Unveiling the impact of biodegradable polylactic acid microplastics on meadow soil health

Unveiling the impact of biodegradable polylactic acid microplastics on meadow soil health | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Unveiling the impact of biodegradable polylactic acid microplastics on meadow soil health Shuming Liu, Binglin Chen, Kaili Wang, Jinghuizi Wang, Yan Suo, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5368532/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 08 Jan, 2025 Read the published version in Environmental Geochemistry and Health → Version 1 posted 9 You are reading this latest preprint version Abstract Soil microplastics (MPs) pollution has garnered considerable attention in recent years. The use of biodegradable plastics for mulching has led to significant quantities of plastic entering agro-ecosystems. However, the effects of biodegradable polylactic acid (PLA) plastics on meadow soils remain underexplored. This study investigates the impacts of PLA microplastics of varying particle sizes and concentrations on soil physicochemical properties, enzyme activities, and microbial communities through a 60-day incubation experiment. PLA-MPs increased the pH, soil organic matter (SOM), total nitrogen (TN) and available potassium (AK) content, as well as enhanced the activities of superoxide dismutase (S-SOD), peroxidase (S-POD), soil catalase (S-CAT), β-glucosidase(S-β-GC) and urease (S-UE) activities. Conversely, a decrease in alkaline phosphatase (S-ALP) activity was observed. The influence of PLA-MPs on soil physicochemical properties was more pronounced with larger particle sizes, whereas smaller particles had a greater effect on enzyme activities. Additionally, PLA-MPs led to an increase in the abundance of Acidobacteriota, Chloroflexi, and Gemmatimonadota, while the abundance of Proteobacteria, Actinobacteriota, and Patescibacteria declined. Mental test analysis indicated that pH, AK, S-UE, and S-β-GC are the primary factors influencing microbial community composition. Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt2) analysis demonstrated that PLA-MPs modify bacterial metabolic pathways. Our results suggest that particle size and concentration of PLA-MPs differentially affect soil nutrients and microbial community structure and function, with more significant effects observed at larger particle sizes and higher concentrations. Microplastics Enzymatic activity Microbial community Meadow soil Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Highlights 1. Microbial community structure and function are related to PLA-MPs size and dose. 2. pH, AK, S-UE and S-β-GC are the main factors regulating microbial community composition in PLA-MPs-contaminated meadow soil. 3. PLA-MPs lead to an enhanced competitive role for microbial communities. Introduction The low cost, diverse functions, and strong durability of plastic products significantly enhance their production efficiency and quality of life, leading to exponential growth in their production and utilization(Fan et al., 2022 ). However, inadequate mechanisms for the management of plastics and inadequate recycling methods have led to the widespread distribution of plastics in marine and terrestrial ecosystems, and their concentration in soil is significantly higher than in water. The use of agricultural films(Huang et al., 2020 ), fertilization(Fang et al., 2024 ), soil amendment, landfill(Yang et al., 2020 ), incineration and sewage irrigation, and atmospheric deposition has facilitated the infiltration of MPs into the soil, where they decompose into microplastics (MPs) owing to mechanical degradation(Sipe et al., 2022 ), chemical oxidation and hydrolysis(Chen et al., 2021 ), and microbial degradation behavior(He et al., 2023 ; Pleiter et al., 2020 ). MPs are plastic particles with an equivalent diameter of less than 5 mm, primarily consisting of polylactic acid (PLA), polyethylene (PE), polyethylene terephthalate (PET), polyvinyl chloride (PVC), and polystyrene (PS), among others(Anbumani & Kakkar, 2018 ). The concentration of these MPs in farmland soils was as high as 67.5 g·kg − 1 soil or 236,000 particles per kg of soil(Xu, 2020). A study by Fuller and Gautam in 2016 reported that up to 7wt% of MPs had already infiltrated the soil environment(Fuller & Gautam, 2016 ). The accumulation of MPs in soil has a great impact on the function of soil ecosystem and the geochemical cycle of materials, which has become a new global environmental problem. Meadow soil is abundant in organic matter(Ziolkowska et al., 2020 ) and plays a crucial role in supporting agriculture and animal husbandry, making it a significant soil type for food production and security in China. Meadow soil stands out as one of the primary soil types in the Xinjiang Uygur Autonomous Region. Notably, within Xinjiang, a key agricultural hub in China, substantial levels of MPs have been identified in the soil, with mulch film remnants amounting to 502 Kg·hm − 2 (Zhang et al., 2016 ). MPs have been shown to induce alterations in soil structure and physicochemical properties such as soil bulk density, water-stable aggregates, soil configuration, water retention capacity, N2O emissions and pH levels(F. Wang et al., 2024 ; Yu et al., 2024 ). Adding 1.5% (w/w) PLA-MPs to paddy soil significantly increased soil pH and changed soil dissolved carbon and nitrogen content(Zhiyu Zhang et al., 2024 ). polyethylene terephthalate MPs can increase the redox potential of soil(Han et al., 2022 ). PE resulted in a decrease in the proportion of sediment particles, and an increase in the content of nitrate nitrogen and the abundance of MPs-degrading bacteria Paenibacillus in the soil of legume farms(La et al., 2024 ). The effects of PP and PE on soil pH value were different(W. Zhou et al., 2023 ). 3% PET-treated forest soil had an eight-fold increase in soil respiration(Ng et al., 2021 ). The treatment of PS and polyphenylene sulfide MPs can reduce the sulfur mineralization in black soil and paddy soil, and increase the sulfur mineralization in meadow soil(Dong et al., 2024 ). PE reduced the microbial available organic carbon content by 18.9%, CO 2 and N 2 O emissions by 26.5%-33.9% and 35.4%-39.7%, respectively(H. Yu et al., 2021 ). Understanding the effects of MPs on physicochemical and biochemical properties and shifts in microbial communities within meadow soils is imperative for sustaining agricultural productivity. Currently, there is a substantial body of research focusing on the impacts of MPs in soil; however, studies specifically addressing their effects within meadow soil environments remain scarce. Soil microbial communities play a crucial role in the functioning of soil ecosystems and are involved in numerous chemical processes. The presence of MPs is associated with modifications in soil pH, moisture retention, and nutrient availability, leading to shifts in microbial community dynamics(J. Ma et al., 2023 ). This disruption of the soil environment can hinder microbial activities essential for organic matter decomposition and nutrient cycling. In addition, MPs contain a diverse array of organic chemicals that can instigate oxidative stress responses in microbial cells through various biochemical pathways, ultimately impacting microbial vitality and diversity (Schöpfer et al., 2022 ). The toxicological effects of these contaminants have been shown to induce physiological stress, inhibit growth, and disrupt community interactions among soil microbes, thereby reshaping community structures(Qi et al., 2024 ). Additionally, the high carbon content of MPs is a hidden carbon source that affects the level of bioavailable carbon in the soil and has a large specific surface area, thus acting as a carbon source and carrier for bacteria, which can alter the structure and function of soil microbial communities and affect geochemical cycling(Ingraffia et al., 2021 ; Seeley et al., 2020 ; Shi et al., 2022 ). PLA-MPs have a greater effect on the composition of microbial community than PE(L. Li et al., 2024 ). Soil microbial community composition of 1% and 5% LDPE treatments differed from that of CK and after 30 days Actinobacteria phylum replaced Ascomycetes phylum as the dominant phylum in 5% LDPE-treated soil(Ren et al., 2020 ). Despite the documented impacts of other types of MPs on microbial communities, the response of soil microbial communities to PLA-MPs remains under-explored. Given the increasing prevalence of biodegradable plastics like PLA in agricultural practices and their potential long-term environmental consequences, understanding the relationship between PLA-MPs, meadow soil properties, and microbial community structures is of paramount importance. Further research in this area may elucidate the mechanisms through which PLA-MPs interact with soil microbial communities, ultimately contributing to our understanding of the ecological implications of plastic pollution in terrestrial ecosystems. In the present study, we investigated the effects of varying concentrations and particle sizes of PLA-MPs on the physicochemical properties and enzymatic activities of meadow soils through a 60-day incubation experiment. The 16S rRNA sequencing technique was used to assess how different concentrations and particle sizes of PLA-MPs influence the microbial community structure within meadow soils. This study aimed to elucidate the interrelationships between physicochemical properties, enzyme activities, and microbial communities in meadow soils exposed to microplastic contamination, as well as to identify successional patterns of key functional microbial groups. Ultimately, this research seeks to assist agricultural producers in predicting potential impacts arising from PLA-MP contamination, while providing a theoretical framework for informed decision-making. Materials and methods Materials Soil samples collected in Ili Kazakh Autonomous Prefecture (81°3′15.008″E,43°55′33.334″N), Xinjiang Uygur Autonomous Region, in October 2023. The soil type was meadow soil and the sampling area was not film mulched. Soil samples were transported to the laboratory and air-dried at room temperature. After removal of stones and plant residues, the naturally air-dried soil samples were sieved through a 200-mesh sieve and mixed thoroughly for subsequent incubation experiments. The basic physical and chemical properties of the soil samples are shown in Table 1 . Table 1 Basic chemical properties of the soi Parameter Mean pH 8.76 SOM 25.42 g·kg − 1 TN 1.60 g·kg − 1 P 30.42 g·kg − 1 K 73.28 mg·kg − 1 The test PLA-MPs were bought from Mingyuxing Plastic Material Co., Ltd. (Guangdong, Chian), with particle sizes of 50 mesh and 100 mesh, respectively, and were washed and dried at 30℃. Table 1 Basic chemical properties of the soil Parameter Mean pH 8.76 SOM 25.42 g·kg-1 TN 1.60 g·kg-1 P 30.42 g·kg-1 K 73.28 mg·kg-1 Incubation experiment First, air-dried and sieved through a 200 mesh sieve was placed in a 18×16×17 cm pot, and PLA-MPs were mixed with the pre-incubated soil to obtain the following treatments: i) CK: 1 kg meadow soil with no PLA-MPs added; ii) J465: 2% (20 g:980 g, w:w) 50 mesh PLA-MPs added; iii) J490: 2% (20 g:980 g, w:w) 100 mesh PLA-MPs added; iv) L465: 7% (70 g:930 g, w:w) 50 mesh PLA-MPs added; v) L490: 7% (70 g:930 g, w:w) 100 mesh PLA-MPs added. Each pot had a total mass of 1 kg and was watered with 200 mL of water every 3 days. The samples were incubated naturally indoors for 60 days at an average daily light duration of 10 h, room temperature of 25–28°C and air humidity of 30–40%. Samples were collected on days 7, 15, 30, 45 and 60, respectively, and one sample was collected on day 60 for microbial community assay, and one sample was uniformly stored with other samples in a refrigerator at -80°C for physicochemical property and enzyme activity assay. Soil physicochemical properties and enzyme activity analysis The collected soil samples were naturally air-dried and sieved through a 200-mesh sieve, and the pH was determined at a ratio of 5:1 (water/soil, v/v). The P concentration, Total N, available K, and organic matter were determined according to our previous research method(Liu et al., 2021 ; Xiao et al., 2023 ). soil alkaline phosphatase (S-ALP), soil β-glucosidase(S-β-GC), soil urease (S-UE), soil superoxide dismutase (S-SOD), soil peroxidase (S-POD) and soil catalase (S-CAT) activities were determined by the kit according to the instructions. The kit was purchased from Beijing Solaibao Technology Co., LTD., and the kit was operated according to the instructions (Invitrogen, Thermo Fisher Scientific, Oregon, USA). DNA extraction and Illumina sequencing DNA extraction and Illumina sequencing The DNA was extracted according to the instructions of the TGuide S96 Magnetic Soil /Stool DNA Kit (Tiangen Biotech (Beijing) Co., Ltd.). Qubit dsDNA HS Assay Kit and Qubit 4.0 Fluorometer were used to measure DNA concentration. The primers 338F: 5'- ACTCCTACGGGAGGCAGCA-3' and 806R: 5'-GGACTACHVGGGTWTCTAAT-3' were utilized to amplify the bacterial 16S rRNA gene from V3-V4 region. The PCR procedure commenced with an initial denaturation at 95°C for 5 minutes, subsequently followed by 25 cycles consisting of denaturation at 95°C for 30 seconds, annealing at 50°C for 30 seconds, and extension at 72°C for 40 seconds. The protocol concluded with a final extension step at 72°C for 7 minutes. The total PCR amplicons were purified using Agencourt AMPure XP Beads (Beckman Coulter, Indianapolis, IN) and quantified with the Qubit dsDNA HS Assay Kit in conjunction with the Qubit 4.0 Fluorometer (Invitrogen, Thermo Fisher Scientific, Oregon, USA). Following individual quantification, the amplicons were pooled in equal quantities. The constructed library was subsequently sequenced utilizing the Illumina NovaSeq 6000 platform (Illumina, Santiago, CA, USA). The raw sequence read data were submitted to the NCBI Sequence Read Archive (SRA) database (PRJNA1163276). Molecular ecological network construction and characterization The network construction method based on Random Matrix Theory (RMT) was utilized to identify Hub and Connector operational taxonomic units (OTUs), employing a similar threshold of 0.94 to ascertain the topological properties(François et al., 2021 ). Several characteristics of the network were measured, including average degree, average path length, average clustering coefficient, and modularity index. The network modules were generated using a fast greedy modularity optimization approach. The network graphical visualization is consistent with previous research reports(Xiao et al., 2024 ). Statistical analysis Data were analyzed statistically using SPSS 25.0, and all data were expressed as mean ± standard deviation (SD) with at least three replicates per treatment. One-way analysis of variance (ANOVA) was used to determine significant differences in parameter differences at the 5% level according to the Tukey’s test. Different upper- and lower-case letters in the pictures and tables indicate significant differences. Details of the bioinformatics analysis are reported in our previous study(Xiao et al., 2024 ). Alpha diversity was calculated and displayed by QIIME2 and R software. Beta diversity was analyzed using QIIME assay and principal coordinate analysis (PCoA) to evaluate the degree of similarity of microbial communities in different samples. Linear Discriminant Analysis (LDA) effect size (LEfSe) was used to test the significant taxonomic difference among group(Segata et al., 2011 ). Mantel and Spearman tests using the R package “vegan”. Mantel-test reveals the association between microbial communities and environmental factors. Result Soil physicochemical properties Soil physicochemical properties, including pH, SOM, TN, P, and AK concentrations, are presented in Fig. 1 a-e. Compared to the control group (CK,7.70), the pH values increased in the L465 (7.95), L490 (8.04), J465 (8.15), and J490 (8.09) treatments by3.25%,4.46%,5.89%, and5.15%, respectively (Fig. 1 a). SOM measurements taken at different time points indicated an increase of 12.41%-50.83% on day 7, 10.65%-58.51% on day 15, 5.70%-54.14% on day 30, 18.38%-73.65% on day 45, and 32.04%-88.84% compared to CK (Fig. 1 b). Over the 60-day period, the SOM showed a decrease of 14.67% in the CK treatment and 6.06% in the J465 treatment, while the L465, L490, and J490 treatments exhibited increases of 7.20%, 18.37%, and 32.76%, respectively (Fig. 1 b). TN contents in the L465, L490, and J465 treatments significantly increased by 23.39%, 18.32%, and 30.41%, respectively, compared to CK (Fig. 1 c). In comparison to CK (30.71 g·kg⁻¹), the J465 treatment (33.03 g·kg⁻¹) resulted in a 7.53% increase in soil P concentration, while no significant effects were observed from the other treatments (Fig. 1 d). Relative to CK (75.24 mg·kg⁻¹), all treatments significantly elevated soil AK content by 7.77% in L465 (81.08 mg·kg⁻¹), 8.49% in L490 (81.63 mg·kg⁻¹), 12.71% in J465 (84.80 mg·kg⁻¹), and 14.06% in J490 (85.82 mg·kg⁻¹) (Fig. 1 e). Soil enzyme activities Additionally, soil enzyme activities, including S-SOD, S-POD, S-CAT, ALP, S-β-GC, S-UE are presented in Fig. 2 a–f. The incorporation of PLA-MPs had variable effects on soil enzyme activities compared to CK. Specifically, L465 (85.44 U·g − 1 ), L490 (93.36 U·g − 1 ), J465 (84.40 U·g − 1 ) and J490 (78.72 U·g − 1 ) resulted in significant enhancements of S-SOD activity by 67.85%, 83.42%, 65.82% and 54.65%, respectively, compared to CK (50.90 U·g − 1 ) (Fig. 2 a). Moreover, L465 (8566.00 U·g − 1 ), J490 (7219.06 U·g − 1 ) and J465 (7829.66 U·g − 1 ) significantly increased S-POD activity by 47.78%, 24.55% and 35.08%, respectively, compared to CK (5796.33 U·g − 1 ) (Fig. 2 b). The application of L465 (929.08 U·g − 1 ), J465 (804.68 U·g − 1 ) and J490 (806.36 U·g − 1 ) resulted in substantial increases in S-CAT activity by 53.75%, 33.16% and 33.44%, respectively, compared to CK (604.30 U·g − 1 ) (Fig. 2 c). In contrast, ALP activity decreased by 13.67% and 22.07% in the J465 (2235.38 U·g − 1 ) and J490 (2017.71 U·g − 1 ), compared to CK (2589.25 U·g − 1 ) (Fig. 2 d). The S-β-GC activity was elevated by 53.61% in J465 (2.35 U·g − 1 ) compared to CK (1.53 U·g − 1 ) (Fig. 2 e). Finally, L465 (153.98 U·g − 1 ), J465 (214.53 U·g − 1 ) and J490 (206.18 U·g − 1 ) significantly enhanced S-UE activity by 51.69%, 111.33% and 103.12%, respectively, in comparison to CK (604.30 U·g − 1 ) (Fig. 2 f). Structure, diversity, and compositions of soil bacterial communities Bacterial communities were detected by 16S rRNA sequencing, and the alpha diversity is presented in Table 2 . The Chao and ACE indices indicated that the PLA-MPs increased microbial abundance, with the J465 exhibiting the highest number of microbial species. Additionally, the Shannon index showed that J465, J490, L465, and L490 had higher values than the CK, indicating that PLA-MPs contribute to greater complexity in the diversity of soil microorganisms. In contrast, the Simpson index revealed that the microbial community structure in the J465 and J490 was more homogeneous. Overall, microbial community diversity was significantly greater in the PLA-MPs treatments compared to CK, particularly in J465. The Venn diagram illustrated that the number of shared operational taxonomic units (OTUs) among CK, J465, J490, L465, and L490 was 680, with unique OTUs number was 4244, 5702, 5016, 4336, and 4666, respectively (Fig. 3 a). Based on Bray-Curtis distance, principal coordinate analysis (PCoA) was performed on the microbial communities from meadow soil under different treatments. The analysis indicated that the contributions of the Pc1 and Pc2 to microbial diversity were 8.89% and 7.94%, respectively, yielding a cumulative contribution rate of 16.63%. Inter-group difference analysis revealed significant disparities in the soil microbial community, while intra-group differences remained relatively small (Fig. 3 b). In total, 41 phyla, 659 families, 1159 genera, and 27,468 OTUs were identified. The community composition varied with the particle size and concentration of PLA-MPs. At the phylum level (Fig. 3 c, Tab. S1), the dominant phyla (relative abundance > 1%) included Proteobacteria (29.03–32.54%), Acidobacteriota (15.84–21.36%), Chloroflexi (10.29–11.1%), Actinobacteriota (4.65–10.02%), Gemmatimonadota (6.43–8.77%), Patescibacteria (1.64–6.08%), Myxococcota (1.57–2.53%), and unclassified_Bacteria (3.47–5.21%). Compared to CK, PLA-MPs resulted in a decrease in Proteobacteria, Actinobacteriota, and Patescibacteria at the phylum level, while Acidobacteriota, Chloroflexi, Gemmatimonadota, unclassified_Bacteria, and Bdellovibrionota increased; Bacteroidota showed no significant change. At genus level (Fig. 3 d, Tab. S2), the dominant genera (relative abundance > 1%) included Pseudomonas (0.64–6.43%), Vicinamibacterales (4.15–5.57%), Gemmatimonadacea (3.78–5.58%), Sphingomonas (2.59–3.68%), unclassified_Bacteria (3.45–5.12%), Vicinamibacteraceae (3.84–3.74%), Lysobacter (2.11–2.88%), Chloroflexi (1.81–2.47%), uncultured_soil_bacterium (2.05–2.35%) and Blastocatellaceae (1.77–2.39%). In comparison to CK, PLA-MPs led to a decrease in the abundance of Pseudomonas , Sphingomonas , Chloroflexi at the genus level, while increases were observed in Vicinamibacterales , Gemmatimonadaceae , unclassified_Bacteria . Vicinamibacteraceae , Lysobacter , and Blastocatellaceae . This study performed a LEfSe of microbial communities in meadow soil to investigate the effects of PLA-MPs at different concentrations and particle sizes on soil microbial communities, from the phylum to species level (Fig. 3 e). A total of 12 biomarkers were identified across seven levels of microbial community analysis under CK and varying concentrations of PLA-MPs. Specifically, there were 2 biomarkers at the species level, 2 at the genus level, 4 at the family level, 4 at the order level, 8 at the class level, 6 at the phylum level, and 1 at the kingdom level. Compared to the CK group, which had 14 markers, significant differences were observed in the microbial communities of meadow soil treated with various concentrations of PLA-MPs, particularly a marked reduction in the number of biological markers. The biological markers identified for L465, L490, J465, and J490 were 2, 2, 1 and 8. The biological markers identified for the L465, L490, J465, and J490 treatments were 2, 2, 1, and 8, respectively. In the CK group, the microbial species of the classes Actinobacteria, Saccharimonadia, and Gammaproteobacteria were relatively abundant, while Alphaproteobacteria was enriched in J465, Anaerolineae and Vicinamibacteria were enriched in J490, and Acidimicrobiia was enriched in L490 (Fig. S1 ). Table 2 Effects of PLA-MPs on the alpha diversity of bacterial communities Group Chao ACE Shannon Simpson CK 2587.84 ± 126.48 c 2616.30 ± 127.82 c 9.4942 ± 0.0405 c 0.9940 ± 0.0001 c L465 2731.49 ± 91.34 bc 2755.56 ± 93.03 bc 9.8888 ± 0.0197 b 0.9970 ± 0.0001 b L490 2814.90 ± 181.38 abc 2837.57 ± 183.19 abc 9.9053 ± 0.0531 b 0.9970 ± 0.0001 J465 3137.05 ± 150.84 a 3161.67 ± 151.86 a 10.163 ± 0.0700 a 0.9982 ± 0.0001 a J490 2964.47 ± 69.10 ab 2989.33 ± 67.06 ab 10.1296 ± 0.0227 a 0.9982 ± 0.0001 a Bacterial co-occurrence network changes in the presence of PLA-MPs Based on 16S rRNA sequencing data from the five groups, five co-occurrence networks were constructed (Fig. 4 a-e). The main topological properties of the five groups of microbial communities of the molecular ecological networks are shown in Table S3. In the case where all nodes were set to 500, the CK group had more links (1351) and a higher percentage of positive links (56.92%) compared to the J465 (1289; 53.06%), J490 (1333; 52.5%), L465 (1301; 52.57%), and L490 (1325; 54.04%). This indicates that the interactions among microbial communities in meadow soil can be disrupted by PLA-MPs. PLA-MPs alter the abundance of various components of microbial communities in meadow soil, whereby different concentrations of PLA-MPs can lead to varying degrees of enrichment or suppression of specific microbial species. Comparisons between the J465 and J490 groups, as well as between the L465 and L490 groups, reflect a positive correlation between grain size and the concentration of PLA-MPs and their detrimental effects on microbial community interactions. Correlations of soil microbial communities and environmental factor The correlation of soil physicochemical properties and enzyme activities with microbial communities was analyzed using multivariate statistical analysis. Acidobacteriota, Actinobacteriota, Gemmatimonadota and Chloroflexi exhibited significant positive correlations with pH, AK, S-UE and S-ALP. These findings indicate that their abundance is closely linked to improved soil conditions, particularly with respect to physicochemical properties. Proteobacteria presented a notable positive correlation with S-β-GC, suggesting a potential relationship between this microbial phylum and carbohydrate availability in the soil. None of the negative correlations between the abundance of these phylum-level microorganisms and SOM, TN, and P were statistically significant, suggesting that these characteristics have limited effects on the abundance of this microbial phylum. Additionally, a correlation was established between soil physical and chemical properties and enzyme activities, with positive correlations noted between pH and TN, P, AK, S-UE and S-β-GC and negative correlations with S-ALP. SOM was positively correlated with S-SOD, S-POD, while AK positively correlated with S-UE and S-GC but negatively correlated with S-ALP. These findings emphasize that soil physicochemical properties and enzyme activities significantly influence the distribution and richness of various microbial communities, particularly Acidobacteriota, Actinobacteriota, Chloroflexi, and Gemmatimonadota. In contrast, Bacteroidota and Proteobacteria exhibited either negative or non-significant correlations with these soil parameters, indicating differentiated ecological niches or adaptive strategies. These insights underscore the importance of soil conditions in shaping microbial community structures and their potential implications for soil health and ecosystem functioning. Analysis of predictive metabolic functions A total of 6 KEGG primary metabolic pathways and 47 secondary metabolic pathways were identified based on the functional prediction of PICRUSt2 amplicon data. The major metabolic functions were characterized by the following percentages: cellular (6.36%-6.54%), environmental information processing (2.33–2.42%), genetic information processing (9.96–10.30%), human diseases (4.93–5.06%), metabolism (73.32–73.71%), organismal Systems (2.37–2.44%) (Tab. S4). The effects of varying particle sizes and concentrations of PLA-MPs on soil metabolic functions are summarized in Table 3 . Treatments L465, J465, and J490 reduced the functions of glycolysis, gluconeogenesis, and the pentose phosphate pathway, while the functions of pentose and glucuronate interconversions, oxidative phosphorylation, and photosynthesis significantly increased. PLA-MPs also differentially affected the degradation functions of chlorocyclohexane, chlorobenzene, benzoate, and bisphenol. Table 3 Results of the effects of PLA-MPs on soil metabolic functions Metabolic pathway CK L465 L490 J465 J490 Glycolysis / Gluconeogenesis 8.25E-03 ± 1.08E-05 a 8.11E-03 ± 1.65E-05 b 8.23E-03 ± 5.75E-06 a 8.12E-03 ± 1.88E-05 b 8.15E-03 ± 3.05E-05 b Pentose phosphate pathway 6.77E-03 ± 5.04E-06 a 6.62E-03 ± 8.54E-06 c 6.72E-03 ± 1.10E-05 ab 6.66E-03 ± 2.93E-05 bc 6.65E-03 ± 5.23E-05 bc Pentose and glucuronate interconversions 2.30E-03 ± 5.43E-06 b 2.41E-03 ± 1.71E-05 a 2.40E-03 ± 2.04E-05 a 2.47E-03 ± 2.00E-05 a 2.44E-03 ± 4.99E-05 a Oxidative phosphorylation 5.94E-03 ± 1.99E-06 c 5.87E-03 ± 1.64E-05 d 6.04E-03 ± 9.60E-06 b 6.05E-03 ± 1.18E-05 b 6.22E-03 ± 1.63E-05 a Photosynthesis 4.29E-03 ± 8.37E-06 c 4.22E-03 ± 3.04E-05 d 4.35E-03 ± 5.91E-06 b 4.36E-03 ± 2.02E-05 b 4.48E-03 ± 2.84E-06 a Chlorocyclohexane and chlorobenzene degradation 1.83E-03 ± 1.35E-05 b 1.93E-03 ± 2.31E-05 a 1.81E-03 ± 1.66E-05 b 1.80E-03 ± 2.72E-05 b 1.73E-03 ± 2.18E-05 c Benzoate degradation 3.08E-03 ± 5.81E-06 b 3.30E-03 ± 2.98E-05 a 3.05E-03 ± 1.41E-05 b 3.07E-03 ± 4.20E-05 b 2.89E-03 ± 3.40E-05 c Bisphenol degradation 3.52E-04 ± 2.12E-05 a 3.61E-04 ± 3.74E-05 a 3.83E-04 ± 2.08E-05 a 2.30E-04 ± 3.24E-05 b 2.44E-04 ± 2.09E-05 b Discussion Effects of PLA-MPs on soil physicochemical Properties Soil pH increased in all treatments (L465, L490, J465, J490) compared to the CK, suggesting that PLA-MPs may have contributed to increased soil alkalinity (Fig. 1 a). This finding contrasts with previous results indicating that PE can lower the pH of meadow soil. For instance, a study found that 0.2% PE decreased pH in acidic soil while increasing it in alkaline soil (Li et al., 2021 ). The selective adsorption of microplastics to soil particles can affect cation exchange capacity, ultimately influencing soil pH (F. Wang et al., 2022 ). Theoretically, biodegradable microplastics could generate organic acids (e.g., 3-hydroxybutyric acid) that lower soil pH (Yuan et al., 2023 ). However, PLA-MPs treatment led to an increase in soil pH, possibly due to microbial biogeochemical processes (Hou et al., 2021 ). This effect may be related to the type of plastic used. Multiple factors, including soil type, microplastic concentration, and particle size, determine whether soil pH increases, decreases, or remains stable (Liu et al., 2023 ; Song et al., 2023 ; Xu et al., 2024 ). The increase in pH may stem from the aging, degradation, and decomposition of PLA-MPs in the soil, where the resultant carbon dioxide and water do not diffuse into the atmosphere (H. Li et al., 2024 ). Instead, they combine with organic matter and are absorbed by plants, ultimately resulting in reduced acid emissions and increased Ph (Yan et al., 2024 ). Furthermore, an increase in pH may enhance the solubility of specific nutrients (Chang et al., 2023 ). PLA-MPs are carbon-rich and serve as an important source of carbon in soil (Rillig & Lehmann, 2020 ). Moreover, substantial increases in SOM across various treatment intervals suggest a potential enhancement of soil health and carbon sequestration capabilities driven by PLA-MPs. Smaller biodegradable microplastics degrade more readily and release carbon into the soil (Li et al., 2022 ). The degradation intermediates of microplastics are often not easily utilized by microorganisms as growth substrates, which ultimately leads to increased SOM content (Meng et al., 2023 ). This is further supported by results indicating that SOM content was higher in the 100 mesh PLA-MPs treatment than in the 50 mesh treatment (Fig. 2 b). The varying rates of SOM accumulation over time underscore the time-dependent responsiveness of soil organic content to the incorporation of PLA-MPs, revealing their potential to stimulate microbial activity and stabilize organic matter. The microbial stimulation induced by PLA-MPs may also regulate organic carbon cycling by enhancing microbial metabolic efficiency or shaping microbial communities (Y. Li et al., 2024 ; Liu et al., 2017 ). The content and bioavailability of N, P and K are critical determinants of soil fertility. TN contents were significantly elevated in all PLA-MP treatments, with the J465 treatment yielding the highest increase (Fig. 2 c). Studies have reported that microplastics increase total soil nitrogen content and mineralization rates (H. Zhang et al., 2024 ), which aligns with our findings. The decomposition of polylactic acid microplastics, which serve as a potential carbon source, increases the release of chitinase and leucine aminopeptidase while enhancing mineral nitrogen content, which promotes nitrification and denitrification processes (J. Zhou et al., 2023 ). However, other research suggests that microplastics can lead to soil nitrogen loss by altering the abundance and function of nitrosative and ammonia-oxidizing bacteria, such as Chloroflexi, subsequently promoting denitrification reactions and reducing NO 3 − -N concentrations (Li et al., 2022 ; Q. Wang et al., 2022 ). PLA-MPs reduced the abundance of nitrifying bacteria, such as Nitrosira and Ellin6067 , resulting in N depletion (Q. Wang et al., 2022 ). The impact of microplastics on soil nitrogen content is influenced not only by concentration but also by the nature of the substances involved (H. Zhang et al., 2024 ). The slight increase in phosphorus content, particularly in J465, further supports the notion that PLA-MPs can enhance nutrient availability, although not all treatments exhibited significant changes (Fig. 2 d). AK contents similarly increased across all treatments, suggesting enhanced soil fertility (Fig. 2 e). MPs can also influence P and K contents by altering the relative abundance of Firmicutes associated with P and K cycling (Cui et al., 2018 ). This enhancement may stem from changes in microbial composition, biomass accumulation, enzyme activity, and the abundance of genes associated with the N, P, and K cycles that elevate soil nutrient content (Tang et al., 2024 ). Effects of PLA-MPs on soil enzyme activities The analysis of enzyme activities underscores the role of PLA-MPs in stimulating soil biochemical processes. Notably, the significant enhancement of S-SOD, S-PO, and S-CAT activities in response to PLA-MP applications indicates an adaptive microbial response to oxidative stress (Fig. 2 a-c). Huang et al. reported a dramatic increase in catalase activity in soils amended with microplastics, rising by 149% and 139% on the 30th and 90th days, respectively (Huang et al., 2019b ). Moreover, soil catalase activity significantly increased with the content of PVC-MPs, demonstrating increases of 79.17–158.33% compared to untreated soil (Zhang et al., 2023 ). In addition, we observed activities of S-ALP, S-β-GC and S-UE activity. Interestingly, the reduction in S-ALP activity was noted in the J465 and J490 treatments, whereas it remained unchanged in the L465 and L490 treatments, suggesting that the particle size of PLA-MPs may influence S-ALP activity (Fig. 2 d). S-ALP is crucial for the mineralization of organic phosphorus, and a decrease in ALP activity can subsequently diminish available phosphorus (Xu et al., 2022 ). Notably, while PLA-MPs decreased ALP activity in the J465 and J490 treatments, an increase in phosphorus content was observed in the J465 treatment. This discrepancy may be attributed to decreased effective phosphorus content and the inability of microorganisms to effectively uptake phosphorus. Furthermore, only the J465 treatment resulted in elevated S-β-GC activity in soil (Fig. 2 e). Oladele et al. found that 2 and 4% w/w PS-MPs resulted in decreased S-ALP activity coupled with increased S-β-GC activity(Oladele et al., 2023 ). Elevated S-UE activity in the PLA-MP treatments indicates enhanced nitrogen cycling capacity, and this is further supported by elevated TN content in the soil physicochemical analyses. Previous studies have indicated that low-density polyethylene increases S-UE and S-CAT activities in soil (Huang et al., 2019a ). Conversely, it was reported that polyhydroxyalkanoates decreased both S-β-GC and S-UE activities(Guo et al., 2024 ), a finding that contrasts with our results and may be attributed to differing types of microplastics. Additionally, PVC degradation can adsorb and accumulate toxic substances such as lead, which may reduce S-β-GC activity (Zang et al., 2020 ). Thus, the decrease in soil enzyme activity may not solely result from the introduction of microplastics, but could also stem from harmful substances absorbed by the microplastics in the soil. Effects of PLA-MPs on soil bacterial community diversity and structure Soil microorganisms play a pivotal role in nutrient geochemical cycling. Findings from 16S rRNA sequencing elucidate the profound impact of PLA-MPs on the diversity and composition of soil microbial communities. The changes induced by microplastics in soil spatial heterogeneity may contribute to alterations in the structure of bacterial communities. Our results indicate that PLA-MPs enhanced both the biodiversity and structural homogeneity of soil bacteria, implying that PLA-MPs facilitate greater ecological complexity. Venn diagram analysis and PCoA highlight distinct differences in community structure between PLA-MP treatments and control groups, reflecting shifts in microbial relationships. Numerous studies have demonstrated the positive effects of microplastics on microbial communities (Li et al., 2022 ; R. Ma et al., 2023 ; Shang et al., 2024 ; Zekun Zhang et al., 2024 ). PLA-MPs, formed through lactic acid polymerization, yield degradation products that can be utilized as exogenous carbon by microorganisms, thereby altering microbial community dynamics. Actinobacteria, Proteobacteria, Acidobacteria, Bacteroidota, and Chloroflexi were the dominant flora in the soil, consistent with previous research findings (Guo et al., 2024 ; Hou et al., 2021 ). Bacterial abundance at the phylum level revealed that disposal of PLA-MPs increased the abundance of Myxococcota, Bdellovibrionota, Chloroflexi, and Gemmatimonadota. Smaller-sized biodegradable microplastics are known to enhance the abundance of stress-tolerant bacteria (Liu et al., 2024 ). The increased abundance of Myxococcota and Bdellovibrionota reflects their adaptive responses to environmental changes induced by PLA-MP pollution. Myxococcota are instrumental in decomposing organic matter, thus increasing soil nutrient levels, and they significantly influence microbial community structure and nutrient cycling (Colette et al., 2023 ). Bdellovibrionota contribute positively to microbial diversity and stability. Chloroflexi are among the primary bacteria involved in the soil carbon cycle, impacting soil nutrients and aiding in the stabilization of carbon in SOM (Bovio-Winkler et al., 2023 ; Diao et al., 2022 ). Although there are fewer reports concerning Gemmatimonadota, evidence suggests a positive correlation with SOM, nitrogen, and potassium, along with a greater resilience to adverse conditions (Deng et al., 2019 ). Additionally, several bacterial groups exhibited reduced abundance under PLA-MP treatment, including Proteobacteria, Actinobacteriota, and Patescibacteria. Microplastics induce oxidative stress in certain bacteria, disrupting cell membrane integrity, which may lead to a decrease in their abundance. Biodegradable microplastics are more prone to release harmful substances into the soil, causing biotoxicity(Liu et al., 2024 ). The relatively low resilience of Proteobacteria, Actinobacteriota, and Patescibacteria may further contribute to their decline in abundance. Proteobacteria require abundant nutrients for growth (Zhang et al., 2021 ), and have historically occupied a dominant position in contaminated soils. Certain members, such as Burkholderiaceae (Li et al., 2023 ), Bradyrhizobiaceae (S. Wang et al., 2024 ) etc. participate in nitrogen fixation and carbon cycling (Feng et al., 2022 ). Several studies have indicated that Proteobacteria positively correlate with SOM and TN(F. Yu et al., 2021 ). In our research, we identified a significant positive correlation between Proteobacteria and S-β-GC, potentially linked to carbohydrates present in the soil, reinforcing the notion that Proteobacteria are involved in the carbon cycle. Co-occurrence networks have gained prominence in characterizing the effects of environmental factors on soil microbial communities (Hou, 2019). Five co-occurrence networks constructed in this study investigated the influence of PLA-MPs of varying concentrations and particle sizes on microbial community interactions. Compared with the control, PLA-MPs treatment diminished both the positive correlation among soil microbial communities and the overall complexity of these communities (Fig. 4 ). This suggests that PLA-MPs adversely impact positive interactions between microbial communities. In other words, variations in concentrations and particle sizes of PLA-MPs have differential effects on microbial communities, resulting in either the enrichment or loosening of specific bacterial populations (Fang et al., 2024 ). The observed decline in positively correlated links indicates an intensified competitive relationship and weakened synergistic interactions between bacteria. Changes in bacterial abundance at key nodes may ultimately compromise the overall functional capacity of the microbial community, thereby affecting soil health and nutrient cycling. Relationship between soil environmental factors and bacterial communities at the dominant phylum level The relationship between soil environmental factors and dominant phylum-level bacterial communities was elucidated through a mental test analysis. Positive correlations between Acidobacteriota, Actinobacteriota, Gemmatimonadota, and Chloroflexi and soil parameters such as pH, AK, S-UE, and S-ALP indicate that the growth and activity of these microbial communities are closely tied to soil nutrient enhancement. Furthermore, Proteobacteria exhibited a significant positive correlation with S-β-GC, suggesting its potential importance in the degradation of organic substrates, which leads to the release of monosaccharides that can serve as an energy source for various soil microorganisms. The correlations between soil physical and chemical properties and enzyme activities further emphasize the functional roles of these microbial communities within soil ecosystems. The significant positive correlation between SOM and S-SOD and S-POD activities may indicate that SOM aids in mitigating oxidative stress in the soil environment. Notably, soil pH positively correlated with the activities of enzymes such as S-UE and S-β-GC, which might enhance the abundance of associated microbial communities. Effects of PLA-MPs on bacterial community functions Changes in the structure of soil microbial communities have substantial effects on the metabolic functions of these communities. The results of the KEGG annotation indicate that the functions of pentose and glucuronate interconversions, oxidative phosphorylation, and photosynthesis were significantly increased, while the functions of glycolysis, gluconeogenesis, and the pentose phosphate pathway were reduced. These findings suggest that PLA-MPs disrupt the Embden-Meyerhof-Parnas (EMP) pathway and the hexose monophosphate pathway (HMP), while enhancing the pentose phosphate pathway. These pathways are critical for carbohydrate metabolism and energy production (Morelli & Scholkmann, 2024 ), indicating that PLA-MPs may hinder essential metabolic processes crucial for microbial growth and function. The disruption of EMP and HMP leads to reduced energy availability for the microbial community (Ni et al., 2023 ). Conversely, the significant increases in the activities of the pentose and glucuronate interconversions, oxidative phosphorylation, and photosynthesis pathways suggest a compensatory adaptation by microbial communities. The enhancement of the pentose and glucuronate interconversion pathway signifies a shift towards alternative carbon metabolism (Riaz et al., 2024 ), reflecting the microbial community's efforts to utilize available substrates more effectively in the presence of PLA-MPs. Similarly, the increase in oxidative phosphorylation indicates enhanced aerobic respiration, potentially meeting higher energy demands under altered conditions (Ugya et al., 2024 ). T This metabolic shift may bolster microbial resilience against the stress introduced by microplastic contamination, albeit at the potential cost of altered community structure. Additionally, the increased function of photosynthesis in microbial communities residing in microplastic-affected soils may indicate a stabilization mechanism, wherein microbial symbionts or photosynthetic organisms adapt to convert light energy into chemical energy more effectively (X. Li et al., 2024 ), possibly mitigating some negative impacts of PLA-MPs. The interactions between PLA-MPs and the degradation functions of various compounds, such as chlorocyclohexane, chlorobenzene, benzoate, and bisphenol, carry significant implications for bioremediation processes. The ability of microbial communities to adapt their metabolic pathways to degrade these compounds in the presence of microplastics suggests that PLA-MPs could alter biogeochemical cycles, affecting contaminant breakdown dynamics in soils. The effects of varying particle sizes and concentrations of PLA-MPs on microbial metabolic functions illustrate not only a disruption of fundamental metabolic pathways but also an adaptive response from microbial communities. These dynamics underscore the necessity for further research to understand the implications of microplastic contamination in soil ecosystems, particularly regarding how shifts in microbial metabolic functions affect nutrient cycling, pollutant degradation potential, and overall ecological resilience in the face of ongoing environmental changes. Conclusion The effects of different particle sizes and concentrations of PLA-MPs on soil physicochemical properties (SOM, TN, P, AK, and pH), enzyme activities (S-SOD, S-POD, S-CAT, S-ALP, S-GC, and S-UE), and microbial community diversity and structure were investigated through a 60-day incubation experiment. The results demonstrate that PLA-MPs significantly affect soil physicochemical properties and enzyme activities. In terms of soil physicochemical properties, PLA-MPs increased pH and enhanced SOM, TN, and AK contents. Additionally, in regards to soil enzyme activities, PLA-MPs enhanced antioxidant enzymes, increased S-β-GC and S-UE activities, and decreased S-ALP activities. Furthermore, PLA-MPs influenced microbial community diversity and composition, with Proteobacteria, Actinobacteria, Acidobacteria, Bacteroidota, and Chloroflexi predominating at the phylum level. Vicinamibacterales, Gemmatimonadaceae, Sphingomonas, unclassified Bacteria, Vicinamibacteraceae, Lysobacter, and Blastocatellaceae were identified as the main genera. pH, AK, S-UE, and S-β-GC were key factors influencing microbial community composition. PICRUSt2 analysis revealed that PLA-MPs disrupt the pathways of glycolysis and pentose phosphorylation but enhance the pathways of pentose and glucuronate interconversions and oxidative phosphorylation. Overall, larger-sized PLA-MPs exerted a greater effect on soil physicochemical properties, while smaller-sized PLA-MPs had a more significant impact on soil enzyme activities, with higher levels of PLA-MPs being particularly disruptive to microbial community interactions. Consequently, the profound effects of changes in particle size and concentration on meadow soils due to the long-term accumulation of PLA-MPs warrant further investigation to formulate strategies aimed at mitigating plastic pollution in agricultural systems. Declarations Ethical Approval This article does not contain any studies with human participants performed by any of the authors. Consent to Participate This manuscript is approved by all authors for participation. Consent to Publish This manuscript is approved by all authors for publication. Competing Interests The authors have no competing interests to declare. Funding This research was financially supported by the Yili Normal University School Program (2023YSYB011); The Natural Science Foundation of Xinjiang Uygur Autonomous Region (2024D01C197); Basic research expenses of universities in autonomous region (XJEDU2024P067). Author Contribution SML and YQL contributed to the conception and design of this study. Research, material preparation, data collection, and analysis were performed by JHZW, KLW, YKZ, JXZ, XYY, YS and MCL. The first draft of the manuscript was written by SML and KLW. YQL and MCL commented on the previous versions of the manuscript. 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Responses of maize (Zea mays L.) seedlings growth and physiological traits triggered by polyvinyl chloride microplastics is dominated by soil available nitrogen. Ecotoxicology and Environmental Safety, 252 . https://doi.org/10.1016/j.ecoenv.2023.114618 Zhang, X., Li, Y., Ouyang, D., Lei, J., Tan, Q., Xie, L., Li, Z., Liu, T., Xiao, Y., & Farooq, T. H. (2021). Systematical review of interactions between microplastics and microorganisms in the soil environment. Journal of Hazardous Materials, 418 , 126288. https://doi.org/10.1016/j.jhazmat.2021.126288 Zhang, Z., Wang, W., Liu, J., & Wu, H. (2024). Discrepant responses of bacterial community and enzyme activities to conventional and biodegradable microplastics in paddy soil. Science of The Total Environment, 909 (168513). https://doi.org/10.1016/j.scitotenv.2023.168513 Zhang, Z., Zhao, L., Jin, Q., Luo, Q., & He, H. (2024). Combined contamination of microplastic and antibiotic alters the composition of microbial community and metabolism in wheat and maize rhizosphere soil. Journal of Hazardous Materials , 473 . https://doi.org/10.1016/j.jhazmat.2024.134618 Zhou, J., Jia, R., Brown, R. W., Yang, Y., Zeng, Z., Jones, D. L., & Zang, H. (2023). The long-term uncertainty of biodegradable mulch film residues and associated microplastics pollution on plant-soil health. Journal of Hazardous Materials, 442. https://doi.org/10.1016/j.jhazmat.2022.130055 Zhou, W., Wang, Q., Wei, Z., Jiang, J., & Deng, J. (2023). Effects of microplastic type on growth and physiology of soil crops: Implications for farmland yield and food quality. Environmental Pollution, 326. https://doi.org/10.1016/j.envpol.2023.121512 Ziolkowska, A., Debska, B., & Banach-Szott, M. (2020). Transformations of phenolic compounds in meadow soils. Scientific Reports, 10 (1). https://doi.org/10.1038/s41598-020-76316-7 Additional Declarations No competing interests reported. Supplementary Files Supplementarymaterials.docx Cite Share Download PDF Status: Published Journal Publication published 08 Jan, 2025 Read the published version in Environmental Geochemistry and Health → Version 1 posted Editorial decision: Revision requested 18 Dec, 2024 Reviews received at journal 18 Dec, 2024 Reviewers agreed at journal 06 Dec, 2024 Reviews received at journal 29 Nov, 2024 Reviewers agreed at journal 04 Nov, 2024 Reviewers invited by journal 04 Nov, 2024 Editor assigned by journal 03 Nov, 2024 Submission checks completed at journal 01 Nov, 2024 First submitted to journal 31 Oct, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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\u003cstrong\u003e(b)\u003c/strong\u003e Organic matter; \u003cstrong\u003e(c) \u003c/strong\u003eTotal N; \u003cstrong\u003e(d)\u003c/strong\u003e P concentration; \u003cstrong\u003e(e)\u003c/strong\u003e Available K.\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5368532/v1/0e49b049bd42356d3db85d7e.jpg"},{"id":68920857,"identity":"d4a2fd1b-ad7e-4c4f-abd9-a7118ce7ae27","added_by":"auto","created_at":"2024-11-13 13:45:58","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":171388,"visible":true,"origin":"","legend":"\u003cp\u003eSoil enzyme activities of the soil. \u003cstrong\u003e(a)\u003c/strong\u003e Soil SOD; \u003cstrong\u003e(b)\u003c/strong\u003e Soil POD; \u003cstrong\u003e(c) \u003c/strong\u003eSoil CAT; \u003cstrong\u003e(d)\u003c/strong\u003eAlkaline phosphatase activities; \u003cstrong\u003e(e)\u003c/strong\u003e Glucosidase activity; \u003cstrong\u003e(f) \u003c/strong\u003eUrease activity.\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5368532/v1/a4e2ef95aafd3f1d8d3bf63a.jpg"},{"id":68921929,"identity":"f50614c6-adf1-4232-947f-d426ce537845","added_by":"auto","created_at":"2024-11-13 13:53:59","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":573822,"visible":true,"origin":"","legend":"\u003cp\u003eMicrobial community structure, composition and diversity. \u003cstrong\u003e(a) \u003c/strong\u003eVenn plot; \u003cstrong\u003e(b) \u003c/strong\u003ePlots of\u003cstrong\u003e \u003c/strong\u003ePCoA; \u003cstrong\u003e(c)\u003c/strong\u003e Compositions in phylum level; \u003cstrong\u003e(d) \u003c/strong\u003eCompositions in genus level; \u003cstrong\u003e(e) \u003c/strong\u003eLefSe\u003c/p\u003e","description":"","filename":"Picture3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5368532/v1/c977d65be1423bac6bd2862d.jpg"},{"id":68920859,"identity":"7251eaee-5653-40cf-a7ca-f390a61252d1","added_by":"auto","created_at":"2024-11-13 13:45:59","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":575914,"visible":true,"origin":"","legend":"\u003cp\u003eCo-occurrence Networks analysis. \u003cstrong\u003e(a) \u003c/strong\u003eCK; \u003cstrong\u003e(b) \u003c/strong\u003eL465; \u003cstrong\u003e(c)\u003c/strong\u003e L490; \u003cstrong\u003e(d)\u003c/strong\u003eJ465; \u003cstrong\u003e(e) \u003c/strong\u003eJ490\u003c/p\u003e","description":"","filename":"Picture4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5368532/v1/1395ab9137669e02c072fb79.jpg"},{"id":68920855,"identity":"42673105-b834-44f3-930a-b533fe9c507b","added_by":"auto","created_at":"2024-11-13 13:45:58","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":155200,"visible":true,"origin":"","legend":"\u003cp\u003eMental test for soil physicochemical properties, enzymatic activities and microbial communities at the major phylum level\u003c/p\u003e","description":"","filename":"Picture5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5368532/v1/280ae6b3822ee20fc53bd100.jpg"},{"id":73694982,"identity":"3a876ebf-ec9c-4fb9-9fac-3e618ce98da8","added_by":"auto","created_at":"2025-01-13 16:14:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2828173,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5368532/v1/613b368f-3845-4651-89ef-b9c69b43d3ae.pdf"},{"id":68921928,"identity":"01f4980a-3971-476f-8e1a-7b626daffef6","added_by":"auto","created_at":"2024-11-13 13:53:58","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":120515,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-5368532/v1/e77ecb559ba57391de8d0b7b.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Unveiling the impact of biodegradable polylactic acid microplastics on meadow soil health","fulltext":[{"header":"Highlights","content":"\u003cp\u003e1. Microbial community structure and function are related to PLA-MPs size and dose.\u003c/p\u003e\u003cp\u003e2. pH, AK, S-UE and S-β-GC are the main factors regulating microbial community composition in PLA-MPs-contaminated meadow soil.\u003c/p\u003e\u003cp\u003e3. PLA-MPs lead to an enhanced competitive role for microbial communities.\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003eThe low cost, diverse functions, and strong durability of plastic products significantly enhance their production efficiency and quality of life, leading to exponential growth in their production and utilization(Fan et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, inadequate mechanisms for the management of plastics and inadequate recycling methods have led to the widespread distribution of plastics in marine and terrestrial ecosystems, and their concentration in soil is significantly higher than in water. The use of agricultural films(Huang et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), fertilization(Fang et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), soil amendment, landfill(Yang et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), incineration and sewage irrigation, and atmospheric deposition has facilitated the infiltration of MPs into the soil, where they decompose into microplastics (MPs) owing to mechanical degradation(Sipe et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), chemical oxidation and hydrolysis(Chen et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and microbial degradation behavior(He et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Pleiter et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). MPs are plastic particles with an equivalent diameter of less than 5 mm, primarily consisting of polylactic acid (PLA), polyethylene (PE), polyethylene terephthalate (PET), polyvinyl chloride (PVC), and polystyrene (PS), among others(Anbumani \u0026amp; Kakkar, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The concentration of these MPs in farmland soils was as high as 67.5 g\u0026middot;kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e soil or 236,000 particles per kg of soil(Xu, 2020). A study by Fuller and Gautam in 2016 reported that up to 7wt% of MPs had already infiltrated the soil environment(Fuller \u0026amp; Gautam, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The accumulation of MPs in soil has a great impact on the function of soil ecosystem and the geochemical cycle of materials, which has become a new global environmental problem.\u003c/p\u003e \u003cp\u003eMeadow soil is abundant in organic matter(Ziolkowska et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and plays a crucial role in supporting agriculture and animal husbandry, making it a significant soil type for food production and security in China. Meadow soil stands out as one of the primary soil types in the Xinjiang Uygur Autonomous Region. Notably, within Xinjiang, a key agricultural hub in China, substantial levels of MPs have been identified in the soil, with mulch film remnants amounting to 502 Kg\u0026middot;hm\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e(Zhang et al., \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). MPs have been shown to induce alterations in soil structure and physicochemical properties such as soil bulk density, water-stable aggregates, soil configuration, water retention capacity, N2O emissions and pH levels(F. Wang et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Yu et al., \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Adding 1.5% (w/w) PLA-MPs to paddy soil significantly increased soil pH and changed soil dissolved carbon and nitrogen content(Zhiyu Zhang et al., \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). polyethylene terephthalate MPs can increase the redox potential of soil(Han et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). PE resulted in a decrease in the proportion of sediment particles, and an increase in the content of nitrate nitrogen and the abundance of MPs-degrading bacteria \u003cem\u003ePaenibacillus\u003c/em\u003e in the soil of legume farms(La et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The effects of PP and PE on soil pH value were different(W. Zhou et al., \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). 3% PET-treated forest soil had an eight-fold increase in soil respiration(Ng et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The treatment of PS and polyphenylene sulfide MPs can reduce the sulfur mineralization in black soil and paddy soil, and increase the sulfur mineralization in meadow soil(Dong et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). PE reduced the microbial available organic carbon content by 18.9%, CO\u003csub\u003e2\u003c/sub\u003e and N\u003csub\u003e2\u003c/sub\u003eO emissions by 26.5%-33.9% and 35.4%-39.7%, respectively(H. Yu et al., \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Understanding the effects of MPs on physicochemical and biochemical properties and shifts in microbial communities within meadow soils is imperative for sustaining agricultural productivity. Currently, there is a substantial body of research focusing on the impacts of MPs in soil; however, studies specifically addressing their effects within meadow soil environments remain scarce.\u003c/p\u003e \u003cp\u003eSoil microbial communities play a crucial role in the functioning of soil ecosystems and are involved in numerous chemical processes. The presence of MPs is associated with modifications in soil pH, moisture retention, and nutrient availability, leading to shifts in microbial community dynamics(J. Ma et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This disruption of the soil environment can hinder microbial activities essential for organic matter decomposition and nutrient cycling. In addition, MPs contain a diverse array of organic chemicals that can instigate oxidative stress responses in microbial cells through various biochemical pathways, ultimately impacting microbial vitality and diversity (Sch\u0026ouml;pfer et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The toxicological effects of these contaminants have been shown to induce physiological stress, inhibit growth, and disrupt community interactions among soil microbes, thereby reshaping community structures(Qi et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Additionally, the high carbon content of MPs is a hidden carbon source that affects the level of bioavailable carbon in the soil and has a large specific surface area, thus acting as a carbon source and carrier for bacteria, which can alter the structure and function of soil microbial communities and affect geochemical cycling(Ingraffia et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Seeley et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Shi et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). PLA-MPs have a greater effect on the composition of microbial community than PE(L. Li et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Soil microbial community composition of 1% and 5% LDPE treatments differed from that of CK and after 30 days Actinobacteria phylum replaced Ascomycetes phylum as the dominant phylum in 5% LDPE-treated soil(Ren et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Despite the documented impacts of other types of MPs on microbial communities, the response of soil microbial communities to PLA-MPs remains under-explored. Given the increasing prevalence of biodegradable plastics like PLA in agricultural practices and their potential long-term environmental consequences, understanding the relationship between PLA-MPs, meadow soil properties, and microbial community structures is of paramount importance. Further research in this area may elucidate the mechanisms through which PLA-MPs interact with soil microbial communities, ultimately contributing to our understanding of the ecological implications of plastic pollution in terrestrial ecosystems.\u003c/p\u003e \u003cp\u003eIn the present study, we investigated the effects of varying concentrations and particle sizes of PLA-MPs on the physicochemical properties and enzymatic activities of meadow soils through a 60-day incubation experiment. The 16S rRNA sequencing technique was used to assess how different concentrations and particle sizes of PLA-MPs influence the microbial community structure within meadow soils. This study aimed to elucidate the interrelationships between physicochemical properties, enzyme activities, and microbial communities in meadow soils exposed to microplastic contamination, as well as to identify successional patterns of key functional microbial groups. Ultimately, this research seeks to assist agricultural producers in predicting potential impacts arising from PLA-MP contamination, while providing a theoretical framework for informed decision-making.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eMaterials\u003c/h2\u003e \u003cp\u003eSoil samples collected in Ili Kazakh Autonomous Prefecture (81\u0026deg;3\u0026prime;15.008\u0026Prime;E,43\u0026deg;55\u0026prime;33.334\u0026Prime;N), Xinjiang Uygur Autonomous Region, in October 2023. The soil type was meadow soil and the sampling area was not film mulched. Soil samples were transported to the laboratory and air-dried at room temperature. After removal of stones and plant residues, the naturally air-dried soil samples were sieved through a 200-mesh sieve and mixed thoroughly for subsequent incubation experiments. The basic physical and chemical properties of the soil samples are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBasic chemical properties of the soi\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSOM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.42 g\u0026middot;kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.60 g\u0026middot;kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30.42 g\u0026middot;kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e73.28 mg\u0026middot;kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe test PLA-MPs were bought from Mingyuxing Plastic Material Co., Ltd. (Guangdong, Chian), with particle sizes of 50 mesh and 100 mesh, respectively, and were washed and dried at 30℃.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBasic chemical properties of the soil\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSOM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.42 g\u0026middot;kg-1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.60 g\u0026middot;kg-1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30.42 g\u0026middot;kg-1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e73.28 mg\u0026middot;kg-1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eIncubation experiment\u003c/h3\u003e\n\u003cp\u003eFirst, air-dried and sieved through a 200 mesh sieve was placed in a 18\u0026times;16\u0026times;17 cm pot, and PLA-MPs were mixed with the pre-incubated soil to obtain the following treatments: i) CK: 1 kg meadow soil with no PLA-MPs added; ii) J465: 2% (20 g:980 g, w:w) 50 mesh PLA-MPs added; iii) J490: 2% (20 g:980 g, w:w) 100 mesh PLA-MPs added; iv) L465: 7% (70 g:930 g, w:w) 50 mesh PLA-MPs added; v) L490: 7% (70 g:930 g, w:w) 100 mesh PLA-MPs added. Each pot had a total mass of 1 kg and was watered with 200 mL of water every 3 days. The samples were incubated naturally indoors for 60 days at an average daily light duration of 10 h, room temperature of 25\u0026ndash;28\u0026deg;C and air humidity of 30\u0026ndash;40%. Samples were collected on days 7, 15, 30, 45 and 60, respectively, and one sample was collected on day 60 for microbial community assay, and one sample was uniformly stored with other samples in a refrigerator at -80\u0026deg;C for physicochemical property and enzyme activity assay.\u003c/p\u003e\n\u003ch3\u003eSoil physicochemical properties and enzyme activity analysis\u003c/h3\u003e\n\u003cp\u003eThe collected soil samples were naturally air-dried and sieved through a 200-mesh sieve, and the pH was determined at a ratio of 5:1 (water/soil, v/v). The P concentration, Total N, available K, and organic matter were determined according to our previous research method(Liu et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Xiao et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). soil alkaline phosphatase (S-ALP), soil β-glucosidase(S-β-GC), soil urease (S-UE), soil superoxide dismutase (S-SOD), soil peroxidase (S-POD) and soil catalase (S-CAT) activities were determined by the kit according to the instructions. The kit was purchased from Beijing Solaibao Technology Co., LTD., and the kit was operated according to the instructions (Invitrogen, Thermo Fisher Scientific, Oregon, USA).\u003c/p\u003e\n\u003ch3\u003eDNA extraction and Illumina sequencing\u003c/h3\u003e\n\u003cdiv class=\"Heading\"\u003eDNA extraction and Illumina sequencing\u003c/div\u003e \u003cp\u003eThe DNA was extracted according to the instructions of the TGuide S96 Magnetic Soil /Stool DNA Kit (Tiangen Biotech (Beijing) Co., Ltd.). Qubit dsDNA HS Assay Kit and Qubit 4.0 Fluorometer were used to measure DNA concentration. The primers 338F: 5'- ACTCCTACGGGAGGCAGCA-3' and 806R: 5'-GGACTACHVGGGTWTCTAAT-3' were utilized to amplify the bacterial 16S rRNA gene from V3-V4 region. The PCR procedure commenced with an initial denaturation at 95\u0026deg;C for 5 minutes, subsequently followed by 25 cycles consisting of denaturation at 95\u0026deg;C for 30 seconds, annealing at 50\u0026deg;C for 30 seconds, and extension at 72\u0026deg;C for 40 seconds. The protocol concluded with a final extension step at 72\u0026deg;C for 7 minutes. The total PCR amplicons were purified using Agencourt AMPure XP Beads (Beckman Coulter, Indianapolis, IN) and quantified with the Qubit dsDNA HS Assay Kit in conjunction with the Qubit 4.0 Fluorometer (Invitrogen, Thermo Fisher Scientific, Oregon, USA). Following individual quantification, the amplicons were pooled in equal quantities. The constructed library was subsequently sequenced utilizing the Illumina NovaSeq 6000 platform (Illumina, Santiago, CA, USA). The raw sequence read data were submitted to the NCBI Sequence Read Archive (SRA) database (PRJNA1163276).\u003c/p\u003e\n\u003ch3\u003eMolecular ecological network construction and characterization\u003c/h3\u003e\n\u003cp\u003eThe network construction method based on Random Matrix Theory (RMT) was utilized to identify Hub and Connector operational taxonomic units (OTUs), employing a similar threshold of 0.94 to ascertain the topological properties(Fran\u0026ccedil;ois et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Several characteristics of the network were measured, including average degree, average path length, average clustering coefficient, and modularity index. The network modules were generated using a fast greedy modularity optimization approach. The network graphical visualization is consistent with previous research reports(Xiao et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eData were analyzed statistically using SPSS 25.0, and all data were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) with at least three replicates per treatment. One-way analysis of variance (ANOVA) was used to determine significant differences in parameter differences at the 5% level according to the Tukey\u0026rsquo;s test. Different upper- and lower-case letters in the pictures and tables indicate significant differences. Details of the bioinformatics analysis are reported in our previous study(Xiao et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Alpha diversity was calculated and displayed by QIIME2 and R software. Beta diversity was analyzed using QIIME assay and principal coordinate analysis (PCoA) to evaluate the degree of similarity of microbial communities in different samples. Linear Discriminant Analysis (LDA) effect size (LEfSe) was used to test the significant taxonomic difference among group(Segata et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Mantel and Spearman tests using the R package \u0026ldquo;vegan\u0026rdquo;. Mantel-test reveals the association between microbial communities and environmental factors.\u003c/p\u003e \u003c/div\u003e"},{"header":"Result","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eSoil physicochemical properties\u003c/h2\u003e \u003cp\u003eSoil physicochemical properties, including pH, SOM, TN, P, and AK concentrations, are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea-e. Compared to the control group (CK,7.70), the pH values increased in the L465 (7.95), L490 (8.04), J465 (8.15), and J490 (8.09) treatments by3.25%,4.46%,5.89%, and5.15%, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). SOM measurements taken at different time points indicated an increase of 12.41%-50.83% on day 7, 10.65%-58.51% on day 15, 5.70%-54.14% on day 30, 18.38%-73.65% on day 45, and 32.04%-88.84% compared to CK (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). Over the 60-day period, the SOM showed a decrease of 14.67% in the CK treatment and 6.06% in the J465 treatment, while the L465, L490, and J490 treatments exhibited increases of 7.20%, 18.37%, and 32.76%, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). TN contents in the L465, L490, and J465 treatments significantly increased by 23.39%, 18.32%, and 30.41%, respectively, compared to CK (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec). In comparison to CK (30.71 g\u0026middot;kg⁻\u0026sup1;), the J465 treatment (33.03 g\u0026middot;kg⁻\u0026sup1;) resulted in a 7.53% increase in soil P concentration, while no significant effects were observed from the other treatments (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed). Relative to CK (75.24 mg\u0026middot;kg⁻\u0026sup1;), all treatments significantly elevated soil AK content by 7.77% in L465 (81.08 mg\u0026middot;kg⁻\u0026sup1;), 8.49% in L490 (81.63 mg\u0026middot;kg⁻\u0026sup1;), 12.71% in J465 (84.80 mg\u0026middot;kg⁻\u0026sup1;), and 14.06% in J490 (85.82 mg\u0026middot;kg⁻\u0026sup1;) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eSoil enzyme activities\u003c/h2\u003e \u003cp\u003eAdditionally, soil enzyme activities, including S-SOD, S-POD, S-CAT, ALP, S-β-GC, S-UE are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea\u0026ndash;f. The incorporation of PLA-MPs had variable effects on soil enzyme activities compared to CK. Specifically, L465 (85.44 U\u0026middot;g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), L490 (93.36 U\u0026middot;g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), J465 (84.40 U\u0026middot;g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and J490 (78.72 U\u0026middot;g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) resulted in significant enhancements of S-SOD activity by 67.85%, 83.42%, 65.82% and 54.65%, respectively, compared to CK (50.90 U\u0026middot;g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). Moreover, L465 (8566.00 U\u0026middot;g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), J490 (7219.06 U\u0026middot;g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and J465 (7829.66 U\u0026middot;g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) significantly increased S-POD activity by 47.78%, 24.55% and 35.08%, respectively, compared to CK (5796.33 U\u0026middot;g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). The application of L465 (929.08 U\u0026middot;g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), J465 (804.68 U\u0026middot;g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and J490 (806.36 U\u0026middot;g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) resulted in substantial increases in S-CAT activity by 53.75%, 33.16% and 33.44%, respectively, compared to CK (604.30 U\u0026middot;g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). In contrast, ALP activity decreased by 13.67% and 22.07% in the J465 (2235.38 U\u0026middot;g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and J490 (2017.71 U\u0026middot;g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), compared to CK (2589.25 U\u0026middot;g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed). The S-β-GC activity was elevated by 53.61% in J465 (2.35 U\u0026middot;g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) compared to CK (1.53 U\u0026middot;g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee). Finally, L465 (153.98 U\u0026middot;g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), J465 (214.53 U\u0026middot;g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and J490 (206.18 U\u0026middot;g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) significantly enhanced S-UE activity by 51.69%, 111.33% and 103.12%, respectively, in comparison to CK (604.30 U\u0026middot;g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ef).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eStructure, diversity, and compositions of soil bacterial communities\u003c/h2\u003e \u003cp\u003eBacterial communities were detected by 16S rRNA sequencing, and the alpha diversity is presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The Chao and ACE indices indicated that the PLA-MPs increased microbial abundance, with the J465 exhibiting the highest number of microbial species. Additionally, the Shannon index showed that J465, J490, L465, and L490 had higher values than the CK, indicating that PLA-MPs contribute to greater complexity in the diversity of soil microorganisms. In contrast, the Simpson index revealed that the microbial community structure in the J465 and J490 was more homogeneous. Overall, microbial community diversity was significantly greater in the PLA-MPs treatments compared to CK, particularly in J465.\u003c/p\u003e \u003cp\u003eThe Venn diagram illustrated that the number of shared operational taxonomic units (OTUs) among CK, J465, J490, L465, and L490 was 680, with unique OTUs number was 4244, 5702, 5016, 4336, and 4666, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). Based on Bray-Curtis distance, principal coordinate analysis (PCoA) was performed on the microbial communities from meadow soil under different treatments. The analysis indicated that the contributions of the Pc1 and Pc2 to microbial diversity were 8.89% and 7.94%, respectively, yielding a cumulative contribution rate of 16.63%. Inter-group difference analysis revealed significant disparities in the soil microbial community, while intra-group differences remained relatively small (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb).\u003c/p\u003e \u003cp\u003eIn total, 41 phyla, 659 families, 1159 genera, and 27,468 OTUs were identified. The community composition varied with the particle size and concentration of PLA-MPs. At the phylum level (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec, Tab. S1), the dominant phyla (relative abundance\u0026thinsp;\u0026gt;\u0026thinsp;1%) included Proteobacteria (29.03\u0026ndash;32.54%), Acidobacteriota (15.84\u0026ndash;21.36%), Chloroflexi (10.29\u0026ndash;11.1%), Actinobacteriota (4.65\u0026ndash;10.02%), Gemmatimonadota (6.43\u0026ndash;8.77%), Patescibacteria (1.64\u0026ndash;6.08%), Myxococcota (1.57\u0026ndash;2.53%), and unclassified_Bacteria (3.47\u0026ndash;5.21%). Compared to CK, PLA-MPs resulted in a decrease in Proteobacteria, Actinobacteriota, and Patescibacteria at the phylum level, while Acidobacteriota, Chloroflexi, Gemmatimonadota, unclassified_Bacteria, and Bdellovibrionota increased; Bacteroidota showed no significant change. At genus level (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ed, Tab. S2), the dominant genera (relative abundance\u0026thinsp;\u0026gt;\u0026thinsp;1%) included \u003cem\u003ePseudomonas\u003c/em\u003e (0.64\u0026ndash;6.43%), \u003cem\u003eVicinamibacterales\u003c/em\u003e (4.15\u0026ndash;5.57%), \u003cem\u003eGemmatimonadacea\u003c/em\u003e (3.78\u0026ndash;5.58%), \u003cem\u003eSphingomonas\u003c/em\u003e (2.59\u0026ndash;3.68%), \u003cem\u003eunclassified_Bacteria\u003c/em\u003e (3.45\u0026ndash;5.12%), \u003cem\u003eVicinamibacteraceae\u003c/em\u003e (3.84\u0026ndash;3.74%), \u003cem\u003eLysobacter\u003c/em\u003e (2.11\u0026ndash;2.88%), \u003cem\u003eChloroflexi\u003c/em\u003e (1.81\u0026ndash;2.47%), \u003cem\u003euncultured_soil_bacterium\u003c/em\u003e (2.05\u0026ndash;2.35%) \u003cem\u003eand Blastocatellaceae\u003c/em\u003e (1.77\u0026ndash;2.39%). In comparison to CK, PLA-MPs led to a decrease in the abundance of \u003cem\u003ePseudomonas\u003c/em\u003e, \u003cem\u003eSphingomonas\u003c/em\u003e, \u003cem\u003eChloroflexi\u003c/em\u003e at the genus level, while increases were observed in \u003cem\u003eVicinamibacterales\u003c/em\u003e, \u003cem\u003eGemmatimonadaceae\u003c/em\u003e, \u003cem\u003eunclassified_Bacteria\u003c/em\u003e. \u003cem\u003eVicinamibacteraceae\u003c/em\u003e, \u003cem\u003eLysobacter\u003c/em\u003e, and \u003cem\u003eBlastocatellaceae\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eThis study performed a LEfSe of microbial communities in meadow soil to investigate the effects of PLA-MPs at different concentrations and particle sizes on soil microbial communities, from the phylum to species level (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ee). A total of 12 biomarkers were identified across seven levels of microbial community analysis under CK and varying concentrations of PLA-MPs. Specifically, there were 2 biomarkers at the species level, 2 at the genus level, 4 at the family level, 4 at the order level, 8 at the class level, 6 at the phylum level, and 1 at the kingdom level. Compared to the CK group, which had 14 markers, significant differences were observed in the microbial communities of meadow soil treated with various concentrations of PLA-MPs, particularly a marked reduction in the number of biological markers. The biological markers identified for L465, L490, J465, and J490 were 2, 2, 1 and 8. The biological markers identified for the L465, L490, J465, and J490 treatments were 2, 2, 1, and 8, respectively. In the CK group, the microbial species of the classes Actinobacteria, Saccharimonadia, and Gammaproteobacteria were relatively abundant, while Alphaproteobacteria was enriched in J465, Anaerolineae and Vicinamibacteria were enriched in J490, and Acidimicrobiia was enriched in L490 (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEffects of PLA-MPs on the alpha diversity of bacterial communities\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChao\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eACE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eShannon\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSimpson\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2587.84\u0026thinsp;\u0026plusmn;\u0026thinsp;126.48 c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2616.30\u0026thinsp;\u0026plusmn;\u0026thinsp;127.82 c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.4942\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0405 c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.9940\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0001 c\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL465\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2731.49\u0026thinsp;\u0026plusmn;\u0026thinsp;91.34 bc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2755.56\u0026thinsp;\u0026plusmn;\u0026thinsp;93.03 bc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.8888\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0197 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.9970\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0001 b\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL490\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2814.90\u0026thinsp;\u0026plusmn;\u0026thinsp;181.38 abc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2837.57\u0026thinsp;\u0026plusmn;\u0026thinsp;183.19 abc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.9053\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0531 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.9970\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJ465\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3137.05\u0026thinsp;\u0026plusmn;\u0026thinsp;150.84 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3161.67\u0026thinsp;\u0026plusmn;\u0026thinsp;151.86 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.163\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0700 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.9982\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0001 a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJ490\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2964.47\u0026thinsp;\u0026plusmn;\u0026thinsp;69.10 ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2989.33\u0026thinsp;\u0026plusmn;\u0026thinsp;67.06 ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.1296\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0227 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.9982\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0001 a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eBacterial co-occurrence network changes in the presence of PLA-MPs\u003c/h2\u003e \u003cp\u003eBased on 16S rRNA sequencing data from the five groups, five co-occurrence networks were constructed (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea-e). The main topological properties of the five groups of microbial communities of the molecular ecological networks are shown in Table S3. In the case where all nodes were set to 500, the CK group had more links (1351) and a higher percentage of positive links (56.92%) compared to the J465 (1289; 53.06%), J490 (1333; 52.5%), L465 (1301; 52.57%), and L490 (1325; 54.04%). This indicates that the interactions among microbial communities in meadow soil can be disrupted by PLA-MPs. PLA-MPs alter the abundance of various components of microbial communities in meadow soil, whereby different concentrations of PLA-MPs can lead to varying degrees of enrichment or suppression of specific microbial species. Comparisons between the J465 and J490 groups, as well as between the L465 and L490 groups, reflect a positive correlation between grain size and the concentration of PLA-MPs and their detrimental effects on microbial community interactions.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eCorrelations of soil microbial communities and environmental factor\u003c/h2\u003e \u003cp\u003eThe correlation of soil physicochemical properties and enzyme activities with microbial communities was analyzed using multivariate statistical analysis. Acidobacteriota, Actinobacteriota, Gemmatimonadota and Chloroflexi exhibited significant positive correlations with pH, AK, S-UE and S-ALP. These findings indicate that their abundance is closely linked to improved soil conditions, particularly with respect to physicochemical properties. Proteobacteria presented a notable positive correlation with S-β-GC, suggesting a potential relationship between this microbial phylum and carbohydrate availability in the soil. None of the negative correlations between the abundance of these phylum-level microorganisms and SOM, TN, and P were statistically significant, suggesting that these characteristics have limited effects on the abundance of this microbial phylum. Additionally, a correlation was established between soil physical and chemical properties and enzyme activities, with positive correlations noted between pH and TN, P, AK, S-UE and S-β-GC and negative correlations with S-ALP. SOM was positively correlated with S-SOD, S-POD, while AK positively correlated with S-UE and S-GC but negatively correlated with S-ALP. These findings emphasize that soil physicochemical properties and enzyme activities significantly influence the distribution and richness of various microbial communities, particularly Acidobacteriota, Actinobacteriota, Chloroflexi, and Gemmatimonadota. In contrast, Bacteroidota and Proteobacteria exhibited either negative or non-significant correlations with these soil parameters, indicating differentiated ecological niches or adaptive strategies. These insights underscore the importance of soil conditions in shaping microbial community structures and their potential implications for soil health and ecosystem functioning.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis of predictive metabolic functions\u003c/h2\u003e \u003cp\u003eA total of 6 KEGG primary metabolic pathways and 47 secondary metabolic pathways were identified based on the functional prediction of PICRUSt2 amplicon data. The major metabolic functions were characterized by the following percentages: cellular (6.36%-6.54%), environmental information processing (2.33\u0026ndash;2.42%), genetic information processing (9.96\u0026ndash;10.30%), human diseases (4.93\u0026ndash;5.06%), metabolism (73.32\u0026ndash;73.71%), organismal Systems (2.37\u0026ndash;2.44%) (Tab. S4). The effects of varying particle sizes and concentrations of PLA-MPs on soil metabolic functions are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Treatments L465, J465, and J490 reduced the functions of glycolysis, gluconeogenesis, and the pentose phosphate pathway, while the functions of pentose and glucuronate interconversions, oxidative phosphorylation, and photosynthesis significantly increased. PLA-MPs also differentially affected the degradation functions of chlorocyclohexane, chlorobenzene, benzoate, and bisphenol.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of the effects of PLA-MPs on soil metabolic functions\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetabolic pathway\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCK\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eL465\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eL490\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eJ465\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eJ490\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlycolysis / Gluconeogenesis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.25E-03\u0026thinsp;\u0026plusmn;\u0026thinsp;1.08E-05 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.11E-03\u0026thinsp;\u0026plusmn;\u0026thinsp;1.65E-05 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.23E-03\u0026thinsp;\u0026plusmn;\u0026thinsp;5.75E-06 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.12E-03\u0026thinsp;\u0026plusmn;\u0026thinsp;1.88E-05 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.15E-03\u0026thinsp;\u0026plusmn;\u0026thinsp;3.05E-05 b\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePentose phosphate pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.77E-03\u0026thinsp;\u0026plusmn;\u0026thinsp;5.04E-06 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.62E-03\u0026thinsp;\u0026plusmn;\u0026thinsp;8.54E-06 c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.72E-03\u0026thinsp;\u0026plusmn;\u0026thinsp;1.10E-05 ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.66E-03\u0026thinsp;\u0026plusmn;\u0026thinsp;2.93E-05 bc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.65E-03\u0026thinsp;\u0026plusmn;\u0026thinsp;5.23E-05 bc\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePentose and glucuronate interconversions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.30E-03\u0026thinsp;\u0026plusmn;\u0026thinsp;5.43E-06 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.41E-03\u0026thinsp;\u0026plusmn;\u0026thinsp;1.71E-05 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.40E-03\u0026thinsp;\u0026plusmn;\u0026thinsp;2.04E-05 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.47E-03\u0026thinsp;\u0026plusmn;\u0026thinsp;2.00E-05 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.44E-03\u0026thinsp;\u0026plusmn;\u0026thinsp;4.99E-05 a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOxidative phosphorylation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.94E-03\u0026thinsp;\u0026plusmn;\u0026thinsp;1.99E-06 c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.87E-03\u0026thinsp;\u0026plusmn;\u0026thinsp;1.64E-05 d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.04E-03\u0026thinsp;\u0026plusmn;\u0026thinsp;9.60E-06 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.05E-03\u0026thinsp;\u0026plusmn;\u0026thinsp;1.18E-05 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.22E-03\u0026thinsp;\u0026plusmn;\u0026thinsp;1.63E-05 a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhotosynthesis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.29E-03\u0026thinsp;\u0026plusmn;\u0026thinsp;8.37E-06 c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.22E-03\u0026thinsp;\u0026plusmn;\u0026thinsp;3.04E-05 d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.35E-03\u0026thinsp;\u0026plusmn;\u0026thinsp;5.91E-06 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.36E-03\u0026thinsp;\u0026plusmn;\u0026thinsp;2.02E-05 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.48E-03\u0026thinsp;\u0026plusmn;\u0026thinsp;2.84E-06 a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChlorocyclohexane and chlorobenzene degradation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.83E-03\u0026thinsp;\u0026plusmn;\u0026thinsp;1.35E-05 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.93E-03\u0026thinsp;\u0026plusmn;\u0026thinsp;2.31E-05 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.81E-03\u0026thinsp;\u0026plusmn;\u0026thinsp;1.66E-05 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.80E-03\u0026thinsp;\u0026plusmn;\u0026thinsp;2.72E-05 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.73E-03\u0026thinsp;\u0026plusmn;\u0026thinsp;2.18E-05 c\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBenzoate degradation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.08E-03\u0026thinsp;\u0026plusmn;\u0026thinsp;5.81E-06 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.30E-03\u0026thinsp;\u0026plusmn;\u0026thinsp;2.98E-05 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.05E-03\u0026thinsp;\u0026plusmn;\u0026thinsp;1.41E-05 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.07E-03\u0026thinsp;\u0026plusmn;\u0026thinsp;4.20E-05 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.89E-03\u0026thinsp;\u0026plusmn;\u0026thinsp;3.40E-05 c\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBisphenol degradation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.52E-04\u0026thinsp;\u0026plusmn;\u0026thinsp;2.12E-05 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.61E-04\u0026thinsp;\u0026plusmn;\u0026thinsp;3.74E-05 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.83E-04\u0026thinsp;\u0026plusmn;\u0026thinsp;2.08E-05 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.30E-04\u0026thinsp;\u0026plusmn;\u0026thinsp;3.24E-05 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.44E-04\u0026thinsp;\u0026plusmn;\u0026thinsp;2.09E-05 b\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eEffects of PLA-MPs on soil physicochemical Properties\u003c/h2\u003e \u003cp\u003eSoil pH increased in all treatments (L465, L490, J465, J490) compared to the CK, suggesting that PLA-MPs may have contributed to increased soil alkalinity (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). This finding contrasts with previous results indicating that PE can lower the pH of meadow soil. For instance, a study found that 0.2% PE decreased pH in acidic soil while increasing it in alkaline soil (Li et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The selective adsorption of microplastics to soil particles can affect cation exchange capacity, ultimately influencing soil pH (F. Wang et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Theoretically, biodegradable microplastics could generate organic acids (e.g., 3-hydroxybutyric acid) that lower soil pH (Yuan et al., \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). However, PLA-MPs treatment led to an increase in soil pH, possibly due to microbial biogeochemical processes (Hou et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This effect may be related to the type of plastic used. Multiple factors, including soil type, microplastic concentration, and particle size, determine whether soil pH increases, decreases, or remains stable (Liu et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Song et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Xu et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The increase in pH may stem from the aging, degradation, and decomposition of PLA-MPs in the soil, where the resultant carbon dioxide and water do not diffuse into the atmosphere (H. Li et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Instead, they combine with organic matter and are absorbed by plants, ultimately resulting in reduced acid emissions and increased Ph (Yan et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Furthermore, an increase in pH may enhance the solubility of specific nutrients (Chang et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePLA-MPs are carbon-rich and serve as an important source of carbon in soil (Rillig \u0026amp; Lehmann, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Moreover, substantial increases in SOM across various treatment intervals suggest a potential enhancement of soil health and carbon sequestration capabilities driven by PLA-MPs. Smaller biodegradable microplastics degrade more readily and release carbon into the soil (Li et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The degradation intermediates of microplastics are often not easily utilized by microorganisms as growth substrates, which ultimately leads to increased SOM content (Meng et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This is further supported by results indicating that SOM content was higher in the 100 mesh PLA-MPs treatment than in the 50 mesh treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). The varying rates of SOM accumulation over time underscore the time-dependent responsiveness of soil organic content to the incorporation of PLA-MPs, revealing their potential to stimulate microbial activity and stabilize organic matter. The microbial stimulation induced by PLA-MPs may also regulate organic carbon cycling by enhancing microbial metabolic efficiency or shaping microbial communities (Y. Li et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe content and bioavailability of N, P and K are critical determinants of soil fertility. TN contents were significantly elevated in all PLA-MP treatments, with the J465 treatment yielding the highest increase (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). Studies have reported that microplastics increase total soil nitrogen content and mineralization rates (H. Zhang et al., \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), which aligns with our findings. The decomposition of polylactic acid microplastics, which serve as a potential carbon source, increases the release of chitinase and leucine aminopeptidase while enhancing mineral nitrogen content, which promotes nitrification and denitrification processes (J. Zhou et al., \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). However, other research suggests that microplastics can lead to soil nitrogen loss by altering the abundance and function of nitrosative and ammonia-oxidizing bacteria, such as Chloroflexi, subsequently promoting denitrification reactions and reducing NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N concentrations (Li et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Q. Wang et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). PLA-MPs reduced the abundance of nitrifying bacteria, such as \u003cem\u003eNitrosira\u003c/em\u003e and \u003cem\u003eEllin6067\u003c/em\u003e, resulting in N depletion (Q. Wang et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The impact of microplastics on soil nitrogen content is influenced not only by concentration but also by the nature of the substances involved (H. Zhang et al., \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The slight increase in phosphorus content, particularly in J465, further supports the notion that PLA-MPs can enhance nutrient availability, although not all treatments exhibited significant changes (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed). AK contents similarly increased across all treatments, suggesting enhanced soil fertility (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee). MPs can also influence P and K contents by altering the relative abundance of Firmicutes associated with P and K cycling (Cui et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This enhancement may stem from changes in microbial composition, biomass accumulation, enzyme activity, and the abundance of genes associated with the N, P, and K cycles that elevate soil nutrient content (Tang et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eEffects of PLA-MPs on soil enzyme activities\u003c/h2\u003e \u003cp\u003eThe analysis of enzyme activities underscores the role of PLA-MPs in stimulating soil biochemical processes. Notably, the significant enhancement of S-SOD, S-PO, and S-CAT activities in response to PLA-MP applications indicates an adaptive microbial response to oxidative stress (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea-c). Huang et al. reported a dramatic increase in catalase activity in soils amended with microplastics, rising by 149% and 139% on the 30th and 90th days, respectively (Huang et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019b\u003c/span\u003e). Moreover, soil catalase activity significantly increased with the content of PVC-MPs, demonstrating increases of 79.17\u0026ndash;158.33% compared to untreated soil (Zhang et al., \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn addition, we observed activities of S-ALP, S-β-GC and S-UE activity. Interestingly, the reduction in S-ALP activity was noted in the J465 and J490 treatments, whereas it remained unchanged in the L465 and L490 treatments, suggesting that the particle size of PLA-MPs may influence S-ALP activity (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed). S-ALP is crucial for the mineralization of organic phosphorus, and a decrease in ALP activity can subsequently diminish available phosphorus (Xu et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Notably, while PLA-MPs decreased ALP activity in the J465 and J490 treatments, an increase in phosphorus content was observed in the J465 treatment. This discrepancy may be attributed to decreased effective phosphorus content and the inability of microorganisms to effectively uptake phosphorus. Furthermore, only the J465 treatment resulted in elevated S-β-GC activity in soil (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee). Oladele et al. found that 2 and 4% w/w PS-MPs resulted in decreased S-ALP activity coupled with increased S-β-GC activity(Oladele et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Elevated S-UE activity in the PLA-MP treatments indicates enhanced nitrogen cycling capacity, and this is further supported by elevated TN content in the soil physicochemical analyses. Previous studies have indicated that low-density polyethylene increases S-UE and S-CAT activities in soil (Huang et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019a\u003c/span\u003e). Conversely, it was reported that polyhydroxyalkanoates decreased both S-β-GC and S-UE activities(Guo et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), a finding that contrasts with our results and may be attributed to differing types of microplastics. Additionally, PVC degradation can adsorb and accumulate toxic substances such as lead, which may reduce S-β-GC activity (Zang et al., \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Thus, the decrease in soil enzyme activity may not solely result from the introduction of microplastics, but could also stem from harmful substances absorbed by the microplastics in the soil.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eEffects of PLA-MPs on soil bacterial community diversity and structure\u003c/h2\u003e \u003cp\u003eSoil microorganisms play a pivotal role in nutrient geochemical cycling. Findings from 16S rRNA sequencing elucidate the profound impact of PLA-MPs on the diversity and composition of soil microbial communities. The changes induced by microplastics in soil spatial heterogeneity may contribute to alterations in the structure of bacterial communities. Our results indicate that PLA-MPs enhanced both the biodiversity and structural homogeneity of soil bacteria, implying that PLA-MPs facilitate greater ecological complexity. Venn diagram analysis and PCoA highlight distinct differences in community structure between PLA-MP treatments and control groups, reflecting shifts in microbial relationships. Numerous studies have demonstrated the positive effects of microplastics on microbial communities (Li et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; R. Ma et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Shang et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Zekun Zhang et al., \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). PLA-MPs, formed through lactic acid polymerization, yield degradation products that can be utilized as exogenous carbon by microorganisms, thereby altering microbial community dynamics.\u003c/p\u003e \u003cp\u003eActinobacteria, Proteobacteria, Acidobacteria, Bacteroidota, and Chloroflexi were the dominant flora in the soil, consistent with previous research findings (Guo et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Hou et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Bacterial abundance at the phylum level revealed that disposal of PLA-MPs increased the abundance of Myxococcota, Bdellovibrionota, Chloroflexi, and Gemmatimonadota. Smaller-sized biodegradable microplastics are known to enhance the abundance of stress-tolerant bacteria (Liu et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The increased abundance of Myxococcota and Bdellovibrionota reflects their adaptive responses to environmental changes induced by PLA-MP pollution. Myxococcota are instrumental in decomposing organic matter, thus increasing soil nutrient levels, and they significantly influence microbial community structure and nutrient cycling (Colette et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Bdellovibrionota contribute positively to microbial diversity and stability. Chloroflexi are among the primary bacteria involved in the soil carbon cycle, impacting soil nutrients and aiding in the stabilization of carbon in SOM (Bovio-Winkler et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Diao et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Although there are fewer reports concerning Gemmatimonadota, evidence suggests a positive correlation with SOM, nitrogen, and potassium, along with a greater resilience to adverse conditions (Deng et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAdditionally, several bacterial groups exhibited reduced abundance under PLA-MP treatment, including Proteobacteria, Actinobacteriota, and Patescibacteria. Microplastics induce oxidative stress in certain bacteria, disrupting cell membrane integrity, which may lead to a decrease in their abundance. Biodegradable microplastics are more prone to release harmful substances into the soil, causing biotoxicity(Liu et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The relatively low resilience of Proteobacteria, Actinobacteriota, and Patescibacteria may further contribute to their decline in abundance. Proteobacteria require abundant nutrients for growth (Zhang et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and have historically occupied a dominant position in contaminated soils. Certain members, such as \u003cem\u003eBurkholderiaceae\u003c/em\u003e(Li et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), \u003cem\u003eBradyrhizobiaceae\u003c/em\u003e(S. Wang et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) etc. participate in nitrogen fixation and carbon cycling (Feng et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Several studies have indicated that Proteobacteria positively correlate with SOM and TN(F. Yu et al., \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In our research, we identified a significant positive correlation between Proteobacteria and S-β-GC, potentially linked to carbohydrates present in the soil, reinforcing the notion that Proteobacteria are involved in the carbon cycle.\u003c/p\u003e \u003cp\u003eCo-occurrence networks have gained prominence in characterizing the effects of environmental factors on soil microbial communities (Hou, 2019). Five co-occurrence networks constructed in this study investigated the influence of PLA-MPs of varying concentrations and particle sizes on microbial community interactions. Compared with the control, PLA-MPs treatment diminished both the positive correlation among soil microbial communities and the overall complexity of these communities (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). This suggests that PLA-MPs adversely impact positive interactions between microbial communities. In other words, variations in concentrations and particle sizes of PLA-MPs have differential effects on microbial communities, resulting in either the enrichment or loosening of specific bacterial populations (Fang et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The observed decline in positively correlated links indicates an intensified competitive relationship and weakened synergistic interactions between bacteria. Changes in bacterial abundance at key nodes may ultimately compromise the overall functional capacity of the microbial community, thereby affecting soil health and nutrient cycling.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eRelationship between soil environmental factors and bacterial communities at the dominant phylum level\u003c/h2\u003e \u003cp\u003eThe relationship between soil environmental factors and dominant phylum-level bacterial communities was elucidated through a mental test analysis. Positive correlations between Acidobacteriota, Actinobacteriota, Gemmatimonadota, and Chloroflexi and soil parameters such as pH, AK, S-UE, and S-ALP indicate that the growth and activity of these microbial communities are closely tied to soil nutrient enhancement. Furthermore, Proteobacteria exhibited a significant positive correlation with S-β-GC, suggesting its potential importance in the degradation of organic substrates, which leads to the release of monosaccharides that can serve as an energy source for various soil microorganisms. The correlations between soil physical and chemical properties and enzyme activities further emphasize the functional roles of these microbial communities within soil ecosystems. The significant positive correlation between SOM and S-SOD and S-POD activities may indicate that SOM aids in mitigating oxidative stress in the soil environment. Notably, soil pH positively correlated with the activities of enzymes such as S-UE and S-β-GC, which might enhance the abundance of associated microbial communities.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eEffects of PLA-MPs on bacterial community functions\u003c/h2\u003e \u003cp\u003eChanges in the structure of soil microbial communities have substantial effects on the metabolic functions of these communities. The results of the KEGG annotation indicate that the functions of pentose and glucuronate interconversions, oxidative phosphorylation, and photosynthesis were significantly increased, while the functions of glycolysis, gluconeogenesis, and the pentose phosphate pathway were reduced. These findings suggest that PLA-MPs disrupt the Embden-Meyerhof-Parnas (EMP) pathway and the hexose monophosphate pathway (HMP), while enhancing the pentose phosphate pathway. These pathways are critical for carbohydrate metabolism and energy production (Morelli \u0026amp; Scholkmann, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), indicating that PLA-MPs may hinder essential metabolic processes crucial for microbial growth and function. The disruption of EMP and HMP leads to reduced energy availability for the microbial community (Ni et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Conversely, the significant increases in the activities of the pentose and glucuronate interconversions, oxidative phosphorylation, and photosynthesis pathways suggest a compensatory adaptation by microbial communities. The enhancement of the pentose and glucuronate interconversion pathway signifies a shift towards alternative carbon metabolism (Riaz et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), reflecting the microbial community's efforts to utilize available substrates more effectively in the presence of PLA-MPs. Similarly, the increase in oxidative phosphorylation indicates enhanced aerobic respiration, potentially meeting higher energy demands under altered conditions (Ugya et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). T This metabolic shift may bolster microbial resilience against the stress introduced by microplastic contamination, albeit at the potential cost of altered community structure. Additionally, the increased function of photosynthesis in microbial communities residing in microplastic-affected soils may indicate a stabilization mechanism, wherein microbial symbionts or photosynthetic organisms adapt to convert light energy into chemical energy more effectively (X. Li et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), possibly mitigating some negative impacts of PLA-MPs. The interactions between PLA-MPs and the degradation functions of various compounds, such as chlorocyclohexane, chlorobenzene, benzoate, and bisphenol, carry significant implications for bioremediation processes. The ability of microbial communities to adapt their metabolic pathways to degrade these compounds in the presence of microplastics suggests that PLA-MPs could alter biogeochemical cycles, affecting contaminant breakdown dynamics in soils. The effects of varying particle sizes and concentrations of PLA-MPs on microbial metabolic functions illustrate not only a disruption of fundamental metabolic pathways but also an adaptive response from microbial communities. These dynamics underscore the necessity for further research to understand the implications of microplastic contamination in soil ecosystems, particularly regarding how shifts in microbial metabolic functions affect nutrient cycling, pollutant degradation potential, and overall ecological resilience in the face of ongoing environmental changes.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe effects of different particle sizes and concentrations of PLA-MPs on soil physicochemical properties (SOM, TN, P, AK, and pH), enzyme activities (S-SOD, S-POD, S-CAT, S-ALP, S-GC, and S-UE), and microbial community diversity and structure were investigated through a 60-day incubation experiment. The results demonstrate that PLA-MPs significantly affect soil physicochemical properties and enzyme activities. In terms of soil physicochemical properties, PLA-MPs increased pH and enhanced SOM, TN, and AK contents. Additionally, in regards to soil enzyme activities, PLA-MPs enhanced antioxidant enzymes, increased S-β-GC and S-UE activities, and decreased S-ALP activities. Furthermore, PLA-MPs influenced microbial community diversity and composition, with Proteobacteria, Actinobacteria, Acidobacteria, Bacteroidota, and Chloroflexi predominating at the phylum level. Vicinamibacterales, Gemmatimonadaceae, Sphingomonas, unclassified Bacteria, Vicinamibacteraceae, Lysobacter, and Blastocatellaceae were identified as the main genera. pH, AK, S-UE, and S-β-GC were key factors influencing microbial community composition. PICRUSt2 analysis revealed that PLA-MPs disrupt the pathways of glycolysis and pentose phosphorylation but enhance the pathways of pentose and glucuronate interconversions and oxidative phosphorylation. Overall, larger-sized PLA-MPs exerted a greater effect on soil physicochemical properties, while smaller-sized PLA-MPs had a more significant impact on soil enzyme activities, with higher levels of PLA-MPs being particularly disruptive to microbial community interactions. Consequently, the profound effects of changes in particle size and concentration on meadow soils due to the long-term accumulation of PLA-MPs warrant further investigation to formulate strategies aimed at mitigating plastic pollution in agricultural systems.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eEthical Approval\u003c/h2\u003e \u003cp\u003eThis article does not contain any studies with human participants performed by any of the authors.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent to Participate\u003c/strong\u003e \u003cp\u003eThis manuscript is approved by all authors for participation.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent to Publish\u003c/strong\u003e \u003cp\u003eThis manuscript is approved by all authors for publication.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting Interests\u003c/h2\u003e \u003cp\u003eThe authors have no competing interests to declare.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis research was financially supported by the Yili Normal University School Program (2023YSYB011); The Natural Science Foundation of Xinjiang Uygur Autonomous Region (2024D01C197); Basic research expenses of universities in autonomous region (XJEDU2024P067).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eSML and YQL contributed to the conception and design of this study. Research, material preparation, data collection, and analysis were performed by JHZW, KLW, YKZ, JXZ, XYY, YS and MCL. The first draft of the manuscript was written by SML and KLW. YQL and MCL commented on the previous versions of the manuscript. All authors have read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eData availability\u003c/h2\u003e \u003cp\u003e16S rRNA sequencing data were deposited in the Sequence Read Archive (SRA) of the National Center for Biotechnology Information (NCBI) under accession number PRJNA1163276.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAnbumani, S., \u0026amp; Kakkar, P. (2018). Ecotoxicological effects of microplastics on biota: a review. 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Scientific Reports, \u003cem\u003e10\u003c/em\u003e(1). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41598-020-76316-7\u003c/span\u003e\u003cspan address=\"10.1038/s41598-020-76316-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"environmental-geochemistry-and-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"egah","sideBox":"Learn more about [Environmental Geochemistry and Health](https://www.springer.com/journal/10653)","snPcode":"10653","submissionUrl":"https://submission.nature.com/new-submission/10653/3","title":"Environmental Geochemistry and Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Microplastics, Enzymatic activity, Microbial community; Meadow soil","lastPublishedDoi":"10.21203/rs.3.rs-5368532/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5368532/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSoil microplastics (MPs) pollution has garnered considerable attention in recent years. The use of biodegradable plastics for mulching has led to significant quantities of plastic entering agro-ecosystems. However, the effects of biodegradable polylactic acid (PLA) plastics on meadow soils remain underexplored. This study investigates the impacts of PLA microplastics of varying particle sizes and concentrations on soil physicochemical properties, enzyme activities, and microbial communities through a 60-day incubation experiment. PLA-MPs increased the pH, soil organic matter (SOM), total nitrogen (TN) and available potassium (AK) content, as well as enhanced the activities of superoxide dismutase (S-SOD), peroxidase (S-POD), soil catalase (S-CAT), β-glucosidase(S-β-GC) and urease (S-UE) activities. Conversely, a decrease in alkaline phosphatase (S-ALP) activity was observed. The influence of PLA-MPs on soil physicochemical properties was more pronounced with larger particle sizes, whereas smaller particles had a greater effect on enzyme activities. Additionally, PLA-MPs led to an increase in the abundance of Acidobacteriota, Chloroflexi, and Gemmatimonadota, while the abundance of Proteobacteria, Actinobacteriota, and Patescibacteria declined. Mental test analysis indicated that pH, AK, S-UE, and S-β-GC are the primary factors influencing microbial community composition. Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt2) analysis demonstrated that PLA-MPs modify bacterial metabolic pathways. Our results suggest that particle size and concentration of PLA-MPs differentially affect soil nutrients and microbial community structure and function, with more significant effects observed at larger particle sizes and higher concentrations.\u003c/p\u003e","manuscriptTitle":"Unveiling the impact of biodegradable polylactic acid microplastics on meadow soil health","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-13 13:45:53","doi":"10.21203/rs.3.rs-5368532/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-12-18T08:36:01+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-12-18T07:07:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"234211038617082462152939493983508402657","date":"2024-12-06T05:25:49+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-11-29T15:12:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"167439839989716062987089662457343185128","date":"2024-11-04T13:55:17+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-11-04T08:56:21+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-11-03T09:49:49+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-11-01T16:03:01+00:00","index":"","fulltext":""},{"type":"submitted","content":"Environmental Geochemistry and Health","date":"2024-10-31T17:33:38+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"environmental-geochemistry-and-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"egah","sideBox":"Learn more about [Environmental Geochemistry and Health](https://www.springer.com/journal/10653)","snPcode":"10653","submissionUrl":"https://submission.nature.com/new-submission/10653/3","title":"Environmental Geochemistry and Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"f2d9f115-be99-4814-bbe0-cb966ad6567f","owner":[],"postedDate":"November 13th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-01-13T16:12:49+00:00","versionOfRecord":{"articleIdentity":"rs-5368532","link":"https://doi.org/10.1007/s10653-025-02358-3","journal":{"identity":"environmental-geochemistry-and-health","isVorOnly":false,"title":"Environmental Geochemistry and Health"},"publishedOn":"2025-01-08 15:57:36","publishedOnDateReadable":"January 8th, 2025"},"versionCreatedAt":"2024-11-13 13:45:53","video":"","vorDoi":"10.1007/s10653-025-02358-3","vorDoiUrl":"https://doi.org/10.1007/s10653-025-02358-3","workflowStages":[]},"version":"v1","identity":"rs-5368532","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5368532","identity":"rs-5368532","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}