Unexpected species diversity in the understanding of selenium- containing soil invertebrates

Unexpected species diversity in the understanding of selenium- containing soil invertebrates | 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 Article Unexpected species diversity in the understanding of selenium- containing soil invertebrates Bin Mao, XiangLiang Fang, HongLing Lei, YunLi Xiao, Yue Fu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5255864/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 29 Jan, 2025 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract Yutangba, situated in Enshi City, Hubei Province, is globally noted its high selenium (Se) content. Soil invertebrates are essential to the functionality and services of terrestrial ecosystems, yet their community composition in this region remains under-explored. This study utilized environmental DNA metabarcoding to investigate the interrelations among environmental factors, soil invertebrate diversity, and community characteristics concerning soil Se content, pH, and moisture content in the region. Environmental factors such as Se concentration, water content, and pH were strongly associated with the alpha and beta diversity of soil invertebrates in Se-rich areas, affecting their distribution and abundance. Among these, Se notably emerges as the primary regulatory factor influencing soil invertebrate diversity. The acidic soil pH, along with moisture, plays a fine-tuning role in regulating species diversity by directly or indirectly influencing the availability and bioavailability of Se, impacting the species richness and community composition. Unexpectedly, certain species, such as the Formicidae (ants, e.g., Odontomachus troglodytes ), the Noctuidae (e.g., Diarsia rosaria ), and the annelid Haplotaxida Perionyx excavates , exhibit a strong positive association with Se, indicating a high level of Se tolerance among the native species. This novel perspective reveals the complex role of Se in soil ecosystems, emphasizing the necessity of understanding its ecological functions and potential implications for ecosystem health and stability. Diversity Selenium Soil Invertebrates Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Highlight Soil invertebrates in Se-rich areas are more tolerant to Se. Moisture and pH fine-tune soil invertebrate diversity in Se-rich areas. Some Diptera and Formicidae species diversity increased in Se-rich areas. 1 Introduction The soil microbiome is crucial for ecosystem health, influencing nutrient cycling, organismal growth, and climate regulation through greenhouse gas emissions (Dantas and Sommer, 2014 ). Soil invertebrates, beyond their role in decomposition, actively break down organic matter via enzymatic processes, thereby affecting both soil and plant dynamics (Joly et al., 2020 ; Griffiths et al., 2021 ; Kane et al., 2023 ). Studies demonstrate that invertebrates independently degrade organic materials without microbial aid, significantly contributing to the global recycling of plant matter (Joly et al., 2020 ; Kane et al., 2023 ). Moreover, soil organisms are instrumental in soil formation and development, modifying soil properties, facilitating material translocation, and converting energy (Wall et al., 2008 ; García-Palacios et al., 2013 ; Briones, 2018 ; Griffiths et al., 2021 ), all of which are vital for ecosystem material cycling. Studies examining the relationship between soil invertebrates and environmental conditions have identified parent rock type, soil pH, nutrient availability, organic matter content, and climate significantly influence the distribution of soil animal communities (Bird et al., 2000 ; Ponge et al., 2003 ; Cassagne et al., 2006 ). These communities are key indicators of forest health and disturbances. Selenium (Se), an essential trace element for numerous organisms (National Research Council, 1983), exhibits beneficial or toxic effects based on its concentration (Schwarz and Foltz, 1957 ; See et al., 2006 ; MacFarquhar et al., 2010 ; Zhang et al., 2021 ). Soil pH significantly affects animal diversity and the composition of functional communities, with distinct decomposer species thriving in either acidic or alkaline environments (Schaefer, 1990 ; Salmon et al., 2006 ; Pollierer et al., 2021 ). This indicates that regional abiotic factors, such as soil pH, exert a greater influence on decomposer communities than local biotic factors. Soil pH, determined by parent rock and stand type, is fundamental to the availability and structure of resources within soil food webs (Ruess et al., 1996 ; Lauber et al., 2008 ; Rousk et al., 2010 ). Consequently, soil Se content and pH are primary determinants of soil organism distribution. Se distribution exhibits significant variability across the globe, with concentrations reaching up to 1000 mg/kg in certain Se-rich regions, juxtaposed with areas where it is nearly nonexistent (Hartikainen, 2005 ). Outside these enriched zones, Se is also found in uranium and phosphate ore deposits. Yutangba, recognized worldwide for its high Se content, is notable for containing the only known independent Se deposit, located within black rock series (Yao et al., 2002 ; Zhu et al., 2000 ; Wen et al., 2007 ). Despite its small area of merely 0.01 km², Yutangba demonstrates considerable heterogeneity in soil Se distribution, predominantly shaped by topographical variations and soil particle size (Zhu et al., 1998 ). Soil organisms significantly influence soil formation, yet the effect of the region's uneven Se distribution on their distribution is not well understood. Soil invertebrates near the ancient Se mine have likely evolved adaptive mechanisms due to extended exposure (De La Riva and Trumble, 2016 ). Consequently, it is hypothesized that Se-rich environments support greater soil invertebrate diversity, with factors such as Se content and soil pH playing substantial roles in shaping this diversity. Environmental DNA (eDNA) technology, utilizing molecular sequence analysis of genetic material in environmental samples, allows for efficient identification and monitoring of biological species through comparison with reference species databases. This technology marks a substantial advancement in biodiversity science since the early 21st century (Wang et al. 2019 , Zhang 2019 ). This study employed eDNA technology to compile foundational data on the soil animal community in the region. By analyzing the relationships between soil invertebrate diversity indicators and soil properties such as Se content, the research established a framework for understanding the association between soil Se levels and soil fauna and monitoring soil ecological health. The results offer valuable insights for future research into the characteristics and evolutionary dynamics of soil animal diversity in the area. 2 Materials and methods 2.1 Sample collection and the separation of soil organisms The designated soil sampling route at Yutangba, Enshi City, Hubei Province, as illustrated in Fig. 1 , targeted the central zone of a distinct Se reserve, beginning at sites K and A. The route traced two watercourses, merging at site G and then extending downstream. Eleven sampling locations were established, with three subplots at each site arranged in S-shaped or daisy-shaped patterns to ensure randomness and equitable volume, representing a composite of multiple points. Soil sampling was conducted thrice at each of the 11 sites in July, September, and November 2015, yielding 99 soil specimens. Post-sampling, the soil specimens were transported to the laboratory, separated using modified Tullgren funnels, and subjected to a 48-hour drying period. The dried samples were then categorized and preserved in an 85% ethanol solution. For environmental DNA analysis, 33 composite samples were prepared from the corresponding sample points. 2.2 Determination of moisture content Upon returning to the laboratory, labeled soil samples were collected. Each sample was weighed in a clean culture dish, recording the mass as M dish . After adding the soil to the dish, the combined mass was documented as M dish+soil sample . Samples were then dried to a constant weight in a temperature-controlled drying oven, and the mass was noted as M dish + dried . Moisture content of the soil sample was calculated using the formula: Moisture content (%) = [(Mdish + soil sample - Mdish + dried) / (Mdish + dried - Mdish)] × 100%. 2.3 Determination of selenium content Determining soil Se concentration adhered to the Chinese National Standard GB 5009.93—2017 (The Ministry of Health of the People's Republic of China, 2017 ). Dried soil samples were ground and sieved through a 200-mesh screen before being stored in sealed plastic bags. A precise 0.05 g portion of each soil sample was weighed and placed in a digestion tube. To enable digestion, 8 mL of concentrated nitric acid, 2 mL of concentrated hydrochloric acid, and 2 mL of hydrogen peroxide were added to each tube, with the samples soaking for 24 hours. The digestion process entailed a gradual temperature increase in a digestion furnace until the solution achieved clarity and transparency. The solution volume was then reduced, and hydrochloric acid was added to maintain clarity. The digested solutions containing Se were transferred to volumetric flasks and diluted to a known volume with ultrapure water. Analysis was performed using an AFS-922 dual-channel atomic fluorescence spectrometer, as detailed in Appendix A. The Se content, expressed as micrograms per gram (µg/g), was calculated by comparing the initial weight of the soil samples with the final volume of the digested solutions for subsequent analysis. 2.4 Determination of pH Post moisture content assessment, the remaining soil samples were exposed to natural air drying and subsequently sieved through a 1 mm mesh. A 20-gram portion of the sieved, air-dried soil was weighed and transferred into a 120 ml wide-mouth bottle with a cover. Then, 100 ml of CO2-free distilled water was added, maintaining a soil-to-water ratio of 1:5. The mixture was blended for 2 minutes and allowed to settle for 30 minutes. The pH of the resulting solution was measured with a pH meter, and the data were recorded. 2.5 DNA extraction and PCR amplification DNA from soil eukaryotic invertebrates was extracted from 33 samples using the E.Z.N.A.® Soil DNA Kit (Omega Biotek, Norcross, GA, U.S.), adhering to the manufacturer's protocols. The COI gene underwent PCR amplification under these conditions: initial denaturation at 95°C for 2 minutes, followed by 25 cycles of 95°C for 30 seconds, 55°C for 30 seconds, and 72°C for 30 seconds, with a final extension at 72°C for 5 minutes. Two oligonucleotide primers, mlCOlintF (5’-GGWACWGGWTGAACWGTWTAYCCYCC-3’) and jgHCO2198 (5’-TAIACYTCIGGRTGICCRAARAAYCA-3’), were utilized. Each PCR was performed in triplicate in a 20 µL volume containing 4 µL of 5 × FastPfu Buffer, 2 µL of 2.5 mM dNTP mix, 0.8 µL of each primer at 5 µM, 0.4 µL of FastPfu Polymerase, and 10 ng of DNA template. DNA fragments were isolated from 2% agarose gels and purified using the AxyPrep DNA Gel Extraction Kit (Axygen Biosciences, Union City, CA, U.S.), following the manufacturer's guidelines precisely. 2.6 DNA sequencing and data processing Concentrations of the PCR products were measured using the Qubit® 3.0 Fluorometer (Life Invitrogen). Equal molar amounts of the twenty-four amplicons, tagged with a specific barcode, were combined to create a composite sample. This composite DNA was utilized to construct a paired-end library suitable for Illumina sequencing platforms, following the provided protocol for genomic DNA library preparation. The library underwent paired-end sequencing (2 × 250 bp) on an Illumina MiSeq system (provided by Shanghai BIOZERON Co., Ltd.), adhering to the standard sequencing protocols. Raw fastq files were processed with custom Perl scripts to demultiplex data using unique barcode sequences for each sample. The demultiplexing adhered to stringent criteria: (i) Reads of 250 base pairs were truncated if a sliding window of 10 bases had an average quality score below 20, and truncated reads shorter than 50 base pairs were discarded. (ii) Reads with exact barcode matches, more than 2 nucleotide mismatches in primer sequences, or ambiguous nucleotide codes were excluded. (iii) Overlapping sequences were assembled only if the overlap exceeded 10 base pairs, and reads failing to meet this overlap requirement were rejected. 2.7 Statistical analysis Statistical analyses and visualizations were conducted using R (version 4.3.0) and the ggplot2 package (Wickham, 2016 ), except where noted. Data from eleven sample site groups were assessed for normality. Normally distributed data were analyzed using ANOVA and the least significant difference (LSD) multiple comparison test. Non-normally distributed data were evaluated using the Kruskal-Wallis (KW) test and the Wilcoxon test. Statistical significance was set at P < 0.05. Species richness estimation and diversity comparison among samples employed rarefaction and extrapolation methods. Invertebrate alpha diversity and abundance were assessed using the Chao1 estimator, Abundance-based Coverage Estimator (ACE), and observed species index, calculated via R scripts. Relationships between alpha indices and environmental variables were examined through Canonical Correlation Analysis (CCorA). Beta diversity of invertebrates was analyzed using PCoA based on Bray-Curtis distances and PERMANOVA, utilizing the vegan package in R (Oksanen, 2002). Soil community structure differences were investigated with a nonparametric multivariate analysis of variance (Adonis). Canonical correspondence analysis (CCA) assessed the relationships between environmental variables and species/operational taxonomic units (OTUs). The envfit test within the R package vegan subsequently identified environmental factors significantly impacting species distribution. Additionally, Mantel correlograms with 9,999 permutations tested the significance of correlation trends in concentration changes. The Mantel test further examined correlations between species and environmental variables, including Se, H 2 O, and pH, using Spearman's rank correlation, with significance determined by 9,999 permutations. Significant correlations were defined by Spearman’s rho values exceeding 0.2 and P-values below 0.05. Data visualization was performed in Cytoscape ( http://www.cytoscape.org ) to elucidate the relationships between species and environmental factors. Canonical correspondence analysis (CCA) assessed the relationships between environmental variables and species/operational taxonomic units (OTUs). Following CCA, the envfit test in the R package vegan identified specific environmental factors significantly impacting species distribution. Additionally, Mantel correlograms with 9,999 permutations were utilized for significance testing to assess the correlation trends of concentration changes. Moreover, the Mantel test was conducted to explore correlations between species and environmental variables including Se, H 2 O, and pH, using Spearman's rank correlation, with significance assessed through 9999 permutations. A Spearman’s rank correlation coefficient (Spearman’s rho) greater than 0.6 and a significance level ( P ) less than 0.05 were considered significant. 3 Results 3.1 Analysis of environmental factors Samples were collected from 11 locations adjacent to the stream, where two streams converge downstream of site G and upstream of site F. Site A was positioned at the selenium cave, while site K was located near selenium mining waste (Fig. 1 ). To assess environmental factor variations, month and site relationships were analyzed. The results showed no significant interactions for Se (F (10, 11) = 1.75, P = 0.19), H 2 O (F (10, 11) = 0.39, P = 0.93), and pH (F (10, 11) = 1.42, P = 0.29). Then, variations in pH, H 2 O, and Se were assessed individually across months and sites. Results showed no significant differences among the months (Fig. 2 a-c, all P > 0.05), but significant site-specific differences were observed (Fig. 2 d-f, all P < 0.05, Appendix B). All sites exhibited acidic pH values below 7.0, with the highest at 6.4, suggesting a generally weakly acidic soil environment. Sites with higher Se concentrations had more acidic pH levels (Fig. 2 d-e). Soil water content ranged from 27.6–48.7%, peaking at site C with 62.56% and the lowest at site A. Despite site A's low water content, it had a high Se concentration of 254.37 µg/g, indicating that both Se concentration and water content influence soil organism diversity. 3.2 Taxa composition and abundance analysis In July, September, and November 2015, 33 samples were collected from 11 sites. COI amplification sequencing produced 1,478,635 circular consensus sequencing (CCS) sequences with an average length of 312.23 bp. Optimized sequences totaling 1,468,280, ranging from 301 to 350 bp, represented 99.30% of the total, ensuring annotation accuracy (Appendix C). Analysis of taxonomic composition and differential relative abundance of soil invertebrates revealed distinct patterns across various sites (Fig. 3 ). The phyla Arthropoda and Annelida consistently exhibited high abundances. Within these groups, Diptera (including Culicidae and Tachinidae ) in the Insecta class and Haplotaxida (including Henicopidae and Megascolecidae ) in the Chilopoda class were particularly prominent. Additionally, sites C, H, and I, which recorded the highest humidity levels, showed a greater abundance of Anopheles mosquitoes , indicating their preference for aquatic environments. Variations in environmental factors, such as Se concentration and water content, are linked to the distribution and abundance patterns of soil invertebrates. 3.3 Alpha diversity signatures A comparative analysis was conducted to investigate the impact of various sites and environmental factors on alpha diversity. Despite site B having lower Se concentration but higher pH and water content compared to site A (Fig. 2 d-f), alpha diversity was relatively higher at site B (Fig. 4 a-d). This suggests that pH and water content, among other environmental factors, significantly influence soil invertebrate alpha diversity, shaping biodiversity. Given the spatial distribution of sites along the stream, interrelated data from these locations exhibit notable correlations. Analysis of alpha indices across different sites revealed significant inter-site correlations (Fig. 4 e). To further explore the relationships between alpha diversity indices and environmental variables, including Se, pH, and H 2 O, CCorA was performed. This analysis indicated a substantial correlation between environmental factors and alpha diversity at various sampling sites. Specifically, CCorA results demonstrated a strong correlation between alpha diversity indices and environmental variables (canonical correlation coefficient = 0.85, P = 0.014; Wilks' statistic = 0.20, df = 24) (Fig. 4 e). These data highlight the robust association between environmental factors and alpha diversity. 3.4 Beta diversity PCoA of OTU data on species diversity indicated that three axes accounted for 21.5% of the variance (Fig. 5 a-b). The composition of invertebrates in the Yutangbae area was significantly different among the various sites (PERMANOVA R 2 = 0.37, P = 0.001), while no significant differences were observed among different months (PERMANOVA R 2 = 0.03, P = 0.23). It suggests that spatial variations have a greater impact on soil invertebrate diversity than temporal variations. The combined CCA and envfit analysis identified significant correlations between environmental factors such as Se, water content, and pH with variations in species composition within soil animal communities (Fig. 5 c-d). This analysis highlighted the substantial impact of Se and pH on the structure and dynamics of these communities. R 2 values (0.31, 0.60, and 0.68) revealed that Se, H 2 O, and pH accounted for 31%, 60%, and 68% of the observed variation, respectively, with low P- values of 0.005, 0.001, and 0.001, confirming statistical significance. These results highlight the essential roles of Se, H 2 O, and pH in determining species composition. The strong association between environmental factors and community structure highlights the necessity of considering these variables in ecological studies and management. Analysis of environmental variables pH, H 2 O, and Se revealed no significant correlation between Se and the other two factors (Fig. 6 a). However, a significant positive correlation was identified between H 2 O and pH (rho = 0.47, P < 0.01) (Fig. 6 a). The stability of pH across different sample sites may be due to their proximity to water sources, where pH remains relatively constant. A Mantel test was performed to evaluate the relationship between species beta diversity and specific environmental factors, revealing a significant positive correlation between species beta diversity and sample sites ( P < 0.05) (Fig. 6 a). Additionally, H 2 O significantly influenced site A (rho = 0.23, P = 0.046). Sites A, J, and K, characterized by high species diversity and elevated Se concentrations (Fig. 6 a, Fig. 2 d), suggest that Se significantly enhances species diversity at Se-enriched areas. To analyze the relationship between species diversity and changes in environmental factors such as alpha diversity, Se content, H 2 O content, or pH, we used Mantel correlograms with 9999 permutations for significance tests (Fig. 6 b). Results indicate a significant negative correlation between species diversity and Se content in Se-rich areas with low soil Se ( r = -0.52, P = 0.008), implying a necessary Se threshold for soil invertebrate survival. Unexpectedly, in regions with high Se concentrations, a significant positive correlation emerges between species diversity and Se concentration (r = 0.68, P = 8E-4), indicating species tolerance to elevated Se levels. Furthermore, significant positive correlations were observed with high alpha diversity (r = 0.39, P = 0.036), high water content (r = 0.78, P = 5E-04), and high pH (r = 0.42, P = 7E-4), suggesting that these environmental factors were also associated with species beta diversity. 3.5 Relationships between environmental variables and soil invertebrates Correlation analysis between soil invertebrates and environmental factors (Fig. 7 , Appendix D) identified significant associations for 83 distinct species with Se concentration, soil moisture content, and pH. Insects demonstrated notable correlations with environmental factors, with 74% of species belonging to the order Insecta. The majority of soil organisms exhibited a strong and statistically significant relationship with Se concentration, as 67% of the correlation coefficients (rho) exceeded 0.5. The Formicidae family (ants), including species such as Odontomachus troglodytes , Lasius emarginatus , and Lasius niger , along with the Noctuidae family, such as Diarsia rosaria , and Haplotaxida , specifically Perionyx excavates , showed a high correlation with Se. In contrast, the aquatic larvae of Diptera, such as Drosophila littoralis , were strongly associated with moisture content. In addition, Coleoptera (beetles) exhibited a notable correlation with soil pH. The number of species associated with Se significantly exceeded those linked to water and pH, indicating that Se distribution and concentration had a more substantial impact on insect diversity and distribution. Furthermore, the correlation coefficient (rho) between species related to Se and water is typically higher than that between species related to pH. This suggests that Se and water may have a more direct and significant impact on insects, particularly during the larval stage when they are more sensitive to environmental changes. Although five species exhibited significant correlations with both Se concentration and pH, the correlation coefficients (rho) with Se were consistently higher than those with pH. This indicates that the abundance of these soil invertebrates is more significantly influenced by Se concentration. 4 Discussion Robinson et al. ( 2018 ) investigated the impact of soil temperature on the structure and diversity of invertebrate communities. Despite fluctuations in local moisture content and temperature regimes across different months, species diversity remained unaffected, suggesting that environmental conditions in Se-rich areas are relatively stable over time. Therefore, future research should focus on how spatial variations in these factors influence soil invertebrate diversity, rather than temporal changes. Soil pH influences Se adsorption and desorption, thereby controlling its bioavailability. In acidic soils, Se predominantly exists as tetravalent selenite, forming stable complexes with iron and manganese oxides (Guo, 2012 ), which sequesters Se in the soil and maintains high Se levels. This study identified a correlation between soil moisture and pH, both affecting the distribution of soil invertebrate communities (Sylvain et al., 2014 ; Kökdener and Şahin Yurtgan, 2022 ; Rai et al., 2022 ; Wu et al., 2023 ). Soil pH regulates the adsorption and desorption of Se, affecting its bioavailability. In acidic soil, Se predominantly exists as tetravalent selenite, which forms stable complexes or precipitates with iron and manganese oxides (Guo, 2012 ), thus sequestering Se and maintaining high Se levels. Soil samples from Yutangba, generally exhibiting a weakly acidic environment, indicate that Se is primarily in its tetravalent form, potentially impacting soil health (Guo, 2012 ). High Se concentrations are often associated with more acidic pH levels, suggesting that pH significantly influences Se bioavailability in the Yutangba region. However, the content of Se showed no significant correlation with factors such as pH and H 2 O (Fig. 6 a), even though pH and H 2 O were significantly correlated. These findings suggest that Se significantly influences species diversity in Se-rich environments, enhancing beta diversity at high concentrations while reducing it at low concentrations, with both moisture content and pH serving as fine-tuning factors in the dynamics of Se bioavailability and ecological processes (Sylvain et al., 2014 ; Kökdener and Şahin Yurtgan, 2022 ). It is well established that selenium is an essential element for animal survival, and its deficiency can negatively impact species viability (So et al., 2023 ). This study not only confirms the importance of selenium but also unexpectedly reveals that Se enhances species diversity at high concentrations. This finding challenges the conventional understanding that high selenium concentrations typically inhibit growth and potentially affect survival (Xiao et al., 2018 ; Yue et al., 2021 ). The pivotal role of earthworms in soil ecosystems (Butenschoen et al., 2009 ; Singh et al., 2016 ) is further underscored by the significant positive correlation observed between Se concentration and the abundance of earthworm species, such as P. excavates (Fig. 6 b and Appendix D). Additionally, earthworms can reduce local heavy metal content (Singh et al., 2016 ), which may indirectly contribute to Se tolerance. Previous research has highlighted the importance of moisture and pH for earthworm distribution (Singh et al., 2020 ). This study, however, found no significant correlation between the beta diversity of P. excavatus and moisture or pH levels, suggesting that selenium concentration is the predominant factor influencing earthworm distribution in Se-enriched areas. Aligned with the finding that insects exhibit a certain level of tolerance to Se and have developed mechanisms to control its absorption into their tissues (Lalitha et al., 1994 ). In Yutangba’s soil, Se was widely enriched, providing insects with additional nutrients (Guo, 2012 ). This nutrient benefits plant absorption and utilization (Guo, 2012 ; Wang et al., 2022a ; Chen et al., 2023 ), as evidenced in Cardamine hupingshanesis (Brassicaceae), a plant highly tolerant to Se (Yuan et al., 2013 ). It also influences the distribution of soil microbial populations, including Se-tolerant bacteria (Wang et al., 2022b , 2023 ; Yuan et al., 2023 ; Zang et al., 2023 ). Consequently, these soil nutrients may directly and indirectly impact soil invertebrate biodiversity (Yang et al., 2022 ). Despite difference in absorption efficiency between selenite and selenate, their Se bioavailability remains roughly equivalent due to the metabolic conversion of selenate to selenite and substantial pre-metabolic excretion of excess selenate (Burk and Hill, 2015 ; Vickerman et al., 2004 ). Additionally, parasitic insects expose larvae directly to organic selenium rather than selenate, thereby circumventing selenium toxicity (Vickerman et al., 2004 ). This mechanism may contribute to the higher Se tolerance observed in native species (De La Riva and Trumble, 2016 ). Due to the relatively lower concentration of water-soluble Se in Enshi’s aquatic environments (Shao, 2020 ), a Se gradient forms in small streams, enabling species to select optimal Se levels for growth and reproduction within the high Se soil conditions. Furthermore, certain native species have developed unique adaptabilities to selenium. For example, the abundance of ants like O. troglodytes , L. emarginatus , and L. niger is positively correlated with Se concentrations, which is consistent with research indicating high Se tolerance in ants relative to other native species (De La Riva and Trumble, 2016 ). This correlation implies that extended exposure to Se-rich environments, such as mine caves, may have led to greater Se tolerance in these invertebrates compared to those in low Se areas. Long-term exposure to Se appears to enhance Se tolerance in soil invertebrates in such areas, supporting our hypothesis. In summary, environmental factors intricately impact soil health and biodiversity. In Se-enriched habitats, Se significantly shapes species diversity, with its bioavailability being further modulated by moisture and pH levels, thus finely tuning the ecological dynamics in these regions. Notably, the sampled site, a natural Se mine, indicates that certain native species have likely adapted to high-Se environments. Balanced Se concentrations in soil enhance species diversity. This study elucidates the extensive implications of Se on invertebrate biodiversity and provides valuable insights into the intricate interplay between Se and soil ecosystem health. 5 Conclusions This study conducted at Yutangba, within the Se-rich Enshi region, examined the correlation between soil invertebrate diversity and environmental variables, with a specific emphasis on Se, moisture, and pH. The findings revealed a substantial impact of these factors on the alpha diversity of soil invertebrates. High alpha diversity areas demonstrated a close association between beta diversity and soil moisture as well as Se content. In contrast, regions with fluctuating pH and moisture levels exhibited beta diversity that was independent of Se concentrations. These data suggest that in Se-rich areas, Se primarily influences beta diversity, whereas in low-Se conditions, moisture content also significantly regulates beta diversity. Declarations Author Contribution Conceptualization, Y.F., B.M; methodology, B.M., X.-L.F.; software, B.M., X.-L.F.; formal analysis, B.M., X.-L.F.; investigation, Y.F.; resources, Y.F.; writing—original draft preparation, Y.F., B.M., H.-L.L.; writing—review and editing, Y.F., Y.-L.X.; visualization, B.M.; supervision, Y.F.; project administration, Y.F.; funding acquisition, Y.F.; All authors have read and agreed to the published version of the manuscript. Acknowledgments This study was supported by the National Natural Science Foundation of China (NSFC) (Grant No. 32070483, 31460572), Natural Science Foundation of Hubei Province (Grant No. 2020CFB757), Scientific Research Starting Foundation for Ph.D. of Huanggang Normal University (Grant No. 2020010, 2042024378), Scientific Research Project of Education Department of Hubei Province (Grant No. Q20232901), Huanggang Normal University Major Project Incubation Plan-Funded Program (Grant No. 204202315204). Data availability The data obtained in this study are available from the NCBI under the GenBank number PRJNA1055709. All other data are available in this text and in the Appendixes. References Bird S, Coulson R N, Crossley D A (2000). Impacts of silvicultural practices on soil and litter arthropod diversity in a Texas pine plantation. Forest Ecology and Management, 131: 65-80. Briones M J I. (2018). 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Ecological Engineering, 90: 1-5. So J, Choe D H, Rust M K, Trumble J T, and Lee C Y (2023). The impact of selenium on insects. Journal of economic entomology, 116(4): 1041-1062. Sylvain Z A, Wall D H, Cherwin K L, Peters D P, Reichmann L G, and Sala O E (2014). Soil animal responses to moisture availability are largely scale, not ecosystem dependent: insight from a cross-site study. Global change biology, 20(8): 2631-2643. The Ministry of Health of the People's Republic of China. (2017). Determination of selenium in foods (GB 5009.93—2017). (in Chinese). Vickerman D B, Trumble J T, George G N, Pickering II, Nichol H (2004). Selenium biotransformations in an insect ecosystem: effects of insects on phytoremediation. Environmental science & technology, 38(13): 3581-3586. Wall D, Bradford M, St John M, Trofymow J, Behan-Pelletier V, Bignell D, Dangerfield J, Parton W, Rusek J, Voigt W , et al. (2008). Global decomposition experiment shows soil animal impacts on decomposition are climate. Global change biology, 14(11): 2661-2677. Wang P, Yan Z, Yang S, Wang S, Zheng X, Fan J, Zhang T (2019). Environmental DNA: An Emerging Tool in Ecological Assessment. Bulletin of Environmental Contamination and Toxicology, 103(5): 651-656. Wang M, Sun M, Zhao Y, Shi Y, Sun S, Wang S, Zhou Y, Chen L (2023). Seasonal changes of soil microbiota and its association with environmental factors in coal mining subsidence area. AMB Express, 13(1): 147. Wang Y, Kong L, Wang K, Tao Y, Qi H, Wan Y, Wang Q, Li H (2022a). The combined impacts of selenium and phosphorus on the fate of arsenic in rice seedlings (Oryza sativa L.). Chemosphere, 08(Pt 3): 136590. Wang Z, Huang W, Pang F. Selenium in Soil-Plant-Microbe: A Review (2022b). Bulletin of environmental contamination and toxicology, 108(2): 167-181. Wen H, Jean C, Hu R, Fan H, Chang B, and Yang G (2007). Discovery and indicative significance of the largest selenium isotopic fractionation in Yutangba selenium deposit in Hubei province. Chinese Science Bulletin(in Chinese) 52(17): 1845-1848. Wickham H (2016). ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag, New York. Wu B, Jiao X, Sun A, Li F, He J Z, and Hu H W (2023). Precipitation seasonality and soil pH drive the large-scale distribution of soil invertebrate communities in agricultural ecosystems. FEMS microbiology ecology, 99(11): fiad131. Xiao K, Song M, Liu J, Chen H, Li D, and Wang K (2018). Differences in the bioaccumulation of selenium by two earthworm species (Pheretima guillemi and Eisenia fetida). Chemosphere, 202: 560-566. Yang H, Yang X, Ning Z, Kwon S Y, Li M L, Tack F M G, Kwon E E, Rinklebe J, Yin R (2022). The beneficial and hazardous effects of selenium on the health of the soil-plant-human system: An overview. Journal of hazardous materials, 422: 126876. Yao L, Gao Z, Yang Z, and Long H (2002). The formation of selenium-rich siliceous rocks in the Yutangba selenium deposit. Science in China Series D-Earth Sciences (in Chinese), 32(1): 54–63. Yuan L, Xia Z, He C (2023). A novel selenite-tolerant rhizosphere bacterium Wautersiella enshiensis sp. nov., isolated from Chinese selenium hyperaccumulator, Cardamine hupingshanensis. Journal of basic microbiology, 63(11): 1305-1315. Yuan L, Zhu Y, Lin Z Q, Banuelos G, Li W, Yin X (2013). A novel selenocystine-accumulating plant in selenium-mine drainage area in Enshi, China. PLoS One, 8(6): e65615. Yue S, Huang C, Wang R, and Qiao Y (2021). Selenium toxicity, bioaccumulation, and distribution in earthworms (Eisenia fetida) exposed to different substrates. Ecotoxicology and environmental safety, 217: 112250. Zang H, Tong X, Yuan L, Zhang Y, Zhang R, Li M, Zhu R (2023). Life-cycle selenium accumulation and its correlations with the rhizobacteria and endophytes in the hyperaccumulating plant Cardamine hupingshanensis. 264:115450. Zhang H Y, Zhang A R, Lu Q B, Zhang X A, Zhang Z J, Guan X G, Che T L, Yang Y, Li H, Liu W , et al. (2021). Association between fatality rate of COVID-19 and selenium deficiency in China. BMC infectious diseases, 21(1): 452. Zhang X W (2019). Environmental DNA Shaping a new era of ecotoxicological research. Environmental Science & Technology, 53(10): 5605-5612. Zhu J M, Zheng B S, Wang Z L, Zhu G W, Mao D J, and Su H C (1998). Distribution pattern of soil selenium and its influencing factors in the micro-local high-selenium environment of Yutangba. Environmental Science (in Chinese), 19(6): 33–36. Zhu J, Zheng B, and Liu S R (2000). Some new forms of native selenium and their genetic investigation. Acta Mineralogica Sinica, 20(4): 337-341. Additional Declarations No competing interests reported. Supplementary Files Supplementarymaterial.docx Appendixes The supplementary materials include the following Appendixes: Appendix A: Atomic fluorescence spectrometer; Appendix B Analysis data of environmental factors at different sites;Appendix C Length distribution of valid sequences. Appendix D: Correlation coefficients and significance tests obtained from the Mantel test between different species and environmental factors. Cite Share Download PDF Status: Published Journal Publication published 29 Jan, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 14 Nov, 2024 Reviews received at journal 13 Nov, 2024 Reviews received at journal 03 Nov, 2024 Reviewers agreed at journal 29 Oct, 2024 Reviewers agreed at journal 29 Oct, 2024 Reviewers invited by journal 28 Oct, 2024 Editor assigned by journal 28 Oct, 2024 Editor invited by journal 28 Oct, 2024 Submission checks completed at journal 25 Oct, 2024 First submitted to journal 13 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5255864","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":370416548,"identity":"534f32f5-c873-4381-8206-3268490e03db","order_by":0,"name":"Bin Mao","email":"","orcid":"","institution":"Huanggang Normal University","correspondingAuthor":false,"prefix":"","firstName":"Bin","middleName":"","lastName":"Mao","suffix":""},{"id":370416549,"identity":"175450c3-6f83-4068-af15-90d227737889","order_by":1,"name":"XiangLiang Fang","email":"","orcid":"","institution":"Huanggang Normal University","correspondingAuthor":false,"prefix":"","firstName":"XiangLiang","middleName":"","lastName":"Fang","suffix":""},{"id":370416550,"identity":"5cfeb745-ec1c-425c-9330-29689c8d2ca2","order_by":2,"name":"HongLing Lei","email":"","orcid":"","institution":"Hubei University for Nationalities","correspondingAuthor":false,"prefix":"","firstName":"HongLing","middleName":"","lastName":"Lei","suffix":""},{"id":370416551,"identity":"ad5083dd-7e3c-451c-872c-3319422ca80a","order_by":3,"name":"YunLi Xiao","email":"","orcid":"","institution":"Huanggang Normal University","correspondingAuthor":false,"prefix":"","firstName":"YunLi","middleName":"","lastName":"Xiao","suffix":""},{"id":370416552,"identity":"5cac5260-d5b1-4cf7-8e6f-ceabd946f470","order_by":4,"name":"Yue Fu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+ElEQVRIiWNgGAWjYBAC9gYQWSHBw8/M2Pj4R4WEnDwhLTwHQOQZGxnJ9uZmY4YzFsaGDcRoYWxLszE4c7xNmrGtIpHhACEtEjlmEh/YDvMY3EhskC6cJ5HA2MD88NENAlokZ/Ac5pEEajGeuU0ij52Bzdg4B48We6AWaR6Jwzx8QC0JvNskihkbeNik8WkB2SL9x+AwDwNQywHeORJAkhgtDAlpPAJnDjY28zYQo4XnWbFlzwEbHsn2xmbGGcckjA2bCfiFhz15442f/yTs+ZnZn//4UFMnJ8/e/PAxPi0MDBwGaALMeJWDAPsDgkpGwSgYBaNghAMA08RLW6UA8xUAAAAASUVORK5CYII=","orcid":"","institution":"Hubei Zhongke Research Institute of Industrial Technology, Huanggang Normal University","correspondingAuthor":true,"prefix":"","firstName":"Yue","middleName":"","lastName":"Fu","suffix":""}],"badges":[],"createdAt":"2024-10-13 14:53:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5255864/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5255864/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-87917-5","type":"published","date":"2025-01-29T15:57:39+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":67647967,"identity":"cee902d0-4524-4cff-a90b-3756c21da54c","added_by":"auto","created_at":"2024-10-28 11:16:40","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":873136,"visible":true,"origin":"","legend":"\u003cp\u003eSampling sites near selenium mines. (a) Locations of 11 sampling sites in Enshi City, Hubei Province. The stream was illustrated based on relative positioning. (b) Selenium cave at site A. (c) Sampling site at site G. Scale bar: 50m.\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-5255864/v1/7287f6670815c289e7f3af54.png"},{"id":67647966,"identity":"f5d62728-88eb-407f-a092-5466cc217e72","added_by":"auto","created_at":"2024-10-28 11:16:34","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":125518,"visible":true,"origin":"","legend":"\u003cp\u003eEnvironmental factor Analysis. Relationships between months (a-c) and sampling points (d-f) with environmental factors, including Se (μg/g dry soil), pH, and H\u003csub\u003e2\u003c/sub\u003eO (%), were examined. Variations in environmental factors across sites were assessed using the Kruskal-Wallis test with subsequent pairwise comparisons, as detailed in Appendix B.\u003c/p\u003e","description":"","filename":"Fig.2.png","url":"https://assets-eu.researchsquare.com/files/rs-5255864/v1/317e6d0e9abf28f7e69d6ffa.png"},{"id":67647961,"identity":"194428db-de13-4bf3-8fed-40870ee70b2d","added_by":"auto","created_at":"2024-10-28 11:16:34","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":352721,"visible":true,"origin":"","legend":"\u003cp\u003eTaxonomic composition and differential relative abundance of soil invertebrates. The top 10 relative abundance groups for phyla (a), classes (b), orders (c), and families (d) were visualized, with each taxonomic group represented by a distinct color.\u003c/p\u003e","description":"","filename":"Fig.3.png","url":"https://assets-eu.researchsquare.com/files/rs-5255864/v1/ccf2f8946d34ef38618e52cd.png"},{"id":67649125,"identity":"c02fe692-0abb-4035-ad4d-3e42b6c40842","added_by":"auto","created_at":"2024-10-28 11:24:34","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":247102,"visible":true,"origin":"","legend":"\u003cp\u003eThe alpha diversity analysis of OTUs across various sample sites. Analysis of variance (ANOVA) results for alpha diversity indices include observed species (a), ACE (b), and Chao1 (c). Panel (d) illustrates the rarefaction plot of richness at different sample sites, while panel (e) features a heatmap of alpha diversity indices across these sites. The lower-left section depicts correlations among alpha diversity indices at different sites. The upper-right section displays the results of CCorA between alpha diversity indices and environmental factors.\u003c/p\u003e","description":"","filename":"Fig.4.png","url":"https://assets-eu.researchsquare.com/files/rs-5255864/v1/c81b860e19971ca1d465f45c.png"},{"id":67647963,"identity":"ce364c38-3dcd-4c71-b15f-4efa85c87c1d","added_by":"auto","created_at":"2024-10-28 11:16:34","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":131448,"visible":true,"origin":"","legend":"\u003cp\u003ePCoA and CCA of soil organisms. PCoA based on Bray–Curtis distances and PERMANOVA of the archaeal community were performed. Differences between PCoA1 and PCoA2 (a) and PCoA1 and PCoA3 (b) across various sample sites were compared. (c) CCA illustrated the relationship between sample sites and environmental factors. (d) Bar graph showing the explanatory power of environmental factors on community structure differences, determined by the envfit test using the vegan package. The x-axis denoted the environmental factors, and the y-axis indicated the percentage of variance explained. Each bar represented a specific environmental factor, and significance levels (\u003cem\u003eP-\u003c/em\u003evalues) were indicated by asterisks (*\u003cem\u003eP \u0026lt;\u003c/em\u003e0.05, **\u003cem\u003eP \u0026lt;\u003c/em\u003e 0.01).\u003c/p\u003e","description":"","filename":"Fig.5.png","url":"https://assets-eu.researchsquare.com/files/rs-5255864/v1/1e2934a739dfb58b120d148b.png"},{"id":67647962,"identity":"4628a6ef-2b45-4173-ab3e-f3a0730521e3","added_by":"auto","created_at":"2024-10-28 11:16:34","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":93556,"visible":true,"origin":"","legend":"\u003cp\u003eThe relationships between species diversity and environmental factors based on the Mantel test. (a) The heatmap displays correlations between various environmental factors, with each row and column representing a specific factor. The color intensity indicated the strength and direction of the correlation coefficient, where darker shades signified stronger positive or negative correlations, and lighter shades denoted weaker or nonsignificant correlations. Connecting lines between the sites and environmental factors highlighted significant Mantel test correlations. (b) The Mantel correlogram of alpha diversity, Se, H\u003csub\u003e2\u003c/sub\u003eO, and pH showed red dots indicating statistical significance at \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"Fig.6.png","url":"https://assets-eu.researchsquare.com/files/rs-5255864/v1/65b923e172b912a3f33123c7.png"},{"id":67647965,"identity":"e177632a-f8e5-401e-8fa1-8326e29ede64","added_by":"auto","created_at":"2024-10-28 11:16:34","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":283171,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap analysis of soil organisms in Se-enriched areas based on environmental factors, using a Mantel test with permutation, shows a Spearman’s correlation coefficient. *\u003cem\u003eP\u003c/em\u003e value \u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"Fig.7.png","url":"https://assets-eu.researchsquare.com/files/rs-5255864/v1/12a3881510ec3844eb183ac2.png"},{"id":75351937,"identity":"3bb7edae-0990-45b6-bab6-50d0dcb3946c","added_by":"auto","created_at":"2025-02-03 16:12:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2790713,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5255864/v1/826fee0c-dc81-4e29-ab9f-462c02e33f4e.pdf"},{"id":67647964,"identity":"35bfed5d-82cc-404c-8c0e-3cf08a1d4da2","added_by":"auto","created_at":"2024-10-28 11:16:34","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":57730,"visible":true,"origin":"","legend":"\u003cp\u003eAppendixes\u003c/p\u003e\n\u003cp\u003eThe supplementary materials include the following Appendixes: Appendix A: Atomic fluorescence spectrometer; Appendix B Analysis data of environmental factors at different sites;Appendix C Length distribution of valid sequences. Appendix D: Correlation coefficients and significance tests obtained from the Mantel test between different species and environmental factors.\u003c/p\u003e","description":"","filename":"Supplementarymaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-5255864/v1/f958dd750c0559d24e91d5ee.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Unexpected species diversity in the understanding of selenium- containing soil invertebrates","fulltext":[{"header":"Highlight","content":"\u003col\u003e\n \u003cli\u003eSoil invertebrates in Se-rich areas are more tolerant to Se.\u003c/li\u003e\n \u003cli\u003eMoisture and pH fine-tune soil invertebrate diversity in Se-rich areas.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eSome Diptera and Formicidae species diversity increased in Se-rich areas.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"1 Introduction","content":"\u003cp\u003eThe soil microbiome is crucial for ecosystem health, influencing nutrient cycling, organismal growth, and climate regulation through greenhouse gas emissions (Dantas and Sommer, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Soil invertebrates, beyond their role in decomposition, actively break down organic matter via enzymatic processes, thereby affecting both soil and plant dynamics (Joly et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Griffiths et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Kane et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Studies demonstrate that invertebrates independently degrade organic materials without microbial aid, significantly contributing to the global recycling of plant matter (Joly et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Kane et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Moreover, soil organisms are instrumental in soil formation and development, modifying soil properties, facilitating material translocation, and converting energy (Wall et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Garc\u0026iacute;a-Palacios et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Briones, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Griffiths et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), all of which are vital for ecosystem material cycling.\u003c/p\u003e \u003cp\u003eStudies examining the relationship between soil invertebrates and environmental conditions have identified parent rock type, soil pH, nutrient availability, organic matter content, and climate significantly influence the distribution of soil animal communities (Bird et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Ponge et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Cassagne et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). These communities are key indicators of forest health and disturbances. Selenium (Se), an essential trace element for numerous organisms (National Research Council, 1983), exhibits beneficial or toxic effects based on its concentration (Schwarz and Foltz, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1957\u003c/span\u003e; See et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; MacFarquhar et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Soil pH significantly affects animal diversity and the composition of functional communities, with distinct decomposer species thriving in either acidic or alkaline environments (Schaefer, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e1990\u003c/span\u003e; Salmon et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Pollierer et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This indicates that regional abiotic factors, such as soil pH, exert a greater influence on decomposer communities than local biotic factors. Soil pH, determined by parent rock and stand type, is fundamental to the availability and structure of resources within soil food webs (Ruess et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Lauber et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Rousk et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Consequently, soil Se content and pH are primary determinants of soil organism distribution.\u003c/p\u003e \u003cp\u003eSe distribution exhibits significant variability across the globe, with concentrations reaching up to 1000 mg/kg in certain Se-rich regions, juxtaposed with areas where it is nearly nonexistent (Hartikainen, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Outside these enriched zones, Se is also found in uranium and phosphate ore deposits. Yutangba, recognized worldwide for its high Se content, is notable for containing the only known independent Se deposit, located within black rock series (Yao et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Zhu et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Wen et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Despite its small area of merely 0.01 km\u0026sup2;, Yutangba demonstrates considerable heterogeneity in soil Se distribution, predominantly shaped by topographical variations and soil particle size (Zhu et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). Soil organisms significantly influence soil formation, yet the effect of the region's uneven Se distribution on their distribution is not well understood. Soil invertebrates near the ancient Se mine have likely evolved adaptive mechanisms due to extended exposure (De La Riva and Trumble, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Consequently, it is hypothesized that Se-rich environments support greater soil invertebrate diversity, with factors such as Se content and soil pH playing substantial roles in shaping this diversity.\u003c/p\u003e \u003cp\u003eEnvironmental DNA (eDNA) technology, utilizing molecular sequence analysis of genetic material in environmental samples, allows for efficient identification and monitoring of biological species through comparison with reference species databases. This technology marks a substantial advancement in biodiversity science since the early 21st century (Wang et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2019\u003c/span\u003e, Zhang \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). This study employed eDNA technology to compile foundational data on the soil animal community in the region. By analyzing the relationships between soil invertebrate diversity indicators and soil properties such as Se content, the research established a framework for understanding the association between soil Se levels and soil fauna and monitoring soil ecological health. The results offer valuable insights for future research into the characteristics and evolutionary dynamics of soil animal diversity in the area.\u003c/p\u003e"},{"header":"2 Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Sample collection and the separation of soil organisms\u003c/h2\u003e \u003cp\u003eThe designated soil sampling route at Yutangba, Enshi City, Hubei Province, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, targeted the central zone of a distinct Se reserve, beginning at sites K and A. The route traced two watercourses, merging at site G and then extending downstream. Eleven sampling locations were established, with three subplots at each site arranged in S-shaped or daisy-shaped patterns to ensure randomness and equitable volume, representing a composite of multiple points. Soil sampling was conducted thrice at each of the 11 sites in July, September, and November 2015, yielding 99 soil specimens. Post-sampling, the soil specimens were transported to the laboratory, separated using modified Tullgren funnels, and subjected to a 48-hour drying period. The dried samples were then categorized and preserved in an 85% ethanol solution. For environmental DNA analysis, 33 composite samples were prepared from the corresponding sample points.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Determination of moisture content\u003c/h2\u003e \u003cp\u003eUpon returning to the laboratory, labeled soil samples were collected. Each sample was weighed in a clean culture dish, recording the mass as M\u003csub\u003edish\u003c/sub\u003e. After adding the soil to the dish, the combined mass was documented as M\u003csub\u003edish+soil sample\u003c/sub\u003e. Samples were then dried to a constant weight in a temperature-controlled drying oven, and the mass was noted as M\u003csub\u003edish\u003c/sub\u003e+\u003csub\u003edried\u003c/sub\u003e. Moisture content of the soil sample was calculated using the formula: Moisture content (%) = [(Mdish\u0026thinsp;+\u0026thinsp;soil sample - Mdish\u0026thinsp;+\u0026thinsp;dried) / (Mdish\u0026thinsp;+\u0026thinsp;dried - Mdish)] \u0026times; 100%.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Determination of selenium content\u003c/h2\u003e \u003cp\u003eDetermining soil Se concentration adhered to the Chinese National Standard GB 5009.93\u0026mdash;2017 (The Ministry of Health of the People's Republic of China, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Dried soil samples were ground and sieved through a 200-mesh screen before being stored in sealed plastic bags. A precise 0.05 g portion of each soil sample was weighed and placed in a digestion tube. To enable digestion, 8 mL of concentrated nitric acid, 2 mL of concentrated hydrochloric acid, and 2 mL of hydrogen peroxide were added to each tube, with the samples soaking for 24 hours. The digestion process entailed a gradual temperature increase in a digestion furnace until the solution achieved clarity and transparency. The solution volume was then reduced, and hydrochloric acid was added to maintain clarity. The digested solutions containing Se were transferred to volumetric flasks and diluted to a known volume with ultrapure water. Analysis was performed using an AFS-922 dual-channel atomic fluorescence spectrometer, as detailed in Appendix A. The Se content, expressed as micrograms per gram (\u0026micro;g/g), was calculated by comparing the initial weight of the soil samples with the final volume of the digested solutions for subsequent analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Determination of pH\u003c/h2\u003e \u003cp\u003ePost moisture content assessment, the remaining soil samples were exposed to natural air drying and subsequently sieved through a 1 mm mesh. A 20-gram portion of the sieved, air-dried soil was weighed and transferred into a 120 ml wide-mouth bottle with a cover. Then, 100 ml of CO2-free distilled water was added, maintaining a soil-to-water ratio of 1:5. The mixture was blended for 2 minutes and allowed to settle for 30 minutes. The pH of the resulting solution was measured with a pH meter, and the data were recorded.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 DNA extraction and PCR amplification\u003c/h2\u003e \u003cp\u003eDNA from soil eukaryotic invertebrates was extracted from 33 samples using the E.Z.N.A.\u0026reg; Soil DNA Kit (Omega Biotek, Norcross, GA, U.S.), adhering to the manufacturer's protocols. The COI gene underwent PCR amplification under these conditions: initial denaturation at 95\u0026deg;C for 2 minutes, followed by 25 cycles of 95\u0026deg;C for 30 seconds, 55\u0026deg;C for 30 seconds, and 72\u0026deg;C for 30 seconds, with a final extension at 72\u0026deg;C for 5 minutes. Two oligonucleotide primers, mlCOlintF (5\u0026rsquo;-GGWACWGGWTGAACWGTWTAYCCYCC-3\u0026rsquo;) and jgHCO2198 (5\u0026rsquo;-TAIACYTCIGGRTGICCRAARAAYCA-3\u0026rsquo;), were utilized. Each PCR was performed in triplicate in a 20 \u0026micro;L volume containing 4 \u0026micro;L of 5 \u0026times; FastPfu Buffer, 2 \u0026micro;L of 2.5 mM dNTP mix, 0.8 \u0026micro;L of each primer at 5 \u0026micro;M, 0.4 \u0026micro;L of FastPfu Polymerase, and 10 ng of DNA template. DNA fragments were isolated from 2% agarose gels and purified using the AxyPrep DNA Gel Extraction Kit (Axygen Biosciences, Union City, CA, U.S.), following the manufacturer's guidelines precisely.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 DNA sequencing and data processing\u003c/h2\u003e \u003cp\u003eConcentrations of the PCR products were measured using the Qubit\u0026reg; 3.0 Fluorometer (Life Invitrogen). Equal molar amounts of the twenty-four amplicons, tagged with a specific barcode, were combined to create a composite sample. This composite DNA was utilized to construct a paired-end library suitable for Illumina sequencing platforms, following the provided protocol for genomic DNA library preparation. The library underwent paired-end sequencing (2 \u0026times; 250 bp) on an Illumina MiSeq system (provided by Shanghai BIOZERON Co., Ltd.), adhering to the standard sequencing protocols.\u003c/p\u003e \u003cp\u003eRaw fastq files were processed with custom Perl scripts to demultiplex data using unique barcode sequences for each sample. The demultiplexing adhered to stringent criteria: (i) Reads of 250 base pairs were truncated if a sliding window of 10 bases had an average quality score below 20, and truncated reads shorter than 50 base pairs were discarded. (ii) Reads with exact barcode matches, more than 2 nucleotide mismatches in primer sequences, or ambiguous nucleotide codes were excluded. (iii) Overlapping sequences were assembled only if the overlap exceeded 10 base pairs, and reads failing to meet this overlap requirement were rejected.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Statistical analysis\u003c/h2\u003e \u003cp\u003eStatistical analyses and visualizations were conducted using R (version 4.3.0) and the ggplot2 package (Wickham, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), except where noted. Data from eleven sample site groups were assessed for normality. Normally distributed data were analyzed using ANOVA and the least significant difference (LSD) multiple comparison test. Non-normally distributed data were evaluated using the Kruskal-Wallis (KW) test and the Wilcoxon test. Statistical significance was set at \u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003eSpecies richness estimation and diversity comparison among samples employed rarefaction and extrapolation methods. Invertebrate alpha diversity and abundance were assessed using the Chao1 estimator, Abundance-based Coverage Estimator (ACE), and observed species index, calculated via R scripts. Relationships between alpha indices and environmental variables were examined through Canonical Correlation Analysis (CCorA). Beta diversity of invertebrates was analyzed using PCoA based on Bray-Curtis distances and PERMANOVA, utilizing the vegan package in R (Oksanen, 2002). Soil community structure differences were investigated with a nonparametric multivariate analysis of variance (Adonis).\u003c/p\u003e \u003cp\u003eCanonical correspondence analysis (CCA) assessed the relationships between environmental variables and species/operational taxonomic units (OTUs). The envfit test within the R package vegan subsequently identified environmental factors significantly impacting species distribution. Additionally, Mantel correlograms with 9,999 permutations tested the significance of correlation trends in concentration changes. The Mantel test further examined correlations between species and environmental variables, including Se, H\u003csub\u003e2\u003c/sub\u003eO, and pH, using Spearman's rank correlation, with significance determined by 9,999 permutations. Significant correlations were defined by Spearman\u0026rsquo;s rho values exceeding 0.2 and P-values below 0.05. Data visualization was performed in Cytoscape (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.cytoscape.org\u003c/span\u003e\u003cspan address=\"http://www.cytoscape.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to elucidate the relationships between species and environmental factors.\u003c/p\u003e \u003cp\u003eCanonical correspondence analysis (CCA) assessed the relationships between environmental variables and species/operational taxonomic units (OTUs). Following CCA, the envfit test in the R package vegan identified specific environmental factors significantly impacting species distribution. Additionally, Mantel correlograms with 9,999 permutations were utilized for significance testing to assess the correlation trends of concentration changes. Moreover, the Mantel test was conducted to explore correlations between species and environmental variables including Se, H\u003csub\u003e2\u003c/sub\u003eO, and pH, using Spearman's rank correlation, with significance assessed through 9999 permutations. A Spearman\u0026rsquo;s rank correlation coefficient (Spearman\u0026rsquo;s rho) greater than 0.6 and a significance level (\u003cem\u003eP\u003c/em\u003e) less than 0.05 were considered significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"3 Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Analysis of environmental factors\u003c/h2\u003e \u003cp\u003eSamples were collected from 11 locations adjacent to the stream, where two streams converge downstream of site G and upstream of site F. Site A was positioned at the selenium cave, while site K was located near selenium mining waste (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo assess environmental factor variations, month and site relationships were analyzed. The results showed no significant interactions for Se (F \u003csub\u003e(10, 11)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;1.75, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.19), H\u003csub\u003e2\u003c/sub\u003eO (F \u003csub\u003e(10, 11)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.39, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.93), and pH (F \u003csub\u003e(10, 11)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;1.42, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.29). Then, variations in pH, H\u003csub\u003e2\u003c/sub\u003eO, and Se were assessed individually across months and sites. Results showed no significant differences among the months (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea-c, all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05), but significant site-specific differences were observed (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed-f, all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Appendix B). All sites exhibited acidic pH values below 7.0, with the highest at 6.4, suggesting a generally weakly acidic soil environment. Sites with higher Se concentrations had more acidic pH levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed-e). Soil water content ranged from 27.6\u0026ndash;48.7%, peaking at site C with 62.56% and the lowest at site A. Despite site A's low water content, it had a high Se concentration of 254.37 \u0026micro;g/g, indicating that both Se concentration and water content influence soil organism diversity.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Taxa composition and abundance analysis\u003c/h2\u003e \u003cp\u003eIn July, September, and November 2015, 33 samples were collected from 11 sites. COI amplification sequencing produced 1,478,635 circular consensus sequencing (CCS) sequences with an average length of 312.23 bp. Optimized sequences totaling 1,468,280, ranging from 301 to 350 bp, represented 99.30% of the total, ensuring annotation accuracy (Appendix C).\u003c/p\u003e \u003cp\u003eAnalysis of taxonomic composition and differential relative abundance of soil invertebrates revealed distinct patterns across various sites (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The phyla Arthropoda and Annelida consistently exhibited high abundances. Within these groups, \u003cem\u003eDiptera\u003c/em\u003e (including \u003cem\u003eCulicidae\u003c/em\u003e and \u003cem\u003eTachinidae\u003c/em\u003e) in the \u003cem\u003eInsecta\u003c/em\u003e class and \u003cem\u003eHaplotaxida\u003c/em\u003e (including \u003cem\u003eHenicopidae\u003c/em\u003e and \u003cem\u003eMegascolecidae\u003c/em\u003e) in the \u003cem\u003eChilopoda\u003c/em\u003e class were particularly prominent. Additionally, sites C, H, and I, which recorded the highest humidity levels, showed a greater abundance of \u003cem\u003eAnopheles mosquitoes\u003c/em\u003e, indicating their preference for aquatic environments. Variations in environmental factors, such as Se concentration and water content, are linked to the distribution and abundance patterns of soil invertebrates.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Alpha diversity signatures\u003c/h2\u003e \u003cp\u003eA comparative analysis was conducted to investigate the impact of various sites and environmental factors on alpha diversity. Despite site B having lower Se concentration but higher pH and water content compared to site A (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed-f), alpha diversity was relatively higher at site B (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea-d). This suggests that pH and water content, among other environmental factors, significantly influence soil invertebrate alpha diversity, shaping biodiversity.\u003c/p\u003e \u003cp\u003eGiven the spatial distribution of sites along the stream, interrelated data from these locations exhibit notable correlations. Analysis of alpha indices across different sites revealed significant inter-site correlations (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ee). To further explore the relationships between alpha diversity indices and environmental variables, including Se, pH, and H\u003csub\u003e2\u003c/sub\u003eO, CCorA was performed. This analysis indicated a substantial correlation between environmental factors and alpha diversity at various sampling sites. Specifically, CCorA results demonstrated a strong correlation between alpha diversity indices and environmental variables (canonical correlation coefficient\u0026thinsp;=\u0026thinsp;0.85, \u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.014; Wilks' statistic\u0026thinsp;=\u0026thinsp;0.20, df\u0026thinsp;=\u0026thinsp;24) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ee). These data highlight the robust association between environmental factors and alpha diversity.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Beta diversity\u003c/h2\u003e \u003cp\u003ePCoA of OTU data on species diversity indicated that three axes accounted for 21.5% of the variance (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea-b). The composition of invertebrates in the Yutangbae area was significantly different among the various sites (PERMANOVA R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.37, \u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.001), while no significant differences were observed among different months (PERMANOVA R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.03, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.23). It suggests that spatial variations have a greater impact on soil invertebrate diversity than temporal variations. The combined CCA and envfit analysis identified significant correlations between environmental factors such as Se, water content, and pH with variations in species composition within soil animal communities (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec-d). This analysis highlighted the substantial impact of Se and pH on the structure and dynamics of these communities. R\u003csup\u003e2\u003c/sup\u003e values (0.31, 0.60, and 0.68) revealed that Se, H\u003csub\u003e2\u003c/sub\u003eO, and pH accounted for 31%, 60%, and 68% of the observed variation, respectively, with low \u003cem\u003eP-\u003c/em\u003evalues of 0.005, 0.001, and 0.001, confirming statistical significance. These results highlight the essential roles of Se, H\u003csub\u003e2\u003c/sub\u003eO, and pH in determining species composition. The strong association between environmental factors and community structure highlights the necessity of considering these variables in ecological studies and management.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAnalysis of environmental variables pH, H\u003csub\u003e2\u003c/sub\u003eO, and Se revealed no significant correlation between Se and the other two factors (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea). However, a significant positive correlation was identified between H\u003csub\u003e2\u003c/sub\u003eO and pH (rho\u0026thinsp;=\u0026thinsp;0.47, \u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.01) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea). The stability of pH across different sample sites may be due to their proximity to water sources, where pH remains relatively constant. A Mantel test was performed to evaluate the relationship between species beta diversity and specific environmental factors, revealing a significant positive correlation between species beta diversity and sample sites (\u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea). Additionally, H\u003csub\u003e2\u003c/sub\u003eO significantly influenced site A (rho\u0026thinsp;=\u0026thinsp;0.23, \u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.046). Sites A, J, and K, characterized by high species diversity and elevated Se concentrations (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed), suggest that Se significantly enhances species diversity at Se-enriched areas.\u003c/p\u003e \u003cp\u003eTo analyze the relationship between species diversity and changes in environmental factors such as alpha diversity, Se content, H\u003csub\u003e2\u003c/sub\u003eO content, or pH, we used Mantel correlograms with 9999 permutations for significance tests (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb). Results indicate a significant negative correlation between species diversity and Se content in Se-rich areas with low soil Se (\u003cem\u003er =\u003c/em\u003e -0.52, \u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.008), implying a necessary Se threshold for soil invertebrate survival. Unexpectedly, in regions with high Se concentrations, a significant positive correlation emerges between species diversity and Se concentration (r\u0026thinsp;=\u0026thinsp;0.68, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;8E-4), indicating species tolerance to elevated Se levels. Furthermore, significant positive correlations were observed with high alpha diversity (r\u0026thinsp;=\u0026thinsp;0.39, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.036), high water content (r\u0026thinsp;=\u0026thinsp;0.78, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5E-04), and high pH (r\u0026thinsp;=\u0026thinsp;0.42, \u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;7E-4), suggesting that these environmental factors were also associated with species beta diversity.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Relationships between environmental variables and soil invertebrates\u003c/h2\u003e \u003cp\u003eCorrelation analysis between soil invertebrates and environmental factors (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e, Appendix D) identified significant associations for 83 distinct species with Se concentration, soil moisture content, and pH. Insects demonstrated notable correlations with environmental factors, with 74% of species belonging to the order Insecta. The majority of soil organisms exhibited a strong and statistically significant relationship with Se concentration, as 67% of the correlation coefficients (rho) exceeded 0.5. The Formicidae family (ants), including species such as \u003cem\u003eOdontomachus troglodytes\u003c/em\u003e, \u003cem\u003eLasius emarginatus\u003c/em\u003e, and \u003cem\u003eLasius niger\u003c/em\u003e, along with the Noctuidae family, such as \u003cem\u003eDiarsia rosaria\u003c/em\u003e, and \u003cem\u003eHaplotaxida\u003c/em\u003e, specifically \u003cem\u003ePerionyx excavates\u003c/em\u003e, showed a high correlation with Se. In contrast, the aquatic larvae of Diptera, such as \u003cem\u003eDrosophila littoralis\u003c/em\u003e, were strongly associated with moisture content. In addition, Coleoptera (beetles) exhibited a notable correlation with soil pH. The number of species associated with Se significantly exceeded those linked to water and pH, indicating that Se distribution and concentration had a more substantial impact on insect diversity and distribution. Furthermore, the correlation coefficient (rho) between species related to Se and water is typically higher than that between species related to pH. This suggests that Se and water may have a more direct and significant impact on insects, particularly during the larval stage when they are more sensitive to environmental changes. Although five species exhibited significant correlations with both Se concentration and pH, the correlation coefficients (rho) with Se were consistently higher than those with pH. This indicates that the abundance of these soil invertebrates is more significantly influenced by Se concentration.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eRobinson et al. (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) investigated the impact of soil temperature on the structure and diversity of invertebrate communities. Despite fluctuations in local moisture content and temperature regimes across different months, species diversity remained unaffected, suggesting that environmental conditions in Se-rich areas are relatively stable over time. Therefore, future research should focus on how spatial variations in these factors influence soil invertebrate diversity, rather than temporal changes.\u003c/p\u003e \u003cp\u003eSoil pH influences Se adsorption and desorption, thereby controlling its bioavailability. In acidic soils, Se predominantly exists as tetravalent selenite, forming stable complexes with iron and manganese oxides (Guo, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), which sequesters Se in the soil and maintains high Se levels. This study identified a correlation between soil moisture and pH, both affecting the distribution of soil invertebrate communities (Sylvain et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; K\u0026ouml;kdener and Şahin Yurtgan, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Rai et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Wu et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Soil pH regulates the adsorption and desorption of Se, affecting its bioavailability. In acidic soil, Se predominantly exists as tetravalent selenite, which forms stable complexes or precipitates with iron and manganese oxides (Guo, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), thus sequestering Se and maintaining high Se levels. Soil samples from Yutangba, generally exhibiting a weakly acidic environment, indicate that Se is primarily in its tetravalent form, potentially impacting soil health (Guo, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). High Se concentrations are often associated with more acidic pH levels, suggesting that pH significantly influences Se bioavailability in the Yutangba region. However, the content of Se showed no significant correlation with factors such as pH and H\u003csub\u003e2\u003c/sub\u003eO (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea), even though pH and H\u003csub\u003e2\u003c/sub\u003eO were significantly correlated. These findings suggest that Se significantly influences species diversity in Se-rich environments, enhancing beta diversity at high concentrations while reducing it at low concentrations, with both moisture content and pH serving as fine-tuning factors in the dynamics of Se bioavailability and ecological processes (Sylvain et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; K\u0026ouml;kdener and Şahin Yurtgan, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIt is well established that selenium is an essential element for animal survival, and its deficiency can negatively impact species viability (So et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This study not only confirms the importance of selenium but also unexpectedly reveals that Se enhances species diversity at high concentrations. This finding challenges the conventional understanding that high selenium concentrations typically inhibit growth and potentially affect survival (Xiao et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Yue et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The pivotal role of earthworms in soil ecosystems (Butenschoen et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Singh et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) is further underscored by the significant positive correlation observed between Se concentration and the abundance of earthworm species, such as \u003cem\u003eP. excavates\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb and Appendix D). Additionally, earthworms can reduce local heavy metal content (Singh et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), which may indirectly contribute to Se tolerance. Previous research has highlighted the importance of moisture and pH for earthworm distribution (Singh et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This study, however, found no significant correlation between the beta diversity of P. excavatus and moisture or pH levels, suggesting that selenium concentration is the predominant factor influencing earthworm distribution in Se-enriched areas.\u003c/p\u003e \u003cp\u003eAligned with the finding that insects exhibit a certain level of tolerance to Se and have developed mechanisms to control its absorption into their tissues (Lalitha et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). In Yutangba\u0026rsquo;s soil, Se was widely enriched, providing insects with additional nutrients (Guo, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). This nutrient benefits plant absorption and utilization (Guo, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2022a\u003c/span\u003e; Chen et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), as evidenced in \u003cem\u003eCardamine hupingshanesis\u003c/em\u003e (Brassicaceae), a plant highly tolerant to Se (Yuan et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). It also influences the distribution of soil microbial populations, including Se-tolerant bacteria (Wang et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2022b\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Yuan et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Zang et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Consequently, these soil nutrients may directly and indirectly impact soil invertebrate biodiversity (Yang et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Despite difference in absorption efficiency between selenite and selenate, their Se bioavailability remains roughly equivalent due to the metabolic conversion of selenate to selenite and substantial pre-metabolic excretion of excess selenate (Burk and Hill, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Vickerman et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Additionally, parasitic insects expose larvae directly to organic selenium rather than selenate, thereby circumventing selenium toxicity (Vickerman et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). This mechanism may contribute to the higher Se tolerance observed in native species (De La Riva and Trumble, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Due to the relatively lower concentration of water-soluble Se in Enshi\u0026rsquo;s aquatic environments (Shao, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), a Se gradient forms in small streams, enabling species to select optimal Se levels for growth and reproduction within the high Se soil conditions. Furthermore, certain native species have developed unique adaptabilities to selenium. For example, the abundance of ants like \u003cem\u003eO. troglodytes\u003c/em\u003e, \u003cem\u003eL. emarginatus\u003c/em\u003e, and \u003cem\u003eL. niger\u003c/em\u003e is positively correlated with Se concentrations, which is consistent with research indicating high Se tolerance in ants relative to other native species (De La Riva and Trumble, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). This correlation implies that extended exposure to Se-rich environments, such as mine caves, may have led to greater Se tolerance in these invertebrates compared to those in low Se areas. Long-term exposure to Se appears to enhance Se tolerance in soil invertebrates in such areas, supporting our hypothesis.\u003c/p\u003e \u003cp\u003eIn summary, environmental factors intricately impact soil health and biodiversity. In Se-enriched habitats, Se significantly shapes species diversity, with its bioavailability being further modulated by moisture and pH levels, thus finely tuning the ecological dynamics in these regions. Notably, the sampled site, a natural Se mine, indicates that certain native species have likely adapted to high-Se environments. Balanced Se concentrations in soil enhance species diversity. This study elucidates the extensive implications of Se on invertebrate biodiversity and provides valuable insights into the intricate interplay between Se and soil ecosystem health.\u003c/p\u003e"},{"header":"5 Conclusions","content":"\u003cp\u003eThis study conducted at Yutangba, within the Se-rich Enshi region, examined the correlation between soil invertebrate diversity and environmental variables, with a specific emphasis on Se, moisture, and pH. The findings revealed a substantial impact of these factors on the alpha diversity of soil invertebrates. High alpha diversity areas demonstrated a close association between beta diversity and soil moisture as well as Se content. In contrast, regions with fluctuating pH and moisture levels exhibited beta diversity that was independent of Se concentrations. These data suggest that in Se-rich areas, Se primarily influences beta diversity, whereas in low-Se conditions, moisture content also significantly regulates beta diversity.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization, Y.F., B.M; methodology, B.M., X.-L.F.; software, B.M., X.-L.F.; formal analysis, B.M., X.-L.F.; investigation, Y.F.; resources, Y.F.; writing\u0026mdash;original draft preparation, Y.F., B.M., H.-L.L.; writing\u0026mdash;review and editing, Y.F., Y.-L.X.; visualization, B.M.; supervision, Y.F.; project administration, Y.F.; funding acquisition, Y.F.; All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\u003cp\u003eAcknowledgments\u003c/p\u003e\n\u003cp\u003eThis study was supported by the National Natural Science Foundation of China (NSFC) (Grant No. 32070483, 31460572), Natural Science Foundation of Hubei Province (Grant No. 2020CFB757), Scientific Research Starting Foundation for Ph.D. of Huanggang Normal University (Grant No. 2020010, 2042024378), Scientific Research Project of Education Department of Hubei Province (Grant No. Q20232901), Huanggang Normal University Major Project Incubation Plan-Funded Program (Grant No. 204202315204).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data obtained in this study are available from the NCBI under the GenBank number PRJNA1055709. All other data are available in this text and in the Appendixes.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBird S, Coulson R N, Crossley D A (2000). Impacts of silvicultural practices on soil and litter arthropod diversity in a Texas pine plantation. Forest Ecology and Management, 131: 65-80.\u003c/li\u003e\n\u003cli\u003eBriones M J I. (2018). The Serendipitous Value of Soil Fauna in Ecosystem Functioning: The Unexplained Explained. Frontiers in Environmental Science, 6.\u003c/li\u003e\n\u003cli\u003eButenschoen O, Marhan S, Langel R, and Scheu S (2009). Carbon and nitrogen mobilisation by earthworms of different functional groups as affected by soil sand content. Pedobiologia, 52: 263-272.\u003c/li\u003e\n\u003cli\u003eBurk R F, Hill K E (2015). Regulation of Selenium Metabolism and Transport. Annual review of nutrition, 35, 109\u0026ndash;134.\u003c/li\u003e\n\u003cli\u003eCassagne N, Gauquelin T, Bal-Serin M C, Gers C (2006). 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Acta Mineralogica Sinica, 20(4): 337-341.\u003c/li\u003e\n\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":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Diversity, Selenium, Soil, Invertebrates","lastPublishedDoi":"10.21203/rs.3.rs-5255864/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5255864/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eYutangba, situated in Enshi City, Hubei Province, is globally noted its high selenium (Se) content. Soil invertebrates are essential to the functionality and services of terrestrial ecosystems, yet their community composition in this region remains under-explored. This study utilized environmental DNA metabarcoding to investigate the interrelations among environmental factors, soil invertebrate diversity, and community characteristics concerning soil Se content, pH, and moisture content in the region. Environmental factors such as Se concentration, water content, and pH were strongly associated with the alpha and beta diversity of soil invertebrates in Se-rich areas, affecting their distribution and abundance. Among these, Se notably emerges as the primary regulatory factor influencing soil invertebrate diversity. The acidic soil pH, along with moisture, plays a fine-tuning role in regulating species diversity by directly or indirectly influencing the availability and bioavailability of Se, impacting the species richness and community composition. Unexpectedly, certain species, such as the Formicidae (ants, e.g., \u003cem\u003eOdontomachus\u003c/em\u003e \u003cem\u003etroglodytes\u003c/em\u003e), the Noctuidae (e.g., \u003cem\u003eDiarsia rosaria\u003c/em\u003e), and the annelid Haplotaxida\u003cem\u003e Perionyx excavates\u003c/em\u003e, exhibit a strong positive association with Se, indicating a high level of Se tolerance among the native species. This novel perspective reveals the complex role of Se in soil ecosystems, emphasizing the necessity of understanding its ecological functions and potential implications for ecosystem health and stability.\u003c/p\u003e","manuscriptTitle":"Unexpected species diversity in the understanding of selenium- containing soil invertebrates","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-28 11:16:28","doi":"10.21203/rs.3.rs-5255864/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-11-14T05:07:18+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-11-13T15:28:10+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-11-04T03:32:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"329968952846271773068760790582367518602","date":"2024-10-29T06:37:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"256091489459602997935407601200012170101","date":"2024-10-29T06:32:24+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-10-29T03:41:23+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-10-29T00:46:29+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-10-28T16:42:05+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-10-25T13:09:31+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-10-13T14:49:06+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"cbb0608e-b8cb-4d94-8b4b-706fa83300f4","owner":[],"postedDate":"October 28th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-02-03T16:09:04+00:00","versionOfRecord":{"articleIdentity":"rs-5255864","link":"https://doi.org/10.1038/s41598-025-87917-5","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-01-29 15:57:39","publishedOnDateReadable":"January 29th, 2025"},"versionCreatedAt":"2024-10-28 11:16:28","video":"","vorDoi":"10.1038/s41598-025-87917-5","vorDoiUrl":"https://doi.org/10.1038/s41598-025-87917-5","workflowStages":[]},"version":"v1","identity":"rs-5255864","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5255864","identity":"rs-5255864","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}