Microbial Bioactives

1. Introduction

Lead (Pb) contamination has become one of the more persistent and ecologically disruptive forms of soil pollution associated with industrialization, mining, smelting activities, urban expansion, and intensive agricultural practices. Although soils are often perceived merely as physical substrates that support plant growth, they are, in reality, extraordinarily dynamic biological systems inhabited by diverse microbial communities that regulate nutrient cycling, organic matter decomposition, carbon sequestration, and ecosystem productivity (Fierer, 2017). The integrity of these microbial networks is deeply intertwined with soil health and ecological resilience, meaning that disturbances affecting microbial diversity may ultimately compromise broader ecosystem functioning (Delgado-Baquerizo et al., 2016). In recent years, growing concern has emerged over how toxic metals, particularly Pb, alter these belowground biological systems in ways that are not always immediately visible but may have long-lasting environmental consequences.

Unlike certain trace metals that serve physiological functions at low concentrations, Pb has no known biological role in microbial metabolism and is considered toxic even at relatively low exposure levels (Violante et al., 2010). What makes Pb especially problematic is not merely its toxicity, but its persistence. Once introduced into soils, Pb strongly associates with clay particles, oxides, and organic matter, allowing it to remain in the environment for decades or even centuries (Alengebawy et al., 2021). This prolonged residence time means that microbial communities are often exposed to chronic rather than acute contamination, creating sustained ecological pressure that may reshape community composition, reduce biodiversity, and alter functional processes over time (Giller et al., 2009). In heavily contaminated environments such as mining districts and industrial zones, these changes can become profound enough to transform the biological identity of the soil itself.

Yet, the ecological response to Pb contamination is rarely straightforward. Soil microbial communities do not respond uniformly across landscapes or contamination gradients. Instead, responses appear to depend heavily on factors such as pH, organic matter content, moisture, redox potential, metal speciation, and interactions with co-occurring contaminants (Zhao et al., 2020). Acidic soils, for instance, often increase Pb mobility and bioavailability, intensifying microbial exposure and toxicity, whereas soils rich in organic matter may partially immobilize Pb through chelation and adsorption processes (Violante et al., 2010). This environmental complexity makes it difficult to predict microbial outcomes using Pb concentration alone. In some soils, modest contamination may produce little detectable effect, while in others, similar concentrations may trigger sharp reductions in microbial diversity and metabolic activity.

Over the past decade, advances in molecular ecology have significantly improved understanding of how microbial communities respond to heavy metal stress. Traditional cultivation-based approaches captured only a fraction of microbial diversity, often overlooking rare or unculturable taxa that nonetheless contribute meaningfully to ecosystem stability. More recently, tools such as PCR-DGGE, high-throughput 16S rRNA sequencing, metagenomics, and functional gene analyses have enabled researchers to investigate microbial assemblages with far greater resolution (Bhakta et al., 2018). These approaches have revealed that Pb contamination can reshape both taxonomic composition and ecological interactions within soil microbiomes. Certain microbial groups decline rapidly under metal stress, whereas others persist or even proliferate, suggesting varying levels of resistance and adaptive capacity among taxa (Lin et al., 2019).

A recurring observation across contaminated environments is the decline in microbial diversity and richness as heavy metal burdens increase. Studies conducted near smelting sites, mining areas, and contaminated farmlands consistently report reductions in indices such as Shannon diversity and Chao1 richness under elevated Pb concentrations (Luo et al., 2018; Tseng et al., 2021; Zhao et al., 2020). These declines likely reflect selective pressures favoring metal-tolerant microorganisms while sensitive taxa diminish or disappear. Although some degree of community restructuring may represent ecological adaptation, persistent biodiversity loss raises concerns regarding ecosystem multifunctionality because diverse microbial communities tend to support more stable and efficient biogeochemical processes (Delgado-Baquerizo et al., 2016).

Interestingly, the relationship between Pb contamination and microbial diversity does not always appear linear. Several investigations suggest the existence of threshold-dependent responses in which microbial communities remain relatively stable up to a certain contamination level before experiencing abrupt structural collapse (Lin et al., 2019; Gao et al., 2019). Such ecological thresholds are particularly important because they imply that microbial systems may tolerate gradual environmental stress only to a point, beyond which resilience mechanisms become overwhelmed. This notion aligns with broader ecological theories concerning tipping points and nonlinear ecosystem responses under persistent disturbance. Understanding where these thresholds occur may therefore be essential for environmental risk assessment and remediation planning.

Beyond shifts in diversity, Pb contamination also influences microbial functionality, particularly processes associated with nitrogen cycling. Denitrification, the stepwise microbial reduction of nitrate to gaseous nitrogen compounds, is especially sensitive to heavy metal stress because many of the enzymes involved are membrane-bound or periplasmic and thus more exposed to environmental contaminants (Liu et al., 2018; Sobolev & Begonia, 2008). Disruption of denitrifying communities may reduce nitrogen transformation efficiency, increase nitrate accumulation, and contribute to elevated emissions of nitrous oxide (N₂O), a potent greenhouse gas. Functional disturbances of this kind suggest that Pb contamination affects not only “who is present” within microbial communities but also “what these communities are capable of doing.” In some contaminated soils, reductions in microbial biomass, respiration, and enzyme activity have been observed alongside compositional changes, reinforcing the idea that structural and functional responses are closely linked (Hu et al., 2019; Fajardo et al., 2019; Gong et al., 2021).

At the same time, microbial communities possess varying degrees of resistance, resilience, and redundancy that may buffer ecosystems against environmental disturbance. Resistance refers to the ability of microbial communities to remain relatively unchanged despite stress, whereas resilience describes the capacity to recover after disturbance (Allison & Martiny, 2008; Shade et al., 2012). Functional redundancy further suggests that multiple microbial taxa may perform similar ecological roles, allowing critical processes to continue even when some species decline (Griffiths & Philippot, 2012). However, the extent to which redundancy truly protects ecosystem functioning under chronic Pb exposure remains uncertain. Rare microbial taxa, often overlooked because of their low abundance, may play disproportionately important ecological roles during environmental stress or recovery phases (Jousset et al., 2017). Consequently, even subtle diversity losses may have implications that are not immediately apparent.

Another complicating factor is the temporal dimension of contamination. Microbial communities in long-term contaminated soils may differ substantially from those exposed to recent Pb inputs. Chronic contamination can drive ecological adaptation, leading to communities dominated by resistant taxa that tolerate heavy metal stress more effectively (Beattie et al., 2018). While such adaptation may preserve some ecosystem functions, it can also fundamentally alter microbial interactions, metabolic pathways, and nutrient dynamics. Moreover, adapted communities may not readily revert to their original states following remediation efforts, suggesting that historical contamination can leave lasting ecological legacies (Kuppusamy et al., 2016).

The effects of Pb are also rarely isolated. Heavy metal-contaminated soils often contain mixtures of pollutants, including cadmium (Cd), zinc (Zn), chromium (Cr), copper (Cu), pesticides, and metalloids, which may interact synergistically or antagonistically (Alengebawy et al., 2021; Wyszkowska et al., 2023). These interactions complicate interpretation because microbial responses observed in field studies may reflect combined contaminant pressures rather than Pb alone. For example, co-contaminants may intensify oxidative stress, alter microbial membrane integrity, or shift competitive interactions within microbial networks (Cui et al., 2018; Gao et al., 2019). Consequently, understanding Pb toxicity requires a more integrative perspective that considers the broader physicochemical context of contaminated soils.

Despite substantial research activity, findings across individual studies remain fragmented and sometimes inconsistent due to differences in soil characteristics, contamination histories, molecular methods, and ecological metrics. Systematic reviews and meta-analytical approaches therefore provide an important opportunity to synthesize available evidence, identify broader ecological patterns, and evaluate whether threshold-dependent responses consistently emerge across studies. Meta-analysis also allows for the assessment of publication bias and variability among datasets through approaches such as funnel plot analysis and asymmetry testing (Egger et al., 1997; Sterne et al., 2011). Such synthesis is increasingly necessary as environmental scientists seek not only to describe contamination effects, but also to predict ecological outcomes and guide remediation strategies more effectively.

In this context, the present systematic review examines the threshold-dependent effects of Pb contamination on soil microbial diversity and denitrifying function. By integrating evidence from studies conducted across contaminated agricultural lands, mining regions, and industrial environments, this review aims to clarify how Pb influences microbial community structure, functional resilience, and nitrogen-transforming processes under varying environmental conditions. Particular attention is given to nonlinear microbial responses, ecological thresholds, and the interplay between soil chemistry and microbial adaptation. Ultimately, understanding these relationships may help inform more ecologically grounded approaches to soil remediation, contamination management, and long-term ecosystem sustainability.

2. Materials and Methods

2.1. Study Design and Review Framework

This study was conducted as a systematic review with quantitative synthesis to evaluate how lead (Pb) contamination influences soil microbial diversity, community structure, and denitrification-related functions across different environmental settings. The methodological framework was developed before the review process began to minimize subjective bias and improve consistency during evidence synthesis. Reporting procedures followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) guidelines, which provide an internationally recognized framework for transparent and reproducible systematic reviews (Page et al., 2021) (Figure 1). In addition, methodological decisions related to study screening, data extraction, and evidence synthesis were guided by recommendations outlined in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins et al., 2022).

The review addressed studies examining microbial responses to Pb contamination under both field and laboratory conditions. Observational, cross-sectional, and experimental studies were considered eligible if they quantitatively assessed microbial diversity indices, community composition, or denitrification-related functional indicators in soils exposed to Pb. The review question was structured according to the Population–Exposure–Comparator–Outcome (PECO) framework. Within this framework, the population consisted of soil microbial communities, the exposure referred to environmentally relevant Pb contamination, comparators included uncontaminated or less-contaminated soils, and outcomes encompassed microbial diversity metrics, taxonomic changes, and denitrification-associated functional responses.

Meta-analysis was conducted when at least three independent studies reported sufficiently comparable exposure and outcome data. Where methodological inconsistency or insufficient quantitative reporting prevented statistical pooling, findings were synthesized narratively while maintaining systematic review principles. This mixed analytical approach allowed broader integration of evidence while preserving methodological rigor (Borenstein et al., 2009).

2.2. Literature Search Strategy and Study Selection

A comprehensive literature search was performed using major scientific databases, including PubMed/MEDLINE, Web of Science, and Scopus. The search covered peer-reviewed articles published in English up to December 2022. Search strategies combined controlled vocabulary and free-text terms associated with Pb contamination and soil microbiology. Core search terms included combinations of “lead,” “Pb,” “soil microbial community,” “bacterial diversity,” “heavy metals,” “denitrification,” “nirK,” “nirS,” and “16S rRNA.” Boolean operators and database-specific filters were applied to optimize retrieval sensitivity and specificity.

All retrieved records were imported into reference management software, and duplicate articles were removed before screening. Study selection was conducted in two sequential stages. Initially, titles and abstracts were screened to exclude studies clearly unrelated to the review objective, including investigations focused solely on aquatic environments, plant physiology, animal toxicology, or contaminants other than Pb without separate Pb-specific data. Subsequently, full-text articles were evaluated against predefined inclusion and exclusion criteria.

Studies were included if they: (i) quantified soil Pb concentrations using recognized analytical methods; (ii) evaluated microbial diversity, microbial community composition, or denitrification-related functions; and (iii) provided sufficient statistical or descriptive information for effect size extraction or qualitative interpretation. Studies were excluded if they were review papers, conference abstracts lacking complete datasets, editorials, or investigations without quantitative microbial outcomes. Screening disagreements were resolved through discussion and repeated evaluation to ensure consistency

Figure 1: PRISMA 2020 Flow Diagram of Study Identification, Screening, Eligibility Assessment, and Inclusion Criteria for the Systematic Review and Meta-analysis of Lead (Pb) Effects on Soil Microbial Diversity and Denitrifying Functions. A total of 6 studies fulfilled the predefined criteria for quantitative synthesis (meta-analysis) based on comparable microbial diversity indices, Pb exposure measurements, and functional outcome data.

and reduce selection bias, following systematic review recommendations proposed by Higgins et al. (2022).

2.3. Data Extraction and Quality Assessment

Data extraction was performed using a standardized template specifically developed for this review. Information collected from each study included publication details, geographical location, soil type, land-use characteristics, contamination source, Pb concentration range, exposure duration, and co-occurring contaminants where reported. Additional soil physicochemical parameters, including pH, organic matter content, and moisture conditions, were also extracted because these variables may substantially influence Pb bioavailability and microbial responses.

Microbial outcome variables included diversity indices such as Shannon diversity, Chao1 richness, and Simpson diversity, as well as measurements related to microbial biomass, taxonomic composition, and denitrification-associated functions. Functional indicators included abundance of denitrification genes (e.g., nirK and nirS), nitrate reduction activity, and other reported denitrification-related parameters. Where numerical values were presented only in graphical form, digital extraction software was used to obtain approximate quantitative data while maintaining consistency across studies.

The methodological quality of included studies was evaluated using criteria adapted for environmental microbiology research. Assessment domains included clarity of study design, adequacy of Pb quantification methods, reliability of microbial analytical techniques, statistical transparency, and completeness of reported outcome data. Studies were categorized as having low, moderate, or high risk of bias based on overall methodological quality. These assessments were used to contextualize findings and support interpretation during synthesis rather than to exclude studies entirely.

2.4. Quantitative Synthesis and Meta-Analysis

Quantitative synthesis was conducted when studies reported sufficiently comparable microbial outcomes and exposure definitions. Effect sizes were calculated primarily using standardized mean differences comparing Pb-contaminated soils with uncontaminated or lower-contamination reference soils. Standardized effect size approaches are widely recommended for environmental and ecological meta-analyses because they facilitate comparisons across studies using different measurement scales (Borenstein et al., 2009).

Given the anticipated ecological and methodological variability among studies, random-effects models were applied during meta-analysis. This approach assumes that observed effect sizes may vary across studies because of differences in environmental conditions, microbial assessment methods, contamination history, and soil characteristics (DerSimonian & Laird, 1986). Random-effects models were therefore considered more appropriate than fixed-effects models for representing heterogeneous ecological datasets.

Statistical heterogeneity among studies was evaluated using the I² statistic, which quantifies the proportion of total variation attributable to between-study heterogeneity rather than sampling error (Higgins et al., 2003). I² values exceeding 50% were interpreted as indicating substantial heterogeneity. Where heterogeneity was elevated, subgroup analyses were conducted based on Pb concentration ranges, soil pH categories, contamination duration, and presence of co-contaminants. These subgroup analyses aimed to identify environmental conditions under which microbial responses became more pronounced or variable.

Threshold-dependent responses were further explored by examining nonlinear patterns in microbial diversity decline across increasing Pb concentrations. Rather than assuming a strictly linear dose–response relationship, emphasis was placed on identifying potential ecological tipping points where microbial communities exhibited abrupt structural or functional changes. Sensitivity analyses were additionally conducted by excluding studies classified as high risk of bias to evaluate the robustness and stability of pooled effect estimates.

2.5. Publication Bias and Narrative Synthesis

Potential publication bias was evaluated using funnel plot inspection and Egger’s regression asymmetry test, both of which are commonly applied in meta-analytical studies to assess the possibility of selective reporting or small-study effects (Egger et al., 1997). Interpretation of funnel plot asymmetry followed recommendations outlined in systematic review methodology literature to avoid overinterpretation in highly heterogeneous datasets. In cases where statistical pooling was not feasible because of methodological diversity or insufficient quantitative data, findings were synthesized narratively. Narrative synthesis focused on the direction, magnitude, and consistency of reported microbial responses across studies while integrating ecological interpretation with statistical observations. Particular attention was given to whether shifts in microbial diversity corresponded with alterations in denitrification-related functions, resilience patterns, or evidence of threshold-dependent ecological disruption.

Overall, the analytical strategy combined systematic review methodology with ecological interpretation to provide a comprehensive understanding of how Pb contamination influences soil microbial diversity and denitrifying functions across varying environmental conditions.

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 that collectively support both linear and threshold-dependent responses of soil microbial communities to Pb stress.

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 2, 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 3 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 4, 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

Table 1. Effects of Lead and Mixed Heavy Metal Contamination on Soil Microbial Alpha Diversity Assessed Using Shannon Diversity Indices Across Contaminated Environmental Systems. This table summarizes changes in microbial alpha diversity between uncontaminated reference soils and heavy metal–contaminated soils from industrial, agricultural, riverbank, and experimental environments. Lower treatment values relative to controls indicate suppression of microbial diversity under Pb and mixed-metal stress, highlighting the sensitivity of soil microbial communities to contamination intensity and environmental context.

Table 2. Changes in Soil Microbial Richness Metrics (Chao1 and Observed OTUs) Following Exposure to Lead and Mixed Heavy Metal Contamination. This table presents microbial richness indicators, including Chao1 estimators and observed operational taxonomic units (OTUs), under control and contaminated soil conditions. Declines in richness metrics demonstrate the loss of microbial taxa and reduced ecological complexity associated with heavy metal exposure, particularly under elevated Pb concentrations.

Figure 2. Forest Plot Showing the Pooled Effects of Heavy Metal Contamination on Soil Microbial Alpha Diversity Based on Shannon Diversity Indices. This forest plot presents individual and pooled effect size estimates comparing microbial alpha diversity between contaminated and uncontaminated soils. Negative pooled effects indicate significant reductions in microbial diversity under Pb and mixed-metal exposure, while confidence intervals reflect variability among environmental studies.

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 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. Table 3 summarizes the comparative effects of Pb and mixed heavy metal exposure on soil microbial community composition and diversity-related parameters across different contaminated environments. Overall, treatment soils exposed to Pb, Cu, Zn, Cr, or mixed industrial pollutants consistently exhibited lower microbial abundance and diversity indices than their corresponding control or reference soils, suggesting that heavy metal stress disrupts microbial ecosystem stability and alters community structure. Notable reductions were observed in Pb-contaminated smelting and agricultural soils, while mixed-metal contamination in electroplating and riverbank environments demonstrated broader ecological suppression of microbial populations, highlighting the cumulative toxicity of multi-metal exposure conditions (Table 3).

Table 4 presents quantitative alterations in soil microbial richness and diversity metrics under heavy metal contamination conditions. Across studies, contaminated soils generally demonstrated substantial declines in Chao1 estimators, observed OTUs, and bacterial richness values relative to control soils, indicating a strong negative effect of metal stress on microbial diversity. The calculated effect differences (Δ) revealed marked reductions in microbial richness, particularly in highly contaminated industrial soils, supporting the hypothesis that Pb and associated heavy metal pollutants exert threshold-dependent ecological pressure on soil microbial communities and reduce overall microbial ecosystem resilience (Table 4).

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

Table 3. Comparative Effects of Pb and Mixed Pollutant Exposure on Soil Microbial Community Composition and Diversity-Related Metrics. This table compares microbial community responses across studies examining Pb alone or in combination with other heavy metals such as Cr, Cu, and Zn. Treatment conditions generally showed reduced microbial abundance or diversity compared with reference soils, reflecting the disruptive influence of metal stress on soil microbial ecosystem structure.

Table 4. Quantitative Changes in Soil Microbial Diversity and Richness Parameters Under Heavy Metal Contamination Conditions. This table summarizes calculated effect differences between control and contaminated soils for microbial richness and diversity metrics, including Chao1 and OTU-based measurements. Negative effect values indicate substantial reductions in microbial diversity associated with pollutant exposure, supporting the threshold-dependent ecological impacts of Pb contamination on soil microbial systems.

Figure 3. Forest Plot Illustrating the Impact of Heavy Metal Stress on Soil Microbial Richness Metrics Including Chao1 Estimators and Operational Taxonomic Units (OTUs). 

Figure 4. Funnel Plot Assessing Publication Bias and Small-Study Effects in Meta-analytical Estimates of Heavy Metal Impacts on Soil Microbial Richness. This funnel plot evaluates the distribution symmetry of effect sizes associated with microbial richness responses to Pb and mixed heavy metal contamination. The overall symmetry of plotted studies suggests relatively low publication bias and supports the statistical robustness of the pooled meta-analytical findings.

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). 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. 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). 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