Biocrusts significantly affect the bioavailability and ecological risk of heavy metals in gold mine tailings

Biocrusts are important living covers in ecologically fragile regions that intercept metals entering the soil and indicate heavy metal contamination. This study explored the potential of biocrusts as a novel approach for remediating heavy metal pollution in mining areas. We also investigated the capacity of biocrusts to enrich or degrade heavy metals in gold mine tailings and analyzed the migration, transformation mechanisms, and potential toxic effects of heavy metals in the underlying biocrusts. We used the BCR sequential extraction procedure to analyze the speciation of heavy metals in the underlying biocrust layer (moss crusts, mixed crusts (moss + algal), and algal crusts). The risk assessment code (RAC) and potential ecological risk index (Er) were used to evaluate the impact of biocrusts on the ecological risk assessment of heavy metals in soil. The results showed that (1) well-developed biocrusts had a strong ability to enrich heavy metals, with these metals accumulating at the surface; (2) biocrust growth facilitated the conversion of heavy metals from an inert state to an active form in the underlying layer, enhancing their bioavailability; (3) Spearman’s correlation and redundancy analysis (RDA) revealed the total amount of heavy metals as the primary factor driving the translocation of soil heavy metals, with soil pH, cationic exchange capacity (CEC) and organic matter content (SOM) exerting varying influences; (4) the comprehensive potential ecological risk index indicated that heavy metals in gold tailings at the strong risk levels, mainly due to arsenic exceeded the standard (~ 7 × background values). However, biocrusts reduced the Er of heavy metals in the underlying layer. The RAC results indicated low mobility and bioavailability of heavy metals in the underlying layer, associated with low ecological risk. As the ‘skin’ of soil, biocrusts could protect soil from heavy metal contamination. Despite enhancing heavy metal bioavailability, their enrichment effect was much greater than their activation effect. As a result, biocrusts hold great promise for remediating heavy metal pollution in degraded ecosystems. Further exploration of the influencing mechanism of biocrusts on heavy metals will help validate their use in mine restoration processes.


Introduction
Metal tailings resulting from mining operations pose significant environmental challenges.These tailings leach heavy metals, such as arsenic (As) and chromium (Cr), from sulfides in the piles, leading to surface fragmentation, nutrient losses, and heavy metal toxicity (Buch et al. 2021;Khan et al. 2008).These contaminants impede natural vegetation colonization and ecosystem reassembly and can threaten human health through various exposure pathways.For example, excess Cr exposure can cause gastrointestinal disorders, bleeding, and convulsions, with an increased risk of lung cancer in individuals chronically exposed to Cr 6+ (Stout et al. 2009), while As can lead to disorders of the nervous and cardiovascular systems (Rodríguez-Lado et al. 2013).The Ma'anqiao gold mine tailings, established in 1996 and closed in 2017, had an accumulated storage capacity of 7,476,600 m 3 and discharges of 13,084,100 t into the tailings.Various efforts have been made to mitigate heavy metal pollution in these mine tailings, such as: (1) the local government investing in the ecological treatment of 20 hm 2 of tailings land in 2004 through soil-covering (50 cm) and afforestation.After four years of remediation, the forestry eco-treatment effectively mitigated heavy metal pollution in soil, water, and leaves (Han et al. 2008).However, the forestry measures were costly and required large amounts of irrigation water, making it challenging to implement on a large scale; (2) As leaching tests on the tailings leachate revealed a decreasing trend in As content over time, but the leachate was acidic and easily migrated As in tailings residue increased significantly, impacting soil and surface water (Chen and Lu 2010).Despite various methods and technologies being used to repair heavy metal pollution in mine tailings, such as the soil change method (Douay et al. 2008), leaching method (Kuhlman and Greenfield 1999), phytoremediation method (McGrath et al. 2001), biochar remediation method (da Silva Medeiros et al. 2021).However, these approaches are costly, inefficient, and often result in secondary pollution.Thus, we must explore more environmentally friendly and effective repair materials like biocrusts.
Biocrusts are complex organic aggregationscemented by soil particles and microorganisms, algae and mosses-that are ecologically adaptable and highly tolerant of toxic environments (Bu et al. 2013;Belnap et al. 2014).Biocrusts are typically categorized as algae crusts, lichen crusts, and moss crusts based on the dominant phytoplankton in the crust (Li et al. 2003).In the revegetation process of mine tailings, biocrusts act as pioneer colonizing organisms and dominant ground covers.They play a crucial role in refining soil particles, enriching topsoil organic matter and nutrients, and improving soil structure by adsorbing and trapping atmospheric dustfall and minerals dissolved in precipitation, impacting mineral circulation and nutrient redistribution in fragile ecosystems (Evans and Belnap 1999;Li et al. 2010;Xu et al. 2013).Algae and mosses can tolerate heavy metals (Venter et al. 2018) and are good monitors of heavy metal contamination.For example, Orlekowsky et al. (2013) investigated algae species and 11 heavy metal contents in gold mine tailings in South Africa; after 15 years of remediation, the tailings had significantly more algal species and higher heavy metal contents (except Cr and U) than unrepaired tailings.Mao et al. (2022) used moss bags to monitor atmospheric heavy metal pollution in Xichang and showed that T. taxirameum accumulated heavy metals and was a good biomonitor of air pollution.However, despite their potential benefits, biocrusts can also become enriched with heavy metal pollutants (Wu et al. 2011), posing ecological risks to mine tailings and surrounding areas (Di Palma et al. 2017;Sonter et al. 2018).
Previous studies have focused on the total amounts of heavy metals, but understanding their bioavailability is crucial for assessing their impact on the soil environment (Lin et al. 2014(Lin et al. , 2022)).Analyzing the forms and speciation of heavy metals can provide valuable insights into their toxicity, mobility, and bioavailability in the environment (Hu et al. 2022;Siahcheshm et al. 2022;Zhang et al. 2017).However, the distribution patterns of biocrusts on metalliferous substrates and the mechanisms of heavy metal degradation and elimination by biocrusts remain poorly understood.Moreover, the influence of physicochemical properties on the migration and transformation of heavy metals at small spatial scales is not welldocumented.Therefore, it is essential to investigate the main factors and mechanisms of heavy metal migration by biocrusts to assess their feasibility as an ecological remediation measure.
This study focuses on three typical biocrusts (moss crusts, algal crusts, and moss-algal mixed crusts) from the Ma'anqiao gold tailings in the Qinling Mountains.We hypothesized that different biocrust types exhibit varying abilities to enrich heavy metals, subsequently influencing the morphological distributions of heavy metals in the underlying soil layer.We aimed to explore how different biocrust types affect heavy metal enrichment and transformation in soil, identify key chemical factors driving the migration of heavy metal speciation, and assess the impact of biocrust succession on heavy metal bioavailability and ecological risk to uncover the potential of biocrusts as a promising ecological remediation measure for heavy metal pollution in mining areas.

Study site
In September 2021, we undertook research on the Ma'anqiao gold mine tailings in Zhouzhi County, Xi'an City, Shaanxi Province, China (107°53′12″-108°11′39″ E, 33°44 ′49″-33° 53′ 50″ N; Fig. 1a).The site is situated in the northern foothills of the Qinling Mountains and characterized by a temperate continental-monsoon climate, with an annual average temperature of 13.2 °C and precipitation of 699.98 mm.The tailings consist of precious metal minerals of natural gold, with pyrite as the main metal mineral (particle size 0.03-0.05mm, poor gold content) and quartz, clay minerals, and calcite as the main gangue minerals.The tailings are oversaturated with SiO 2 and low in Mg, Ca, Fe, and Mn, and the mineralized element combination is Au-As-Sb-Hg.The tailings have a bulk density of 1.75 t.m -3 and an average particle size of 0.036 mm (Zhu et al. 2010).Numerous heavy metals exceed the background concentration at various plots in the tailings (Wu et al. 2011), resulting in reduced soil fertility, low biodiversity, sparse vegetation, and poor plant growth.Despite these challenges, a large area of biocrusts has developed (Fig. 2a), including 3-5 mm thick, dark-colored algal crusts continuously distributed under natural conditions (Fig. 2b) and 7-13 mm thick, patchy moss crusts that appear dark when dry and green when wet, and often mixed with algal crusts (Fig. 2c, d).

Sample collection
We established five representative biocrust plots (40 × 40 m, at least 50 m apart) (Fig. 1b), with each plot containing algal crusts, algal-moss crusts, and moss crusts.Five samples of each biocrust type from each plot were randomly collected using a sterile cutting ring and mixed to create five composite samples per biocrust type.The same method was used to collect soil from the 0-5 cm underlying biocrusts, and adjacent bare soil samples were collected as controls (Appendix Fig. S1).Thirty-five composite samples were collected (15 each from the biocrust and underlying layers, 5 from bare soil).The composite samples were divided into two parts for further analysis.The first part was air-dried to analyze soil heavy metal forms, while the second part was stored at 4 °C to analyze soil properties.
Soil pH was measured in the supernatant of a 1: 2.5 (soil: water ratio) extract using a pH meter (pH S-25, Leici, Shanghai, China).Cation exchange capacity (CEC) was determined using the flame photometric method (Bache 1976).Redox potential (Eh) was measured directly in the field using a soil redox potential meter (TR-901, Leici, Shanghai, China) following the depolarization method (Rabenhorst et al. 2009).Soil organic carbon was determined using the potassium dichromate oxidation and external heating method (Rowell and Coetzee 2003).
Total Cr and As contents were determined using an inductively coupled plasma emission spectrometer (ICP-OES, Optima 8000, PerkinElmer, USA) after digesting the samples with a microwave digester (Multiwave PRO, Antonpa, Austria).Cr was digested with HNO 3 -3HCl-HClO 4 and As with HNO 3 -HClO 4 -H 2 SO 4 .The chemical fractions of heavy metals in the samples were analyzed using the BCR sequential extraction procedure, which separates the metal distribution into acid-soluble (F1), reducible or Fe-Mn oxides (F2), oxidizable or organic matter-bound (F3), and residual (F4) fractions.Details of the extraction processes are in Rauret et al. (1999).ICP-OES was used to analyze the heavy metal contents in the extracted solutions.

Potential ecological risk index
The potential ecological risk assessment method, proposed by Hakanson (1980), reflects the pollution level of individual heavy metals and their combined ecological impact.The index is calculated as follows: where C i is the measured value of heavy metal i (total content), C i n is the reference value of heavy metal i selected from the background value of soils in Shaanxi Province (China National Environmental Monitoring Centre 1990; Cr = 62 mg/kg, As = 11.1 mg/kg), T i r is the toxicity coefficient of heavy metal i (Cr = 2, As = 10), E i r is the potential ecological risk coefficient of heavy metal i, and RI is the overall potential risk for all heavy metals in a region.Table 1 shows the potential ecological risk classification of heavy metals.
Limited by the number and nature of heavy metals, direct application of the Hakanson grading criteria may result in poor accuracy (Li et al. 2016).Therefore, we synthesized the literature (Fernandez and Carballeira 2001;Hakanson 1980;Ma et al. 2020) to adjust the grading standard for the single potential ecological risk index (Er) and the comprehensive potential ecological risk index (RI).
The first upper limit of Er value was obtained by multiplying the non-polluting pollution factor ( C i f =1) by the maximum toxicity factor among the pollutants, while the upper limit values of other risk levels were obtained by multiplying the risk value of the previous level by 2. Because the T value of As in this study was the largest (10), the upper limit of the first level (slight ecological risk) was adjusted to 10.
The RI value in the grading scale was adjusted by calculating the unit toxicity coefficient (1.13) for the pollutants by dividing Hakanson's first upper limit value (150) by the sum of the toxicity factors (133) for the eight pollutants, multiplying the sum of the toxicity factors (12) for the specific metals (As, Cr) evaluated in this study, and then taking ten integers to get the first level upper limit value (20) for RI.The values for each of the other levels were double the previous level's threshold value.

Risk assessment code
The RAC ecological risk assessment method determines the risk level based on the proportion of the total bioavailable amount (Sundaray et al. 2011), calculated as follows: where A i is the concentration of metal i in the acidsoluble fraction, and T i is the total concentration of metal i in the four fractions.The RAC index was divided into five levels: <1% (no risk), 1-10% (low risk), 11-30% (medium risk), 31-50% (high risk), and > 50% (very high risk).

Statistical analysis
The Shapiro-Wilk test was used to check for normal distribution.One-way ANOVA (analysis of variance) was used to examine differences between treatments, preceded by a test for variance homogeneity.If the variance was homogeneous, the least significant difference (LSD) method was used for comparison; otherwise, Tamhane's T2 method was used.Descriptive data analysis was performed using SPSS 26 (IBM Corporation, NY, USA).Spearman's correlation analysis was conducted to evaluate the relationships between the total heavy metal contents and key chemical factors.Redundancy analysis (RDA) was performed to investigate the relationships between chemical fractions of heavy metals and environmental factors.Figures were constructed using Origin 2021 (OriginLab, Northampton, MA, USA) and Canoco5.0 (Microcomputer Power, Ithaca, NY, USA).Vol:.( 1234567890)

Results
Accumulation and distribution of heavy metals in the biocrust and underlying layers The total Cr contents in the tested samples ranged from 21.54 to 36.49mg/kg (Table 2), below the average background concentrations in Shannxi (62 mg/ kg).The moss biocrust had the highest Cr content (36.49mg/kg), significantly higher than the lowest value in algal biocrust (32.67 mg/kg).In contrast, Cr enrichment in the underlying layer ranked algal crust > mixed crust > moss crust, with lower values than the biocrust layer (P < 0.05).
The As concentrations ranged from 76.06 to 97.54 mg/kg (average 79.37 mg/kg), up to 7.15 times the background value.The As accumulation in the biocrust and underlying layers followed a similar trend to Cr but with no significant differences between layers (Table 2).Moreover, unlike Cr, the underlying layer of the algal crusts and mixed crusts had 9.59 and 1.08 mg/kg higher average As contents, respectively, than the biocrust layer.

Heavy metal fractions and bioavailability in the underlying layer
The residual fraction of Cr significantly decreased in the underlying biocrusts compared to bare soil, with Ms (underlying layer of moss crust), Ts (underlying layer of mixed crust), and Cs (underlying layer of algal crust) decreasing by 8.04%, 5.24% and 4.04%, respectively (Fig. 3a).However, all other fractions increased.The greatest proportion of non-residual Cr increased in Ms, with acid-soluble, reducible, and oxidizable fractions increasing by 1.05%, 6.68%, and 0.31%, respectively.These findings indicate that biocrust growth facilitates the conversion of heavy metal speciation from an inert form to an active form in the underlying layer, enhancing their mobility.
The residual fraction of As also significantly decreased in the underlying biocrusts compared to bare soil (Fig. 3b), with Ms, Ts, and Cs decreasing by 5.81%, 7.07%, and 6.21%, respectively.However, the largest percentage increases for Ts and Cs occurred in the reducible and oxidizable fractions, respectively.Heavy metal bioavailability can be evaluated with the bioactivity coefficient (Xu et al. 2022;Zhang et al. 2019), usually divided into available state (acid-soluble/total forms), potentially available state ((reducible and oxidizable)/total forms), and inert state (residual/ total forms) based on their chemical fractions.In the underlying layer, available and potentially available states for Cr and As followed the order: moss crust > mixed crust > algal crust > bare soil, with the inert state the opposite (Fig. 3a, b).The available state for Cr and potentially available state for As were significantly higher than bare soil, while the reverse was true for the inert state (P < 0.05) (Appendix Information; Table S1).
Influencing factors of total amount and speciation of heavy metals in the underlying layer

Total content
With the developmental succession of biocrusts, soil pH and Eh gradually decreased, while CEC and SOM gradually increased in the underlying layer (Table 3).In particular, the underlying moss crust had significantly lower soil pH and Eh but significantly higher CEC and SOM than the bare soil (ANOVA, P < 0.05).
According to Spearman's correlation analysis (Table 4), total Cr in the underlying layer positively correlated with pH (P = 0.007).In contrast, total As in the underlying layer positively correlated with As in the biocrust layer(P = 0.000) and SOM (P = 0.042) but negatively correlated with CEC (P = 0.039).

Chemical fraction
The RDA indicated that soil environmental factors explained 39.57% and 9.54% of the variation in the chemical fractions of Cr in the underlying layer in Axis 1 and Axis 2, respectively (Fig. 4a).F4 was the most strongly correlated with total Cr (P = 0.000), F3 was the most strongly correlated with CEC, and F1 and F2 were the most strongly correlated with SOM (P = 0.000; P = 0.001) (Appendix Information; Table S2).The migration in Cr by each factor was ranked: total Cr (37.52%) > pH (30.5%) > CEC (15.5%) > SOM (13.0%) > Eh (4.1%).Moreover, total Cr (P = 0.002) and pH (P = 0.004) significantly affected Cr migration and transformation (Table 5).

Effect of biocrusts on the ecological risk of heavy metals in the underlying layer
The highest Er value for As in bare soil was 87.87, indicating a very strong ecological risk level (Fig. 5a).
Biocrusts could lessen the potential ecological risk of heavy metals in the underlying layer, with the Er value of As ranked: algal crusts (77.94) > mixed crusts (75.11) > moss crusts (73.62).The ecological risk level of Cr was low in the study area (Er values < 10).The main tailings had a similar comprehensive potential ecological risk as As (Fig. 5b), with the highest RI in bare soil (88.69, very strong), higher than the underlying layer (75.56, strong).
The RAC results based on heavy metal forms revealed no risk of Cr and As in the bare soil, which means the tailings metals are stable and not easily transported.However, the risks of Cr and As in the underlying layer increased with biocrust succession, with RAC-Cr always higher than RAC-As, indicating  that biocrusts facilitate the migration of heavy metals from the inactive to active form, increasing the ecological risk but not exceeding low-risk thresholds (Fig. 6).Although the tailings had much higher total As than Cr, Cr had a higher bioavailability ratio than As.

Effect of biocrusts on heavy metal enrichment
As a protective 'skin' on the soil surface, biocrusts can improve soil texture by adsorbing and capturing wind-and water-eroded materials and atmospheric dustfall.However, they can also enrich heavy metals, adversely affecting soil physicochemical properties such as pH and organic matter in the 2-5 cm underlying biocrust (Gao et al. 2018;Guo et al. 2022).Our study confirms that highly developed biocrusts enrich heavy metals (Fan et al. 2021;Hu et al. 2022;Xu et al. 2013).The varying adsorption mechanisms of different biocrust types for heavy metals contribute to their different enrichment capabilities, with algal crusts mainly adsorbing heavy metals by secreting extracellular polymers (Mota et al. 2016), while moss crusts have a high CEC and unique hairy branching structure that can absorb heavy metal ions directly from the leaf surface through ion exchange and particle capture (Fernandez et al. 2002;Gallego-Cartagena et al. 2021).Moreover, biocrust development improves soil particles, enriches nutrient contents, and enhances microbial functions, facilitating the attachment of heavy metals (Carlson and Bazzaz 1977).Xu et al. (2013) reported that biocrust development reduced heavy metal contamination in the underlying layer, with the reducing ability ranked moss crust > mixed crust > algal crust.Our results revealed that the underlying layer had 25-40% lower Cr contents than the biocrust layer because the Cr 3+ in alkaline soil is rapidly adsorbed and fixed by soil colloids, making it less mobile (Dhal et al. 2013;Guo et al. 2021;Hu et al. 2016).Unlike Cr, most minerals have a weak capacity to adsorb As in alkaline environments (Chen et al. 2004;Schmitt et al. 2002).Yao et al. (2016) reported that pH and Eh influenced the damage degree of As, with increasing pH decreasing As sorption by soil particles.In this study, the total As of algal crusts and mixed crusts in the underlying layer was 9.6 mg/kg and 1.1 mg/kg higher than the biocrust layer, respectively, possibly due to the alkaline soil in the tailings pond (pH = 8.9) preventing As from being quickly immobilized in the biocrust layer, and the hypothesis that abundant summer precipitation in the Qinling area results in secondary aggregation in subsurface soil, with As leached downward with rainwater (Zhou et al. 2010).

Effect of biocrusts on the migration and transformation of heavy metals in the underlying layer
The biocrust surface contains numerous hydroxyl and carboxylic acid groups (Gardea-Torresdey et al. 1990) that can complexes with heavy metal ions in the soil, increasing their solubility in soil solution and enhancing heavy metal migration (Christensen et al. 1996).Our results indicated that biocrusts affect heavy metal forms in the underlying layer, compared with bare soil, with the proportion of F4 decreasing by 4.01-8.04%and the proportion of F2, F3, and F1 increasing, more so in F2 (3.54-6.69%).This shift in heavy metal distribution could be due to (1) biocrust succession improving soil texture in degraded ecosystems, changing the proportion of metals bound to Fe/Mn oxides, and distributing heavy metals (Bartoli et al. 2012;Chamizo et al. 2012;Yıldırım and Tokalıoğlu 2016); (2) Fe/Mn oxides in the soil environment immobilizing heavy metals through adsorption and co-precipitation, which could react with Mn or Fe to form relatively stable compounds (Burachevskaya et al. 2021, Krupadam et al. 2007, Zhang et al. 2017).The speciation distribution of heavy metals reflects their migration patterns and circular processes of heavy metals in soil and their bioavailability status (Sungur et al. 2015), with the degree of bioavailability of metal forms ranked F1 > F2 > F3 > F4 (Adebiyi and Ayeni 2022; Fu et al. 2019;Rauret et al. 1999).According to Xian (1989), heavy metals in the acid-soluble fraction have the highest solubility, with the reducible state and oxidizable form having high bioactive stability that does not directly affect their uptake by plants.In this study, the availability and potential availability of heavy metals significantly increased in the underlying layer, with moss crusts > mixed crusts > algal crusts (Fig. 3), reflecting variation in heavy metal mobility and bioavailability by biocrust type and heavy metal properties.Biocrusts secrete acidic substances, lowering the pH of alkaline soils to promote the uptake of acid-soluble metals.We speculate that the available As and Cr increased most in the underlying layer of mixed crusts and moss crusts, respectively, due to differences in As and Cr solubility (Burachevskaya et al. 2021;Zakir et al. 2008).

Influencing factors of heavy metal migration and transformation
In this study, total Cr content positively correlated with its residual fraction (F4) in the underlying layer (R = 0.945, P = 0.000), which could be due to the inherently low Cr content in the four components of mine tailings (Appendix Information, Table S3).In addition, the residual fraction mainly occurs in secondary minerals and silicate lattice (Nemati et al. 2009), reducing soil compactness and increasing the adsorption of other forms of Cr by soil colloids.However, total As positively correlated with its reducible fractions (R = 0.659, P = 0.003), indicating that soil As adsorption depends on the release of reducible metals adsorbed on Fe/Mn oxides.In alkaline soils, dissociating and releasing Fe/Mn oxide colloids could promote the accumulation and precipitation of available As in subsurface soils (Cheng et al. 2022).
Soil pH plays a crucial role in determining the total amount of heavy metals in soil and influencing the distribution pattern of geochemical components of heavy metals, thus affecting their bioavailability (Bai et al. 2012;Krupadam et al. 2007).The RDA revealed that pH restricted heavy metal bioavailability (Cr, P = 0.002; As, P = 0.034), with a significant positive correlation between pH and residual fraction, indicating that increasing pH favored the enrichment of less mobile forms (Egbenda et al. 2015;Park et al. 2013).The tailings bare soil had a high pH ( pH = 9.02), but biocrust components, such as moss, which secrete acidic substances, can lower the pH of the moss substrate (Zhang et al. 2022).As a result, biocrusts may regulate the pH of alkaline soil.Furthermore, as biocrusts develop and succeed, pH gradually decreased (Table 3) with the absorption of organic matter and exchangeable cations in soil solution onto soil colloids and clay mineral surfaces (Burachevskaya et al. 2021;Orlekowsky et al. 2013;Tyopine et al. 2018), facilitating the conversion of heavy metals from inactive to active forms.In this study, pH and Eh significantly decreased with biocrust development, while CEC and SOM significantly increased in the underlying layer (Table 2).The correlation analysis revealed that pH and Eh negatively correlated with F1 and F2 but positively correlated with F4, while SOM and CEC positively correlated with F2 and F3 but negatively correlated with F4 (Fig. 4a), indicating that biocrusts increased the availability of metal Cr and As by adjusting pH and Eh and enriching organic matter and cationic sorption sites (Li et al. 2009), with moss crust > mixed crust > algal crust (Fig. 3a), consistent with Xu et al. (2013) in the Kubuqi Desert.
Heavy metal properties also influence the effect of organic matter on heavy metal speciation.The significant positive correlation between As in both layers and organic matter (Table 4; P = 0.028, 0.046) confirmed this metal affinity against organic compounds (Sungur et al. 2015;Siahcheshm et al. 2022;Wang et al. 2011).The complexation reaction between heavy metals and organic matter determines, to a certain extent, the morphology, bioavailability, and transfer efficiency of metals (Hu et al. 2018;Peng et al. 2009).Li and Yang (2004) showed that dissolved organic matter reduced the adsorption of metal Cr in soil, enhancing Cr bioactivity and mobility.Yamaguchi et al. (2011) observed that As mainly existed as anions in soil; as pH rises, the negative charge increases on the surface of soil colloids and fights with As -for positive charge, desorbing As from soil colloids and further increasing the soluble As content.We also found that organic matter positively correlated with metal acid-soluble fractions (Cr, R = 0.789, P = 0.000; As, R = 0.586, P = 0.011), Vol.: (0123456789) possibly due to the study area being located in typical gold mine tailings in the Qinling Mountains, where biocrusts are enriched with large amounts of organicrich dustfall.The strong complexation between organic matter and As significantly altered microbial activities associated with soil As metabolism (Jeong et al. 2019), indirectly affecting As availability.
Effect of biocrusts on the ecological risk of heavy metals in the underlying layer The RI results suggest that soil pollution in the gold mine tailings was a strong ecological risk, mainly due to the high level of As contamination.However, the underlying layer had significantly lower Er and RI values than the bare soil, indicating that the biocrusts, as the protective 'skin' of the soil ecosystem, could resist the impact of heavy metal pollutants on the soil environment, consistent with other studies (Orlekowsky et al. 2013;Xu et al. 2012Xu et al. , 2013)).The mobility and stability of different fractions of heavy metals play a crucial role in determining their potential ecological risk.F1 has stronger mobility, while F2 and F3 are unstable fractions that can be released under reducing and weak oxidizing conditions.These fractions are considered potentially toxic and present a potential risk for living organisms (Anju and Banerjee 2010;Lin et al. 2014;Yang et al. 2019a).The RAC evaluation showed that Cr and As were risk-free in bare soil.However, with biocrust succession, the RAC values of Cr and As gradually increased in the underlying layer, indicating that biocrust development activated the metal fraction F1, directly affecting the degree of hazard to organisms and, thus, increasing the ecological risk of heavy metal pollutants.This is essentially due to changes in physicochemical parameters such as particle size and pH (Belnap 2003;Sun et al. 2004).Yang et al. (2019b) reported the potential risk of heavy metal As in soils by Er and RAC method in the Xiaoqing River sewage irrigation area, with a slight-medium risk Er value and low-risk RAC.Xiao et al. (2022) reported that the Er value for As was a serious ecological risk, while the RAC was low-risk in the antimony tailings of Qinglong, Guizhou.Unlike the Er method, which focuses on the total amount of heavy metals, the RAC method focuses on the pollution degree of the directly usable form of heavy metals.Assessing the ecological risk of heavy metals based on the total amount or form may lead to cognitive biases.The Er method (total concentrations) and the RAC method (fractions) should complement each other to improve the evaluation results.
More developed biocrusts have a better capacity for heavy metal enrichment, and in terrestrial ecosystems, moss crusts are a good material for remediating heavy metal pollution.However, we should be aware of their adverse effects.Specifically, moss crusts have a higher available form of heavy metals than algal crusts, which makes them a higher ecological risk.In this study, the 'activation effect' of biocrusts on heavy metals appeared very small compared to the 'enrichment effect'.However, it is not clear what the activation effect of biocrusts on heavy metals will be in the long term.Therefore, controlling or removing moss crust development is important for the ecological restoration of gold mine tailings under some conditions (Chen et al. 2009).Besides, successful colonization of heavy metal-tolerant herbaceous plants, such as Pteris vittata and Bombax ceiba L., can concentrate the metals in their tissues, and the synergy of biocrusts with these plants may be more favorable for remediating heavy metal contamination.However, removing and resolving potential heavy metal risks from biocrusts require longer-term observations and should be based on comprehensive vegetation related studies.

Conclusions
This study highlights the significant role of biocrusts in the enrichment of heavy metals and surface accumulation of heavy metals in gold tailings ponds.The heavy metals present in mine tailings were predominantly in the residual fraction.Biocrusts increased the metal availability in the underlying layer by adjusting pH and redox potential and enriching organic matter and cationic sorption sites.While the gold mine tailings had a much higher total As concentration than Cr accumulation, Cr had a higher bioavailable proportion than As.Biocrust succession promoted the migration and transformation of heavy metals but also increased its ecological risk.However, it remains uncertain whether continuous growth and enrichment of heavy metals in biocrusts will cause the RAC index to exceed the low-risk threshold.
Vol:. ( 1234567890) Long-term experimental research on the migration of heavy metals in biocrusts and their interaction mechanisms with environmental factors should be undertaken to reveal the ecological functions and response mechanisms for biocrust remediation of contaminated soils.

Fig. 1
Fig. 1 Location of study area and distribution of sample plots

Fig. 2 a
Fig. 2 a Landscape of the gold mine tailings, b algae crusts, c moss crusts, and d mixed crusts

Fig. 6
Fig. 6 RAC results for the heavy metals in the underlying layer of biocrusts.Ms, underlying layer of moss crust; Ts, underlying layer of mixed crust; Cs, underlying layer of algal crust; L, bare soil

Table 1
Potential ecological risk index and classification of heavy metal pollution

Table 2
Heavy metal content in the biocrust and underlying layers (mean ± S.D., n = 5) Different uppercase and lowercase letters indicate significant differences among different soil layers in the same crust type and different crust types in the same layer, respectively, at P < 0.05

Table 4
Spearman's correlation analysis among heavy metal contents and physicochemical properties in the underlying layer (mean ± S.D., n = 15)Reported is Spearman's rho, * and ** significant at P < 0.05 and P < 0.01 level, respectively

Table 5
Significance of environmental factors in redundancy analysis