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Assembly and Source of the Lithobiontic Microbial Community in Limestone

Key Laboratory of Plant Resources Conservation and Germplasm Innovation in Mountainous Region (Ministry of Education), College of Life Sciences & Institute of Agro-Bioengineering, Guizhou University, Guiyang 550025, China
School of Ecological Engineering, Guizhou University of Engineering Science, Bijie 551700, China
Institute of Mountain Resources of Guizhou Academy of Sciences, Guiyang 550001, China
Author to whom correspondence should be addressed.
Fermentation 2023, 9(7), 672;
Original submission received: 30 June 2023 / Revised: 15 July 2023 / Accepted: 17 July 2023 / Published: 18 July 2023
(This article belongs to the Special Issue Application of Extremophiles in Biological Degradation and Conversion)


Due to its unique rock properties (e.g., porous nature, rough texture, and high calcium and magnesium content), limestone exhibits a high degree of bioreceptivity. However, the mechanisms underlying the establishment of limestone lithobiontic microbial communities (LLMCs) and the extent to which their composition is influenced by the surrounding environment remain enigmatic. Herein, after collecting limestone sand samples, we applied various treatments: rain shelter (RS), organic acid (Oa), nutrients (Nut), inorganic acid (Ia), inorganic acid combined with nutrients (Ia+Nut15), and a blank control (CK). Subsequently, we sampled the treatments after a duration of 60 days. In addition, we collected rotted wood, concrete fences, and soil from the surrounding environment as microbial sources, while using treated limestone samples as microbial sinks. This study yields the following findings: (1) Limestone exhibits high bioreceptivity, allowing rapid microbial colonization within 60 days. Furthermore, compared to the surrounding environment, limestone can accommodate a greater diversity of microbial species. (2) The fungal and bacterial community compositions were explained by surrounding sources to the extent of 35.38% and 40.88%, respectively. The order of sources, in terms of contribution, is as follows: unknown sources > soil > rotted wood > concrete fences. (3) Higher concentrations of Ia and Ia+Nut15 treatments facilitate the colonization of fungi from the surrounding environment onto limestone while inhibiting bacterial colonization. (4) The process of establishing LLMCs is primarily driven by stochastic processes. However, Ia and Ia+Nut15 can mediate transitions in the establishment processes of bacterial communities, while Ia is solely responsible for mediating transitions in the establishment process of fungal communities. Our study offers a fresh perspective on the establishment and origins of microbial communities in limestone habitats. We believe that limestone serves as an excellent substrate for microbial colonization and holds immense potential in ecological restoration efforts within degraded karst areas.

1. Introduction

Our understanding of the relative importance of deterministic and stochastic processes in governing microbial community structure, succession, and other factors remains limited [1,2,3]. Lithobiontic microorganisms (LMs) are a group of microorganisms capable of inhabiting and colonizing both the interior and surface of rocks [4]. They exert their influence on rocks primarily through the secretion of organic and inorganic acids, resulting in biodeterioration, as observed by Zhang et al. [5]. Heterotrophic microorganisms dissolve mineral substances during heterotrophic leaching processes, which encompass acidolysis and complexolysis [6]. Additionally, certain types of microorganisms, such as bacteria, may induce redox reactions. Further, nutrient availability plays a crucial role in shaping the colonization of microorganisms in rock environments, as highlighted by Chen et al. [7]. In our recent study, we discovered that the predominant fungal groups associated with carbonate lithotrophs include Ascomycota, Basidiomycota, and Chytridiomycota, while the dominant bacterial groups mainly consist of Proteobacteria, Bacteroidota, and Actinobacteriota [7,8]. Moreover, the dominant archaeal taxa observed were Euryarchaeota and Thaumarchaeota [8]. LMs have a significant impact on rock bio-weathering, environmental monitoring, biocontainment, and elemental cycling. Karst aquifers of carbonate sedimentary origin underlie a land surface covering approximately 15% of the planet and supply approximately 25% of the world’s population with potable water [9,10]. Therefore, comprehending the formation and origins of limestone LM communities is crucial for understanding the functions and roles of microorganisms within karst ecosystems. Improving our understanding of the associated processes will help to reveal the role of microorganisms in the Earth’s historical evolution. Further, this knowledge will also set a scientific foundation for the conservation, utilization, and environmental restoration of karst environments.
The formation and origin of LLMCs involve a complex interplay of various factors. Firstly, the physical and chemical properties of limestone significantly influence the colonization of microorganisms already inhabiting the rock. Limestone predominantly consists of calcite and aragonite, both of which are primarily composed of calcium carbonate [11]. Moreover, carbonate minerals present in limestone can undergo reactions with carbonic acid [12]. As a result, the weathering of limestone is primarily driven by chemical dissolution and the precipitation of calcium ions [13,14], leading to the formation of grikes from the dissolved portions and clints from the remaining portions [15]. The pores and cracks formed during these processes provide ideal ecological niches for the colonization of LMs [16,17]. Furthermore, the porosity of limestone also provides a unique habitat for the establishment of LMs [18]. Our recent research has revealed that limestone contains abundant elements such as calcium, magnesium, and iron [7,8], which are essential for microbial growth and development and can selectively influence the diversity and functionality of LMs [19,20,21]. Secondly, environmental factors are also crucial for the construction of LLMCs. Climate conditions (e.g., light and humidity) and hydrological characteristics (e.g., rainfall and water pH) can influence the composition and distribution of microorganisms [18]. The limited availability of water and nutrients on rock surfaces means that pioneer microorganisms inhabiting rocks can settle with the limited moisture, inorganic substances, and organic compounds present in the air [22]. As a result, microbial diversity can vary under different environmental conditions. For example, the limestone-dwelling fungi in Feilaifeng, Zhejiang, China, are different from those previously reported in limestone environments in Guizhou, China [7,23]. Lastly, external input sources may also serve as important pathways for the origin of lithophilic microbial communities. Microorganisms in the surrounding environment, such as those present in the soil [21], rainfall [12], or airborne dust [24], can be transported to rock surfaces by wind, water flow, or other means, thereby influencing the composition and structure of microbial communities.
Limestone, a common rock type in the karst areas of southwestern China, serves as a prevalent building material [8]. The exposure of limestone and other carbonate rocks has caused significant desertification, posing a major ecological degradation issue in Guizhou, the central region of the karst area in China, which spans over 500,000 km2 [25]. The delicate ecology of the karst region, coupled with a dense population, exacerbates the vicious cycle of ecological problems [26]. Therefore, urgent ecological restoration measures are required to address the degraded karst area. LMs play a crucial role in the initial stages of limestone bio-weathering. Examining the origin and community formation of LMs in limestone can provide a theoretical foundation for the ecological restoration of degraded karst areas.
Previous studies have revealed that rock-associated microbial communities originate from the surrounding environment, including the air and nearby soil. However, these communities are significantly influenced by rock properties, such as pH, permeability, and metal element content [20,24]. Nevertheless, the proportion of community composition derived from the surrounding environment and the extent to which rock properties affect the formation of rock-associated microbial communities remain unclear. Therefore, our study sought to investigate the source–sink relationship between microbial communities in the surrounding environment (e.g., decaying wood, concrete fences, and soil) and those associated with limestone habitats exposed to different conditions.
Additionally, we worked to examine the processes involved in the formation of microbial communities under different treatments (i.e., rain shelter (RS), organic acid (Oa), nutrients (Nut), inorganic acid (Ia), inorganic acid combined with nutrients (Ia+Nut15), and a blank control (CK)) within limestone habitats. Our primary research questions were four-fold: (i) how does the microbial carrying capacity of limestone compare to that of the surrounding environment? (ii) Does the construction of microbial communities in limestone habitats vary under different treatments? (iii) To what extent can the surrounding environment explain the proportion of microbial sources in limestone habitats? (iv) Do different treatments promote or inhibit microbial dispersal?
Through this study, we sought to explore the construction process and source mechanisms of microbial communities in limestone habitats, deepen our understanding of the interactions between microorganisms and limestone, and provide a foundation and reference for future research in geobiology and geomicrobiology.

2. Materials and Methods

2.1. Experimental Design and Sample Collection

Our samples were exclusively sourced from limestone particles with a particle size range of 1.5–3 mm. These samples underwent various treatments, namely RS, Oa, Nut, Ia, Ia+Nut15, and CK. The sampling process occurred over a span of 60 days, specifically from 15 January 2022 to 15 March 2022. The experimental design and sample treatments were carried out as previously described [7].
At the experimental site (Figure S1), apart from air and rainfall, samples were placed in an open environment where the potential microbial sources mainly included the surrounding environment. Firstly, decaying wood rich in cellulose and humic substances provided an ideal habitat for microbial colonization. The placement of decaying wood at elevated positions facilitated the dispersion of microorganisms residing on the wood through wind transport. Secondly, a concrete fence encircled the area approximately 1 m above the ground, hosting abundant lichens with fungal spores that could potentially be disperse by wind. Lastly, scattered soil particles in the vicinity of the site could also become a source of microbial population through wind-mediated dispersal to the experimental samples. Therefore, we collected multiple samples of decaying wood from the surrounding area of the test site and combined them to create a composite decaying wood sample. Similarly, a composite sample of the surrounding soil and a mixed sample of concrete fence (Figure S1) were prepared using the same methodology.

2.2. Sample Processing and Sequencing

Each sample, weighing approximately 50 g, was mixed with approximately 125 mL of sterile water. Subsequently, the samples were cleaned using an ultrasonic cleaning machine followed by filtration to obtain membrane samples for high-throughput sequencing. Samples were processed and sequenced as previously described [7]. The high-quality raw sequencing data, obtained after quality control and screening, were subsequently uploaded to the NCBI SRA database under the accession number PRJNA944278.

2.3. Quantification of the Community Assembly Process

We employed Stegen’s QPEN (quantifying assembly processes based on entire-community null model analysis) framework [2,27] to quantify the process of community assembly. Initially, we measured the phylogenetic turnover between each pair of communities (β-MNTDobs) and compared that to the null distribution (β-MNTDnull). The magnitude of deviation between β-MNTDobs and β-MNTDnull is represented by the β-nearest taxon index (β-NTI) value. Significant β-NTI values (|β-NTI| > 2) indicate the presence of environmental selection. β-NTI values less than -2 and greater than 2 indicate homogeneous selection (HoS) and heterogeneous selection (HeS), respectively.
For non-significant β-NTI values (|β-NTI| < 2), we assessed the deviation between BCobs (Bray–Curtis dissimilarity based on community composition) and BCnull using the Raup–Crick value (RCbray). Typically, RCbray values less than −0.95 indicate homogenizing dispersal (HD), RCbray values greater than 0.95 represent dispersal limitation (DL), and |RCbray| ≤ 0.95 indicates undominated/drift (DR) processes.

2.4. Microbial Source Tracking

To estimate the potential sources of environmental conditions for bacteria and fungi occurring in limestone under different treatments, we designated 66 limestone samples (3 CK, 3 RS, 15 Oa, 15 Ia, 15 Nut, and 15 Ia+Nut15) as sinks. As sources, we considered three surrounding environmental samples: rotted wood, concrete fence, and the surrounding soil.
Furthermore, to assess the influence of acid corrosion and nutrient availability on the composition of bacterial and fungal communities associated with limestone, we calculated the contribution rate of the known sources (i.e., the three surrounding environmental samples). This rate, denoted as Cr, was determined using the following formula:
C r = T r K r T r × 100
Here, Cr represents the contribution rate, Tr represents the known source proportions of different treatment groups, and Kr represents the known source proportion of the CK (control) group. A positive Cr value suggests that the treatment promotes microbial community composition, while a negative value indicates an inhibitory effect.

2.5. Statistical Analyses

All analyses were conducted using the R Environment v4.2.2 (R Core Team, Vienna, Austria), and plots were generated using the ggplot2 package. A permutation t-test does not impose strict requirements on the normality and homoscedasticity of the data, making it suitable for most ecological datasets. To test the significance of the same source between fungi and bacteria, we employed a two-sample permutation Student’s t-test (two-sided) [28] using the perm.t.test() function from the RVAideMemoire package. For the Kruskal–Wallis test and multiple comparison of treatments [29], we utilized the kruskal() function from the agricolae package, and the resulting p-values were adjusted using the false discovery rate method.
Principal coordinate analysis (PCoA) was performed using the pcoa() function from the ape package [30], while permutational multivariate analysis of variance (PerMANOVA) was conducted using the adonis() function from the vegan package [31]. Fast expectation-maximization microbial source tracking analysis was carried out using the FEAST() function from the FEAST package [32]. The process of community assembly was quantified using the qpen() function from the iCAMP package [2,27,33,34]. Linear models were fitted using the lm() function from the stats package [35].

3. Results

3.1. Microbial Community Composition and Diversity in Different Habitats

After filtering out OTUs that aligned to chloroplast and mitochondrial sequences with a 97% similarity threshold and appeared in at least five out of three samples, we obtained a total of 499 bacterial OTUs and 2122 fungal OTUs from the limestone rock surface. Among the 69 samples (3 ENV, 3 RS, 3 CK, 15 Oa, 15 Nut, 15 Ia, and 15 Ia+Nut15), the dominant bacterial phyla were Proteobacteria, Bacteroidota, and Actinobacteriota (Figure S1A), while the dominant fungal phyla were Ascomycota and Basidiomycota (Figure S1B).
Regarding the bacterial community, the abundance of limestone habitats treated with acid (Oa, Ia, and Ia+Nut15) was significantly higher than that of the surrounding environments (Figure 1A). In the fungal community, the abundance of the Nut, Ia, and Ia+Nut15 groups was significantly higher than that of the surrounding environment (Figure 1B). These findings suggest that the composition of bacterial and fungal communities under different treatment conditions is similar to the surrounding environment (Figure S2). However, compared to other surrounding habitats, limestone rock surfaces under different treatment conditions can support a higher abundance of microbial communities.
Furthermore, the PCoA revealed that the bacterial community (Figure 1C, R2 = 0.60) was more influenced by the habitat than the fungal community (Figure 1D, R2 = 0.36), indicating that bacteria are more sensitive to environmental factors than fungi.

3.2. Assembly Process of LLMCs under Different Treatment Conditions

Overall, the construction process of LLMCs is primarily driven by neutral processes (Figure 2A,C). In the construction process of the fungal community, deterministic processes account for 49.7% (with heterogeneous selection accounting for 47.23% and homogeneous selection accounting for 2.47%), while neutral processes account for 50.3% (with dispersal limitation accounting for 17.39%, homogenizing dispersal accounting for 5.24%, and undominated accounting for 27.67%). For the bacterial community construction process, deterministic processes account for 35.46% (with heterogeneous selection accounting for 35.46%), while neutral processes account for 64.54% (with dispersal limitation accounting for 30.4% and undominated accounting for 34.14%).
Different treatments have varying effects on the construction of microbial communities, particularly treatments involving Ia and Ia+Nut15, which significantly impact the selective processes in microbial community construction. In bacterial communities, Nut has a significant influence on the distribution of β-NTI compared to the CK (Figure 2D, Table S1). In fungal communities, Nut, Ia, and Ia+Nut15 have a significant influence on the distribution of β-NTI compared to the CK (Figure 2D, Table S2). Additionally, in bacterial communities, the construction process of communities in the Ia and Ia+Nut15 treatment groups is primarily driven by deterministic processes (heterogeneous selection) (β-NTI > 2), while in fungal communities, the construction process of communities in the Ia+Nut15 treatment group is primarily driven by deterministic processes (heterogeneous selection) (Figure 2B,D).

3.3. Factors Influencing the Assembly Process of LLMCs under Different Treatment Conditions

We performed a regression analysis on the difference between the β-NTI and environmental factors among pairwise samples. Our findings revealed that a greater difference in organic carbon (OC) between two samples leads to a larger β-NTI value. Additionally, pH and rock density exhibited a negative correlation with β-NTI, indicating that as pH and rock density increase, β-NTI decreases. However, no significant relationship was observed between the difference in other environmental factors and β-NTI (Figure 3). Notably, we made an interesting observation that when the difference in OC exceeds ~0.3, the absolute value of β-NTI surpasses 2, indicating a transition from a neutral process to a deterministic process (heterogeneous selection) in community assembly.
Regarding bacterial communities, a larger difference in total nitrogen (TN) between two samples results in a larger β-NTI value. Once the TN difference exceeds 0.025, the assembly process of bacterial communities shifts from being predominantly neutral to being predominantly deterministic (heterogeneous selection) (Figure S3).

3.4. Source Tracking of Fungal and Bacterial Communities

The tracking analysis revealed that the proportions of limestone-associated bacterial and fungal communities derived from rotted wood, concrete fences, and surrounding soil differ (Figure 4). In the bacterial community, the average composition consists of 40.88% from the three environmental samples, with 0.2% from rotted wood, 4.18% from concrete fences, 36.5% from surrounding soil, and the remaining 59.1% from unknown sources. For the fungal community, the average composition consists of 35.38% from the three environmental samples, with 1.08% from rotted wood, 6.7% from concrete fences, 27.6% from surrounding soil, and 64.6% from unknown sources.
Furthermore, there is no significant difference in the proportion of bacterial and fungal community composition derived from rotted wood. However, in fungi, the proportion derived from concrete fences is significantly higher compared to bacteria, while the proportion derived from surrounding soil is significantly lower compared to bacteria. Additionally, the proportion of unknown sources in the fungal community composition is significantly larger than that in the bacterial community (Figure 4).

3.5. Contribution of Different Treatments to the Sources of Bacterial and Fungal Community Composition

Different treatments exert varying effects on the composition of bacterial and fungal communities derived from known sources. Compared to bacterial communities, fungal communities show a smaller inhibitory effect under different treatments (Figure 5). In the fungal community, low concentrations of Ia and Ia+Nut15 treatments hindered the colonization of known sources on limestone by fungal communities. However, higher concentrations of these treatments, along with Nut treatment, promoted the colonization of known fungal sources (Figure 5A–C). In the bacterial community, both the Ia treatment and Ia+Nut15 treatment, as well as the Nut treatment alone, inhibited the colonization of known bacterial sources (Figure 5E–G). Moreover, moderate concentration gradients of Oa treatments exhibited inhibitory effects on both bacterial and fungal communities, whereas low and high concentrations of organic acids had stimulatory effects (Figure 5D,H).

4. Discussion

4.1. Diversity of Microorganisms Inhabiting Limestone

The main components of limestone primarily consist of carbonate minerals, along with a small proportion of other minerals [11]. After microbial colonization, the metabolic byproducts of microorganisms, such as H+ and other acidic substances like organic acids, dissolve and transform carbonate minerals into other compounds [13], resulting in surface changes and increased roughness, which is characteristic of limestone. This enhanced roughness, in turn, promotes biofouling compared to smoother surfaces, owing to the larger surface area and the creation of diverse microenvironments that offer shelter for biofouling organisms [18]. Given the porous nature and inherent roughness of limestone [11,18], it is not surprising that we observed an increase in microbial abundance on limestone surfaces compared to the surrounding environment (Figure 1A,B). Additionally, previous research has indicated that nutrient availability can contribute to increased biodiversity on rocky substrates [36]. On one hand, inorganic compounds generated from acid corrosion reactions, such as calcium, iron, and magnesium-related compounds, can serve as essential elements for microbial growth and reproduction [20]. On the other hand, the Hoagland’s nutrient solution used in the experiment contains various elements required for microbial growth, which can be directly absorbed and utilized by microorganisms [7]. Consequently, nutrient availability enhances the abundance of microorganisms dwelling on limestone surfaces.

4.2. The Surrounding Environment Can Account for a Certain Proportion of the Source of LLMCs

In this study, we found that the surrounding environment accounted for 35.38% and 40.88% of the fungal and bacterial community sources, respectively. Previous studies have indicated that rock-associated microorganisms are not highly similar to the surrounding environment, suggesting that the community composition originates from a small fraction of the surrounding environment but is strongly influenced by rock characteristics (e.g., porosity, permeability, roughness, and chemical composition) [20,24]. However, it is important to note that previous reports were based on stable microbial communities already established on the rock surface. In contrast, in this study, sampling was conducted on the 60th day after treatment as fungal colonization on limestone surfaces occurs after 60 days of growth [37]. Given the relatively short time frame, microorganisms from the surrounding environment may still be dispersing and adapting to the different treated limestone surfaces, resulting in a lower selection effect of rock properties. Therefore, our source tracking analysis revealed that the surrounding environment contributes to a certain proportion of the composition of rock-associated microbial communities.

4.3. Inorganic Acids and Nutrient Treatments Promote Fungal Colonization of Limestone in the Surrounding Environment While Inhibiting Bacterial Colonization

In our previous study [7], we found that fungal community diversity was higher than bacterial community diversity under different treatment conditions. In line with those findings, the present study demonstrated that higher concentrations of inorganic acids, inorganic acids + nutrients, and nutrient addition increased the contribution of fungal community composition from the surrounding environment (Figure 5A–C), while reducing the contribution of bacterial community composition (Figure 5E–G).
Fungi generally exhibit stronger environmental resistance, while bacteria possess superior recovery abilities [7,38,39]. This difference in ecological traits may explain the observed phenomenon at a specific time point, namely, after 60 days of colonization. The increased resistance of fungi allows them to maintain a relatively higher diversity and retain their composition from the surrounding environment, while bacteria may experience more pronounced changes and adaptations during colonization.

4.4. The Community Construction Process of Limestone LMs

The results obtained from the QPEN analysis reveal that the assembly of LLMCs is influenced by both deterministic and neutral processes, with neutral processes playing a more dominant role (Figure 2). This pattern aligns with the conceptual model proposed by Dini-Andreote et al. [40] for microbial community assembly. According to this model, the initial stage of community formation is driven by stochastic processes, and as local environmental conditions change, deterministic selection becomes increasingly important. Eventually, a stable environment leads to a consistent level of deterministic selection.
Moreover, previous studies have reported that early-stage microbial communities, such as those found in drinking water biofilms, exhibit a disordered structure and show strong randomness [41]. Given our relatively short sampling duration of 60 days, it is not surprising that stochastic processes primarily govern the assembly of LLMCs. Furthermore, in nutrient-rich conditions with low competition, stochastic processes are known to dominate the early stages of microbial community assembly [42,43]. In this study, acid etching and nutrient addition both increased nutrient availability in the limestone, leading to a prevalence of stochastic processes in community assembly.
Lastly, Chase [44] suggested that randomness tends to dominate community assembly when a wide range of organisms coexist in the environment. In our study, both the fungal and bacterial communities were dominated by common microbial taxa (Figure S1), which may also contribute to the predominance of stochastic community assembly in limestone lithobiontic microbes.
An interesting finding of this study is the differential influence of treatments on the construction of bacterial and fungal communities in limestone rocks. In the treatments with Ia and I+Nut15, bacterial community assembly is primarily driven by deterministic processes, specifically heterogeneous selection. In the treatment with Ia+Nut15, the assembly of fungal communities also shows a dominance of deterministic processes. Notably, we observed that differences in organic carbon content can shift the assembly of fungal communities from stochastic to deterministic processes, while differences in organic nitrogen content can have a similar effect on bacterial communities. These findings support the idea that the construction of limestone lithobiontic bacterial communities is influenced by the treatments of Ia and Ia+Nut15, leading to environmental heterogeneity and resulting in variations in community structure [2].
Furthermore, due to the faster reproduction rate and higher turnover rate of bacterial communities [8,45,46,47], they are more susceptible to deterministic processes such as environmental filtering (e.g., organic nitrogen) and biotic interactions. On the other hand, the construction of limestone lithobiontic fungal communities is influenced by the treatment of Ia+Nut15, which may be attributed to the increased differences in OC content. These differences contribute to environmental heterogeneity and selective effects on surrounding fungi.

5. Conclusions

This study provides novel insights into the construction and sources of microbial communities in limestone habitats. Firstly, the unique properties of limestone allow for a higher acceptance of biota, enabling a greater abundance of microorganisms. Secondly, the surrounding environment can account for 35.38% of the sources of the fungal community and 40.88% of the sources of the bacterial community. Thirdly, higher concentrations of the Ia and Ia+Nut15 treatments promote the proliferation of fungal communities while inhibiting the proliferation of bacterial communities. Lastly, the construction process of LLMCs is primarily influenced by stochasticity, and the transformation of fungal community construction was mediated by the Ia+Nut15 treatment, while the transformation of bacterial community construction was mediated by the Ia and Ia+Nut15 treatments. Future studies should aim to investigate the mechanisms by which specific rock properties of limestone, such as porosity and chemical composition, influence microbial colonization. Additionally, it is important to determine the proportion of microorganisms derived from the air and rainfall. These investigations will help uncover the corresponding relationships between rock properties and specific microbial communities and address the issue of the origin of rock-dwelling microbial communities in limestone.

Supplementary Materials

The following supporting information can be downloaded at:, Figure S1: Experimental design schematic diagram; Figure S2: Abundance of bacteria and fungi at the phylum level in different habitats (limestone, rotted wood, concrete fence, and surrounding soil); Figure S3: Relative influences of deterministic and stochastic assembly processes on bacterial communities in limestone rocks: exploring the relationship between β-NTI and variations in environmental factors for fungal communities. Table S1: Pairwise comparisons using Wilcoxon rank sum exact test (bacteria); Table S2: Pairwise comparisons using Wilcoxon rank sum exact test (fungi).

Author Contributions

Data curation, J.C. and F.L. (Fangbing Li); investigation, J.C., F.L. (Fangbing Li), X.Z. and L.Z.; methodology, J.C., Y.W. and L.Y. (Lifei Yu); resources, L.Y. (Lifei Yu); software, J.C., F.L. (Fangbing Li), X.Z. and L.Y. (Lingbin Yan); visualization, F.L. (Feng Liu); writing—original draft, J.C. and L.Y. (Lifei Yu); writing—review and editing, D.Y. and L.Y. (Lifei Yu). All authors have read and agreed to the published version of the manuscript.


This research was funded by the Ministry of Science and Technology of the People’s Republic of China, grant number 2016YFC0502604, and the Department of Education of Guizhou Province, grant numbers GNYL[2017]009 and YJSKYJJ[2021]079.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.


We would like to thank the editors and reviewers for their selfless help.

Conflicts of Interest

The authors declare no conflict of interest.


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Figure 1. Comparative analysis of alpha diversity and principal coordinate analysis (PCoA) of bacterial communities (A,C) and fungal communities (B,D) across distinct habitats. Note: distinct lowercase letters denote statistically significant differences between two groups, while the same lowercase letter indicates no statistically significant difference between two groups.
Figure 1. Comparative analysis of alpha diversity and principal coordinate analysis (PCoA) of bacterial communities (A,C) and fungal communities (B,D) across distinct habitats. Note: distinct lowercase letters denote statistically significant differences between two groups, while the same lowercase letter indicates no statistically significant difference between two groups.
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Figure 2. Elucidating the process of bacterial and fungal community assembly under diverse treatment conditions. The relative proportions of fungal and bacterial community assembly processes (A) and the differentiation test of β-NTI between bacterial and fungal taxa (C); the relative proportions of fungal and bacterial community assembly processes under different treatments (B) and the differential test of β-NTI (D) for fungal and bacterial communities.
Figure 2. Elucidating the process of bacterial and fungal community assembly under diverse treatment conditions. The relative proportions of fungal and bacterial community assembly processes (A) and the differentiation test of β-NTI between bacterial and fungal taxa (C); the relative proportions of fungal and bacterial community assembly processes under different treatments (B) and the differential test of β-NTI (D) for fungal and bacterial communities.
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Figure 3. Relative influences of deterministic and stochastic assembly processes on fungal communities in limestone rocks: exploring the relationship between β-NTI and variations in environmental factors for fungal communities. Note: the environmental factors examined include total carbon (TC, %), organic nitrogen (ON, %), organic carbon (OC, %), organic sulfur (OS, %), and the bulk density of rock particles (density, g/cm3). The blue lines represent the fitted lines for the differences in environmental factors and β-NTI differentials and the shaded areas around the fitted regression line represent the 95% confidence intervals.
Figure 3. Relative influences of deterministic and stochastic assembly processes on fungal communities in limestone rocks: exploring the relationship between β-NTI and variations in environmental factors for fungal communities. Note: the environmental factors examined include total carbon (TC, %), organic nitrogen (ON, %), organic carbon (OC, %), organic sulfur (OS, %), and the bulk density of rock particles (density, g/cm3). The blue lines represent the fitted lines for the differences in environmental factors and β-NTI differentials and the shaded areas around the fitted regression line represent the 95% confidence intervals.
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Figure 4. Comparison of different sources of bacterial and fungal community composition.* p < 0.05; ** p < 0.01.
Figure 4. Comparison of different sources of bacterial and fungal community composition.* p < 0.05; ** p < 0.01.
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Figure 5. Quantifying the contribution rates of various treatments to the community composition of fungi (AD) and bacteria (EH). The red bars represent positive contribution rates, while the blue bars represent negative contribution rates.
Figure 5. Quantifying the contribution rates of various treatments to the community composition of fungi (AD) and bacteria (EH). The red bars represent positive contribution rates, while the blue bars represent negative contribution rates.
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Chen, J.; Li, F.; Zhao, X.; Wang, Y.; Zhang, L.; Liu, F.; Yang, D.; Yan, L.; Yu, L. Assembly and Source of the Lithobiontic Microbial Community in Limestone. Fermentation 2023, 9, 672.

AMA Style

Chen J, Li F, Zhao X, Wang Y, Zhang L, Liu F, Yang D, Yan L, Yu L. Assembly and Source of the Lithobiontic Microbial Community in Limestone. Fermentation. 2023; 9(7):672.

Chicago/Turabian Style

Chen, Jin, Fangbing Li, Xiangwei Zhao, Yang Wang, Limin Zhang, Feng Liu, Dan Yang, Lingbin Yan, and Lifei Yu. 2023. "Assembly and Source of the Lithobiontic Microbial Community in Limestone" Fermentation 9, no. 7: 672.

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