e (L.)Nyl. [Accumulation of heavy metals and morphological changes in thalli of \\u003cem\\u003eHypogymnia physodes\\u003c/em\\u003e (L.)Nyl.) lichen]. \\u003cem\\u003eMonit. Środowiska Przyrodniczego\\u003c/em\\u003e. \\u003cb\\u003e8\\u003c/b\\u003e, 51\\u0026ndash;56 (2007).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eKapusta, P., Stanek, M., Szarek-Łukaszewska, G. \\u0026amp; Godzik, B. Long-term moss monitoring of atmospheric deposition near a large steelworks reveals the growing importance of local non-industrial sources of pollution. \\u003cem\\u003eChemosphere\\u003c/em\\u003e \\u003cb\\u003e230\\u003c/b\\u003e, 29\\u0026ndash;39 (2019).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eKapusta, P., Szarek-Łukaszewska, G. \\u0026amp; Kiszka, J. Spatial analysis of lichen species richness in a disturbed ecosystem (Niepołomice Forest, S Poland). \\u003cem\\u003eLichenologist\\u003c/em\\u003e \\u003cb\\u003e36\\u003c/b\\u003e (3\\u0026ndash;4), 249\\u0026ndash;260 (2004).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eKiszka, J. Porosty Kotliny Sandomierskiej. Część I. Porosty Okręgu Puszczy Niepołomickiej [The lichens of the Sandomierz Lowland. Part I: Lichens of Niepołomice Forest district]. \\u003cem\\u003eFragmenta Floristica et Geobotanica\\u003c/em\\u003e. \\u003cb\\u003e10\\u003c/b\\u003e (4), 527\\u0026ndash;564 (1964).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eKiszka, J. Bioindykacja środowiska przyrodniczego na przykładzie porost\\u0026oacute;w w Krakowie i Puszczy Niepołomickiej. [Bioindication of the natural environment on the example of lichens of Cracow and the Niepołomice Forest]. In: W. Grodziński, W. Juszczyk, J. Kiszka, A. Medwecka-Kornaś (Ed.). Problemy ekologiczne i fizjologiczne w ochronie środowiska makroregionu Południowego. [Ecological and physiological problems in the protection of the environment of the Southern macro-region]. \\u003cem\\u003eSympozjum \\u0026bdquo;Człowiek i Środowisko, Sesja XXX-lecia PRL\\u003c/em\\u003e: 11\\u0026ndash;17. (1974).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eKiszka, J. Wpływ emisji miejskich i przemysłowych na florę porost\\u0026oacute;w (Lichenes) Krakowa i Puszczy Niepołomickiej. [Influence of urban and industrial emissions on the lichen flora (Lichenes) of Krak\\u0026oacute;w and the Niepołomice Forest]. \\u003cem\\u003ePrace Monograficzne Wyższej Szkoły Pedagogicznej w Krakowie\\u003c/em\\u003e. \\u003cb\\u003e19\\u003c/b\\u003e, 5\\u0026ndash;32 (1977).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eKiszka, J. Porosty rezerwatu Lip\\u0026oacute;wka w Puszczy Niepołomickiej [The lichens in the forest reserve of Lip\\u0026oacute;wka in the Niepołomice Forest]. \\u003cem\\u003eStudia Nat. Seria A\\u003c/em\\u003e. \\u003cb\\u003e17\\u003c/b\\u003e, 149\\u0026ndash;158 (1978).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eKiszka, J. Lichens. In: K. Grodzińska (Ed.). Acidification of forest environment (Niepołomice Forest) caused by SO2 emissions from steel mills (Final report on investigations from the period July 1.1976-June 30.). \\u003cem\\u003eInstitute of Botany Polish Academy of Sciences, Cracow\\u003c/em\\u003e: 86\\u0026ndash;89. (1980).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eKiszka, J. Flora porost\\u0026oacute;w (Lichenes) Puszczy Niepołomickiej. [Flora of lichens (Lichenes) of the Niepołomice Forest]. \\u003cem\\u003eStudia Ośrodka Dokumentacji Fizjograficznej\\u003c/em\\u003e. \\u003cb\\u003e9\\u003c/b\\u003e, 335\\u0026ndash;356 (1981).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eKiszka, J. Lichenoindykacja obszaru wojew\\u0026oacute;dztwa krakowskiego. [Licheno-indication of the area of the Cracow voivodeship]. \\u003cem\\u003eStudia Ośrodka Dokumentacji Fizjograficznej\\u003c/em\\u003e. \\u003cb\\u003e18\\u003c/b\\u003e, 201\\u0026ndash;212 (1990).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eKiszka, J. \\u0026amp; Grodzińska, K. Lichen flora and air pollution in the Niepolomice Forest (S Poland) in 1960\\u0026thinsp;\\u0026ndash;\\u0026thinsp;200. \\u003cem\\u003eBiol. (Bratislava)\\u003c/em\\u003e. \\u003cb\\u003e59\\u003c/b\\u003e (1), 25\\u0026ndash;37 (2004). ISSN 0006-3088.\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eKov\\u0026aacute;čik, J., Dresler, S., Babula, P. \\u0026amp; Hladk\\u0026yacute;J., Sowa, I. Calcium has protective impact on cadmium-induced toxicity in lichens. \\u003cem\\u003ePlant Physiol. Biochem.\\u003c/em\\u003e \\u003cb\\u003e156\\u003c/b\\u003e, 591\\u0026ndash;599. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1016/j.plaphy.2020.10.007\\u003c/span\\u003e\\u003cspan address=\\\"10.1016/j.plaphy.2020.10.007\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2020).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eLaemmli, U. K. Cleavage of structural proteins during the assembly of the head of bacteriophage T4. \\u003cem\\u003eNature\\u003c/em\\u003e \\u003cb\\u003e227\\u003c/b\\u003e, 680\\u0026ndash;685. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1038/227680a0\\u003c/span\\u003e\\u003cspan address=\\\"10.1038/227680a0\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (1970).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eLin, C. K. et al. A Global Perspective on Sulfur Oxide Controls in Coal-Fired Power Plants and Cardiovascular Disease. \\u003cem\\u003eSci. Rep.\\u003c/em\\u003e \\u003cb\\u003e8\\u003c/b\\u003e, 2611. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1038/s41598-018-20404-2\\u003c/span\\u003e\\u003cspan address=\\\"10.1038/s41598-018-20404-2\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2018).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eLucadamo, L., Gallo, L. \\u0026amp; Corapi, A. Detection of air quality improvement within a suburban district (southern Italy) by means of lichen biomonitoring. \\u003cem\\u003eAtmospheric Pollution Res.\\u003c/em\\u003e \\u003cb\\u003e13\\u003c/b\\u003e (3), 101346. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1016/j.apr.2022.101346\\u003c/span\\u003e\\u003cspan address=\\\"10.1016/j.apr.2022.101346\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2022).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eMaring, T., Kumar, S., Jha, A. K., Kumar, N. \\u0026amp; Pandey, S. P. Airborne Particulate Matter and Associated Heavy Metals: A Review. \\u003cem\\u003eMacromolecular Symposia\\u003c/em\\u003e. \\u003cb\\u003e407\\u003c/b\\u003e, 2100487. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1002/masy.202100487\\u003c/span\\u003e\\u003cspan address=\\\"10.1002/masy.202100487\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2023).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eMarumoto, K., Hayashi, M. \\u0026amp; Takami, A. Atmospheric mercury concentrations at two sites in the Kyushu Islands, Japan, and evidence of long-range transport from East Asia. \\u003cem\\u003eAtmos. Environ.\\u003c/em\\u003e \\u003cb\\u003e117\\u003c/b\\u003e, 147\\u0026ndash;155. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1016/j.atmosenv.2015.07.019\\u003c/span\\u003e\\u003cspan address=\\\"10.1016/j.atmosenv.2015.07.019\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2015).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eMasindi, V., Mkhonza, P. \\u0026amp; Tekere, M. Sources of heavy metals pollution. In: Inamuddin, Ahamed M.I., Lichtfouse E., Altalhi T. (Ed.). Remediation of heavy metals. environmental chemistry for a sustainable world 70. \\u003cem\\u003eSpringer\\u003c/em\\u003e, Cham: 419\\u0026ndash;454. (2021). \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1007/978-3-030-80334-6_17\\u003c/span\\u003e\\u003cspan address=\\\"10.1007/978-3-030-80334-6_17\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eMatei, E. et al. Covaliu-Mierlă C.I. Heavy metals in particulate matter\\u0026mdash;trends and impacts on environment. \\u003cem\\u003eMolecules\\u003c/em\\u003e \\u003cb\\u003e30\\u003c/b\\u003e (7), 1455. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.3390/molecules30071455\\u003c/span\\u003e\\u003cspan address=\\\"10.3390/molecules30071455\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2025).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eMinisterstwo Klimatu i Środowiska. Krajowy bilans emisji SO2, NOX, CO, NH3, NMLZO, pył\\u0026oacute;w, metali ciężkich i TZO za lata 1990\\u0026ndash;2018. Raport syntetyczny. [National emissions balance of SO2, NOX, CO, NH3, NMLZO, dust, heavy metals and TZO for the period 1990\\u0026ndash;2018. Synthesis report]. Krajowy Ośrodek Inwentaryzacji i Raportowania Emisji, Instytut Ochrony Środowiska \\u0026ndash; Państwowy Instytut Badawczy, Warszawa. (2020).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eMinisterstwo Klimatu i Środowiska. Krajowy bilans emisji SO2, NOX, CO, NH3, NMLZO, pył\\u0026oacute;w, metali ciężkich i TZO za lata 1990\\u0026ndash;2019. Raport syntetyczny. [National emissions balance of SO2, NOX, CO, NH3, NMLZO, dust, heavy metals and TZO for the period 1990\\u0026ndash;2019. Synthesis report]. Krajowy Ośrodek Inwentaryzacji i Raportowania Emisji, Instytut Ochrony Środowiska \\u0026ndash; Państwowy Instytut Badawczy, Warszawa. (2021).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eMittler, R. Oxidative stress, antioxidants and stress tolerance. \\u003cem\\u003eTrends Plant Sci.\\u003c/em\\u003e \\u003cb\\u003e7\\u003c/b\\u003e (9), 405\\u0026ndash;410. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1016/S1360-1385(02)02312-9\\u003c/span\\u003e\\u003cspan address=\\\"10.1016/S1360-1385(02)02312-9\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2002).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eNimis, P. L., Lazzarin, G., Lazzarin, A. \\u0026amp; Skert, N. Biomonitoring of trace elements with lichens in Veneto (NE Italy). \\u003cem\\u003eSci. Total Environ.\\u003c/em\\u003e \\u003cb\\u003e255\\u003c/b\\u003e (1\\u0026ndash;3), 97\\u0026ndash;111. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1016/S0048-9697(00)00454-X\\u003c/span\\u003e\\u003cspan address=\\\"10.1016/S0048-9697(00)00454-X\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2000).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eNzihou, A. \\u0026amp; Stanmore, B. The fate of heavy metals during combustion and gasification of contaminated biomass - A brief review. \\u003cem\\u003eJ. Hazard. Mater.\\u003c/em\\u003e \\u003cb\\u003e256\\u0026ndash;257\\u003c/b\\u003e, 56\\u0026ndash;66. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1016/j.jhazmat.2013.02.050\\u003c/span\\u003e\\u003cspan address=\\\"10.1016/j.jhazmat.2013.02.050\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2013).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eOlivia, S. R. \\u0026amp; Rautio, P. Could ornamental plants serve as passive biomonitors in urban area? \\u003cem\\u003eJ. Atmos. Chem.\\u003c/em\\u003e \\u003cb\\u003e49\\u003c/b\\u003e, 137\\u0026ndash;148. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1007/s10874-004-1220-0\\u003c/span\\u003e\\u003cspan address=\\\"10.1007/s10874-004-1220-0\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2004).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eOsyczka, P., Chowaniec, K. \\u0026amp; Skubała, K. Membrane lipid peroxidation in lichens determined by the TBARS assay as a suitable biomarker for the prediction of elevated level of potentially toxic trace elements in soil. \\u003cem\\u003eEcol. Ind.\\u003c/em\\u003e \\u003cb\\u003e146\\u003c/b\\u003e, 109910. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1016/j.ecolind.2023.109910\\u003c/span\\u003e\\u003cspan address=\\\"10.1016/j.ecolind.2023.109910\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2023).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003ePurvis, O. W. \\u0026amp; Pawlik-Skowrońska, B. Lichens and metals. \\u003cem\\u003eBr. Mycological Soc. Symposia Ser.\\u003c/em\\u003e \\u003cb\\u003e27\\u003c/b\\u003e, 175\\u0026ndash;200. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1016/S0275-0287(08)80054-9\\u003c/span\\u003e\\u003cspan address=\\\"10.1016/S0275-0287(08)80054-9\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2008).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eQu, Y., An, J., He, Y. \\u0026amp; Zheng, J. An overview of emissions of SO2 and NOx and the long-range transport of oxidized sulfur and nitrogen pollutants in East Asia. \\u003cem\\u003eJ. Environ. Sci.\\u003c/em\\u003e \\u003cb\\u003e44\\u003c/b\\u003e, 13\\u0026ndash;25. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1016/j.jes.2015.08.028\\u003c/span\\u003e\\u003cspan address=\\\"10.1016/j.jes.2015.08.028\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2016).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eR Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL (2020). \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://www.R-project.org/\\u003c/span\\u003e\\u003cspan address=\\\"https://www.R-project.org/\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eRučov\\u0026aacute;, D. et al. Investigation of Calcium Forms in Lichens from Travertine Sites. \\u003cem\\u003ePlants\\u003c/em\\u003e 11, 620. (2022). \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.3390/plants11050620\\u003c/span\\u003e\\u003cspan address=\\\"10.3390/plants11050620\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eSantos, A. M. D. et al. Impacts of Cd Pollution on the Vitality, Anatomy and Physiology of Two Morphologically Different Lichen Species of the Genera Parmotrema and Usnea. \\u003cem\\u003eEvaluated under Experimental Conditions Divers.\\u003c/em\\u003e \\u003cb\\u003e14\\u003c/b\\u003e, 926. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.3390/d14110926\\u003c/span\\u003e\\u003cspan address=\\\"10.3390/d14110926\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2022).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eSawicka-Kapusta, K., Zakrzewska, M., Dudzik, P. \\u0026amp; Gołuszka, K. Zanieczyszczenia powietrza Stacji Bazowych ZMSP w 2011 roku na podstawie koncentracji metali ciężkich i siarki w plechach porostu \\u003cem\\u003eHypogymnia physodes\\u003c/em\\u003e zebranych z naturalnego środowiska. [Air pollution of the base stations of the Integrated Monitoring of Natural Environment in 2011 on the basis of heavy metals and sulphur concentration in lichen \\u003cem\\u003eHypogymnia physodes\\u003c/em\\u003e collected from natural environment]. \\u003cem\\u003eMonit. Środowiska Przyrodniczego\\u003c/em\\u003e. \\u003cb\\u003e16\\u003c/b\\u003e, 49\\u0026ndash;57 (2014).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eSawicka-Kapusta, K., Zakrzewska, M., Gdula-Argasińska, J. \\u0026amp; Bydłoń, G. Air pollution in the base stations of the environmental integrated monitoring system in Poland. In: Brebbia C.A. (Ed.) Air Pollution XIII. \\u003cem\\u003eWIT Transaction on Ecology and the Environment\\u003c/em\\u003e 82: 465\\u0026ndash;475. ISSN 1743\\u0026ndash;3541. (2005).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eSeaward, M. R. D. Lichens and sulphur dioxide air pollution: field studies. \\u003cem\\u003eEnviron. Reviews\\u003c/em\\u003e. \\u003cb\\u003e1\\u003c/b\\u003e (2). \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1139/a93-007\\u003c/span\\u003e\\u003cspan address=\\\"10.1139/a93-007\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (1993).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eShikhovtsev, M. Y. et al. Features of temporal variability of the concentrations of gaseous trace pollutants in the air of the urban and rural areas in the Southern Baikal region (East Siberia, Russia). \\u003cem\\u003eAppl. Sci.\\u003c/em\\u003e \\u003cb\\u003e14\\u003c/b\\u003e (18), 8327. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.3390/app14188327\\u003c/span\\u003e\\u003cspan address=\\\"10.3390/app14188327\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2024).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eSigler, J. M., Lee, X. \\u0026amp; Munger, W. Emission and long-range transport of gaseous mercury from a large-scale Canadian boreal forest fire. \\u003cem\\u003eEnviron. Sci. Technol.\\u003c/em\\u003e \\u003cb\\u003e37\\u003c/b\\u003e (19), 4343\\u0026ndash;4347. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1021/es026401r\\u003c/span\\u003e\\u003cspan address=\\\"10.1021/es026401r\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2003).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eSippula, O., Hokkinen, J., Puustinen, H., Yli-Piril\\u0026auml;, P. \\u0026amp; Jokiniemi, J. Comparison of particle emissions from small heavy fuel oil and wood-fired boilers. \\u003cem\\u003eAtmospheric Environ.\\u003c/em\\u003e \\u003cb\\u003e43\\u003c/b\\u003e (32), 4855\\u0026ndash;4864. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1016/j.atmosenv.2009.07.022\\u003c/span\\u003e\\u003cspan address=\\\"10.1016/j.atmosenv.2009.07.022\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2009).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eSzarek-Łukaszewska, G., Grodzińska, K. \\u0026amp; Braniewski, S. Heavy metal concentration in the moss \\u003cem\\u003ePleurozium\\u003c/em\\u003e Schreberi in the Niepołomice Forest, Poland: changes during 20 years. \\u003cem\\u003eEnviron. Monit. Assess.\\u003c/em\\u003e \\u003cb\\u003e79\\u003c/b\\u003e, 231\\u0026ndash;237. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1023/A:1020226526451\\u003c/span\\u003e\\u003cspan address=\\\"10.1023/A:1020226526451\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2002).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eŚwietlik, R., Trojanowska, M. \\u0026amp; Rabek, P. Distribution patterns of Cd, Cu, Mn, Pb and Zn in wood fly ash emitted from domestic boilers. \\u003cem\\u003eChem. Speciat. Bioavailab.\\u003c/em\\u003e \\u003cb\\u003e35\\u003c/b\\u003e (1), 63\\u0026ndash;70. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.3184/095422912X13497968675047\\u003c/span\\u003e\\u003cspan address=\\\"10.3184/095422912X13497968675047\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2012).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eThakur, M., Bhardwaj, S., Kumar, V. \\u0026amp; Rodrigo-Comino, J. Lichens as effective bioindicators for monitoring environmental changes: A comprehensive review. \\u003cem\\u003eTotal Environ. Adv.\\u003c/em\\u003e \\u003cb\\u003e9\\u003c/b\\u003e, 200085. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1016/j.teadva.2023.200085\\u003c/span\\u003e\\u003cspan address=\\\"10.1016/j.teadva.2023.200085\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2024).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eTurhan, S. B., Oruc, I. \\u0026amp; Ozdemir, H. Impact of heating season on the soil pollution in Kirklareli province of Turkey. \\u003cem\\u003eEnviron. Monit. Assess.\\u003c/em\\u003e \\u003cb\\u003e193\\u003c/b\\u003e, 209. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1007/s10661-021-09002-4\\u003c/span\\u003e\\u003cspan address=\\\"10.1007/s10661-021-09002-4\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2021).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eUchwała nr XVIII/243/16 Sejmiku. \\u003cem\\u003eXVIII/243/16 of the Sejmik of the Małopolskie Voivodeship of 15.01.2016. On the introduction in the area of the Municipality of Krakow of restrictions on the operation of installations in which fuel is burned]\\u003c/em\\u003e (Poland, 2016). Wojew\\u0026oacute;dztwa Małopolskiego z dnia 15.01.2016. W sprawie wprowadzenia na obszarze Gminy Miejskiej Krak\\u0026oacute;w ograniczeń w zakresie ekspoatacji instalacji, w kt\\u0026oacute;rych następuje spalanie paliw. [Resolution No.\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eWeiner, J., Fredro-Boniecki, S., Reed, D., Maclean, A. \\u0026amp; Strong, M. Niepołomice Forest - a GIS analysis of ecosystem response to industrial pollution. \\u003cem\\u003eEnviron. Pollut.\\u003c/em\\u003e \\u003cb\\u003e98\\u003c/b\\u003e (3), 381\\u0026ndash;388. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1016/S0269-7491(97)00152-8\\u003c/span\\u003e\\u003cspan address=\\\"10.1016/S0269-7491(97)00152-8\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (1997).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eWiseman, R. D. \\u0026amp; Wadleigh, M. A. Lichen response to changes in atmospheric sulphur: isotopic evidence. \\u003cem\\u003eEnvironmental Pollution\\u003c/em\\u003e 116(2): 235\\u0026ndash;241. (2002). \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1016/S0269-7491(01)00133-6\\u003c/span\\u003e\\u003cspan address=\\\"10.1016/S0269-7491(01)00133-6\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (2002).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eWojew\\u0026oacute;dzki Inspektorat Ochrony Środowiska w Krakowie. \\u003cem\\u003eRaport o stanie środowiska w wojew\\u0026oacute;dztwie małopolskim w 2016 roku. [Report on the state of the environment in the Małopolskie Voivodeship in 2016]\\u003c/em\\u003e (Wojew\\u0026oacute;dzki Inspektorat Ochrony Środowiska w Krakowie, 2017).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eXiao, H., Carmichael, G. R., Durchenwald, J., Thornton, D. \\u0026amp; Bandy, A. Long-range transport of SOx and dust in East Asia during the PEM B Experiment. \\u003cem\\u003eJ. Geophys. Research: Atmos.\\u003c/em\\u003e \\u003cb\\u003e102\\u003c/b\\u003e (D23), 28589\\u0026ndash;28612. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1029/96JD03782\\u003c/span\\u003e\\u003cspan address=\\\"10.1029/96JD03782\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (1997).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eZeedijk, H. \\u0026amp; Velds, C. A. The transport of sulphur dioxide over a long distance. \\u003cem\\u003eAtmospheric Environ.\\u003c/em\\u003e \\u003cb\\u003e7\\u003c/b\\u003e (9), 849\\u0026ndash;862. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1016/0004-6981(73)90107-8\\u003c/span\\u003e\\u003cspan address=\\\"10.1016/0004-6981(73)90107-8\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (1973).\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eClimate-Data.org. \\u003cem\\u003eKlimat: Niepołomice\\u003c/em\\u003e. Climate-Data.org. (2025). \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://pl.climate-data.org/europa/polska/lesser-poland-voivodeship/niepołomice-10403/\\u003c/span\\u003e\\u003cspan address=\\\"https://pl.climate-data.org/europa/polska/lesser-poland-voivodeship/niepołomice-10403/\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e. [access 10-05-2025].\\u003c/span\\u003e\\u003c/li\\u003e\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":true,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"scientific-reports\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"scirep\",\"sideBox\":\"Learn more about [Scientific Reports](http://www.nature.com/srep/)\",\"snPcode\":\"\",\"submissionUrl\":\"\",\"title\":\"Scientific Reports\",\"twitterHandle\":\"\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"stoa\",\"reportingPortfolio\":\"Scientific Reports\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true},\"keywords\":\"\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-7719127/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-7719127/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003eThe Niepołomice Forest, though relatively natural, is affected by air pollutants transported from nearby urban areas. To assess this impact, we examined the bioaccumulation of elements (Ca, Cd, Cu, Fe, Hg, Pb, S, Zn) in thalli of \\u003cem\\u003eHypogymnia physodes\\u003c/em\\u003e (L.) Nyl., together with oxidative stress biomarkers (SOD, TBARS) and thallus condition, at 15 sites. Samples were collected during both heating and non-heating seasons. Seasonal variability was observed: Cd, SOD, and TBARS were higher in the non-heating season, while S increased during the heating season, reflecting emissions from fuel combustion. Spatial differences were most pronounced for Cd, Zn, and TBARS. In the western part of the forest, \\u003cem\\u003eH. physodes\\u003c/em\\u003e was absent at some sites, and lichens showed elevated Pb and Cu concentrations with increased SOD activity, indicating strong traffic-related pollution. In the east, thalli contained a high proportion of degenerated algae, associated with elevated Cd, Hg, and S, as well as other stressors. Overall, element concentrations were similar to those reported from other regions of Poland. The study highlights that even seemingly natural forests are subject to significant pollution pressure. Combining chemical data with biomarkers offers deeper insight into the effects of toxic elements on lichen bioindicators.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Temporal and spatial characteristics of the composition of Hypogymnia physodes (Monk’s-hood lichen) from the Niepołomice Forest in Poland\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2025-10-31 17:04:25\",\"doi\":\"10.21203/rs.3.rs-7719127/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"decision\",\"content\":\"Revision requested\",\"date\":\"2025-11-04T06:09:28+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2025-10-29T10:56:34+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2025-10-27T14:02:15+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"170969030774851516011799141032813731865\",\"date\":\"2025-10-24T09:33:50+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"15677075264008097887854317547384848586\",\"date\":\"2025-10-24T07:15:33+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"132280543931783517141932701141582091509\",\"date\":\"2025-10-22T14:22:07+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"222818186191021554733551482989799945103\",\"date\":\"2025-10-22T08:51:10+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"227939589623557792227635446704966481042\",\"date\":\"2025-10-21T21:09:26+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"103918310536563226062052169261031886415\",\"date\":\"2025-10-21T17:54:48+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"274077975588004091626596599827596494605\",\"date\":\"2025-10-21T16:39:14+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"331497488706005537644636572853352837328\",\"date\":\"2025-10-21T13:37:31+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewersInvited\",\"content\":\"\",\"date\":\"2025-10-21T13:31:21+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvited\",\"content\":\"\",\"date\":\"2025-09-30T09:56:14+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorAssigned\",\"content\":\"\",\"date\":\"2025-09-29T08:28:16+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"checksComplete\",\"content\":\"\",\"date\":\"2025-09-27T00:50:35+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"submitted\",\"content\":\"Scientific Reports\",\"date\":\"2025-09-26T07:45:39+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"scientific-reports\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"scirep\",\"sideBox\":\"Learn more about [Scientific Reports](http://www.nature.com/srep/)\",\"snPcode\":\"\",\"submissionUrl\":\"\",\"title\":\"Scientific Reports\",\"twitterHandle\":\"\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"stoa\",\"reportingPortfolio\":\"Scientific Reports\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"68dd20e0-63e8-4fbc-bf33-8a61a62a4736\",\"owner\":[],\"postedDate\":\"October 31st, 2025\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"published-in-journal\",\"subjectAreas\":[{\"id\":57087384,\"name\":\"Biological sciences/Ecology\"},{\"id\":57087385,\"name\":\"Earth and environmental sciences/Ecology\"},{\"id\":57087386,\"name\":\"Earth and environmental sciences/Environmental sciences\"}],\"tags\":[],\"updatedAt\":\"2025-12-29T16:01:15+00:00\",\"versionOfRecord\":{\"articleIdentity\":\"rs-7719127\",\"link\":\"https://doi.org/10.1038/s41598-025-31463-7\",\"journal\":{\"identity\":\"scientific-reports\",\"isVorOnly\":false,\"title\":\"Scientific Reports\"},\"publishedOn\":\"2025-12-22 15:57:46\",\"publishedOnDateReadable\":\"December 22nd, 2025\"},\"versionCreatedAt\":\"2025-10-31 17:04:25\",\"video\":\"\",\"vorDoi\":\"10.1038/s41598-025-31463-7\",\"vorDoiUrl\":\"https://doi.org/10.1038/s41598-025-31463-7\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-7719127\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-7719127\",\"identity\":\"rs-7719127\",\"version\":[\"v1\"]},\"buildId\":\"8U1c8b4HqxoKbykW_rLl7\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}