Coalescence of soil microbial communities: consequences, mechanisms, and influential factors

Coalescence of soil microbial communities: consequences, mechanisms, and influential factors | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Coalescence of soil microbial communities: consequences, mechanisms, and influential factors Danhong Chen, Zelin Wang, Meiping Chen, Kaifang Liu, Dong Liu, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4024260/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Community coalescence is a major manner of microbial dispersal and a fundamental process of microbial community assembly, yet little is known about its ecological effects, mechanisms, and influential factors. Here, a series of microcosmic experiments including soil mixing, sterilization, as well as microbial extraction and inoculation, were performed to address the knowledge gaps. Results: We found that most physicochemical and microbial properties of the coalesced soils exhibited intermediate characteristics compared to the original soils. Weighted species additive effect emerged as the primary driver for soil microbial community coalescence, with contributions reaching 58.44% (prokaryotes) and 51.57% (fungi). In contrast, the contributions from environmental selection were only less than 20%. Upon the removal of soil particle barrier effects, the contributions of abiotic and biotic environmental selection to soil microbial community coalescence increased to 34.60% and 23.76%, respectively. However, their interactions substantially offset the main effects of abiotic and biotic environmental selection. Original soil differences, mixing ratios, and priority effects were critical factors affecting the consequences of soil microbial community coalescence. Nevertheless, the mechanisms underlying microbial community coalescence were similar under different mixing ratios. Conclusions: Our findings underscore the predictability of soil microbial community coalescence, providing critical insights into comprehending microbial community assembly mechanisms. Soil microorganisms Community coalescence Microbial diversity Microbiome Microbial community assembly Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Background Microbial community coalescence is the process through which environmental fragments carrying different microbial communities intermix and form a new microbial community [ 1 ]. Community coalescence represents a primary manner of microbial dispersal and colonization, and it is also a fundamental process of microbial community assembly [ 2 ]. Despite being a recently proposed concept, this process is pervasive in natural microbial communities [ 1 , 3 , 4 ]. Instances of microbial community coalescence occur during sewage discharge, tides, floods, feeding activities, respiration processes, and even intimate contact such as kissing [ 3 , 5 , 6 ]. Furthermore, microbial community coalescence constitutes an essential process underlying various microbiome technologies including gut microbial transplantation, agricultural microbiome inoculation, and urban sewage purification [ 7 – 9 ]. In soils, microbial community coalescence events also constantly occur in response to natural and anthropogenic processes, such as soil erosion and deposition, landslides, agricultural tillage, manure application, and straw return, probably profoundly impacting ecosystem functioning [ 10 – 12 ]. Therefore, elucidating the ecological consequences, mechanisms, and influential factors of soil microbial community coalescence can largely enhance our understanding of microbial community assembly mechanisms, providing crucial information for developing soil microbiome-based technologies [ 9 ]. Microbial community coalescence can significantly affect microbial abundance, diversity, community composition, and even the frequency of horizontal gene transfer, all of which are likely to profoundly influence the ecological functions mediated by microbes [ 1 ]. Recent studies have extensively investigated the effects of microbial community coalescence in aquatic ecosystems [ 13 – 15 ]. In contrast, research on soil microbial community coalescence remains limited due to the heterogeneity and complexity of soil microenvironment, as well as the high diversity of soil microbial taxa [ 10 ]. Several studies have preliminarily explored the role of soil microbial community coalescence in restoring degraded ecosystems and its synergy with fertilization to potentially enhance plant microbiome functioning [ 12 , 16 – 18 ]. However, these investigations mainly focus on describing the consequences of microbial community coalescence, while lacking systematic knowledge regarding its ecological effects, mechanisms, and influential factors. Soil microbial community coalescence is primarily driven by several ecological mechanisms [ 10 ]. First, each coalescent soil fragment harbors specific microbial taxa, and they are mathematically combined to form a new microbial community at the moment of community coalescing. Most soil microbes are dormant and have limited interactions with their surroundings [ 19 ]. Hence, weighted species addition probably plays a dominant role in soil microbial community coalescence. Second, numerous studies have shown that many soil properties such as pH, moisture content, and nutrient contents are important drivers of microbial community assembly [ 20 , 21 ]. Most physicochemical properties of mixed soils significantly differ from those of the original soils, and thus microbial taxa that have adapted to their original habitats will undergo modifications due to the altered environmental conditions resulting from soil mixing. Therefore, abiotic environmental selection arising from soil mixing represents another critical mechanism underlying soil microbial community coalescence. Third, the significance of microbial interactions in soils has been well-documented [ 2 , 9 ]. The interaction patterns among microbial taxa can be altered by community coalescence through introducing new species and modifying soil physicochemical properties [ 2 , 22 ]. Accordingly, biotic environmental selection can be also an important mechanism driving soil microbial community coalescence. In summary, we proposed that weighted species addition along with abiotic and biotic environmental selection are key underlying mechanisms driving soil microbial community coalescence. Soil microbial community coalescence can be influenced by various factors [ 1 ]. First, differences in microbial community profiles and physicochemical properties of original soils can largely affect the outcomes of soil microbial community coalescence. It is expected that greater dissimilarities among the original soils would result in stronger effects on microbial community coalescence. Second, mixing ratios can substantially affect the properties and microbial community composition of coalesced soils, thereby influencing the consequences of microbial community coalescence [ 1 , 23 ]. Third, priority effects, an important component of historical contingency, refer to the imprints of the order and/or timing of microbial taxa colonizing a habitat on microbial community assembly [ 16 , 24 ]. They also represent a crucial factor influencing soil microbial community coalescence. Preferentially colonizing microbial communities can modify community structure and function through niche preemption and modification, thereby facilitating or inhibiting the establishment of late arrivals [ 15 , 24 , 25 ]. Additionally, the interaction interfaces and temporal dynamics during community coalescence can also have significant impacts on soil microbial community coalescence [ 1 , 10 , 14 ]. However, as mentioned earlier, the influential factors of soil microbial community coalescence remain largely unexplored. This study aimed to shed light on the ecological effects, mechanisms, and influential factors of soil microbial community coalescence. Six pairs of cropland and adjacent grassland or forest soils were collected from southwestern China, a mountainous region renowned for its rich biodiversity and environmental heterogeneity (Fig. S1 and Table S1 ). In this region, intense soil erosion leads to continuous mixing of cropland soils with their adjacent ecosystem soils, providing excellent opportunity to investigate microbial community coalescence. Based on the collected soils, a series of microcosm experiments were performed in conjunction with real-time PCR, amplicon high-throughput sequencing, and metagenome sequencing to explore the effects, mechanisms, and influential factors of soil microbial community coalescence. Based on our current understanding of microbial community coalescence, three hypotheses were proposed. First, soil microbial community coalescence would assemble new microbial communities exhibiting properties mostly intermediate between those of the original communities. Second, weighted species additive effect was expected to play a dominant role in soil microbial community coalescence. Third, variations in original soil properties, mixing ratios, and priority effects during coalescence would significantly impact the outcomes. Methods Study sites and soil collection This study was conducted in southwestern China, a region famous for its rich biodiversity and environmental heterogeneity [ 26 , 27 ]. To ensure the broad applicability of this study, soils were collected from six sites representing a wide range of environments (Fig. S1 ). Each site included a typical cropland as well as an adjacent ecosystem such as subalpine meadow, dry-hot valley shrub-grassland, Yunnan pine forest, Chinese fir forest, and rubber woodland. Within each ecosystem, 5 sub-sampling points were set with a minimum adjacent distance of 10 m, and soil samples (0–20 cm) were collected at each point. The soils from each ecosystem at every study site were homogenized and sieved to ≤ 2 mm. A total of 4 kg of soil was obtained for each ecosystem at each sampling site. For molecular analysis, 200 g of each soil sample was preserved at -80°C; another 200 g of soil was air dried to determine physicochemical properties; and the remaining samples were stored at 4°C for subsequent physicochemical property analysis and microcosm experiments. Mean annual temperature (MAT) and mean annual precipitation (MAP) data were obtained from the WorldClim database ( https://www.worldclim.org ). Detailed descriptions of the study sites are presented in Table S1 . The physiochemical and microbial properties of the original soils collected from croplands and noncroplands at each site substantially differed, laying a solid foundation for investigating soil microbial community coalescence (Fig. S2). Microcosm experiments The first microcosm experiment was conducted to determine the ecological effects and mechanisms of soil microbial community coalescence (Fig. S3). Briefly, three treatments were included for the paired cropland and noncropland soils at each site, and there were four replications for each treatment. The cropland (C) and noncropland (N) controls were constructed with 60 g (dry weight, same below) of respective soils. The equal mixing (EM) treatment comprised a thorough mixture of 30 g cropland soil and 30 g noncropland soil collected from the same study sites. All the soils were placed in 150 mL flasks and incubated at 20°C in darkness for a period of 3 months, with fortnightly water replenishment to maintain the initial moisture levels. The second microcosm experiment was performed to explore the mechanisms underlying soil microbial community coalescence (Fig. S4). This experiment consisted of five treatments for the paired cropland and noncropland soils at each site. The cropland soil inoculation (C-I) and noncropland soil inoculation (N-I) treatments were constructed via inoculating microbes extracted from 12 g of cropland and noncropland soils to 60 g of their respective sterilized original soils. The mixed soil-mixed microbe inoculation (MM-I) treatment was established by inoculating the microbes extracted from mixed cropland soils and their adjacent noncropland soils (6 g each) into the sterilized mixed soils (30 g each). Similarly, mixed soil-cropland microbe inoculation (MC-I) and mixed soil-noncropland microbe inoculation (MN-I) treatments were established by inoculating the microbes extracted from 12 g of cropland and their adjacent noncropland soils to the sterilized mixed soils, respectively. The soils were sterilized four times using an intermittent autoclaving method with three-time intervals lasting 48 hours each. Soil microbes were extracted with sodium pyrophosphate as a dispersant, and this method has been proved to be an effective technique for extracting viable microbes [ 28 ]. Each treatment was replicated four times, and the incubation followed the same procedure as in the first experiment. The third microcosm experiment was designed to determine the effects of mixing ratios on soil microbial community coalescence (Fig. S5). Two mixing ratios ( i.e. , 1:1 and 1:10) were designated as equal mixing (EM) and non-equal mixing (NM) treatments, respectively. The EM treatment was identical to that described in the first experiment. For the NM treatment, 6 g of the soils from above and 60 g from below the hillside were mixed together. The EM and NM treatments represented erosion deposition over a period of 10–20 years under strong and weak erosion conditions, respectively. There were four replicates for each treatment, and all the microcosms were incubated as mentioned above. The fourth microcosm experiment aimed to investigate the influences of priority effects on soil microbial community coalescence [ 24 ]. As shown in Fig. S6, each site had five treatments, with four replications per treatment. For every pair of ecosystems at a study site, 30 g cropland soil and 30 g noncropland soil were mixed and sterilized as the substrates. The three treatments including MM-I, MC-I, and MN-I were identical as described in the second microcosm experiment. Additionally, we set cropland microbe priority inoculation (CP-I) and noncropland microbe priority inoculation (NP-I) treatments. In the CP-I treatment, microbes extracted from 6 g of cropland soils were first inoculated into the substrates and incubated for 1.5 months. Subsequently, the microbes extracted from 6 g of noncropland soils were inoculated and continued to incubate for 1.5 months. The NP-I treatment was set in a similar way, but with noncropland soil microbes being inoculated before cropland soil microbes. We selected a dispersal interval of 1.5 months to ensure stable and permanent priority effects [ 29 ]. DNA extraction and real-time PCR Soil DNA was extracted from 0.40 g of fresh soil using the DNeasy PowerSoil kit (Qiagen, Hilden, Germany) [ 30 ]. The quantification of prokaryotic 16S rRNA gene and fungal ITS copy numbers was performed using a LightCyCler96 real-time PCR System (Roche, Germany). For the amplification of prokaryotic 16S rRNA gene, universal primers 515F (5’-GTG NCA GCM GCC GCG GTA A-3’) [ 31 ] and 806R (5’-GGA CTA CHV GGG TWT CTA AT-3’) [ 32 ] were employed. The universal primers gITS7 (5’-GTG ART CAT CGA RTC TTT G-3’) [ 33 ] and ITS4 (5’-TCC TCC GCT TAT TGA TAT GC-3’) [ 34 ] were utilized for fungal ITS amplification. The real-time PCR reaction mixture (20.0 µL) included 1.0 µL template DNA, 10.0 µL Takara TB Green™ Premix Ex Taq™ II (Tli RNaseH Plus RR820A), 0.5 µL forward and reverse primers (10 µM each), and 8.0 µL nuclease-free water. The standard curves were generated using plasmids inserted with the corresponding 16S rRNA gene and ITS fragments [ 35 ]. The PCR cycle included a predenaturation at 95°C for 40 s and 40 cycles containing denaturation at 95°C for 5 s, annealing at 56°C for 30 s, and extension at 72°C for 40 s. The R 2 values of the standard curves exceeded 0.99, and the amplification efficiency was approximately 88%. NovaSeq sequencing and bioinformatic analysis The prokaryotic 16S rRNA gene and fungal ITS were amplified using universal primer sets 515F-806R and gITS7-ITS4, respectively. For the amplification of 16S rRNA gene, the PCR reaction mix of 50 µL was prepared containing 5 µL 10×Ex Taq Buffer (Mg 2+ free), 4 µL dNTP Mixture, 3 µL MgCl 2 , 0.35 µL TaKaRa Ex Taq, 1 µL template DNA, 35 µL nuclease-free water, and equal amounts (1 µL each) of forward and reverse primers (10 µM). The PCR reaction proceeded with an initial denaturation at 95°C for 5 min, followed by a total of 32 cycles consisting of denaturation at 95°C for 30 s, annealing at 56°C for 30 s, and extension at 72°C for 40 s, then terminated with a final extension at 72°C for 10 min. The PCR products were purified using the EZNA® Cycle Pure Kit (Omega Bio-tek, USA). The PCR mixture for the ITS amplification consisted of 15 µL NEBNext Ultra II Q5 Mix (NEB, MA, USA), 3 µL forward primer and reverse primer (10 µmol L − 1 each), 1 µL template DNA, and 8 µL nuclease-free water. The PCR started with an initial denaturation at 98°C for 30 s, followed by 32 cycles of 10 s at 98°C, 20 s at 56°C, and 30 s at 72°C, and then ended with a final extension at 72°C for 8 min. These PCR products were purified using the GeneJET Gel Extraction Kit (Thermo Scientific, Lithuania). All the PCR products were pooled in equal molar amounts per sample. Finally, the Illumina NovaSeq high-throughput sequencing was performed by MagigeneCo., Ltd (Guangdong, China) using a paired-end (2 × 250 bp) sequencing strategy. The paired-end raw sequences were spliced using USEARCH 11; the low-quality sequences and primers were removed following the UPARSE pipeline [ 36 ]. The UNOISE3 denoising algorithm was applied to generate zero-radius operational taxonomic unit (zOTU) representative sequences, and the zOTUs with sequence numbers less than 9 were excluded [ 37 ]. The otutab script was employed to map the zOTU representative sequences with the merged sequences to generate the zOTU table. The taxonomic information annotations of the prokaryotes and fungi were performed using SILVA138 and UNITE8.2 databases in QIIME2 [ 38 ]. A total of 47413 prokaryotic and 17492 fungal zOTUs were obtained. Rarefaction was applied to normalize the prokaryotic and fungal sequence numbers in each sample to 41683 and 87991, respectively. All the raw sequences have been deposited in the NCBI Sequence Read Archive under the BioProject PRJNA1078791. Metagenomic analysis Soil DNA was extracted as described above. The metagenomic shotgun library was constructed using the TruSeq TM DNA Sample Prep Kit (Illumina, San Diego, CA, USA) and sequenced on the NovaSeq platform (Illumina Inc., San Diego, CA, USA) with a sequencing depth of 12 G per sample. Adapter sequences were removed using Trimmomatic (SLIDINGWINDOW: 4:20, MINLEN: 50) [ 39 ]. The sequences with quality scores < 20 were eliminated through Kneaddata. Host sequences, including human and corn genome sequences, were filtered out using bowtie2 in hypersensitive mode [ 40 ]. After quality control, the clean sequences were assembled using MEGAHIT (k-mer: k-min 21, k-max 141, and k-step 20) [ 41 ]. Contigs longer than 500 bp were retained. Prodigal was employed for predicting open reading frames (ORFs) of the spliced sequences and only those with a length ≥ 100 bp were included for downstream analysis [ 42 ]. A nonredundant gene set was generated using CD-Hit algorithm [ 43 ]. Subsequently, the pathogenic genes and biogeochemical cycling genes were annotated based on PHI-Base and KEGG database, respectively. The relative abundance of each functional gene to the 16S rRNA gene copy number was determined using SOAPaligner at a similarity threshold of 95%. The copy number of each functional gene was imputed based on that of the 16S rRNA gene as described in our previous study [ 44 ]. The raw metagenomic sequencing data have also been deposited in the NCBI Sequence Read Archive under the BioProject PRJNA1078791. Soil physicochemical property measurements The soil moisture content was measured by drying the soils at 105°C to a constant weight [ 45 ]. The soil pH values were determined using a pH meter (Mettler-Toledo, Switzerland) with a soil to water ratio of 1:2.5 [ 46 ]. The contents of soil total nitrogen and total organic carbon were analyzed using an auto-elemental analyzer (NA1500, Fisons Instruments, Milano, Italy). The contents of soil total phosphorus and potassium were determined by alkali fusion-Mo-Sb Anti spectrophotometric (HJ 632–2011) and flame photometric methods [ 47 ], respectively. The soil available potassium content was measured through cold nitric acid extraction flame photometer method [ 48 ]. The soil available phosphorus content was measured through either Olsen method or Bray I method based on the soil pH values [ 48 , 49 ]. The nitrate nitrogen and ammonium nitrogen contents in the soils were quantified by indophenol blue colorimetry and vanadium chloride spectrophotometry after KCl extraction with a solution to soil ratio of 5:1, respectively [ 50 , 51 ]. Statistical analysis All the statistical analyses were performed using R with vegan package [ 52 ]. Two-way nested ANOVA was employed to analyze the effects of study sites and community coalescence on soil physicochemical properties, microbial abundance, and diversity. When the data did not meet the assumptions of normality and homoscedasticity, appropriate data transformation or nonparametric testing methods were applied. Principal co-ordinates analysis (PCoA) and permutational multivariate analysis of variance (PERMANOVA) were utilized to determine the effects of sites and community coalescence on microbial community composition. The effects of community coalescence on microbial functional gene copies were analyzed through Kruskal-Wallis test. The contribution of weighted species additive effects to microbial community coalescence was determined by calculating Bray-Curtis similarities between the composition of observed and theoretical coalesced microbial communities. For the first microcosmic experiment, the theoretical microbial community profiles (T-EM) were constructed as follows. First, the absolute abundance of each zOTU in the C and N groups were calculated by multiplying its relative abundance with the corresponding 16S rRNA gene or ITS copies in each soil sample. Then, the theoretical prokaryotic and fungal community profiles based on absolute abundance were constructed by the paired summation of the C and N absolute-abundance community profiles. Subsequently, the absolute abundance of theoretical microbial communities was calculated through paired summation of the C and N absolute abundance weighted by the soil mixing coefficient ( i.e. , 0.5 for both C and N in the equally mixed microcosmic experiment). Finally, the theoretical microbial community profiles were obtained by normalizing the absolute-abundance zOTU tables based on theoretical absolute abundance. At each study site, 16 theoretical microbial community profiles were obtained. The theoretical microbial community profiles for the second microcosmic experiment (T-MM-I) followed a similar construction method with C-I and N-I. The theoretical microbial community profiles for the third microcosmic experiment (T-NM) also followed a similar approach, but the weighted coefficients for the C and N were 0.909 and 0.091, respectively. The contribution of total environmental selection was determined by the differences between the composition of the observed and theoretical coalesced microbial communities, and represented as the R 2 values from PERMANOVA. The contribution of abiotic and biotic environmental selection to community coalescence was further assessed in the second microcosmic experiment. Specifically, the differences in community profiles between C-I and MC-I, as well as N-I and MN-I, were determined via PERMANOVA. Then, the effects of abiotic environmental selection were represented as the abundance-weighted differences. To determine the effects of biotic environmental selection on community coalescence, theoretical microbial communities (T’-MM-I) were constructed with MC-I and MN-I as described above. Subsequently, the effects of biotic environmental selection were represented as the differences in community composition between the observed communities MM-I and the theoretical microbial communities (T’-MM-I). These differences were also evaluated through PERMANOVA. The influences of original soil differences on soil microbial coalescence were assessed using Pearson correlation test. The impacts of soil mixing ratios on community coalescence were characterized by comparing the NM and EM treatments. The influences of priority effects on community coalescence were examined via comparing the CP-I, NP-I, and MM-I treatments. The partitioning of microbial β diversity among the three priority treatments was performed using betapart package [ 53 , 54 ]. To examine the contribution of niche preemption to priority effects, the zOTUs were divided into two groups. The first group included the zOTUs with significant differences among CP-I, NP-I, and MM-I treatments, while the remaining zOTUs were classified into the second group. Differences among these groups were determined using Kruskal-Wallis tests. Then, their niche overlap indices were calculated based on spaa package [ 55 , 56 ]. Additionally, the differences in soil properties among the CP-I, NP-I, and MM-I treatments, as well as their correlations with microbial community profiles were also examined based on ANOVA and Mantel test, respectively. Results The consequences of soil microbial community coalescence Soil microbial community coalescence significantly altered soil properties. The pH values and the contents of total organic carbon, available potassium, available phosphorus, nitrate nitrogen, and ammonium nitrogen of coalesced soils generally exhibited an intermediate status between the two original soils (Fig. S7). Moreover, substantial changes in soil microbial abundance, diversity, community composition, and functional profiles in response to community coalescence were observed (Fig. 1 , Table S2, Fig. S8). Specifically, community coalescence led to a significant increase in soil microbial richness across several study sites (Fig. 1 b). The abundance, community composition, and functional gene copies of coalesced microbial communities also generally displayed an intermediate status between those of the two original soils (Fig. 1 a and c–f, Table S2, Fig. S8). The ecological mechanisms of soil microbial community coalescence The unsterilized soil directly mixing experiment revealed that the coalescence of soil microbial communities was primarily influenced by weighted species additive effects. The similarities between the observed and theoretical coalesced microbial community profiles reached 58.44% for prokaryotes and 51.57% for fungi, respectively (Fig. 2 ). In contrast, the contribution of total environmental selection was relatively low, accounting for only 15.39% and 19.91% for prokaryotes and fungi, respectively (Fig. 2 c and d). As for the microcosmic experiments separately mixing sterilized soils and microbes, the contribution of weighted species additive effects to microbial community coalescence was reduced to 46.28% and 37.57% for prokaryotes and fungi, respectively (Fig. 3 , Fig. S9). In contrast, the contribution of total environmental selection to prokaryotic and fungal community coalescence showed a substantial improvement, reaching 27.47% and 37.17%, respectively (Fig. 3 c and d, Fig. S9). Furthermore, we separately determined the contributions of abiotic and biotic environmental selection. The average effects of abiotic environmental selection were found to be 34.53% for prokaryotes and 34.68% for fungi (Fig. 3 c and d, Fig. S9). The average effects of biotic environmental selection were 22.12% for prokaryotes and 25.41% for fungi (Fig. 3 c and d, Fig. S9). The disparities between the total environmental selection effects versus the summation of abiotic and biotic selection effects suggest that the interaction between abiotic and biotic selection largely offsets their main effects. The influential factors of soil microbial community coalescence In the unsterilized soil directly mixing experiment, no significant correlations of microbial community coalescence mechanisms with the differences between the original soils were observed ( P ≥ 0.25; Table S3). However, in the microcosmic experiments involving separate mixing of sterilized soils and microbes, negative correlations were found between species additive effects and the differences in original soil microbial community profiles, while positive correlations were observed for total and abiotic environmental selection (Table S3, Fig. S10). Notably, these correlations were strong and statistically significant with r ≥ 0.87 for soil prokaryotes (Fig. S10). In contrast, no significant correlations were found between the differences in original soil physicochemical properties and the mechanisms of microbial community coalescence (Table S3). Soil mixing ratios significantly influenced several outcomes of soil microbial community coalescence. Specifically, soil mixing ratios only significantly changed soil fungal abundance at one study site, but it significantly altered microbial richness of the coalesced soils at nearly half of study sites ( P < 0.05; Fig. 4 a–d, Fig. S11a–d). The prokaryotic richness in the equivalently mixed group was generally significantly lower than that in the non-equivalently mixed group, whereas the fungal richness showed reversed differences ( P < 0.05; Fig. 4 c and d, Fig. S11c and d). Moreover, soil mixing ratios significantly influenced microbial community profiles of the coalesced soils, with non-equivalent mixtures being more similar to the original soil microbial communities with a higher proportion ( P < 0.001; Fig. 4 e and f, Fig. S11e and f). In terms of functional gene copy numbers, there were no significant differences in the copies of pathogens, as well as most carbon, nitrogen, and sulfur cycling genes between the two mixing ratios (Figs. S12 and S13). The ecological mechanisms underlying soil microbial community coalescence with different mixing ratios were generally similar (Fig. 4 g and h). The average contributions of weighted species additive and environmental selection effects to prokaryotic community coalescence were 53.97% and 17.63%, respectively; and their contributions to fungal community coalescence were 46.62% and 24.95%, respectively (Fig. 4 g and h). In comparison to equivalently mixed groups, non-equivalent microbial community coalescence was found to be more influenced by environmental selection effects and less affected by weighted species additive effects (Fig. 4 g and h). However, significant differences were only observed in the comparison of prokaryotic weighted species additive effects ( P = 0.031; Fig. 4 g). The priority effects were identified as another critical factor influencing soil microbial community coalescence. The priorly inoculated soil microbial community profiles showed high similarities with their corresponding individually inoculated communities, with average community composition similarities reaching 54.07% and 60.54% for prokaryotes and fungi, respectively (Fig. 5 a and b, Table S2, Fig. S14). Species turnover was significantly higher than nestedness, accounting for 48.11% and 44.30% of prokaryotic and fungal community profile changes induced by priority effects, respectively (Fig. S15). The microbial taxa that showed significant differences among CP-I, NP-I, and MM-I had significantly higher niche overlap compared to those without significant changes ( P ≤ 0.0001; Fig. 5 c and d). Additionally, soil pH values and the contents of total organic carbon, available potassium, available phosphorus, nitrate nitrogen, and ammonium nitrogen differed significantly among the priority treatments, and they showed significant correlations with soil microbial community composition (Fig. 5 e and f). Discussion Soil microbial richness exhibited significant increases in the coalesced soils (Fig. 1 b), which can be elucidated through the following explanations. Initially, the original soils showed significant differences in microbial community profiles, indicating the introduction of many new microbial species through community coalescence (Fig. S2o). Additionally, community coalescence could also largely diversify soil habitats, indirectly leading to the increases in microbial diversity. Furthermore, a recent study showed that the abundance of some rare microbial taxa, previously undetectable, became observable after community coalescence [ 13 ]. Accordingly, the emergence of rare microbial taxa can also contribute to the microbial richness increase in the coalesced soils [ 13 ]. Finally, as a disturbance, coalescence may also stimulate the growth of dormant microbes, which is another possible cause. In fact, the phenomenon of increased microbial diversity following community coalescence has been widely documented, underscoring the crucial role of community coalescence in maintaining microbial diversity [ 12 , 57 , 58 ]. We also discovered that most properties ( e.g. , abundance, community profiles, and functional gene copies) exhibited an intermediate status in the coalesced soil microbial communities compared to their original counterparts (Fig. 1 , Table S2, Fig. S7, Fig. S8). These findings are in line with our hypothesis, and can be primarily attributed to two reasons. First, as observed in this study, most physicochemical properties of the mixed soils were at the intermediate level between those of the original soils (Fig. S7). The intermediate soil conditions tended to shape microbial communities with intermediate characteristics [ 16 , 59 ]. Second, most microbes are adsorbed or even wrapped by the soil particles [ 60 , 61 ]. In mixed soils, most soil particles remain relatively independent, and thus many microbial properties are simply the arithmetic means of the original soils. This provides another plausible explanation for why coalesced soil microbial communities exhibited an intermediate status compared to their original counterparts. Our findings are consistent with several recent studies, but differ from the coalescence outcomes observed in freshwater and marine water microbial communities [ 13 , 62 ]. These divergent results may be ascribed to the greater differences between freshwater and marine habitats, when compared to those between cropland and noncropland soils included in this study [ 13 , 14 ]. Additionally, inherent differences in soil and water properties may also contribute to these distinct coalescent outcomes. In accordance with our hypothesis, weighted species additive effects were recognized as the dominant mechanism of soil microbial community coalescence, which can be explained as follows (Fig. 2 ). Initially, dormant microbes can account for more than 95% of soil microbial community and are inherently insensitive to environmental selection [ 19 , 63 ]. Thus, after soil mixing, dormant microbial taxa are probably coalesced simply in a mathematically additive manner. Additionally, as mentioned above, soil particles serve as the fundamental unit of soil mixing. Since their diameters generally far exceed those of microbial cells, abiotic selection primarily occurs at the scale of soil particles, and establishing new microbial interactions among soil particles also becomes challenging. Consequently, the physical barrier effects of soil particles can be another critical reason for the prominent role played by weighted species additive effects in shaping coalesced soil microbial communities. This perspective was supported by two lines of evidence. First, fungi typically have larger cellular sizes and interaction radii compared to prokaryotes [ 64 ]. Accordingly, the weighted species additive effects on the fungal community were much weaker than that on the prokaryotic community (Fig. 2 c and d, Fig. 3 c and d, Fig. S9). Second, when the soils and microbes were mixed separately to eliminate physical barrier effects posed by soil particles, the weighted species additive effects were largely attenuated, whereas the effects of abiotic and biotic environmental selection were considerably enhanced (Fig. 2 c and d, Fig. 3 c and d, Fig. S9). Moreover, the interaction between abiotic and biotic environmental selection substantially offset their main effects (Fig. 3 c and d), which can also partially explain the dominant role of weighted species additive effects. Collectively, these findings indicate that soil microbial community coalescence can be a highly predicable process, thereby substantially advancing our understanding regarding soil microbial community assembly. A potential limitation of this study is that non-equivalent coalescence of soil microbial communities occurs far more frequently than equivalent community coalescence, yet our most examinations were based on equivalent community coalescence. Therefore, we also investigated the effects of soil mixing ratios on the outcomes and mechanisms of community coalescence. Our findings indicate that microbial richness and community profiles differed significantly with varying soil mixing ratios (Fig. 4 c–f, Fig. S11c–f). However, the underlying ecological mechanisms governing microbial community coalescence with different mixing ratios were generally similar (Fig. 4 g and h). Thus, the effects of soil mixing ratios on microbial community coalescence were mainly caused by the ratio differences of weighted species addition and the environmental differences elicited by mixing ratios. The similar mechanisms governing microbial community coalescence largely support the reliability of our conclusions. Moreover, we observed that original soil differences did not significantly affect microbial coalescence mechanisms when soils were directly mixed (Table S3). Overall, these findings suggest that the mechanisms revealed in this study are applicable to a wide range of naturally occurring soil microbial community coalescences. The consequences of soil microbial community coalescence were also significantly influenced by priority effects, with the initial colonizers largely dominated the coalesced microbial communities (Fig. 5 a and b, Table S2). Although the priority effects of soil microbes are seldom studied, the findings presented in this study are corroborated by multiple observations in water, nectar, and even human intestine [ 14 , 65 , 66 ]. Similar to many previous studies, the priority effects observed in this study can be elicited through niche preemption and modification [ 24 , 25 ]. Niche preemption refers to the phenomenon that early-arriving microbial taxa consume resources such as nutrients and space, thereby constraining the colonization of late-arriving microbial groups that rely on these resources for survival and reproduction [ 25 ]. We observed that the microbial taxa exhibiting significant differences among the priority treatments possessed considerably higher niche overlaps, indicating that niche preemption could be a crucial mechanism underlying priority effects in the coalesced microbial communities (Fig. 5 c and d). Niche modification refers to the alteration in locally available niches by early-arriving species, resulting in the changes to the identities of late-arriving taxa that can establish themselves within the community [ 25 ]. In this study, the soil physicochemical properties exhibited significant variations among the priority treatments and displayed strong correlations with the microbial community composition (Fig. 5 e and f). Therefore, niche modification could also constitute a pivotal mechanism underlying priority effects in the coalesced soil microbial communities. The strength of priority effects relied on the intervals of dispersal [ 29 , 67 ], and thus our findings actually highlight the crucial roles of stable priority effects in determining the consequences of soil microbial community coalescence. Additionally, this study also represents the first observation of the predominant influences of priority effects on soil microbial community assembly. The findings also suggest that techniques such as microbiome inoculation must overcome the priority effects to achieve more effective manipulation of the microbiome. Conclusions This study demonstrated that the coalescence of soil microbial communities significantly altered soil properties, microbial diversity, and functional profiles. Most of the coalesced soil microbial communities exhibited an intermediate state compared to the original soils. Weighted species additive effects were recognized as the dominated mechanisms of soil microbial community coalescence. However, upon the removal of the barrier effects imposed by soil particles, the influences of abiotic and biotic environmental selection on the coalescence of soil microbial communities became significantly more pronounced. Soil mixing ratios have been proven to be a critical factor influencing microbial community coalescence effects but not mechanisms. The priority effects driven by niche preemption and modification were also recognized as the critical influencing factor of soil microbial community coalescence. Our findings not only offer critical insights into soil microbial community assembly mechanisms, but also provide methodologies for further investigation into microbial coalescence mechanisms. Declarations Acknowledgments We thank all members of the research group for many helpful discussions. Authors’ Contributions R.C. designed research. D.C. performed research. D.C., Z.W., M.C. and K.L. analyzed data. R.C., D.L., X.C., Z.X., K.X. and Y.W. revised the paper. D.C. and R.C. wrote the paper. All authors read and approved the final manuscript. Funding This work was supported by National Natural Science Foundation of China (42261012), Yunnan Fundamental Research Projects (202201AT070210, 202301AW070004, 202301AT070211, and 202301BF070001-006), the Xingdian Youth Talent Support Program of Yunnan Province (YNQR-QNRC-2018-024 and YNQR-QNRC-2020-087), and the Double First-Class University Plan. Availability of data and materials All the amplicon and metagenome raw sequences have been deposited in the NCBI Sequence Read Archive under the BioProject PRJNA1078791. The BioSample accession numbers for the 16S rRNA and ITS raw data are SAMN40032898–SAMN40033192 and SAMN40036496–SAMN40036783, respectively, and those for the metagenome raw sequences are SAMN40077515–SAMN40077538. 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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-4024260","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":277191104,"identity":"cf7bbf88-7377-4e7a-819d-8e927f5d9a50","order_by":0,"name":"Danhong Chen","email":"","orcid":"","institution":"Yunnan University","correspondingAuthor":false,"prefix":"","firstName":"Danhong","middleName":"","lastName":"Chen","suffix":""},{"id":277191105,"identity":"c7292b22-93bf-44a6-9106-e6ca75994f76","order_by":1,"name":"Zelin Wang","email":"","orcid":"","institution":"Yunnan University","correspondingAuthor":false,"prefix":"","firstName":"Zelin","middleName":"","lastName":"Wang","suffix":""},{"id":277191106,"identity":"988fdc70-9280-4689-9370-62a17c1b34d5","order_by":2,"name":"Meiping Chen","email":"","orcid":"","institution":"Yunnan University","correspondingAuthor":false,"prefix":"","firstName":"Meiping","middleName":"","lastName":"Chen","suffix":""},{"id":277191107,"identity":"7eac4775-1364-4709-9178-9d946f8ac821","order_by":3,"name":"Kaifang Liu","email":"","orcid":"","institution":"Yunnan University","correspondingAuthor":false,"prefix":"","firstName":"Kaifang","middleName":"","lastName":"Liu","suffix":""},{"id":277191108,"identity":"0b73dc9d-db12-4484-a9da-45533089f28d","order_by":4,"name":"Dong Liu","email":"","orcid":"","institution":"Yunnan University","correspondingAuthor":false,"prefix":"","firstName":"Dong","middleName":"","lastName":"Liu","suffix":""},{"id":277191109,"identity":"2b28b439-e0ff-4ad1-ab77-f8a89bb2a28d","order_by":5,"name":"Xiaoyong Cui","email":"","orcid":"","institution":"University of Chinese Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Xiaoyong","middleName":"","lastName":"Cui","suffix":""},{"id":277191110,"identity":"4413c5c8-c7c4-496c-b2a4-6db56caeb58b","order_by":6,"name":"Zhihong Xu","email":"","orcid":"","institution":"Griffith University","correspondingAuthor":false,"prefix":"","firstName":"Zhihong","middleName":"","lastName":"Xu","suffix":""},{"id":277191111,"identity":"44e62599-9e97-4de8-84f8-5a183e127d4a","order_by":7,"name":"Kai Xue","email":"","orcid":"","institution":"University of Chinese Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Kai","middleName":"","lastName":"Xue","suffix":""},{"id":277191112,"identity":"e126287b-c2e4-4ef2-9599-a8bb453b9add","order_by":8,"name":"Yanfen Wang","email":"","orcid":"","institution":"University of Chinese Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Yanfen","middleName":"","lastName":"Wang","suffix":""},{"id":277191113,"identity":"fe4d50da-da2a-43dc-b920-1c973a20b0ad","order_by":9,"name":"Rongxiao Che","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8UlEQVRIiWNgGAWjYDACCSjNxsDA+ADCTCBeC7MBaVpAuiSI0sI/u/nYh487ahP72A8fq+bdcZiBnz3HgOHnDjyW3DmWPHPmmePGbDxpabd5zxxmkOx5Y8DYewa3FgOJHGNm3rZjcmwMOWa3edsOMxjcyDFgZmzDpyX/M0gLDxv/G7NikBZ7wlpymIFaauTYJHLMmMG2SBDQInEjzZhxZtsBYzaJZ8mSc9vSeSTOPCs42ItHC/+M5McMH9vqEuf3Jx/88LbNWo6/PXnjg594tEDBYTDJxMPAwANiHCCogYGhDkwy/iBC6SgYBaNgFIw8AACAXEptbYCl2gAAAABJRU5ErkJggg==","orcid":"","institution":"Yunnan University","correspondingAuthor":true,"prefix":"","firstName":"Rongxiao","middleName":"","lastName":"Che","suffix":""}],"badges":[],"createdAt":"2024-03-07 11:31:34","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4024260/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4024260/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":52517231,"identity":"35266972-aa65-4dc1-833e-eb9b0d0f6c99","added_by":"auto","created_at":"2024-03-12 13:21:08","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":88045,"visible":true,"origin":"","legend":"\u003cp\u003eThe effects of community coalescence on soil microbial abundance, richness, community composition, and functional gene copies. C: cropland control; EM: equal mixing treatment; and N: noncropland control. Sites: the effects of sites; Treatments: the effects of community coalescence; S1–S6: study sites 1–6; *: \u003cem\u003eP\u003c/em\u003e\u0026lt; 0.05; **: \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01; ***: \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001; and ns: no significance.\u003c/p\u003e","description":"","filename":"Binder11.png","url":"https://assets-eu.researchsquare.com/files/rs-4024260/v1/4c2ec312aec367718bbab341.png"},{"id":52517230,"identity":"94083e65-c251-4edf-9980-597bc04f4277","added_by":"auto","created_at":"2024-03-12 13:21:08","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":69170,"visible":true,"origin":"","legend":"\u003cp\u003eThe ecological mechanisms of microbial community coalescence determined through directly mixing unsterilized soils. (a)–(b): the PCoA ordination of the observed and theoretical soil microbial communities; (c)–(d): the contribution of weighted species additive effects and total environmental selection to soil microbial community coalescence. C: cropland control; N: noncropland control; T-EM: the theoretical microbial communities calculated based on C and N; and EM: the observed microbial communities of the equal mixing treatment. S1–S6: study sites 1–6.\u003c/p\u003e","description":"","filename":"Binder12.png","url":"https://assets-eu.researchsquare.com/files/rs-4024260/v1/8412684062dbb6916fb28e32.png"},{"id":52517228,"identity":"e12fe214-4ce7-4498-b13c-1e5eff7cea71","added_by":"auto","created_at":"2024-03-12 13:21:08","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":69746,"visible":true,"origin":"","legend":"\u003cp\u003eThe ecological mechanisms of microbial community coalescence determined through separately mixing microbial extracts and sterilized soils. (a)–(b): the PCoA ordination of the observed and theoretical soil microbial communities; (c)–(d): the contribution of weighted species additive effects and environmental selection to soil microbial community coalescence. C-I: cropland soil inoculation treatment; N-I: noncropland soil inoculation treatment; T-MM-I: the theoretical microbial communities calculated based on C-I and N-I; and MM-I: the observed microbial communities of the mixed soil-mixed microbe inoculation treatment. S1–S6: study sites 1–6.\u003c/p\u003e","description":"","filename":"Binder13.png","url":"https://assets-eu.researchsquare.com/files/rs-4024260/v1/809b6bcf7cdc9967138d2cdd.png"},{"id":52517229,"identity":"3f099480-8fea-498a-82a9-1d7109ffca44","added_by":"auto","created_at":"2024-03-12 13:21:08","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":53321,"visible":true,"origin":"","legend":"\u003cp\u003eThe effects of mixing ratios on soil microbial community coalescence. (a)–(b): microbial abundance; (c)–(d): microbial richness; (e)–(f): microbial community composition; and (g)–(h): the mechanisms underlying microbial community coalescence. NM: non-equal mixing treatment, and EM: equal mixing treatment. Sites: the effects of sites; Treatments: the effects of mixing ratios. S1–S6: study sites 1–6. *: \u003cem\u003eP\u003c/em\u003e\u0026lt; 0.05; and ns: no significance.\u003c/p\u003e","description":"","filename":"Binder14.png","url":"https://assets-eu.researchsquare.com/files/rs-4024260/v1/1ce71077da69a59f4cf625b9.png"},{"id":52517232,"identity":"c6706c62-5fc3-4ac1-8577-406f3fef0fb9","added_by":"auto","created_at":"2024-03-12 13:21:08","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":85350,"visible":true,"origin":"","legend":"\u003cp\u003eThe influence of priority effects on soil microbial community coalescence and the underlying mechanisms. (a)–(b): the PCoA ordination of soil microbial community profiles; (c)–(d): the niche overlap indices of zOTUs with significant (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05) and insignificant differences among CP-I, NP-I, and MM-I treatments; (e): the correlations between environmental factors and microbial community composition of the CP-I, NP-I, and MM-I treatments; and (f): the changes in soil physicochemical properties among CP-I, NP-I, and MM-I treatments. MC-I: mixed soil-cropland microbe inoculation treatment; MN-I: mixed soil-noncropland microbe inoculation treatment; CP-I: cropland microbe priority inoculation treatment; MM-I: mixed soil-mixed microbe inoculation treatment; and NP-I: noncropland microbe priority inoculation treatment. TOC: soil total organic carbon content; AK: soil available potassium content; AP: soil available phosphorus content; NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e-N: soil nitrate nitrogen content; and NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N: soil ammonium nitrogen content. S1–S6: study sites 1–6; ****: \u003cem\u003eP\u003c/em\u003e ≤ 0.0001. *: \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05; **: \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01; ns: no significance.\u003c/p\u003e","description":"","filename":"Binder15.png","url":"https://assets-eu.researchsquare.com/files/rs-4024260/v1/d7b9838d6bc93c285fdc53bf.png"},{"id":53319028,"identity":"b1707ae1-2dc4-4965-b226-da3f23090083","added_by":"auto","created_at":"2024-03-23 22:52:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2133450,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4024260/v1/164218d6-ff2d-4982-bfdb-b7cdf4f9e2ef.pdf"},{"id":52517234,"identity":"32107bd5-ef39-4682-9fa4-52e6ff7fe64c","added_by":"auto","created_at":"2024-03-12 13:21:08","extension":"doc","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":8941568,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial.doc","url":"https://assets-eu.researchsquare.com/files/rs-4024260/v1/8b2b984791e5a3163b768029.doc"}],"financialInterests":"No competing interests reported.","formattedTitle":"Coalescence of soil microbial communities: consequences, mechanisms, and influential factors","fulltext":[{"header":"Background","content":"\u003cp\u003eMicrobial community coalescence is the process through which environmental fragments carrying different microbial communities intermix and form a new microbial community [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Community coalescence represents a primary manner of microbial dispersal and colonization, and it is also a fundamental process of microbial community assembly [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Despite being a recently proposed concept, this process is pervasive in natural microbial communities [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Instances of microbial community coalescence occur during sewage discharge, tides, floods, feeding activities, respiration processes, and even intimate contact such as kissing [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Furthermore, microbial community coalescence constitutes an essential process underlying various microbiome technologies including gut microbial transplantation, agricultural microbiome inoculation, and urban sewage purification [\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In soils, microbial community coalescence events also constantly occur in response to natural and anthropogenic processes, such as soil erosion and deposition, landslides, agricultural tillage, manure application, and straw return, probably profoundly impacting ecosystem functioning [\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Therefore, elucidating the ecological consequences, mechanisms, and influential factors of soil microbial community coalescence can largely enhance our understanding of microbial community assembly mechanisms, providing crucial information for developing soil microbiome-based technologies [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMicrobial community coalescence can significantly affect microbial abundance, diversity, community composition, and even the frequency of horizontal gene transfer, all of which are likely to profoundly influence the ecological functions mediated by microbes [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Recent studies have extensively investigated the effects of microbial community coalescence in aquatic ecosystems [\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. In contrast, research on soil microbial community coalescence remains limited due to the heterogeneity and complexity of soil microenvironment, as well as the high diversity of soil microbial taxa [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Several studies have preliminarily explored the role of soil microbial community coalescence in restoring degraded ecosystems and its synergy with fertilization to potentially enhance plant microbiome functioning [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. However, these investigations mainly focus on describing the consequences of microbial community coalescence, while lacking systematic knowledge regarding its ecological effects, mechanisms, and influential factors.\u003c/p\u003e \u003cp\u003eSoil microbial community coalescence is primarily driven by several ecological mechanisms [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. First, each coalescent soil fragment harbors specific microbial taxa, and they are mathematically combined to form a new microbial community at the moment of community coalescing. Most soil microbes are dormant and have limited interactions with their surroundings [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Hence, weighted species addition probably plays a dominant role in soil microbial community coalescence. Second, numerous studies have shown that many soil properties such as pH, moisture content, and nutrient contents are important drivers of microbial community assembly [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Most physicochemical properties of mixed soils significantly differ from those of the original soils, and thus microbial taxa that have adapted to their original habitats will undergo modifications due to the altered environmental conditions resulting from soil mixing. Therefore, abiotic environmental selection arising from soil mixing represents another critical mechanism underlying soil microbial community coalescence. Third, the significance of microbial interactions in soils has been well-documented [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The interaction patterns among microbial taxa can be altered by community coalescence through introducing new species and modifying soil physicochemical properties [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Accordingly, biotic environmental selection can be also an important mechanism driving soil microbial community coalescence. In summary, we proposed that weighted species addition along with abiotic and biotic environmental selection are key underlying mechanisms driving soil microbial community coalescence.\u003c/p\u003e \u003cp\u003eSoil microbial community coalescence can be influenced by various factors [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. First, differences in microbial community profiles and physicochemical properties of original soils can largely affect the outcomes of soil microbial community coalescence. It is expected that greater dissimilarities among the original soils would result in stronger effects on microbial community coalescence. Second, mixing ratios can substantially affect the properties and microbial community composition of coalesced soils, thereby influencing the consequences of microbial community coalescence [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Third, priority effects, an important component of historical contingency, refer to the imprints of the order and/or timing of microbial taxa colonizing a habitat on microbial community assembly [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. They also represent a crucial factor influencing soil microbial community coalescence. Preferentially colonizing microbial communities can modify community structure and function through niche preemption and modification, thereby facilitating or inhibiting the establishment of late arrivals [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Additionally, the interaction interfaces and temporal dynamics during community coalescence can also have significant impacts on soil microbial community coalescence [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. However, as mentioned earlier, the influential factors of soil microbial community coalescence remain largely unexplored.\u003c/p\u003e \u003cp\u003eThis study aimed to shed light on the ecological effects, mechanisms, and influential factors of soil microbial community coalescence. Six pairs of cropland and adjacent grassland or forest soils were collected from southwestern China, a mountainous region renowned for its rich biodiversity and environmental heterogeneity (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e and Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). In this region, intense soil erosion leads to continuous mixing of cropland soils with their adjacent ecosystem soils, providing excellent opportunity to investigate microbial community coalescence. Based on the collected soils, a series of microcosm experiments were performed in conjunction with real-time PCR, amplicon high-throughput sequencing, and metagenome sequencing to explore the effects, mechanisms, and influential factors of soil microbial community coalescence. Based on our current understanding of microbial community coalescence, three hypotheses were proposed. First, soil microbial community coalescence would assemble new microbial communities exhibiting properties mostly intermediate between those of the original communities. Second, weighted species additive effect was expected to play a dominant role in soil microbial community coalescence. Third, variations in original soil properties, mixing ratios, and priority effects during coalescence would significantly impact the outcomes.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy sites and soil collection\u003c/h2\u003e \u003cp\u003eThis study was conducted in southwestern China, a region famous for its rich biodiversity and environmental heterogeneity [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. To ensure the broad applicability of this study, soils were collected from six sites representing a wide range of environments (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Each site included a typical cropland as well as an adjacent ecosystem such as subalpine meadow, dry-hot valley shrub-grassland, Yunnan pine forest, Chinese fir forest, and rubber woodland. Within each ecosystem, 5 sub-sampling points were set with a minimum adjacent distance of 10 m, and soil samples (0\u0026ndash;20 cm) were collected at each point. The soils from each ecosystem at every study site were homogenized and sieved to \u0026le;\u0026thinsp;2 mm. A total of 4 kg of soil was obtained for each ecosystem at each sampling site. For molecular analysis, 200 g of each soil sample was preserved at -80\u0026deg;C; another 200 g of soil was air dried to determine physicochemical properties; and the remaining samples were stored at 4\u0026deg;C for subsequent physicochemical property analysis and microcosm experiments. Mean annual temperature (MAT) and mean annual precipitation (MAP) data were obtained from the WorldClim database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.worldclim.org\u003c/span\u003e\u003cspan address=\"https://www.worldclim.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Detailed descriptions of the study sites are presented in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. The physiochemical and microbial properties of the original soils collected from croplands and noncroplands at each site substantially differed, laying a solid foundation for investigating soil microbial community coalescence (Fig. S2).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eMicrocosm experiments\u003c/h2\u003e \u003cp\u003eThe first microcosm experiment was conducted to determine the ecological effects and mechanisms of soil microbial community coalescence (Fig. S3). Briefly, three treatments were included for the paired cropland and noncropland soils at each site, and there were four replications for each treatment. The cropland (C) and noncropland (N) controls were constructed with 60 g (dry weight, same below) of respective soils. The equal mixing (EM) treatment comprised a thorough mixture of 30 g cropland soil and 30 g noncropland soil collected from the same study sites. All the soils were placed in 150 mL flasks and incubated at 20\u0026deg;C in darkness for a period of 3 months, with fortnightly water replenishment to maintain the initial moisture levels.\u003c/p\u003e \u003cp\u003eThe second microcosm experiment was performed to explore the mechanisms underlying soil microbial community coalescence (Fig. S4). This experiment consisted of five treatments for the paired cropland and noncropland soils at each site. The cropland soil inoculation (C-I) and noncropland soil inoculation (N-I) treatments were constructed via inoculating microbes extracted from 12 g of cropland and noncropland soils to 60 g of their respective sterilized original soils. The mixed soil-mixed microbe inoculation (MM-I) treatment was established by inoculating the microbes extracted from mixed cropland soils and their adjacent noncropland soils (6 g each) into the sterilized mixed soils (30 g each). Similarly, mixed soil-cropland microbe inoculation (MC-I) and mixed soil-noncropland microbe inoculation (MN-I) treatments were established by inoculating the microbes extracted from 12 g of cropland and their adjacent noncropland soils to the sterilized mixed soils, respectively. The soils were sterilized four times using an intermittent autoclaving method with three-time intervals lasting 48 hours each. Soil microbes were extracted with sodium pyrophosphate as a dispersant, and this method has been proved to be an effective technique for extracting viable microbes [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Each treatment was replicated four times, and the incubation followed the same procedure as in the first experiment.\u003c/p\u003e \u003cp\u003eThe third microcosm experiment was designed to determine the effects of mixing ratios on soil microbial community coalescence (Fig. S5). Two mixing ratios (\u003cem\u003ei.e.\u003c/em\u003e, 1:1 and 1:10) were designated as equal mixing (EM) and non-equal mixing (NM) treatments, respectively. The EM treatment was identical to that described in the first experiment. For the NM treatment, 6 g of the soils from above and 60 g from below the hillside were mixed together. The EM and NM treatments represented erosion deposition over a period of 10\u0026ndash;20 years under strong and weak erosion conditions, respectively. There were four replicates for each treatment, and all the microcosms were incubated as mentioned above.\u003c/p\u003e \u003cp\u003eThe fourth microcosm experiment aimed to investigate the influences of priority effects on soil microbial community coalescence [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. As shown in Fig. S6, each site had five treatments, with four replications per treatment. For every pair of ecosystems at a study site, 30 g cropland soil and 30 g noncropland soil were mixed and sterilized as the substrates. The three treatments including MM-I, MC-I, and MN-I were identical as described in the second microcosm experiment. Additionally, we set cropland microbe priority inoculation (CP-I) and noncropland microbe priority inoculation (NP-I) treatments. In the CP-I treatment, microbes extracted from 6 g of cropland soils were first inoculated into the substrates and incubated for 1.5 months. Subsequently, the microbes extracted from 6 g of noncropland soils were inoculated and continued to incubate for 1.5 months. The NP-I treatment was set in a similar way, but with noncropland soil microbes being inoculated before cropland soil microbes. We selected a dispersal interval of 1.5 months to ensure stable and permanent priority effects [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eDNA extraction and real-time PCR\u003c/h2\u003e \u003cp\u003eSoil DNA was extracted from 0.40 g of fresh soil using the DNeasy PowerSoil kit (Qiagen, Hilden, Germany) [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The quantification of prokaryotic 16S rRNA gene and fungal ITS copy numbers was performed using a LightCyCler96 real-time PCR System (Roche, Germany). For the amplification of prokaryotic 16S rRNA gene, universal primers 515F (5\u0026rsquo;-GTG NCA GCM GCC GCG GTA A-3\u0026rsquo;) [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] and 806R (5\u0026rsquo;-GGA CTA CHV GGG TWT CTA AT-3\u0026rsquo;) [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] were employed. The universal primers gITS7 (5\u0026rsquo;-GTG ART CAT CGA RTC TTT G-3\u0026rsquo;) [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] and ITS4 (5\u0026rsquo;-TCC TCC GCT TAT TGA TAT GC-3\u0026rsquo;) [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] were utilized for fungal ITS amplification. The real-time PCR reaction mixture (20.0 \u0026micro;L) included 1.0 \u0026micro;L template DNA, 10.0 \u0026micro;L Takara TB Green\u0026trade; Premix Ex Taq\u0026trade; II (Tli RNaseH Plus RR820A), 0.5 \u0026micro;L forward and reverse primers (10 \u0026micro;M each), and 8.0 \u0026micro;L nuclease-free water. The standard curves were generated using plasmids inserted with the corresponding 16S rRNA gene and ITS fragments [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. The PCR cycle included a predenaturation at 95\u0026deg;C for 40 s and 40 cycles containing denaturation at 95\u0026deg;C for 5 s, annealing at 56\u0026deg;C for 30 s, and extension at 72\u0026deg;C for 40 s. The \u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e values of the standard curves exceeded 0.99, and the amplification efficiency was approximately 88%.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eNovaSeq sequencing and bioinformatic analysis\u003c/h2\u003e \u003cp\u003eThe prokaryotic 16S rRNA gene and fungal ITS were amplified using universal primer sets 515F-806R and gITS7-ITS4, respectively. For the amplification of 16S rRNA gene, the PCR reaction mix of 50 \u0026micro;L was prepared containing 5 \u0026micro;L 10\u0026times;Ex Taq Buffer (Mg\u003csup\u003e2+\u003c/sup\u003e free), 4 \u0026micro;L dNTP Mixture, 3 \u0026micro;L MgCl\u003csub\u003e2\u003c/sub\u003e, 0.35 \u0026micro;L TaKaRa Ex Taq, 1 \u0026micro;L template DNA, 35 \u0026micro;L nuclease-free water, and equal amounts (1 \u0026micro;L each) of forward and reverse primers (10 \u0026micro;M). The PCR reaction proceeded with an initial denaturation at 95\u0026deg;C for 5 min, followed by a total of 32 cycles consisting of denaturation at 95\u0026deg;C for 30 s, annealing at 56\u0026deg;C for 30 s, and extension at 72\u0026deg;C for 40 s, then terminated with a final extension at 72\u0026deg;C for 10 min. The PCR products were purified using the EZNA\u0026reg; Cycle Pure Kit (Omega Bio-tek, USA). The PCR mixture for the ITS amplification consisted of 15 \u0026micro;L NEBNext Ultra II Q5 Mix (NEB, MA, USA), 3 \u0026micro;L forward primer and reverse primer (10 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e each), 1 \u0026micro;L template DNA, and 8 \u0026micro;L nuclease-free water. The PCR started with an initial denaturation at 98\u0026deg;C for 30 s, followed by 32 cycles of 10 s at 98\u0026deg;C, 20 s at 56\u0026deg;C, and 30 s at 72\u0026deg;C, and then ended with a final extension at 72\u0026deg;C for 8 min. These PCR products were purified using the GeneJET Gel Extraction Kit (Thermo Scientific, Lithuania). All the PCR products were pooled in equal molar amounts per sample. Finally, the Illumina NovaSeq high-throughput sequencing was performed by MagigeneCo., Ltd (Guangdong, China) using a paired-end (2 \u0026times; 250 bp) sequencing strategy.\u003c/p\u003e \u003cp\u003eThe paired-end raw sequences were spliced using USEARCH 11; the low-quality sequences and primers were removed following the UPARSE pipeline [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. The UNOISE3 denoising algorithm was applied to generate zero-radius operational taxonomic unit (zOTU) representative sequences, and the zOTUs with sequence numbers less than 9 were excluded [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. The otutab script was employed to map the zOTU representative sequences with the merged sequences to generate the zOTU table. The taxonomic information annotations of the prokaryotes and fungi were performed using SILVA138 and UNITE8.2 databases in QIIME2 [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. A total of 47413 prokaryotic and 17492 fungal zOTUs were obtained. Rarefaction was applied to normalize the prokaryotic and fungal sequence numbers in each sample to 41683 and 87991, respectively. All the raw sequences have been deposited in the NCBI Sequence Read Archive under the BioProject PRJNA1078791.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eMetagenomic analysis\u003c/h2\u003e \u003cp\u003eSoil DNA was extracted as described above. The metagenomic shotgun library was constructed using the TruSeq TM DNA Sample Prep Kit (Illumina, San Diego, CA, USA) and sequenced on the NovaSeq platform (Illumina Inc., San Diego, CA, USA) with a sequencing depth of 12 G per sample. Adapter sequences were removed using Trimmomatic (SLIDINGWINDOW: 4:20, MINLEN: 50) [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. The sequences with quality scores\u0026thinsp;\u0026lt;\u0026thinsp;20 were eliminated through Kneaddata. Host sequences, including human and corn genome sequences, were filtered out using bowtie2 in hypersensitive mode [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. After quality control, the clean sequences were assembled using MEGAHIT (k-mer: k-min 21, k-max 141, and k-step 20) [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Contigs longer than 500 bp were retained. Prodigal was employed for predicting open reading frames (ORFs) of the spliced sequences and only those with a length\u0026thinsp;\u0026ge;\u0026thinsp;100 bp were included for downstream analysis [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. A nonredundant gene set was generated using CD-Hit algorithm [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Subsequently, the pathogenic genes and biogeochemical cycling genes were annotated based on PHI-Base and KEGG database, respectively. The relative abundance of each functional gene to the 16S rRNA gene copy number was determined using SOAPaligner at a similarity threshold of 95%. The copy number of each functional gene was imputed based on that of the 16S rRNA gene as described in our previous study [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. The raw metagenomic sequencing data have also been deposited in the NCBI Sequence Read Archive under the BioProject PRJNA1078791.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSoil physicochemical property measurements\u003c/h2\u003e \u003cp\u003eThe soil moisture content was measured by drying the soils at 105\u0026deg;C to a constant weight [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. The soil pH values were determined using a pH meter (Mettler-Toledo, Switzerland) with a soil to water ratio of 1:2.5 [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. The contents of soil total nitrogen and total organic carbon were analyzed using an auto-elemental analyzer (NA1500, Fisons Instruments, Milano, Italy). The contents of soil total phosphorus and potassium were determined by alkali fusion-Mo-Sb Anti spectrophotometric (HJ 632\u0026ndash;2011) and flame photometric methods [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e], respectively. The soil available potassium content was measured through cold nitric acid extraction flame photometer method [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. The soil available phosphorus content was measured through either Olsen method or Bray I method based on the soil pH values [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. The nitrate nitrogen and ammonium nitrogen contents in the soils were quantified by indophenol blue colorimetry and vanadium chloride spectrophotometry after KCl extraction with a solution to soil ratio of 5:1, respectively [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eAll the statistical analyses were performed using R with vegan package [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Two-way nested ANOVA was employed to analyze the effects of study sites and community coalescence on soil physicochemical properties, microbial abundance, and diversity. When the data did not meet the assumptions of normality and homoscedasticity, appropriate data transformation or nonparametric testing methods were applied. Principal co-ordinates analysis (PCoA) and permutational multivariate analysis of variance (PERMANOVA) were utilized to determine the effects of sites and community coalescence on microbial community composition. The effects of community coalescence on microbial functional gene copies were analyzed through Kruskal-Wallis test.\u003c/p\u003e \u003cp\u003eThe contribution of weighted species additive effects to microbial community coalescence was determined by calculating Bray-Curtis similarities between the composition of observed and theoretical coalesced microbial communities. For the first microcosmic experiment, the theoretical microbial community profiles (T-EM) were constructed as follows. First, the absolute abundance of each zOTU in the C and N groups were calculated by multiplying its relative abundance with the corresponding 16S rRNA gene or ITS copies in each soil sample. Then, the theoretical prokaryotic and fungal community profiles based on absolute abundance were constructed by the paired summation of the C and N absolute-abundance community profiles. Subsequently, the absolute abundance of theoretical microbial communities was calculated through paired summation of the C and N absolute abundance weighted by the soil mixing coefficient (\u003cem\u003ei.e.\u003c/em\u003e, 0.5 for both C and N in the equally mixed microcosmic experiment). Finally, the theoretical microbial community profiles were obtained by normalizing the absolute-abundance zOTU tables based on theoretical absolute abundance. At each study site, 16 theoretical microbial community profiles were obtained. The theoretical microbial community profiles for the second microcosmic experiment (T-MM-I) followed a similar construction method with C-I and N-I. The theoretical microbial community profiles for the third microcosmic experiment (T-NM) also followed a similar approach, but the weighted coefficients for the C and N were 0.909 and 0.091, respectively. The contribution of total environmental selection was determined by the differences between the composition of the observed and theoretical coalesced microbial communities, and represented as the R\u003csup\u003e2\u003c/sup\u003e values from PERMANOVA.\u003c/p\u003e \u003cp\u003eThe contribution of abiotic and biotic environmental selection to community coalescence was further assessed in the second microcosmic experiment. Specifically, the differences in community profiles between C-I and MC-I, as well as N-I and MN-I, were determined via PERMANOVA. Then, the effects of abiotic environmental selection were represented as the abundance-weighted differences. To determine the effects of biotic environmental selection on community coalescence, theoretical microbial communities (T\u0026rsquo;-MM-I) were constructed with MC-I and MN-I as described above. Subsequently, the effects of biotic environmental selection were represented as the differences in community composition between the observed communities MM-I and the theoretical microbial communities (T\u0026rsquo;-MM-I). These differences were also evaluated through PERMANOVA.\u003c/p\u003e \u003cp\u003eThe influences of original soil differences on soil microbial coalescence were assessed using Pearson correlation test. The impacts of soil mixing ratios on community coalescence were characterized by comparing the NM and EM treatments. The influences of priority effects on community coalescence were examined via comparing the CP-I, NP-I, and MM-I treatments. The partitioning of microbial β diversity among the three priority treatments was performed using betapart package [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. To examine the contribution of niche preemption to priority effects, the zOTUs were divided into two groups. The first group included the zOTUs with significant differences among CP-I, NP-I, and MM-I treatments, while the remaining zOTUs were classified into the second group. Differences among these groups were determined using Kruskal-Wallis tests. Then, their niche overlap indices were calculated based on spaa package [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. Additionally, the differences in soil properties among the CP-I, NP-I, and MM-I treatments, as well as their correlations with microbial community profiles were also examined based on ANOVA and Mantel test, respectively.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eThe consequences of soil microbial community coalescence\u003c/h2\u003e \u003cp\u003eSoil microbial community coalescence significantly altered soil properties. The pH values and the contents of total organic carbon, available potassium, available phosphorus, nitrate nitrogen, and ammonium nitrogen of coalesced soils generally exhibited an intermediate status between the two original soils (Fig. S7). Moreover, substantial changes in soil microbial abundance, diversity, community composition, and functional profiles in response to community coalescence were observed (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Table S2, Fig. S8). Specifically, community coalescence led to a significant increase in soil microbial richness across several study sites (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). The abundance, community composition, and functional gene copies of coalesced microbial communities also generally displayed an intermediate status between those of the two original soils (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea and c\u0026ndash;f, Table S2, Fig. S8).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eThe ecological mechanisms of soil microbial community coalescence\u003c/h2\u003e \u003cp\u003eThe unsterilized soil directly mixing experiment revealed that the coalescence of soil microbial communities was primarily influenced by weighted species additive effects. The similarities between the observed and theoretical coalesced microbial community profiles reached 58.44% for prokaryotes and 51.57% for fungi, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In contrast, the contribution of total environmental selection was relatively low, accounting for only 15.39% and 19.91% for prokaryotes and fungi, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec and d).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs for the microcosmic experiments separately mixing sterilized soils and microbes, the contribution of weighted species additive effects to microbial community coalescence was reduced to 46.28% and 37.57% for prokaryotes and fungi, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Fig. S9). In contrast, the contribution of total environmental selection to prokaryotic and fungal community coalescence showed a substantial improvement, reaching 27.47% and 37.17%, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec and d, Fig. S9). Furthermore, we separately determined the contributions of abiotic and biotic environmental selection. The average effects of abiotic environmental selection were found to be 34.53% for prokaryotes and 34.68% for fungi (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec and d, Fig. S9). The average effects of biotic environmental selection were 22.12% for prokaryotes and 25.41% for fungi (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec and d, Fig. S9). The disparities between the total environmental selection effects versus the summation of abiotic and biotic selection effects suggest that the interaction between abiotic and biotic selection largely offsets their main effects.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eThe influential factors of soil microbial community coalescence\u003c/h2\u003e \u003cp\u003eIn the unsterilized soil directly mixing experiment, no significant correlations of microbial community coalescence mechanisms with the differences between the original soils were observed (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026ge;\u0026thinsp;0.25; Table S3). However, in the microcosmic experiments involving separate mixing of sterilized soils and microbes, negative correlations were found between species additive effects and the differences in original soil microbial community profiles, while positive correlations were observed for total and abiotic environmental selection (Table S3, Fig. S10). Notably, these correlations were strong and statistically significant with \u003cem\u003er\u003c/em\u003e\u0026thinsp;\u0026ge;\u0026thinsp;0.87 for soil prokaryotes (Fig. S10). In contrast, no significant correlations were found between the differences in original soil physicochemical properties and the mechanisms of microbial community coalescence (Table S3).\u003c/p\u003e \u003cp\u003eSoil mixing ratios significantly influenced several outcomes of soil microbial community coalescence. Specifically, soil mixing ratios only significantly changed soil fungal abundance at one study site, but it significantly altered microbial richness of the coalesced soils at nearly half of study sites (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea\u0026ndash;d, Fig. S11a\u0026ndash;d). The prokaryotic richness in the equivalently mixed group was generally significantly lower than that in the non-equivalently mixed group, whereas the fungal richness showed reversed differences (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec and d, Fig. S11c and d). Moreover, soil mixing ratios significantly influenced microbial community profiles of the coalesced soils, with non-equivalent mixtures being more similar to the original soil microbial communities with a higher proportion (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ee and f, Fig. S11e and f). In terms of functional gene copy numbers, there were no significant differences in the copies of pathogens, as well as most carbon, nitrogen, and sulfur cycling genes between the two mixing ratios (Figs. S12 and S13). The ecological mechanisms underlying soil microbial community coalescence with different mixing ratios were generally similar (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eg and h). The average contributions of weighted species additive and environmental selection effects to prokaryotic community coalescence were 53.97% and 17.63%, respectively; and their contributions to fungal community coalescence were 46.62% and 24.95%, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eg and h). In comparison to equivalently mixed groups, non-equivalent microbial community coalescence was found to be more influenced by environmental selection effects and less affected by weighted species additive effects (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eg and h). However, significant differences were only observed in the comparison of prokaryotic weighted species additive effects (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.031; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eg).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe priority effects were identified as another critical factor influencing soil microbial community coalescence. The priorly inoculated soil microbial community profiles showed high similarities with their corresponding individually inoculated communities, with average community composition similarities reaching 54.07% and 60.54% for prokaryotes and fungi, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea and b, Table S2, Fig. S14). Species turnover was significantly higher than nestedness, accounting for 48.11% and 44.30% of prokaryotic and fungal community profile changes induced by priority effects, respectively (Fig. S15). The microbial taxa that showed significant differences among CP-I, NP-I, and MM-I had significantly higher niche overlap compared to those without significant changes (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026le;\u0026thinsp;0.0001; Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec and d). Additionally, soil pH values and the contents of total organic carbon, available potassium, available phosphorus, nitrate nitrogen, and ammonium nitrogen differed significantly among the priority treatments, and they showed significant correlations with soil microbial community composition (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ee and f).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eSoil microbial richness exhibited significant increases in the coalesced soils (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb), which can be elucidated through the following explanations. Initially, the original soils showed significant differences in microbial community profiles, indicating the introduction of many new microbial species through community coalescence (Fig. S2o). Additionally, community coalescence could also largely diversify soil habitats, indirectly leading to the increases in microbial diversity. Furthermore, a recent study showed that the abundance of some rare microbial taxa, previously undetectable, became observable after community coalescence [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Accordingly, the emergence of rare microbial taxa can also contribute to the microbial richness increase in the coalesced soils [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Finally, as a disturbance, coalescence may also stimulate the growth of dormant microbes, which is another possible cause. In fact, the phenomenon of increased microbial diversity following community coalescence has been widely documented, underscoring the crucial role of community coalescence in maintaining microbial diversity [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWe also discovered that most properties (\u003cem\u003ee.g.\u003c/em\u003e, abundance, community profiles, and functional gene copies) exhibited an intermediate status in the coalesced soil microbial communities compared to their original counterparts (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Table S2, Fig. S7, Fig. S8). These findings are in line with our hypothesis, and can be primarily attributed to two reasons. First, as observed in this study, most physicochemical properties of the mixed soils were at the intermediate level between those of the original soils (Fig. S7). The intermediate soil conditions tended to shape microbial communities with intermediate characteristics [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. Second, most microbes are adsorbed or even wrapped by the soil particles [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. In mixed soils, most soil particles remain relatively independent, and thus many microbial properties are simply the arithmetic means of the original soils. This provides another plausible explanation for why coalesced soil microbial communities exhibited an intermediate status compared to their original counterparts. Our findings are consistent with several recent studies, but differ from the coalescence outcomes observed in freshwater and marine water microbial communities [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. These divergent results may be ascribed to the greater differences between freshwater and marine habitats, when compared to those between cropland and noncropland soils included in this study [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Additionally, inherent differences in soil and water properties may also contribute to these distinct coalescent outcomes.\u003c/p\u003e \u003cp\u003eIn accordance with our hypothesis, weighted species additive effects were recognized as the dominant mechanism of soil microbial community coalescence, which can be explained as follows (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Initially, dormant microbes can account for more than 95% of soil microbial community and are inherently insensitive to environmental selection [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. Thus, after soil mixing, dormant microbial taxa are probably coalesced simply in a mathematically additive manner. Additionally, as mentioned above, soil particles serve as the fundamental unit of soil mixing. Since their diameters generally far exceed those of microbial cells, abiotic selection primarily occurs at the scale of soil particles, and establishing new microbial interactions among soil particles also becomes challenging. Consequently, the physical barrier effects of soil particles can be another critical reason for the prominent role played by weighted species additive effects in shaping coalesced soil microbial communities. This perspective was supported by two lines of evidence. First, fungi typically have larger cellular sizes and interaction radii compared to prokaryotes [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. Accordingly, the weighted species additive effects on the fungal community were much weaker than that on the prokaryotic community (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec and d, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec and d, Fig. S9). Second, when the soils and microbes were mixed separately to eliminate physical barrier effects posed by soil particles, the weighted species additive effects were largely attenuated, whereas the effects of abiotic and biotic environmental selection were considerably enhanced (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec and d, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec and d, Fig. S9). Moreover, the interaction between abiotic and biotic environmental selection substantially offset their main effects (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec and d), which can also partially explain the dominant role of weighted species additive effects. Collectively, these findings indicate that soil microbial community coalescence can be a highly predicable process, thereby substantially advancing our understanding regarding soil microbial community assembly.\u003c/p\u003e \u003cp\u003eA potential limitation of this study is that non-equivalent coalescence of soil microbial communities occurs far more frequently than equivalent community coalescence, yet our most examinations were based on equivalent community coalescence. Therefore, we also investigated the effects of soil mixing ratios on the outcomes and mechanisms of community coalescence. Our findings indicate that microbial richness and community profiles differed significantly with varying soil mixing ratios (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec\u0026ndash;f, Fig. S11c\u0026ndash;f). However, the underlying ecological mechanisms governing microbial community coalescence with different mixing ratios were generally similar (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eg and h). Thus, the effects of soil mixing ratios on microbial community coalescence were mainly caused by the ratio differences of weighted species addition and the environmental differences elicited by mixing ratios. The similar mechanisms governing microbial community coalescence largely support the reliability of our conclusions. Moreover, we observed that original soil differences did not significantly affect microbial coalescence mechanisms when soils were directly mixed (Table S3). Overall, these findings suggest that the mechanisms revealed in this study are applicable to a wide range of naturally occurring soil microbial community coalescences.\u003c/p\u003e \u003cp\u003eThe consequences of soil microbial community coalescence were also significantly influenced by priority effects, with the initial colonizers largely dominated the coalesced microbial communities (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea and b, Table S2). Although the priority effects of soil microbes are seldom studied, the findings presented in this study are corroborated by multiple observations in water, nectar, and even human intestine [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]. Similar to many previous studies, the priority effects observed in this study can be elicited through niche preemption and modification [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Niche preemption refers to the phenomenon that early-arriving microbial taxa consume resources such as nutrients and space, thereby constraining the colonization of late-arriving microbial groups that rely on these resources for survival and reproduction [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. We observed that the microbial taxa exhibiting significant differences among the priority treatments possessed considerably higher niche overlaps, indicating that niche preemption could be a crucial mechanism underlying priority effects in the coalesced microbial communities (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec and d). Niche modification refers to the alteration in locally available niches by early-arriving species, resulting in the changes to the identities of late-arriving taxa that can establish themselves within the community [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. In this study, the soil physicochemical properties exhibited significant variations among the priority treatments and displayed strong correlations with the microbial community composition (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ee and f). Therefore, niche modification could also constitute a pivotal mechanism underlying priority effects in the coalesced soil microbial communities. The strength of priority effects relied on the intervals of dispersal [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e], and thus our findings actually highlight the crucial roles of stable priority effects in determining the consequences of soil microbial community coalescence. Additionally, this study also represents the first observation of the predominant influences of priority effects on soil microbial community assembly. The findings also suggest that techniques such as microbiome inoculation must overcome the priority effects to achieve more effective manipulation of the microbiome.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study demonstrated that the coalescence of soil microbial communities significantly altered soil properties, microbial diversity, and functional profiles. Most of the coalesced soil microbial communities exhibited an intermediate state compared to the original soils. Weighted species additive effects were recognized as the dominated mechanisms of soil microbial community coalescence. However, upon the removal of the barrier effects imposed by soil particles, the influences of abiotic and biotic environmental selection on the coalescence of soil microbial communities became significantly more pronounced. Soil mixing ratios have been proven to be a critical factor influencing microbial community coalescence effects but not mechanisms. The priority effects driven by niche preemption and modification were also recognized as the critical influencing factor of soil microbial community coalescence. Our findings not only offer critical insights into soil microbial community assembly mechanisms, but also provide methodologies for further investigation into microbial coalescence mechanisms.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank all members of the research group for many helpful discussions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eR.C. designed research. D.C. performed research. D.C., Z.W., M.C. and K.L. analyzed data. R.C., D.L., X.C., Z.X., K.X. and Y.W. revised the paper. D.C. and R.C. wrote the paper. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by National Natural Science Foundation of China (42261012), Yunnan Fundamental Research Projects (202201AT070210, 202301AW070004, 202301AT070211, and 202301BF070001-006), the Xingdian Youth Talent Support Program of Yunnan Province (YNQR-QNRC-2018-024 and YNQR-QNRC-2020-087), and the Double First-Class University Plan.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the amplicon and metagenome raw sequences have been deposited in the NCBI Sequence Read Archive under the BioProject PRJNA1078791. The BioSample accession numbers for the 16S rRNA and ITS raw data are SAMN40032898\u0026ndash;SAMN40033192 and SAMN40036496\u0026ndash;SAMN40036783, respectively, and those for the metagenome raw sequences are SAMN40077515\u0026ndash;SAMN40077538.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors consent to the publication of the article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eRillig MC, Antonovics J, Caruso T, Lehmann A, Powell JR, Veresoglou SD, et al. Interchange of entire communities: microbial community coalescence. 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Environ Microbiol. 2018;20:1120\u0026ndash;1133.\u003c/li\u003e\n\u003c/ol\u003e\n"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Soil microorganisms, Community coalescence, Microbial diversity, Microbiome, Microbial community assembly","lastPublishedDoi":"10.21203/rs.3.rs-4024260/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4024260/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eCommunity coalescence is a major manner of microbial dispersal and a fundamental process of microbial community assembly, yet little is known about its ecological effects, mechanisms, and influential factors. Here, a series of microcosmic experiments including soil mixing, sterilization, as well as microbial extraction and inoculation, were performed to address the knowledge gaps.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eWe found that most physicochemical and microbial properties of the coalesced soils exhibited intermediate characteristics compared to the original soils. Weighted species additive effect emerged as the primary driver for soil microbial community coalescence, with contributions reaching 58.44% (prokaryotes) and 51.57% (fungi). In contrast, the contributions from environmental selection were only less than 20%. Upon the removal of soil particle barrier effects, the contributions of abiotic and biotic environmental selection to soil microbial community coalescence increased to 34.60% and 23.76%, respectively. However, their interactions substantially offset the main effects of abiotic and biotic environmental selection. Original soil differences, mixing ratios, and priority effects were critical factors affecting the consequences of soil microbial community coalescence. Nevertheless, the mechanisms underlying microbial community coalescence were similar under different mixing ratios.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eOur findings underscore the predictability of soil microbial community coalescence, providing critical insights into comprehending microbial community assembly mechanisms.\u003c/p\u003e","manuscriptTitle":"Coalescence of soil microbial communities: consequences, mechanisms, and influential factors","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-12 13:21:03","doi":"10.21203/rs.3.rs-4024260/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f3479ef8-d453-4a04-8398-a76b5b8908bf","owner":[],"postedDate":"March 12th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-03-23T22:44:26+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-12 13:21:03","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4024260","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4024260","identity":"rs-4024260","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}