Experimental warming accelerates positive soil priming in a temperate grassland ecosystem.

Unravelling biosphere feedback mechanisms is crucial for predicting the impacts of global warming. Soil priming, an effect of fresh plant-derived carbon (C) on native soil organic carbon (SOC) decomposition, is a key feedback mechanism that could release large amounts of soil C into the atmosphere. However, the impacts of climate warming on soil priming remain elusive. Here, we show that experimental warming accelerates soil priming by 12.7% in a temperate grassland. Warming alters bacterial communities, with 38% of unique active phylotypes detected under warming. The functional genes essential for soil C decomposition are also stimulated, which could be linked to priming effects. We incorporate lab-derived information into an ecosystem model showing that model parameter uncertainty can be reduced by 32-37%. Model simulations from 2010 to 2016 indicate an increase in soil C decomposition under warming, with a 9.1% rise in priming-induced CO2 emissions. If our findings can be generalized to other ecosystems over an extended period of time, soil priming could play an important role in terrestrial C cycle feedbacks and climate change.

Reduction of microbial diversity in grassland soil is driven by long-term climate warming.

Anthropogenic climate change threatens ecosystem functioning. Soil biodiversity is essential for maintaining the health of terrestrial systems, but how climate change affects the richness and abundance of soil microbial communities remains unresolved. We examined the effects of warming, altered precipitation and annual biomass removal on grassland soil bacterial, fungal and protistan communities over 7 years to determine how these representative climate changes impact microbial biodiversity and ecosystem functioning. We show that experimental warming and the concomitant reductions in soil moisture play a predominant role in shaping microbial biodiversity by decreasing the richness of bacteria (9.6%), fungi (14.5%) and protists (7.5%). Our results also show positive associations between microbial biodiversity and ecosystem functional processes, such as gross primary productivity and microbial biomass. We conclude that the detrimental effects of biodiversity loss might be more severe in a warmer world.

Conversion of marginal land into switchgrass conditionally accrues soil carbon but reduces methane consumption.

Switchgrass is a deep-rooted perennial native to the US prairies and an attractive feedstock for bioenergy production; when cultivated on marginal soils it can provide a potential mechanism to sequester and accumulate soil carbon (C). However, the impacts of switchgrass establishment on soil biotic/abiotic properties are poorly understood. Additionally, few studies have reported the effects of switchgrass cultivation on marginal lands that have low soil nutrient quality (N/P) or in areas that have experienced high rates of soil erosion. Here, we report a comparative analyses of soil greenhouse gases (GHG), soil chemistry, and microbial communities in two contrasting soil types (with or without switchgrass) over 17 months (1428 soil samples). These soils are highly eroded, 'Dust Bowl' remnant field sites in southern Oklahoma, USA. Our results revealed that soil C significantly increased at the sandy-loam (SL) site, but not at the clay-loam (CL) site. Significantly higher CO2 flux was observed from the CL switchgrass site, along with reduced microbial diversity (both alpha and beta). Strikingly, methane (CH4) consumption was significantly reduced by an estimated 39 and 47% at the SL and CL switchgrass sites, respectively. Together, our results suggest that soil C stocks and GHG fluxes are distinctly different at highly degraded sites when switchgrass has been cultivated, implying that carbon balance considerations should be accounted for to fully evaluate the sustainability of deep-rooted perennial grass cultivation in marginal lands.

Resistance potential of soil bacterial communities along a biodiversity gradient in forest ecosystems.

Higher biodiversity is often assumed to be a more desirable scenario for maintaining the functioning of ecosystems, but whether species-richer communities are also more disturbance-tolerant remains controversial. In this study, we investigated the bacterial communities based on 472 soil samples from 28 forests across China with associated edaphic and climatic properties. We developed two indexes (i.e., community mean tolerance breadth [CMTB] and community mean response asynchrony [CMRA]) to explore the relationship between diversity and community resistance potential. Moreover, we examined this resistance potential along the climatic and latitudinal gradients. We revealed that CMTB was significantly and negatively related to species richness, resulting from the changes in balance between relative abundances of putative specialists and generalists. In comparison, we found a unimodal relationship between CMRA and richness, suggesting that higher biodiversity might not always lead to higher community resistance. Moreover, our results showed differential local patterns along latitude. In particular, local patterns in the northern region mainly followed general relationships rather than those for the southern forests, which may be attributed to the differences in annual means and annual variations of climate conditions. Our findings highlight that the community resistance potential depends on the composition of diverse species with differential environmental tolerance and responses. This study provides a new, testable evaluation by considering tolerance breadth and response asynchrony at the community level, which will be helpful in assessing the influence of disturbance under rapid shifts in biodiversity and species composition as a result of global environmental change.

High historical variability weakens the effects of current climate differentiation on microbial community dissimilarity and assembly.

Understanding the influences of global climate change on soil microbial communities is essential in evaluating the terrestrial biosphere's feedback to this alarming anthropogenic disturbance. However, little is known about how intra-site historical climate variability can mediate the influences of current climate differences on community dissimilarity and assembly. To fill this gap, we examined and disentangled the interactive effects of historical climate variability and current climate differences on the soil bacterial community dissimilarity and stochasticity of community assembly among 143 sites from 28 forests across eastern China. We hypothesize that the relative importance of stochasticity and community dissimilarity are related to historical climate variability and that an increasing sum of intra-site historical variability enhances stochasticity while reduces dissimilarity between two communities. To test our hypothesis, we statistically controlled for covariates between sites including differences in soil chemistry, plant diversity, spatial distance, and seasonal climate variations at annual timescales. We observed that an increase in inter-site current climate differences led to a reduced impact of stochasticity in community assembly and a pronounced divergence between communities. In stark contrast, when communities were subjected to a high level of intra-site historical climate fluctuation, the observed impact incurred from current climate differences was substantially weakened. Moreover, the influence of increased historical variability was consistent along the gradient of current temperature differences between sites. However, effects induced by historical fluctuation in precipitation were disproportional and only evident when small inter-site differences were observed. Consequently, if the prior climate variability is ignored, especially regarding environmental factors like temperature, we assert that the influence current climate differentiation has on regulating community dissimilarity and assembly stochasticity will be underestimated. Together, our findings highlight the importance and need of explicitly controlling the mean and the historical variability of climate factors for the next "generation" of climate change experiments to come.

Substrate-dependent competition and cooperation relationships between Geobacter and Dehalococcoides for their organohalide respiration.

Obligate and non-obligate organohalide-respiring bacteria (OHRB) play central roles in the geochemical cycling and environmental bioremediation of organohalides. Their coexistence and interactions may provide functional redundancy and community stability to assure organohalide respiration efficiency but, at the same time, complicate isolation and characterization of specific OHRB. Here, we employed a growth rate/yield tradeoff strategy to enrich and isolate a rare non-obligate tetrachloroethene (PCE)-respiring Geobacter from a Dehalococcoides-predominant microcosm, providing experimental evidence for the rate/yield tradeoff theory in population selection. Surprisingly, further physiological and genomic characterizations, together with co-culture experiments, revealed three unique interactions (i.e., free competition, conditional competition and syntrophic cooperation) between Geobacter and Dehalococcoides for their respiration of PCE and polychlorinated biphenyls (PCBs), depending on both the feeding electron donors (acetate/H2 vs. propionate) and electron acceptors (PCE vs. PCBs). This study provides the first insight into substrate-dependent interactions between obligate and non-obligate OHRB, as well as a new strategy to isolate fastidious microorganisms, for better understanding of the geochemical cycling and bioremediation of organohalides.

Root-associated fungal community reflects host spatial co-occurrence patterns in a subtropical forest.

Plant roots harbor and interact with diverse fungal species. By changing these belowground fungal communities, focal plants can affect the performance of surrounding individuals and the outcome of coexistence. Although highly host related, the roles of these root-associated fungal communities per se in host plant spatial co-occurrence is largely unknown. Here, we evaluated the host dependency of root-associated communities for 39-plant species spatially mapped throughout a 50-ha subtropical forest plot with relevant environmental properties. In addition, we explored whether the differentiation in root fungal associations among plant species can reflect their observed co-occurrence patterns. We demonstrated a strong host-dependency by discriminating the differentiation of root-associated fungal communities regardless of background soil heterogeneity. Furthermore, Random Forest modeling indicated that these nonrandom root fungal associations significantly increased our ability to explain spatial co-occurrence patterns, and to a greater degree than the relative abundance, phylogenetic relatedness, and functional traits of the host plants. Our results further suggested that plants harbor more abundant shared, "generalist" pathogens are likely segregated, while hosting more abundant unique, "specialist" ectomycorrhizal fungi might be an important strategy for promoting spatial aggregation, particularly between early established trees and the heterospecific adults. Together, we provide a conceptual and testable approach to integrate this host-dependent root fungal "fingerprinting" into the plant diversity patterns. We highlight that this approach is complementary to the classic cultivation-based scheme and can deepen our understanding of the community-level effect from overall fungi and its contribution to the pairwise plant dynamics in local species-rich communities.

Critical transition of soil bacterial diversity and composition triggered by nitrogen enrichment.

Soil bacterial communities are pivotal in regulating terrestrial biogeochemical cycles and ecosystem functions. The increase in global nitrogen (N) deposition has impacted various aspects of terrestrial ecosystems, but we still have a rudimentary understanding of whether there is a threshold for N input level beyond which soil bacterial communities will experience critical transitions. Using high-throughput sequencing of the 16S rRNA gene, we examined soil bacterial responses to a long-term (13 yr), multi-level, N addition experiment in a temperate steppe of northern China. We found that plant diversity decreased in a linear fashion with increasing N addition. However, bacterial diversity responded nonlinearly to N addition, such that it was unaffected by N input below 16 g N·m-2 ·yr-1 , but decreased substantially when N input exceeded 32 g N·m-2 ·yr-1 . A meta-analysis across four N addition experiments in the same study region further confirmed this nonlinear response of bacterial diversity to N inputs. Substantial changes in soil bacterial community structure also occurred between N input levels of 16 to 32 g N·m-2 ·yr-1 . Further analysis revealed that the loss of soil bacterial diversity was primarily attributed to the reduction in soil pH, whereas changes in soil bacterial community were driven by the combination of increased N availability, reduced soil pH, and changes in plant community structure. In addition, we found that N addition shifted bacterial communities toward more putatively copiotrophic taxa. Overall, our study identified a threshold of N input level for bacterial diversity and community composition. The nonlinear response of bacterial diversity to N input observed in our study indicates that although bacterial communities are resistant to low levels of N input, further increase in N input could trigger a critical transition, shifting bacterial communities to a low-diversity state.

Fine-scale spatial patterns in microbial community composition in an acid mine drainage.

Microbial community composition is essential for aquatic ecosystem functions and has been explored across diverse environments and various spatial scales. However, documented patterns are often based on samples from spatially/geographically separated locations or sites. Here, we define sampling volume as spatial scale and examine (by Illumina 16S rRNA sequencing) microbial community composition over a scale of 1 mL to 10 L in an acid mine drainage. ß-Diversity analysis revealed that all samples grouped very tightly according to spatial scales and variations between every two scales were significant. Notably, mean ß-diversity within each group was negatively correlated with spatial scales, indicating patchy microbial distribution. Partition of ß-diversity further revealed that it was the relative abundances of some microbial taxa that largely changed among spatial scales. Phylogenetic analysis showed that microbial lineages were not randomly distributed, but displayed a tendency of more phylogenetically clustering at smaller spatial scales. Thus, we documented fine-scale spatial patterns in microbial community composition within a continuous aquatic environment, which may have practical implications for adequate sampling of aquatic systems in future studies.

Conservation of Species- and Trait-Based Modeling Network Interactions in Extremely Acidic Microbial Community Assembly.

Understanding microbial interactions is essential to decipher the mechanisms of community assembly and their effects on ecosystem functioning, however, the conservation of species- and trait-based network interactions along environmental gradient remains largely unknown. Here, by using the network-based analyses with three paralleled data sets derived from 16S rRNA gene pyrosequencing, functional microarray, and predicted metagenome, we test our hypothesis that the network interactions of traits are more conserved than those of taxonomic measures, with significantly lower variation of network characteristics along the environmental gradient in acid mine drainage. The results showed that although the overall network characteristics remained similar, the structural variation was significantly lower at trait levels. The higher conserved individual node topological properties at trait level rather than at species level indicated that the responses of diverse traits remained relatively consistent even though different species played key roles under different environmental conditions. Additionally, the randomization tests revealed that it could not reject the null hypothesis that species-based correlations were random, while the tests suggested that correlation patterns of traits were non-random. Furthermore, relationships between trait-based network characteristics and environmental properties implied that trait-based networks might be more useful in reflecting the variation of ecosystem function. Taken together, our results suggest that deterministic trait-based community assembly results in greater conservation of network interaction, which may ensure ecosystem function across environmental regimes, emphasizing the potential importance of measuring the complexity and conservation of network interaction in evaluating the ecosystem stability and functioning.

Distinct Network Interactions in Particle-Associated and Free-Living Bacterial Communities during a Microcystis aeruginosa Bloom in a Plateau Lake.

Particle-associated bacteria (PAB) and free-living bacteria (FLB) from aquatic environments during phytoplankton blooms differ in their physical distance from algae. Both the interactions within PAB and FLB community fractions and their relationship with the surrounding environmental properties are largely unknown. Here, by using high-throughput sequencing and network-based analyses, we compared the community and network characteristics of PAB and FLB from a plateau lake during a Microcystis aeruginosa bloom. Results showed that PAB and FLB differed significantly in diversity, structure and microbial connecting network. PAB communities were characterized by highly similar bacterial community structure in different sites, tighter network connections, important topological roles for the bloom-causing M. aeruginosa and Alphaproteobacteria, especially for the potentially nitrogen-fixing (Pleomorphomonas) and algicidal bacteria (Brevundimonas sp.). FLB communities were sensitive to the detected environmental factors and were characterized by significantly higher bacterial diversity, less connectivity, larger network size and marginal role of M. aeruginosa. In both networks, covariation among bacterial taxa was extensive (>88% positive connections), and bacteria potentially affiliated with biogeochemical cycling of nitrogen (i.e., denitrification, nitrogen-fixation and nitrite-oxidization) were important in occupying module hubs, such as Meganema, Pleomorphomonas, and Nitrospira. These findings highlight the importance of considering microbial network interactions for the understanding of blooms.

Effect of Environmental Variation on Estimating the Bacterial Species Richness.

Estimating the species richness of microorganisms is of great importance in predicting, maintaining and managing microbial communities. Although the roles of environmental heterogeneity and geographical distance in structuring soil microbial communities have been studied intensively, the effects of environmental and spatial variation on the species richness estimation have not been examined. To this end, we have explored their effects on estimating the belowground soil bacterial species richness within a 50 ha forest dynamic plot (FDP) using a published massive sequencing dataset with intensive sampling scheme. Our resampling analyses showed that, for a given sequencing depth, increasing the sample size could significantly enhance the detection of rare species by capturing more of the environmental and spatial variation, thus obtaining higher observed and estimated species richness. Additionally, the estimates of bacterial species richness were significantly and positively correlated with environmental variation among samples, indicating that environmental filtering was the main mechanism driving the processes of community assembly for belowground soil bacterial communities in the plot. Moreover, this effect of environmental variation could be markedly alleviated when the sample size was higher than 450, and thus we predicted that there were at least 42,866 soil bacterial species based on 8,296,878 sequences from 550 samples in the whole 50 ha FDP. Furthermore, we built a power law environmental heterogeneity equation (EHE) as a decision-tool to determine an approximate sample size for comprehensively capturing the environmental gradient within a given habitat. Collectively, this work further links the inherent environmental and spatial variation to the estimation of soil bacterial species richness within a given region, and provides a useful tool of sampling design for a better understanding of microbial biogeographic patterns and estimation of microbial biodiversity.

Microbial Ecology and Evolution in the Acid Mine Drainage Model System.

Acid mine drainage (AMD) is a unique ecological niche for acid- and toxic-metals-adapted microorganisms. These low-complexity systems offer a special opportunity for the ecological and evolutionary analyses of natural microbial assemblages. The last decade has witnessed an unprecedented interest in the study of AMD communities using 16S rRNA high-throughput sequencing and community genomic and postgenomic methodologies, significantly advancing our understanding of microbial diversity, community function, and evolution in acidic environments. This review describes new data on AMD microbial ecology and evolution, especially dynamics of microbial diversity, community functions, and population genomes, and further identifies gaps in our current knowledge that future research, with integrated applications of meta-omics technologies, will fill.

Predicting taxonomic and functional structure of microbial communities in acid mine drainage.

Predicting the dynamics of community composition and functional attributes responding to environmental changes is an essential goal in community ecology but remains a major challenge, particularly in microbial ecology. Here, by targeting a model system with low species richness, we explore the spatial distribution of taxonomic and functional structure of 40 acid mine drainage (AMD) microbial communities across Southeast China profiled by 16S ribosomal RNA pyrosequencing and a comprehensive microarray (GeoChip). Similar environmentally dependent patterns of dominant microbial lineages and key functional genes were observed regardless of the large-scale geographical isolation. Functional and phylogenetic ß-diversities were significantly correlated, whereas functional metabolic potentials were strongly influenced by environmental conditions and community taxonomic structure. Using advanced modeling approaches based on artificial neural networks, we successfully predicted the taxonomic and functional dynamics with significantly higher prediction accuracies of metabolic potentials (average Bray-Curtis similarity 87.8) as compared with relative microbial abundances (similarity 66.8), implying that natural AMD microbial assemblages may be better predicted at the functional genes level rather than at taxonomic level. Furthermore, relative metabolic potentials of genes involved in many key ecological functions (for example, nitrogen and phosphate utilization, metals resistance and stress response) were extrapolated to increase under more acidic and metal-rich conditions, indicating a critical strategy of stress adaptation in these extraordinary communities. Collectively, our findings indicate that natural selection rather than geographic distance has a more crucial role in shaping the taxonomic and functional patterns of AMD microbial community that readily predicted by modeling methods and suggest that the model-based approach is essential to better understand natural acidophilic microbial communities.

Microbial communities, processes and functions in acid mine drainage ecosystems.

Acid mine drainage (AMD) is generated from the oxidative dissolution of metal sulfides when water and oxygen are available largely due to human mining activities. This process can be accelerated by indigenous microorganisms. In the last several decades, culture-dependent researches have uncovered and validated the roles of AMD microorganisms in metal sulfides oxidation and acid generation processes, and culture-independent studies have largely revealed the diversity and metabolic potentials and activities of AMD communities, leading towards a full understanding of the microbial diversity, functions and interactions in AMD ecosystems. This review describes the diversity of microorganisms and their functions in AMD ecosystems, and discusses their biotechnological applications in biomining and AMD bioremediation according to their capabilities.

Slash-and-char: An ancient agricultural technique holds new promise for management of soils contaminated by Cd, Pb and Zn.

Heavy metal contamination of agricultural soils is of worldwide concern. Unfortunately, there are currently no efficient and sustainable approaches for addressing this concern. In this study, we conducted a field experiment in which an agricultural soil highly contaminated by cadmium (Cd), lead (Pb) and zinc (Zn) was treated on-site by an ancient agricultural technique, 'slash-and-char', that was able to convert the biomass feedstock (rice straw) into biochar in only one day. We found evidence that in comparison to the untreated soil, the treated soil was associated with decreased bioavailability of the heavy metals and increased vegetable yields. Most importantly, the treatment was also coupled with dramatic reductions in concentrations of the heavy metals in vegetables, which made it possible to produce safe crops in this highly contaminated soil. Collectively, our results support the idea that slash-and-char offers new promise for management of soils contaminated by Cd, Pb and Zn.

Ecological roles of dominant and rare prokaryotes in acid mine drainage revealed by metagenomics and metatranscriptomics.

High-throughput sequencing is expanding our knowledge of microbial diversity in the environment. Still, understanding the metabolic potentials and ecological roles of rare and uncultured microbes in natural communities remains a major challenge. To this end, we applied a 'divide and conquer' strategy that partitioned a massive metagenomic data set (>100 Gbp) into subsets based on K-mer frequency in sequence assembly to a low-diversity acid mine drainage (AMD) microbial community and, by integrating with an additional metatranscriptomic assembly, successfully obtained 11 draft genomes most of which represent yet uncultured and/or rare taxa (relative abundance <1%). We report the first genome of a naturally occurring Ferrovum population (relative abundance >90%) and its metabolic potentials and gene expression profile, providing initial molecular insights into the ecological role of these lesser known, but potentially important, microorganisms in the AMD environment. Gene transcriptional analysis of the active taxa revealed major metabolic capabilities executed in situ, including carbon- and nitrogen-related metabolisms associated with syntrophic interactions, iron and sulfur oxidation, which are key in energy conservation and AMD generation, and the mechanisms of adaptation and response to the environmental stresses (heavy metals, low pH and oxidative stress). Remarkably, nitrogen fixation and sulfur oxidation were performed by the rare taxa, indicating their critical roles in the overall functioning and assembly of the AMD community. Our study demonstrates the potential of the 'divide and conquer' strategy in high-throughput sequencing data assembly for genome reconstruction and functional partitioning analysis of both dominant and rare species in natural microbial assemblages.

Comparative metagenomic and metatranscriptomic analyses of microbial communities in acid mine drainage.

The microbial communities in acid mine drainage have been extensively studied to reveal their roles in acid generation and adaption to this environment. Lacking, however, are integrated community- and organism-wide comparative gene transcriptional analyses that could reveal the response and adaptation mechanisms of these extraordinary microorganisms to different environmental conditions. In this study, comparative metagenomics and metatranscriptomics were performed on microbial assemblages collected from four geochemically distinct acid mine drainage (AMD) sites. Taxonomic analysis uncovered unexpectedly high microbial biodiversity of these extremely acidophilic communities, and the abundant taxa of Acidithiobacillus, Leptospirillum and Acidiphilium exhibited high transcriptional activities. Community-wide comparative analyses clearly showed that the AMD microorganisms adapted to the different environmental conditions via regulating the expression of genes involved in multiple in situ functional activities, including low-pH adaptation, carbon, nitrogen and phosphate assimilation, energy generation, environmental stress resistance, and other functions. Organism-wide comparative analyses of the active taxa revealed environment-dependent gene transcriptional profiles, especially the distinct strategies used by Acidithiobacillus ferrivorans and Leptospirillum ferrodiazotrophum in nutrients assimilation and energy generation for survival under different conditions. Overall, these findings demonstrate that the gene transcriptional profiles of AMD microorganisms are closely related to the site physiochemical characteristics, providing clues into the microbial response and adaptation mechanisms in the oligotrophic, extremely acidic environments.

Microbial communities evolve faster in extreme environments.

Evolutionary analysis of microbes at the community level represents a new research avenue linking ecological patterns to evolutionary processes, but remains insufficiently studied. Here we report a relative evolutionary rates (rERs) analysis of microbial communities from six diverse natural environments based on 40 metagenomic samples. We show that the rERs of microbial communities are mainly shaped by environmental conditions, and the microbes inhabiting extreme habitats (acid mine drainage, saline lake and hot spring) evolve faster than those populating benign environments (surface ocean, fresh water and soil). These findings were supported by the observation of more relaxed purifying selection and potentially frequent horizontal gene transfers in communities from extreme habitats. The mechanism of high rERs was proposed as high mutation rates imposed by stressful conditions during the evolutionary processes. This study brings us one stage closer to an understanding of the evolutionary mechanisms underlying the adaptation of microbes to extreme environments.

Correlating microbial diversity patterns with geochemistry in an extreme and heterogeneous environment of mine tailings.

Recent molecular surveys have advanced our understanding of the forces shaping the large-scale ecological distribution of microbes in Earth's extreme habitats, such as hot springs and acid mine drainage. However, few investigations have attempted dense spatial analyses of specific sites to resolve the local diversity of these extraordinary organisms and how communities are shaped by the harsh environmental conditions found there. We have applied a 16S rRNA gene-targeted 454 pyrosequencing approach to explore the phylogenetic differentiation among 90 microbial communities from a massive copper tailing impoundment generating acidic drainage and coupled these variations in community composition with geochemical parameters to reveal ecological interactions in this extreme environment. Our data showed that the overall microbial diversity estimates and relative abundances of most of the dominant lineages were significantly correlated with pH, with the simplest assemblages occurring under extremely acidic conditions and more diverse assemblages associated with neutral pHs. The consistent shifts in community composition along the pH gradient indicated that different taxa were involved in the different acidification stages of the mine tailings. Moreover, the effect of pH in shaping phylogenetic structure within specific lineages was also clearly evident, although the phylogenetic differentiations within the Alphaproteobacteria, Deltaproteobacteria, and Firmicutes were attributed to variations in ferric and ferrous iron concentrations. Application of the microbial assemblage prediction model further supported pH as the major factor driving community structure and demonstrated that several of the major lineages are readily predictable. Together, these results suggest that pH is primarily responsible for structuring whole communities in the extreme and heterogeneous mine tailings, although the diverse microbial taxa may respond differently to various environmental conditions.