Geological Inheritance and Microbial Phosphorus Regulation Strongly Associate with Metal-Specific Bioavailability in Tea Plantations of Subtropical Soils

Abstract

Heavy metal(oid) pollution in tea plantation has become a global concern threatening tea safety, with food safety serving as the cornerstone of the tea industry. In this study, the distribution and migration patterns of seven heavy metal(oid)s in soil-tea systems developed from three parent materials were investigated, in the geologically complex but minimally human disturbed Dabie Mountains. Results showed that although the heavy metal(oid) concentrations in tea at all sampling points meets the food safety standards of China and the European Union, significant differences existed in the bioaccumulation potential of the elements. Hg and Cd showed the highest bioconcentration factors (mean values of 0.45 and 0.33, respectively), while As, Cr, and Pb transfer were inhibited. Geological type significantly influenced the heavy metal(oid) distributions. Random forest models revealed metal-specific transfer mechanisms, with P-related variables (e.g., soil total P, available P, and microbial biomass P) and microbial C-N acquisition enzyme activities serving as key regulatory factors. This study confirms that parent materials indirectly potentially influence heavy metal(oid) bioavailability by shaping soil development and microbial functions, providing scientific basis for geology-informed food safety risk assessment in tea plantations.

1. Introduction

Tea plants (Camellia sinensis) represent a globally significant perennial economic crop, and tea is one of the most widely consumed natural non-alcoholic beverages worldwide, with product safety directly influencing public health [1,2]. Accumulation of heavy metal(oid)s in tea tissues via root uptake has raised increasing concern [3,4,5,6]. Excessive heavy metal(oid)s induce physiological damage in tea plants, including disruption of chloroplast structure and photosynthetic pigments, alteration of cellular morphology, and interference with tea polyphenol biosynthesis and metabolism [7]. The bioaccumulation of heavy metal(oid)s in plants is a complex process. Their absorption and transport capacities vary among plants and even different parts of the same plant [8,9]. The perennial woody plants are deeply rooted, with a long life cycle, and can continuously absorb and accumulate heavy metal(oid)s from the soil. Among them, Hg and Cd exhibit high enrichment potential in tea due to their great mobility and bioavailability [5]. In contrast, As, Cr, and Pb tend to be fixed by soil particles or rhizosphere, and their transfer to the aboveground parts is inhibited than other metal(oid)s [10,11].

Although anthropogenic inputs such as agrochemicals, atmospheric deposition, and industrial emissions are often emphasized as sources of pollution, and increasing evidence suggests that geogenic metals release through bedrock weathering poses substantial and persistent risks to high-elevation tea gardens distant from urban or industrial zones [12,13]. Critically, even when total soil metal concentrations remain below national agricultural risk thresholds, regional geochemical heterogeneity can cause marked variation in bioavailability [14,15], potentially leading to safety standard exceedances in tea products.

Conventional risk assessments predominantly rely on total soil metal concentrations and fractionation [16]. This approach often neglects the foundational role of parent material in soil genesis [17,18,19]. Distinct rock types inherently differ in mineral composition, elemental abundance, and weathering kinetics, thereby imprinting unique geochemical signatures on derived soils [20]. For example, sulfide-bearing granites or arsenic-enriched metamorphic rocks continuously release As, Cd, and Pb during weathering [21,22,23]. Such geogenic release may trigger ecological risks independent of human activity. Consequently, treating geology as a passive covariate rather than an active driver risks misidentifying contamination sources and misinterpreting metal migration pathways [24].

Nevertheless, metal translocation from bedrock to plant tissues is indirect and non-linear. This process is significantly modulated by soil properties and biological activities arising during pedogenesis [25]. Parent material supplies primary minerals and governs key soil attributes including pH, clay content, cation exchange capacity, and organic matter accumulation [17,26]. These properties collectively regulate metal adsorption, precipitation, and solubility. More importantly, these soil attributes further shape microbial community structure and functions. In recent years, extracellular enzyme activities have been widely used to characterize microbial nutrient and resource acquisition strategies [27,28]. Specifically, β-1,4-glucosidase (BG), β-1,4-N-acetylglucosaminidase (NAG), and acid phosphatase (ACP) reflect microbial demands for carbon (C), nitrogen (N), and phosphorus (P), respectively [29,30,31]. Their stoichiometric ratios indicate nutrient limitations, and correlate closely with metal complexation, reduction, or mobilization processes [30,32,33]. Despite this, few studies have systematically examined the sequence from parent material to soil development, microbial function, and ultimately metal bioavailability, particularly in perennial deep-rooted crops like tea.

Against this backdrop, investigating tea-growing regions with high geological heterogeneity but minimal anthropogenic disturbance holds significant scientific value. The Dabie Mountains, located at the suture zone between the Yangtze and North China cratons [34], represent a core production area for high-quality mist-grown teas in China. Yuexi County within this region exemplifies a typical tea-growing zone vital to local agricultural economy. This region hosts diverse lithologies, including Paleoproterozoic gneiss, Early–Middle Jurassic quartz monzonite, and Late Jurassic granodiorite, each exhibiting distinct elemental geochemical signatures. Moreover, local tea plantations are predominantly situated on slopes above 500 m elevation, managed with low inputs of fertilizers and pesticides, and experience few industrial activities. This low level of anthropogenic disturbance is a defining characteristic of Yuexi County, making it an ideal natural laboratory to isolate and study the effect of geological inheritance on soil development, distinct from the masking effects of intensive agricultural or industrial inputs.

Accordingly, this study conducts field sampling across Yuexi County, Dabie Mountains, classifying sampling sites based on three representative parent materials. We quantified seven target elements (ie., As, Cd, Cr, Hg, Ni, Pb, and Zn) in paired soil and mature tea leaf samples, and simultaneously measured soil physicochemical properties, microbial biomass pools, and key enzyme activities central to C–N–P cycling. These seven elements are listed as key controlled pollutants in China’s National Standards (GB 15618-2018 and GB 31608-2023) [35,36], and are widely present in the environment, with clear regulatory constraints and food safety significance. In contrast, although Cu, Fe, Mn, and Co are essential trace elements for plants, they usually do not pose major toxicity risks in conventional agricultural soils, and their bioavailabilities are greatly influenced by the homeostatic regulation mechanisms of plants themselves. Thus, they were not included in our work.

This focused analytical framework is designed not only to address a critical food safety issue but also to contribute to broader global sustainability objectives. The core concern of this study is closely related to the United Nations 2030 Agenda for Sustainable Development (SDGs). Our work directly serves Goal 2 “Zero Hunger” and Goal 3 “Good Health and Well-being” by ensuring the safety of tea and safeguarding the health rights of consumers. By emphasizing geological derivation, this study aims to: (1) elucidate how geological parent material governs heavy metal(oid) distribution in the soil–tea continuum, and (2) identify the dominant soil and microbial controls on metal bioavailability under the widespread P limited Chinese subtropical soils [37,38]. We hypothesize that: (1) metal accumulation in tea is primarily dictated by geogenic constraints on soil development, despite similar anthropogenic management across sites, and (2) the transfer of metals from soil to tea is jointly associated with P-related variables and microbial acquisition strategies in a metal-specific manner. By linking bedrock to tea, this work will reveal the potentially influence of geological type on metal bioavailability, establishing a foundation for geology-informed risk assessment and sustainable tea cultivation practices.

2. Materials and Methods

2.1. Study Area

The research takes place in Yuexi County (30°39′–31°11′ N, 115°50′–116°33′ E), located in the Anhui Province of China, within the southeastern foothills of the Dabie Mountains (see Figure 1). This area features a hilly landscape with an average elevation nearing 600 m and displays a distinct northwest-to-southeast gradient in its topography. The climate is classified as a northern subtropical monsoon type, characterized by an average annual temperature of 14.5 °C and total precipitation around 1400 mm. These climatic factors, along with notable variations in daily temperatures and naturally acidic yellow-brown soils, create ideal agro-ecological conditions that favor the cultivation of high-quality tea on gentle slopes. The underlying geology is diverse, hosting mineral resources such as iron, copper, and lead-zinc deposits. However, the area remains relatively free from significant industrial pollution sources, making it an ideal natural laboratory to investigate the influence of geological background on soil-plant heavy metal(oid) transfer.

Figure 1. Location of the sampling sites. Each solid circle represents a composite soil sample consisted of five subsamples. The composite sample numbers under Paleoproterozoic gneiss, Early-Middle Jurassic quartz monzonite, and Late Jurassic granodiorite were 15, 10, and 15, respectively.

This study was conducted in areas with minimal human management, without conventional tillage or fertilization. The growth of tea trees relies entirely on natural precipitation. Throughout the entire tea production cycle, no agricultural inputs were applied, such as limestone, gypsum, fertilizers, and biocides, or animal manure, and no sustained soil improvement measures were taken. This low human interference management model helps to eliminate the interference of exogenous substances on the migration of elements in the soil-plant system, thereby revealing the natural impact of geological background clearly.

2.2. Sample Collection and Preparation

Sampling was strategically conducted within a 1-km radius of extensive commercial tea gardens during the peak growing season from June to August 2024, when root systems were most active and agricultural management practices were intensive. Although tea metal accumulation can vary seasonally, this study focused on the peak growing season (June–August) to capture the maximum root activity phase. A combined grid-random sampling approach was employed to ensure spatial representativeness while minimizing bias. At each site, paired samples of surface soil (0–20 cm depth) and mature tea leaves (current-year flushes) were collected.

Each composite soil sample was made up of five subsamples that were mixed in the field, whereas tea samples were gathered from mature leaves (healthy leaves from the current year) situated near the sampling locations. Mature leaves were specifically selected as they represent the primary commercial harvest product and provide a more stable integrator of long-term metal uptake compared to tender buds, which are subject to higher seasonal variability. Following the standards for mature tea gardens in China, we selected tea trees older than 30 years to ensure physiological stability and representativeness. Totally 40 soil-tea pairs samples were obtained. Soils were transported to the laboratory, air-dried, and carefully sieved through a 100-mesh nylon sieve after removal of visible plant debris, gravel, and stones. The samples of tea leaves underwent a rinsing process with deionized water to eliminate any surface dust. They were then dried in an oven at 60 °C until a constant weight was achieved, followed by grinding into a fine powder with a stainless-steel mill.

2.3. Determination of Soil and Tea Properties

Heavy metal(oid) concentrations in both soil and tea leaf samples were assessed in accordance with Chinese standards [35,36]. The concentrations with the exception of As and Hg were analyzed using inductively coupled plasma mass spectrometry (ICP-MS). For the determination of As and Hg, an atomic fluorescence spectrophotometer was employed. Prior to measurement, soil samples underwent complete digestion with HNO₃-HCl-HF, while microwave digestion with HNO₃-H₂O₂ was utilized for the tea samples. The detection limits established for As, Cd, Cr, Hg, Ni, Pb, and Zn were 0.05, 0.02, 2, 0.0003, 1, 1, and 2 mg kg⁻¹, respectively. To maintain both analytical precision and accuracy, quality control procedures involved the analysis of three blank samples and three replicate samples for error assessment. Additionally, four standard reference materials were included for each batch of 20 samples to assure quality. The qualification rates for the parallel test and standard reference material was >90% and >98%, respectively.

The bioconcentration factor (BCF) was calculated as the ratio of the heavy metal(oid) concentration in tea leaves to that in the corresponding soil, serving as a key metric for evaluating the phytoaccumulation potential of tea plants. The BCF values also indicate the heavy metal(oid) bioavailabilities.

2.4. Analysis of Soil Physicochemical and Microbial Properties

Soil pH was assessed in a suspension of 1:2.5 soil-to-water utilizing a calibrated glass electrode. The determination of soil organic matter (OM) was performed through Walkley-Black dichromate oxidation. Total nitrogen (TN) and total phosphorus (TP) were measured using an elemental analyzer (Vario MACRO cube) and the molybdenum-antimony colorimetric approach following acid digestion, respectively. Dissolved organic carbon (DOC) was extracted employing 0.5 M K₂SO₄ and quantified with a TOC analyzer. The concentrations of nitrate nitrogen (NO₃⁻) and ammonium nitrogen (NH₄⁺) were identified using a continuous flow analyzer. For soil available phosphorus (AP), extraction was carried out using NH₄F-HCl and subsequent determination was made with the molybdenum-antimony colorimetric method [39]. The quantification of microbial biomass carbon (MBC) and nitrogen (MBN) was achieved through chloroform fumigation-extraction procedure. Additionally, microbial biomass phosphorus (MBP) was assessed using the fumigation-extraction followed by molybdate blue colorimetry.

The activities of three key extracellular enzymes including BG, NAG, and ACP were assayed fluorometrically. All assays were conducted in 50 mM sodium acetate buffer at 25 °C. Each assay included substrate controls, quench controls, and sample blanks to correct background fluorescence and matrix effects.

To assess microbial nutrient limitation status, the vector analysis approach was applied. Vector length and angle were calculated as follows [29]:

$$\mathrm{V}\mathrm{e}\mathrm{c}\mathrm{t}\mathrm{o}\mathrm{r} \mathrm{l}\mathrm{e}\mathrm{n}\mathrm{g}\mathrm{t}\mathrm{h}=\sqrt{{\left({\displaystyle \frac{\mathrm{l}\mathrm{n}\mathrm{B}\mathrm{G}}{\mathrm{l}\mathrm{n}\left[\mathrm{B}\mathrm{G}+\mathrm{N}\mathrm{A}\mathrm{G}+\mathrm{L}\mathrm{A}\mathrm{P}\right]}}\right)}^2+{\left({\displaystyle \frac{\mathrm{l}\mathrm{n}\mathrm{B}\mathrm{G}}{\mathrm{l}\mathrm{n}[\mathrm{B}\mathrm{G}+\mathrm{A}\mathrm{C}\mathrm{P}]}}\right)}^2}$$

$$\mathrm{V}\mathrm{e}\mathrm{c}\mathrm{t}\mathrm{o}\mathrm{r} \mathrm{a}\mathrm{n}\mathrm{g}\mathrm{l}\mathrm{e}=\mathrm{D}\mathrm{e}\mathrm{g}\mathrm{r}\mathrm{e}\mathrm{e}\mathrm{s}[\mathrm{A}\mathrm{t}\mathrm{a}\mathrm{n}2\left({\displaystyle \frac{\mathrm{l}\mathrm{n}\mathrm{B}\mathrm{G}}{\ln \left[\mathrm{B}\mathrm{G}+\mathrm{A}\mathrm{C}\mathrm{P}\right]}}\right),\hspace{1em}\hspace{1em}\left({\displaystyle \frac{\mathrm{l}\mathrm{n}\mathrm{B}\mathrm{G}}{\mathrm{l}\mathrm{n}\left[\mathrm{B}\mathrm{G}+\mathrm{N}\mathrm{A}\mathrm{G}+\mathrm{L}\mathrm{A}\mathrm{P}\right]}}\right)]$$

The longer the vector, the more C limitation microbes faced. A vector angle > 45° typically indicates P limitation, whereas <45° indicates N limitation.

2.5. Statistical Analysis

Before the statistical analysis, all sampling sites were assigned to one of the three geological parent material types based on the 1:200,000 regional geological map of Yuexi County and verified through field lithological observation. The geological types were: (1) Paleoproterozoic gneiss (Type A), characterized by high-grade metamorphic rocks rich in quartz and feldspar; (2) Early–Middle Jurassic quartz monzonite (Type B), an intermediate intrusive igneous rock with moderate silica content; and (3) Late Jurassic granodiorite (Type C), a calc-alkaline plutonic rock typically enriched in plagioclase and biotite. This classification served as the primary categorical variable for evaluating the influence of bedrock geochemistry on soil development and heavy metal(oid) dynamics.

One-way analysis of variance was performed to evaluate the effects of geological type on soil and tea heavy metal(oid) concentrations, BCF values, and soil physicochemical and microbial properties. Post-hoc comparisons among geological types were conducted using Duncan’s test at p < 0.05. Pearson correlation analysis was used to explore bivariate relationships between soil properties and the BCF of each heavy metal(oid). To identify the most influential predictors of BCF, a random forest model was constructed. Variable importance was assessed using the percentage increase in mean squared error.

All statistical analyses were performed with R v. 4.3.1 using the “stats” and “randomForest” packages. Prior to parametric testing, all datasets were verified for normality using the Shapiro-Wilk test and for homogeneity of variances using Levene’s test. Data are presented as means ± standard error (SE).

3. Results

3.1. Influence of Geological Background on Heavy Metal(oid) Distribution and Bioavailability

The geological parent material exerted a significant and element-specific influence on the concentrations of heavy metal(oid)s in both soil and tea leaves (Table 1). Specifically, tea leaf concentrations of As, Cd, and Cr varied significantly across the three geological types (p < 0.05). Type B exhibited the highest levels of As, Cd, and Cr, whereas Type C showed the lowest concentrations for all three elements. In soils, the concentrations of Cr, Ni, Pb, and Zn were significantly affected by geology (p < 0.05). A consistent trend of Type C > Type B > Type A was observed for Cr, Ni, and Pb. Soil Zn concentrations in Types B and C were higher than in Type A (p < 0.05).

Table 1. Effects of geological type on heavy metal(oid) concentration (mg kg⁻¹) in soil and tea leaf. Different letters within a row indicate significant differences among geological types at p < 0.05. Type A, Paleoproterozoic gneiss; Type B, Early-Middle Jurassic quartz monzonite; Type C, Late Jurassic granodiorite.

Heavy Metal(oid)	Soil			Tea Leaf
	Type A (n = 15)	Type B (n = 10)	Type C (n = 15)	Type A (n = 15)	Type B (n = 10)	Type C (n = 15)
As	2.539 ± 0.545	2.949 ± 0.570	2.323 ± 0.253	0.073 ± 0.004 b	0.092 ± 0.011 a	0.062 ± 0.003 b
Cd	0.198 ± 0.045	0.145 ± 0.017	0.131 ± 0.016	0.043 ± 0.005 ab	0.050 ± 0.012 a	0.027 ± 0.003 b
Cr	37.639 ± 5.061 b	39.190 ± 2.099 b	93.453 ± 21.046 a	1.085 ± 0.090 a	1.321 ± 0.303 a	0.567 ± 0.054 b
Hg	0.023 ± 0.004	0.030 ± 0.009	0.022 ± 0.004	0.008 ± 0.001	0.007 ± 0.001	0.007 ± 0.001
Ni	14.240 ± 2.231 b	16.600 ± 1.080 ab	33.827 ± 8.662 a	5.173 ± 0.834	3.850 ± 0.434	4.573 ± 0.853
Pb	20.324 ± 1.692 b	24.770 ± 1.067 ab	29.860 ± 2.170 a	0.255 ± 0.019	0.297 ± 0.026	0.257 ± 0.030
Zn	70.447 ± 4.908 b	95.800 ± 4.817 a	86.093 ± 2.909 a	23.140 ± 0.750	21.790 ± 1.346	19.873 ± 1.089

The BCF revealed substantial differences in the phytoaccumulation efficiency of tea plants for different metals. Hg exhibited the highest BCF (0.45), followed by Cd (BCF = 0.33). In contrast, As (BCF = 0.04), Cr (BCF = 0.03), and Pb (BCF = 0.01) showed minimal transfer from soil to tea. Furthermore, BCF values for Cr, Ni, Pb, and Zn were significantly influenced by geological type (p < 0.05, Figure 2). The Cr accumulation was significantly higher in Types A and B than in Type C (p < 0.05). For Ni and Zn, BCF values in Type A were greater than those in Types B and C, while Pb in Type A was higher than in Type C (p < 0.05). Overall, the BCF under Type A had the highest BCFs among the three geological types. Comparisons between Types B and C revealed a significant difference only for Cr (p < 0.05), whereas no significant differences were observed for other metals (p > 0.05).

Figure 2. Effects of geological type on bioconcentration factors (BCFs) of heavy metal(oid)s, including As (a), Cd (b), Cr (c), Hg (d), Ni (e), Pb (f) and Zn (g). Different letters indicate significant differences among geological types at p < 0.05. Type A, Paleoproterozoic gneiss; Type B, Early-Middle Jurassic quartz monzonite; Type C, Late Jurassic granodiorite. The sampling numbers for type A, B and C were 15, 10, and 15, respectively.

3.2. Effects of Geological Background on Soil Physicochemical and Microbial Properties

Among the measured soil physicochemical properties, only TP was significantly influenced by geological type (p < 0.05, Table 2). Soils derived from Type A had significantly lower TP compared to those from Types B and C (p < 0.05), and no significant differences were observed between Types B and C (p > 0.05).

Table 2. Effects of geological type on soil properties. Different letters within a row indicate significant differences among geological types at p < 0.05. Type A, Paleoproterozoic gneiss; Type B, Early-Middle Jurassic quartz monzonite; Type C, Late Jurassic granodiorite. OM, organic matter; TN, total nitrogen; TP, total phosphorus; DOC, dissolved organic carbon; NO₃⁻, nitrate nitrogen; NH₄⁺, ammonium nitrogen; AP, available phosphorus. The sampling numbers for type A, B and C were 15, 10, and 15, respectively.

Soil Properties	Type A	Type B	Type C	F Value	p Value
pH	5.59 ± 0.19	5.67 ± 0.31	5.51 ± 0.28	0.081	>0.05
OM (g kg−1)	16.30 ± 1.67	21.63 ± 3.54	21.59 ± 3.53	1.132	>0.05
TN (g kg−1)	0.93 ± 0.11	1.22 ± 0.16	1.21 ± 0.20	1.097	>0.05
TP (g kg−1)	0.84 ± 0.08 b	1.55 ± 0.31 a	1.41 ± 0.05 a	6.624	0.003
DOC (g kg−1)	0.10 ± 0.01	0.13 ± 0.02	0.11 ± 0.02	0.663	>0.05
NO3− (mg kg−1)	12.29 ± 1.56	22.40 ± 3.70	16.14 ± 3.06	3.066	>0.05
NH4+ (mg kg−1)	2.09 ± 0.71	2.36 ± 0.84	2.34 ± 0.67	0.045	>0.05
AP (mg kg−1)	32.21 ± 5.09	61.24 ± 35.84	36.17 ± 8.90	0.754	>0.05

Geology significantly influenced microbial enzyme activities (BG and NAG), although microbial biomass pools did not differ significantly across geological types (Figure 3). The activities of both BG and NAG were higher in soils from Types A and B than in those from Type C (p < 0.05), with no difference between A and B. Furthermore, the vector angle was >45° across all sites, confirming a general state of P limitation in the research soils. Compared to Types A and B, the vector angle was higher in Type C soils (p < 0.05).

Figure 3. Effects of geological type on soil microbial properties, including microbial biomass carbon (a), nitrogen (b), phosphorus (c), β-1,4-glucosidase (d), β-1,4-N-acetylglucosaminidase (e), acid phosphatase (f), vector length (g), and vector angle (h). Different letters indicate significant differences among geological types at p < 0.05. Type A, Paleoproterozoic gneiss; Type B, Early-Middle Jurassic quartz monzonite; Type C, Late Jurassic granodiorite. The sampling numbers for type A, B and C were 15, 10, and 15, respectively.

3.3. Linking Soil Properties to Heavy Metal(oid) Bioavailability

Pearson correlation analysis (Figure 4) demonstrated that soil OM, TN, TP, MBN, MBP, and the C- and N- enzyme activities (BG, NAG) showed the strongest correlations with the BCF. Notably, BG and NAG activities were positively correlated with the BCF of most metals, while other properties (e.g., OM, TN, TP) generally exhibited negative correlations with BCF.

Figure 4. Correlation heatmap between soil properties, microbial variables, and BCFs of heavy metal(oid). Pearson correlation coefficients (r) are shown with color intensity. Only significant correlations (p < 0.05) are displayed. OM, organic matter; TN, total nitrogen; TP, total phosphorus; DOC, dissolved organic carbon; NO₃⁻, nitrate nitrogen; NH₄⁺, ammonium nitrogen; AP, available phosphorus. MBC, microbial biomass carbon; MBN, microbial biomass nitrogen; MBP, microbial biomass phosphorus. BG, β-1,4-glucosidase, NAG, β-1,4-N-acetylglucosaminidase; ACP, acid phosphatase. VL, vector length; VA, vector angle. * p < 0.05, ** p < 0.01.

The random forest model identified distinct sets of key predictors for the BCF of each metal (Figure 5). For As, the most important predictors were OM, TN, and AP. Cd bioavailability was primarily associated with TP, MBN, pH, MBC, OM, and AP. Cr transfer was best explained by TP, NAG, vector angle, and AP. Furthermore, Hg was influenced by TN, OM, and TP. Ni showed strong dependence on BG, NAG, TP, and AP. Pb transfer was mainly predicted by AP and BG, whereas Zn was governed by TP, MBP, and vector angle.

Figure 5. Variable importance from random forest models predicting BCFs of heavy metal(oid)s, including As (a), Cd (b), Cr (c), Hg (d), Ni (e), Pb (f) and Zn (g). MSE (Mean Squared Error) represents the prediction error of the model. OM, organic matter; TN, total nitrogen; TP, total phosphorus; DOC, dissolved organic carbon; NO₃⁻, nitrate nitrogen; NH₄⁺, ammonium nitrogen; AP, available phosphorus. MBC, microbial biomass carbon; MBN, microbial biomass nitrogen; MBP, microbial biomass phosphorus. BG, β-1,4-glucosidase, NAG, β-1,4-N-acetylglucosaminidase; ACP, acid phosphatase. VL, vector length; VA, vector angle.

4. Discussion

4.1. Influence of Geological Parent Material on Heavy Metal(oid) Distribution in the Soil–Tea Plant System

This study demonstrates that geological parent material significantly influence the distribution patterns of heavy metal(oid)s in soils and tea plants, as well as their migration to tea plants, through distinct geochemical compositions and weathering characteristics, thereby validating Hypothesis 1. Among the three bedrock types, soils derived from granodiorite (Type C) show the highest concentrations of Cr, Ni, and Pb. This is closely linked to their abundance of ferromagnesian minerals, such as amphibole and biotite, and accessory minerals like chromite and zircon [6,40]. These minerals continuously release siderophile elements, such as Cr and Ni, during chemical weathering, establishing high background values. In contrast, gneiss (Type A), a high-grade metamorphic rock, has undergone intense recrystallization, fixing most original metal-hosting phases in stable silicate lattices [41,42]. Consequently, the total metal concentration in its soil is generally the lowest. Although quartz monzonite (Type B) is an intermediate-acidic intrusive rock, it contains relatively more accessory minerals or fluid inclusions with As and Cd [43,44]. These can release highly active components in the early stages of weathering, making it a key source of As and Cd enrichment in tea.

There is no straightforward positive correlation between metal concentrations in soil and the metal’s bioavailability. Although Type C soil contains the highest metal concentration, the BCFs for tea plants in this soil are significantly lower than in the other two types, particularly for Cr and Pb. This discrepancy can be attributed to the characteristics of its parent soil. The Late Jurassic granodiorite (Type C) is abundant in ferromagnesian silicate minerals and clay. Weathering processes generate a substantial amount of iron-manganese oxides and particles with high specific surface areas [45,46,47]. Combined with low pH, these factors enhance the specific adsorption and co-precipitation of trivalent/divalent metal cations [48]. For instance, Cr(III) is readily immobilized by Fe oxides [49]. Divalent Pb and Ni are sequestered by soils with high cation exchange capacity [50], significantly reducing their bioavailability. However, it is important to note that these interpretations are based on pedogenic inference; the specific mechanisms involving clay content, Fe/Mn oxides, and CEC were not directly measured in this study and warrant further quantification in future work. Conversely, Type A soil, despite its low total metal concentration, exhibits the highest enrichment efficiency for Ni, Pb, and Zn. This may be due to the more soluble forms of metals in its weathering products or the lower content of organic matter and clay particles, which weakens complexation and precipitation abilities [51]. These findings collectively indicate that the geological parent material not only determines the initial abundance of elements but also profoundly influences the bioavailability of heavy metal(oid)s by regulating soil development processes.

The finding that BCFs for all elements are <1 indicates that tea plants effectively limit the transport of these elements from roots to harvestable leaves. Although Hg and Cd have the highest BCFs among all the elements, their concentrations in tea are completely within the strict standards specified by China and EU (Table A1). The low BCFs and safe concentrations highlight the safety of tea in these geologically diverse and low human impact areas. These are crucial for food safety, directly contributing to the SDGs by ensuring a safe and reliable food source and minimizing consumer exposure to potentially toxic elements.

4.2. Coordinated Regulation of Heavy Metal(oid) Bioavailability by P and Microbial Functions

This study effectively identified the key soil and microbial factors influencing the bioavailability of heavy metal(oid)s under prevalent P limitation in subtropical soils, thereby supporting our second hypothesis. The random forest model demonstrated that the transfer mechanism of heavy metal(oid)s from soil to tea leaves is distinctly metal-specific and is jointly associated with interconnected soil chemical and microbial factors. Among these, P-related variables, such as TP, AP, MBP, and vector angle, are particularly critical. P serves not only as an essential nutrient for plants but also as a core ion regulating the metal adsorption-desorption equilibrium [52]. For instance, As(V) shares a similar structural charge with phosphate (P(V)), leading to competitive adsorption on the surface of Fe/Al oxides [53]. Consequently, while increased AP can alleviate plant P deficiency, it may also enhance the desorption of As and the plant uptake of soil P. Similarly, divalent metals like Cd, Pb, and Zn tend to form soluble complexes with dissolved organic P or P-containing ligands released by microorganisms [54,55]. Thus, when soil P content is high, these metals are bound, resulting in a decrease in their BCF and establishing a negative correlation between their BCFs and P-related variables.

In addition, our three types of geological backgrounds further amplify this metal specificity by shaping different P geochemical environments. While soil derived from Type C has the highest TP, it exhibits the lowest average values of AP and MBP. Additionally, it has the largest vector angle, indicating severe microbial P limitation [29]. This limitation significantly reduces the bioavailability of Cr and Pb by influenceing microbial activity which is associated with altered microbial enzymatic strategies and altering metal speciation. In contrast, Type A soil, with the lowest TP content and a smaller vector angle, suggests less P limitation for microorganisms [29]. This condition may enhance microbial activity, creating favorable conditions for metal activation [32,56], which accounts for its relatively high metal bioavailability. Meanwhile, in subtropical regions where P limitation is widespread [37,38], the relatively high activities of BG and NAG in Types A and B soils may promote the mineralization of organic P [57], releasing soluble P components and indirectly enhancing the migration of some metals. Previous studies have also indicated that phytoremediation of soil heavy metal(oid) pollution stimulates the production of microbial extracellular enzymes [58]. Thus, the close coupling of the P cycle with microbial C and N acquisition strategies [57,59] underscores its role as a regulatory hub for heavy metal(oid) migration across different parent rock backgrounds.

4.3. Future Research and Recommendations

Traditional risk assessment often depends on the total threshold of heavy metal(oid)s in soil, which can lead to errors in geologically diverse regions. This study reveals that risk levels for the same metal can differ markedly across various parent rock areas. For instance, although Type C soil has the highest Cr concentration, its strong fixation effect results in the lowest actual Cr content and enrichment coefficient in tea leaves. Since geological background is the primary driver of heavy metal(oid) migration, it should be included in the risk assessment framework to prevent mistaking naturally high backgrounds for pollution or underestimating high migration risks in low-background areas. Additionally, integrating process indicators like TP, AP, and enzyme activity into monitoring provides a more accurate measure of bioavailability than merely relying on total amounts, particularly in P-limited regions.

Limitations of this study include the relatively modest sample size (n = 40) and the reliance on a single sampling campaign during the peak growing season. While this study provides a snapshot of metal behavior under high root activity conditions, it does not capture potential seasonal fluctuations in soil chemistry or plant uptake. Future research should incorporate long-term monitoring across multiple seasons to validate these findings. Meanwhile, it did not thoroughly examine the relationship between microbial community structure, its functional genes, and heavy metal(oid) migration across different geological types. Future research can integrate metagenomics with stable isotope tracing technology to clarify the microscopic mechanisms at the P-metal-microorganism interface. Furthermore, the effects of long-term climate change on heavy metal(oid) dynamics within the geological-soil-plant system warrant further investigation [56,60]. Understanding these migration patterns and their ecological impacts is crucial. Ultimately, this knowledge will facilitate the shift in tea plantation management from “total amount control” to “effectiveness regulation”, enabling precise governance and sustainable development based on the natural geochemical background.

5. Conclusions

Geological background, soil properties, microbial functions, and heavy metal(oid) bioavailability are intrinsically interconnected within tea plantation systems in subtropical regions. Parent materials determine not only the initial concentrations of heavy metal(oid)s in soil but also indirectly associate with their bioavailability by shaping soil physicochemical properties and microbial activities. Heavy metal(oid) transfer exhibits pronounced metal-specificity, with Hg and Cd showing the highest bioaccumulation potential while As, Cr, and Pb transfer are inhibited. Random forest modeling identifies unique key predictor combinations for each metal, with P-cycling variables and microbial C-N acquisition strategies forming a core regulatory network. These findings provide a scientific basis for establishing a geology-informed precision risk assessment system for tea plantations, offering significant practical value for ensuring tea safety and promoting regional sustainable management.