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<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Microbiol.</journal-id>
<journal-title>Frontiers in Microbiology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Microbiol.</abbrev-journal-title>
<issn pub-type="epub">1664-302X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fmicb.2025.1619932</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Microbiology</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Substrate stoichiometry and microbial metabolic preference drive the divergent accumulation of plant and microbial necromass carbon in cropland soils: evidence from a short-term experiment</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name><surname>Wu</surname> <given-names>Hongliang</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
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</contrib>
<contrib contrib-type="author">
<name><surname>Wang</surname> <given-names>Luming</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
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<contrib contrib-type="author">
<name><surname>Liu</surname> <given-names>Xiuping</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
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</contrib>
<contrib contrib-type="author">
<name><surname>Wang</surname> <given-names>Wenyan</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
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<contrib contrib-type="author">
<name><surname>Lu</surname> <given-names>Changai</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
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<contrib contrib-type="author" corresp="yes">
<name><surname>Dong</surname> <given-names>Wenxu</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>&#x0002A;</sup></xref>
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<aff id="aff1"><sup>1</sup><institution>Hebei Key Laboratory of Soil Ecology, Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences</institution>, <addr-line>Shijiazhuang</addr-line>, <country>China</country></aff>
<aff id="aff2"><sup>2</sup><institution>Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences</institution>, <addr-line>Beijing</addr-line>, <country>China</country></aff>
<author-notes>
<fn fn-type="edited-by"><p>Edited by: Jincai Ma, Jilin Unversity, China</p></fn>
<fn fn-type="edited-by"><p>Reviewed by: Marc Vi&#x000F1;as, Institute of Agrifood Research and Technology (IRTA), Spain</p>
<p>Shuaimin Chen, Jilin Academy of Agricultural Sciences, China</p></fn>
<corresp id="c001">&#x0002A;Correspondence: Wenxu Dong <email>dongwx&#x00040;sjziam.ac.cn</email></corresp>
</author-notes>
<pub-date pub-type="epub">
<day>29</day>
<month>07</month>
<year>2025</year>
</pub-date>
<pub-date pub-type="collection">
<year>2025</year>
</pub-date>
<volume>16</volume>
<elocation-id>1619932</elocation-id>
<history>
<date date-type="received">
<day>29</day>
<month>04</month>
<year>2025</year>
</date>
<date date-type="accepted">
<day>07</day>
<month>07</month>
<year>2025</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x000A9; 2025 Wu, Wang, Liu, Wang, Lu and Dong.</copyright-statement>
<copyright-year>2025</copyright-year>
<copyright-holder>Wu, Wang, Liu, Wang, Lu and Dong</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/"><p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p></license>
</permissions>
<abstract>
<p>Substrate input and subsequent <italic>ex vivo</italic> modification and <italic>in vivo</italic> turnover mediated by microbial systems determine the formation of soil organic carbon (C). However, the effects and mechanisms by which substrate stoichiometry (SS) adapts to microbial metabolic preferences and influences the dynamics of plant and microbial necromass C (PNC, MNC) remain unclear. Therefore, the variations and controlling factors of PNC and MNC in top- (0&#x02013;20 cm) and subsoil (20&#x02013;40 cm) across different SS conditions were investigated during the whole maize season. Mainly, the SS of exogenous C, nitrogen (N), phosphorus (P), and sulfur (S) meet the metabolic requirements of fungi (NPS1) and bacteria (NPS3). Results showed that compared to NPS1, NPS3 increased MNC by 5.3% in topsoil and 13.9% in subsoil, while reducing PNC by 7.0% and 16.3%, respectively. These suggested that SS matching bacterial needs could accelerate the digestion of PNC and enhanced the accumulation of MNC, especially in subsoil. Under NPS1, dominant microbial taxa (e.g., <italic>Planctomycetota</italic>), phosphatase, and nutrient availability were key determinants of necromass C (NC) changes, with MNC and PNC being predominantly influenced by available N and P, respectively. <italic>Firmicutes</italic> was particularly influential in the subsoil. Under NPS3, a more diverse bacteria, including <italic>Proteobacteria</italic>, was mobilized, with &#x003B2;-glucosidase and available N being central to NC variations. Changes in PNC were also primarily regulated by fungi, specifically <italic>Mortierellomycota</italic>. Our findings of the short-term experiment suggest that SS influences the digestion or accumulation of PNC and MNC by regulating nutrient availability, C and P cycling enzymes, and functional flora, and meanwhile, emphasize that SS matching bacterial requirements enhances MNC accumulation.</p></abstract>
<kwd-group>
<kwd>agricultural residues</kwd>
<kwd>microbial stoichiometry metabolism</kwd>
<kwd>lignin phenols</kwd>
<kwd>microbial necromass carbon</kwd>
<kwd>carbon and nutrient metabolism</kwd>
</kwd-group>
<counts>
<fig-count count="7"/>
<table-count count="1"/>
<equation-count count="2"/>
<ref-count count="57"/>
<page-count count="13"/>
<word-count count="9277"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Terrestrial Microbiology</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec id="s1">
<title>1 Introduction</title>
<p>Soil organic carbon (SOC) sequestration is essential for both agricultural productivity and global carbon (C) neutrality (Schmidt et al., <xref ref-type="bibr" rid="B40">2011</xref>; Wang et al., <xref ref-type="bibr" rid="B48">2020</xref>). Most research has highlighted that microbial components contribute over more than half of SOC in croplands, surpassing the traditionally recognized recalcitrant plant components (Wang et al., <xref ref-type="bibr" rid="B47">2021</xref>). The formation and accumulation of both plant and microbial components depend on microbial metabolic pathways, substrate stoichiometry (SS), and their alignment with microbial demands (Liang et al., <xref ref-type="bibr" rid="B27">2017</xref>; Zhu et al., <xref ref-type="bibr" rid="B57">2022</xref>). The interplay between SS and microbial requirements drives shifts in microbial catabolism and anabolism, influencing the transformation or accumulation of plant and microbial components, and thereby impacting SOC sequestration (Kirkby et al., <xref ref-type="bibr" rid="B21">2014</xref>; Liang et al., <xref ref-type="bibr" rid="B27">2017</xref>). Therefore, distinguishing and quantifying plant- and microbial-derived C components is fundamental to understanding soil C sinks (Chen et al., <xref ref-type="bibr" rid="B6">2021</xref>). However, few studies have systematically examined how SS preferences of different microbial groups simultaneously regulate both plant- and microbial-derived contributions to SOC accumulation.</p>
<p>Recent advances in research on plant necromass C (PNC) and microbial necromass C (MNC) are elucidating their roles in SOC formation and accumulation (Liang et al., <xref ref-type="bibr" rid="B26">2019</xref>; Qi et al., <xref ref-type="bibr" rid="B37">2023</xref>). PNC, products of microbial catabolism, partitions into both the stable C pool and labile C pool, with the latter being preferentially transferred into microbial assimilation (Chen et al., <xref ref-type="bibr" rid="B7">2020</xref>; Lavallee et al., <xref ref-type="bibr" rid="B23">2019</xref>). Conversely, MNC, derived from microbial assimilation, is primarily embedded into the stable C pool, especially in the form of fungal necromass C (NC) (Liang et al., <xref ref-type="bibr" rid="B27">2017</xref>, <xref ref-type="bibr" rid="B26">2019</xref>). Emerging evidence suggests that PNC and MNC collectively account for more than two-thirds of SOC in cropland (Chen et al., <xref ref-type="bibr" rid="B6">2021</xref>; Li et al., <xref ref-type="bibr" rid="B25">2024</xref>). In fertilized soil, the addition of materials with a high C-to-nitrogen (C/N) ratio lead to slow exogenous C decomposition, resulting in negligible or no accumulation of NC. In contrast, incorporating low C/N ratio materials accelerates PNC accumulation during the early stages and promotes greater MNC accumulation at later stages (Li et al., <xref ref-type="bibr" rid="B25">2024</xref>; Chen et al., <xref ref-type="bibr" rid="B8">2025</xref>). Concurrent assessment the variations of PNC and MNC are essential for a comprehensive understanding of SOC sequestration. However, research on the dynamics of NC in response to SS levels and microbial resource acquisition strategies remains limited.</p>
<p>Functional microbial taxa and associated enzymes control microbial catabolism and assimilation processes, specifically through <italic>ex vivo</italic> and <italic>in vivo</italic> pathways. Microbes employ hydrolases to directly modify the initial C source <italic>ex vivo</italic>, while dominant microbial taxa assimilate the C source <italic>in vivo</italic> (Liang et al., <xref ref-type="bibr" rid="B27">2017</xref>, <xref ref-type="bibr" rid="B26">2019</xref>; Zhu et al., <xref ref-type="bibr" rid="B56">2020</xref>). The different resource acquisition strategies, metabolic preferences, and environmental tolerances exhibited by various microbial taxa significantly shape community composition and function, thereby influencing their adaptive adjustments (Zhu et al., <xref ref-type="bibr" rid="B57">2022</xref>; Li et al., <xref ref-type="bibr" rid="B25">2024</xref>). The inherent variability and complexity of microbial communities present challenges in revealing the microbial mechanisms that drive soil C processes. Grouping microorganisms into copiotrophs and oligotrophs based on their life strategies offers a useful way to link microbial activity with environmental conditions (Hu et al., <xref ref-type="bibr" rid="B14">2023</xref>). This suggests that targeted regulation of microbial communities according to their growth strategies could indirectly influence SOC sequestration. Functional hydrolases are pivotal in balancing microbial biomass production with environmental resource availability, thus affecting soil C and nutrient cycling (Sinsabaugh et al., <xref ref-type="bibr" rid="B42">2009</xref>; Luo et al., <xref ref-type="bibr" rid="B30">2017</xref>). Enzymes such as glucosidase and phosphatase are widely involved in microbial energy and nutrient acquisition, with phosphorus acquisition enzymes being particularly significant in agroecosystems (Wu et al., <xref ref-type="bibr" rid="B50">2022</xref>). However, the interplay between major microbial taxa, functional enzymes, and their roles in <italic>ex vivo</italic> and <italic>in vivo</italic> pathways is underexplored.</p>
<p>In agroecosystems, substrate stoichiometry (SS) and availability are highly sensitive to management practices like organic and inorganic amendments. These alterations ultimately reshape microbial communities and metabolic functions, thereby influencing SOC accumulation (Li et al., <xref ref-type="bibr" rid="B24">2020</xref>; Zhu et al., <xref ref-type="bibr" rid="B57">2022</xref>). Generally, the biogeochemical cycling of C, nitrogen (N), phosphorus (P), and sulfur (S) in substrate is closely linked, where lack or imbalance in any element can hinder SOC sequestration (Kirkby et al., <xref ref-type="bibr" rid="B21">2014</xref>; Fang et al., <xref ref-type="bibr" rid="B10">2018</xref>). Theories such as &#x0201C;microbial nutrient mining&#x0201D; and &#x0201C;microbial stoichiometry metabolism&#x0201D; provide insights into the complex interplay between microorganisms and substrates across environments varying in resource availability (Chen et al., <xref ref-type="bibr" rid="B5">2014</xref>; Heuck et al., <xref ref-type="bibr" rid="B13">2015</xref>). That is, the SS determines the direction and intensity of microbial catabolism and anabolism. For example, while adding C-rich straw alone accelerates SOC minerralization, combining straw with balanced fertilizers promotes SOC accumulation (Fang et al., <xref ref-type="bibr" rid="B10">2018</xref>; Wu et al., <xref ref-type="bibr" rid="B50">2022</xref>). Studies have since explored how regulating SS mediates the balance between C loss (priming) and sequestration (assimilation), thus influencing SOC dynamics (Kirkby et al., <xref ref-type="bibr" rid="B20">2013</xref>, <xref ref-type="bibr" rid="B21">2014</xref>; Zhu et al., <xref ref-type="bibr" rid="B57">2022</xref>). However, microbial communities partition into copiotrophs, which dominate in nutrient-rich conditions, and oligotrophs, adapted to nutrient-poor environments. Prior studies have also pointed out that regulating SS based on the stoichiometric ratio of soil humus may not align with the actual metabolic demands of microorganisms (Kirkby et al., <xref ref-type="bibr" rid="B21">2014</xref>). Hydrolases, which adapt to microbial metabolic strategies and resource availability, also play a crucial role in these interactions (Jiang et al., <xref ref-type="bibr" rid="B16">2019</xref>). Recent efforts to regulate SS according to microbial biomass stoichiometry aim to satisfy the quantitative conversion of C sources (Zhu et al., <xref ref-type="bibr" rid="B57">2022</xref>). This approach helps optimize management practices that meet the needs of oligotrophs or copiotrophs, revealing their impacts on NC accumulation.</p>
<p>Northeast China, a region contributing 25% of the national grain, has lost 0.41 Mg C ha<sup>&#x02212;1</sup> over the past three decades under intensive agriculture (Zhao et al., <xref ref-type="bibr" rid="B54">2018</xref>; Liu et al., <xref ref-type="bibr" rid="B29">2023</xref>). This study aim to investigate the pathways and regulatory factors of SOC accumulation under varying SS levels tailored to microbial preferences (stoichiometric application of C, N, P, and S) in this region. A field <italic>in situ</italic> experiment was conducted throughout the maize season to (a) clarify the formation dynamics of PNC and MNC and their contributions to SOC at 0&#x02013;40 cm soil depth; and (b) reveal the control factors and mechanisms of NC accumulation regulated by SS. We hypothesized that: (I) SS aligned with copiotroph requirements would enhance PNC digestion and MNC entombment; and (II) P-acquiring enzymes dominant NC accumulation under SS favoring oligotrophs (SS<sub>O</sub>), while C-acquiring enzymes prevail under SS meeting copiotrophs (SS<sub>C</sub>).</p></sec>
<sec id="s2">
<title>2 Materials and methods</title>
<sec>
<title>2.1 Site description</title>
<p>Our study was conducted from May to October 2023 at the Changtu Station of the Institute of Applied Ecology (123&#x000B0;57&#x02032;E, 37&#x000B0;48&#x02032;N), Chinese Academy of Sciences, China. This region is characterized by a semi-humid continental monsoon climate, with an average annual temperature of 7&#x000B0;C and an annual rainfall of 580 mm, predominantly occurring from July to September. The average temperature and rainfall during the growing period (May to October) are 20&#x000B0;C and 420 mm, respectively. The soil, classified as Phaeozem (FAO), is loamy clay with 29% sand, 40% silt, and 31% clay. The SOC, total N, P, and S concentrations in the 0&#x02013;20 cm layer were 10.9, 0.90, 0.40, and 0.22 g kg<sup>&#x02212;1</sup>, respectively. The experimental area follows an annual maize cropping system.</p></sec>
<sec>
<title>2.2 Experiment design</title>
<p>To optimize the conversion of exogenous C into SOC, we manipulated the SS to match the requirements ranging from oligotrophs to copiotrophs. We assumed the stoichiometric ratios of fungi (C:N:P:S = 10,000:1,034:110:94) and bacteria (C:N:P:S = 10,000:2,004:494:264) reflected substrate requirements of oligotrophs and copiotrophs based on values published in Kirkby et al. (<xref ref-type="bibr" rid="B21">2014</xref>) and Zhu et al. (<xref ref-type="bibr" rid="B57">2022</xref>). This study provided different SS levels by applying varying amounts of straw and N, P, and S (<xref ref-type="table" rid="T1">Table 1</xref>). A total of five treatment groups were established: straw-amended soil with no nutrient addition (NPS0), NPS0 with nutrient additions to meet the metabolic requirements from fungi (NPS1) to bacteria (NPS3), and a control soil (CK). The ideal humification efficiency of the added straw was set to 30%. The straw, cut into 2&#x02013;5 mm pieces, was mixed with soil at a rate of 2 g per 100 g dry soil. The C, N, P, and S concentrations in the pieces were 417.6, 9.74, 1.20, and 1.19 g kg<sup>&#x02212;1</sup>, respectively. The SS was regulated by adding or not adding the nutrient solutions (NS<sub>1</sub>, NS<sub>2</sub>, or NS<sub>3</sub>) containing ammonium nitrate, potassium dihydrogen phosphate, and ammonium sulfate (pH = 7). The concentrations of N, P, and S in NS<sub>1</sub> were 6.42, 1.79, and 0.95 g L<sup>&#x02212;1</sup>, in NS<sub>2</sub> were 19.50, 3.52, and 1.90 g L<sup>&#x02212;1</sup>, and in NS<sub>3</sub> were 30.72, 9.98, and 4.23 g L<sup>&#x02212;1</sup>, respectively.</p>
<table-wrap position="float" id="T1">
<label>Table 1</label>
<caption><p>The amount of substrates added and their stoichiometric ratio.</p></caption>
<table frame="box" rules="all">
<thead>
<tr style="background-color:#919498;color:#ffffff">
<th valign="top" align="left"><bold>Treatment</bold></th>
<th valign="top" align="center" colspan="4"><bold>Substrate addition (mg 100 g</bold><sup><bold>&#x02212;1</bold></sup> <bold>soil)</bold></th>
<th valign="top" align="center" colspan="4"><bold>Stoichiometric ratio</bold></th>
</tr>
</thead>
<tbody>
<tr style="background-color:#919498;color:#ffffff">
<td/>
<td valign="top" align="center"><bold>IH Maize-C</bold></td>
<td valign="top" align="center"><bold>Nutrient-N</bold></td>
<td valign="top" align="center"><bold>Nutrient-P</bold></td>
<td valign="top" align="center"><bold>Nutrient-S</bold></td>
<td valign="top" align="center"><bold>C:</bold></td>
<td valign="top" align="center"><bold>N:</bold></td>
<td valign="top" align="center"><bold>P:</bold></td>
<td valign="top" align="center"><bold>S</bold></td>
</tr> <tr>
<td valign="top" align="left">CK</td>
<td valign="top" align="center">0</td>
<td valign="top" align="center">0</td>
<td valign="top" align="center">0</td>
<td valign="top" align="center">0</td>
<td valign="top" align="center">&#x02013;</td>
<td valign="top" align="center">&#x02013;</td>
<td valign="top" align="center">&#x02013;</td>
<td valign="top" align="center">&#x02013;</td>
</tr> <tr>
<td valign="top" align="left">NPS0</td>
<td valign="top" align="center">250.54</td>
<td valign="top" align="center">19.49</td>
<td valign="top" align="center">2.39</td>
<td valign="top" align="center">2.38</td>
<td valign="top" align="center">10,000</td>
<td valign="top" align="center">778</td>
<td valign="top" align="center">95</td>
<td valign="top" align="center">95</td>
</tr> <tr>
<td valign="top" align="left">NPS1</td>
<td valign="top" align="center">250.54</td>
<td valign="top" align="center">19.49 &#x0002B; 6.42</td>
<td valign="top" align="center">2.39 &#x0002B; 1.79</td>
<td valign="top" align="center">2.38 &#x0002B; 0.95</td>
<td valign="top" align="center">10,000</td>
<td valign="top" align="center">1,034</td>
<td valign="top" align="center">167</td>
<td valign="top" align="center">133</td>
</tr> <tr>
<td valign="top" align="left">NPS2</td>
<td valign="top" align="center">250.54</td>
<td valign="top" align="center">19.49 &#x0002B; 19.50</td>
<td valign="top" align="center">2.39 &#x0002B; 3.52</td>
<td valign="top" align="center">2.38 &#x0002B; 1.90</td>
<td valign="top" align="center">10,000</td>
<td valign="top" align="center">1,556</td>
<td valign="top" align="center">238</td>
<td valign="top" align="center">171</td>
</tr> <tr>
<td valign="top" align="left">NPS3</td>
<td valign="top" align="center">250.54</td>
<td valign="top" align="center">19.49 &#x0002B; 30.72</td>
<td valign="top" align="center">2.39 &#x0002B; 9.98</td>
<td valign="top" align="center">2.38 &#x0002B; 4.23</td>
<td valign="top" align="center">10,000</td>
<td valign="top" align="center">2,004</td>
<td valign="top" align="center">494</td>
<td valign="top" align="center">264</td>
</tr></tbody>
</table>
<table-wrap-foot>
<p>CK, soil only; NPS0, soil &#x0002B; straw; NPS1&#x02013;NPS3, soil &#x0002B; straw &#x0002B; incremental nitrogen, phosphorus, and sulfur addition; IH Maize-C, ideal humus amount of straw carbon; C:N:P:S, The stoichiometric ratios of carbon, nitrogen, phosphorus and sulfur in the substrates. The data followed the &#x0201C;&#x0002B;&#x0201D; refers to the amount of extra nutrients added of each treatment.</p>
</table-wrap-foot>
</table-wrap></sec>
<sec>
<title>2.3 <italic>In situ</italic> cultivation</title>
<p>Topsoil (0&#x02013;20 cm) and subsoil (20&#x02013;40 cm) samples (8 kg each) were collected, sieved at 2 mm, and air-dry. Any visible plant and animal debris and gravel were removed. The SS (NPS1&#x02013;NPS3) was regulated by adding 1 ml of NS<sub>1</sub>, NS<sub>2</sub>, or NS<sub>3</sub> to 100 g of dry topsoil on a clean and smooth plastic sheet. The soil moisture was then adjusted to 60% field capacity with distilled water, followed by the addition and mixing of 2 g straw fragments. The mixture was then transferred to nylon mesh bags and sealed (aperture: 0.048 mm, length: 20 cm, and width: 15 cm). The subsoil was treated in the same manner. Nine replicates were maintained for each treatment for both topsoil or subsoil. Three soil pits (length: 1.5 m, width: 0.5 m, depth: 0.4 m) spaced at 0.6 m apart were dug in the field, and the topsoil and subsoil were stored separately. Three replicates of each treatment for subsoil were arranged in two rows (spaced &#x0007E;20 cm) and vertically placed at 20&#x02013;40 cm in each pit. Each pit was backfilled with the original subsoil. The same procedure was followed to fill the pits with the replicates of the five treatments for topsoil. Maize (<italic>Xianyu 1483</italic>) was artificially sown in the landfill area (plant spacing: 27 cm and row spacing: 60 cm). All replicates from one pit were collected at 30, 90, and 150 days post-sowing, then brought back to the laboratory with dry ice and stored at &#x02212;80&#x000B0;C.</p></sec>
<sec>
<title>2.4 Soil basic properties</title>
<p>Part of each replicate was air-dried, and any straw residue was carefully removed using the dry-sieving winnowing method (Kirkby et al., <xref ref-type="bibr" rid="B21">2014</xref>). The sample was then passed through a 0.15-mm sieve. The SOC concentration was determined through potassium dichromate oxidation and ferrous sulfate titration (Kalembasa and Jenkinson, <xref ref-type="bibr" rid="B18">1973</xref>). The soil available P (SAP) concentration was determined through sodium bicarbonate solution leaching colorimetry (Sparks et al., <xref ref-type="bibr" rid="B43">2020</xref>). In another part of the fresh soil sample, any incompletely decomposed straw residues were removed. The sample was examined under a low-power electron microscope to confirm the absence of straw debris. The soil moisture content (SM) was measured using the oven-drying method. The concentration of soil available N [AN, ammonium N (<inline-formula><mml:math id="M1"><mml:msubsup><mml:mrow><mml:mtext>NH</mml:mtext></mml:mrow><mml:mrow><mml:mn>4</mml:mn></mml:mrow><mml:mrow><mml:mo>&#x0002B;</mml:mo></mml:mrow></mml:msubsup></mml:math></inline-formula>-N) and nitrate N (<inline-formula><mml:math id="M2"><mml:msubsup><mml:mrow><mml:mtext>NO</mml:mtext></mml:mrow><mml:mrow><mml:mn>3</mml:mn></mml:mrow><mml:mrow><mml:mo>-</mml:mo></mml:mrow></mml:msubsup></mml:math></inline-formula>-N)] was determined through potassium chloride leaching method (soil-liquid ratio 1:5), followed by analysis with a continuous flow analyzer (FLAStar 5000, Foss, Germany).</p></sec>
<sec>
<title>2.5 Microbial necromass C</title>
<p>MNC was assessed using glucosamine (GlcN) and muramic acid (MurA) as biomarkers. An air-dried sample (1 g) was hydrolyzed at 105&#x000B0;C for 8 h in a hydrolytic tube. Then, 100 &#x003BC;L inositol was added to the tube, mixed, filtered, and dried at 65&#x000B0;C. The residue was dissolved in 20 mL pure water (pH: 6.6&#x02013;6.8), centrifuged (4,000 rpm, 10 min), and freeze-dried. The freeze-dried residue was dissolved with 5 mL anhydrous methanol, centrifuged, transferred to a 5-mL bottle for derivatization with N-methylglucosamine after freeze-drying. The sample was reacted with 300 &#x003BC;L of derivative reagent, sealed, and swirled for 30 s. After adding 1 mL of acetic anhydride, 1.5 mL of dichloromethane, and 1 mL of hydrochloric acid to the sample in a water bath, the inorganic phase was removed by phase separation, and this process was repeated thrice. The remaining organic phase was dried with N<sub>2</sub> gas at 45&#x000B0;C, and the residue was dissolved in 300 &#x003BC;L of diluent for gas chromatography analysis (Agilent 6890A, VT-1 column:30 m &#x000D7; 0.25 mm &#x000D7; 0.25 &#x003BC;m). Refer to Chen et al. (<xref ref-type="bibr" rid="B6">2021</xref>) for gas flow rate and column heating procedure.</p>
<p>Bacterial NC (BNC) and fungal NC (FNC) were calculated as follows (Appuhn and Joergensen, <xref ref-type="bibr" rid="B1">2006</xref>; Liang et al., <xref ref-type="bibr" rid="B26">2019</xref>):</p>
<disp-formula id="E1"><mml:math id="M3"><mml:mtable columnalign="left"><mml:mtr><mml:mtd><mml:mtext>BNC</mml:mtext><mml:mo>=</mml:mo><mml:msub><mml:mrow><mml:mtext>C</mml:mtext></mml:mrow><mml:mrow><mml:mtext>MurA</mml:mtext></mml:mrow></mml:msub><mml:mtext>&#x000A0;</mml:mtext><mml:mo>&#x000D7;</mml:mo><mml:mtext>&#x000A0;</mml:mtext><mml:mn>45</mml:mn></mml:mtd></mml:mtr><mml:mtr><mml:mtd><mml:mtext>FNC</mml:mtext><mml:mo>=</mml:mo><mml:mrow><mml:mo stretchy="false">(</mml:mo><mml:mrow><mml:msub><mml:mrow><mml:mtext>C</mml:mtext></mml:mrow><mml:mrow><mml:mtext>GlcN</mml:mtext></mml:mrow></mml:msub><mml:mo>/</mml:mo><mml:mn>179</mml:mn><mml:mo>.</mml:mo><mml:mn>17</mml:mn><mml:mo>-</mml:mo><mml:mn>2</mml:mn><mml:mtext>&#x000A0;</mml:mtext><mml:mo>&#x000D7;</mml:mo><mml:mtext>&#x000A0;</mml:mtext><mml:msub><mml:mrow><mml:mtext>C</mml:mtext></mml:mrow><mml:mrow><mml:mtext>MurA</mml:mtext></mml:mrow></mml:msub><mml:mo>/</mml:mo><mml:mn>251</mml:mn><mml:mo>.</mml:mo><mml:mn>23</mml:mn></mml:mrow><mml:mo stretchy="false">)</mml:mo></mml:mrow><mml:mtext>&#x000A0;</mml:mtext><mml:mo>&#x000D7;</mml:mo><mml:mtext>&#x000A0;</mml:mtext><mml:mn>179</mml:mn><mml:mo>.</mml:mo><mml:mn>17</mml:mn><mml:mtext>&#x000A0;</mml:mtext><mml:mo>&#x000D7;</mml:mo><mml:mtext>&#x000A0;</mml:mtext><mml:mn>9</mml:mn></mml:mtd></mml:mtr></mml:mtable></mml:math></disp-formula>
<p>where C<sub>MurA</sub> and C<sub>GlcN</sub> are the concentrations of MurA and GlcN, respectively (mg g<sup>&#x02212;1</sup>), 45 is the conversion coefficient between MurA and BNC, 179.17 and 251.23 are the relative molecular weights of GlcN and MurA, respectively, and 9 is the conversion coefficient between GlcN and FNC (Joergensen, <xref ref-type="bibr" rid="B17">2018</xref>). MNC was estimated as the sum of FNC and BNC (Sradnick et al., <xref ref-type="bibr" rid="B44">2014</xref>).</p></sec>
<sec>
<title>2.6 Plant necromass C</title>
<p>PNC was assessed using lignin phenols (vanillyl (V), syringyl (S), and cinnamyl (C) phenols) as biomarkers (Hedges and Ertel, <xref ref-type="bibr" rid="B12">1982</xref>). Approximately 0.5 g dry soil was mixed with 500 mg CuO, 100 mg ammonium sulfate, 50 mg glucose, 0.4 mL internal standard, and 15 mL NaOH in a Monard reactor. The oxidation products were centrifuged (3,000 rpm, 15 min), acidified (pH 1.8&#x02013;2.2), and kept in dark for 1 h. After centrifugation, the supernatant was diluted to 100 mL with ethyl acetate, rotary- evaporated (&#x0003C;38&#x000B0;C), and dried with N<sub>2</sub>. The residue was dissolved with 50 &#x003BC;L pyridine and 100 &#x003BC;L N, O-bis (trimethylsilyl) trifluoroacetamide (60&#x000B0;C, 10 min), then analyzed by gas chromatography (Agilent 6890A). PNC is calculated as follows:</p>
<disp-formula id="E2"><mml:math id="M4"><mml:mtable columnalign="left"><mml:mtr><mml:mtd><mml:mtext>PNC</mml:mtext><mml:mo>=</mml:mo><mml:mrow><mml:mo stretchy="false">(</mml:mo><mml:mrow><mml:msub><mml:mrow><mml:mtext>C</mml:mtext></mml:mrow><mml:mrow><mml:mtext>V</mml:mtext></mml:mrow></mml:msub><mml:mo>/</mml:mo><mml:mn>0</mml:mn><mml:mo>.</mml:mo><mml:mn>33</mml:mn><mml:mtext>&#x000A0;</mml:mtext><mml:mo>&#x0002B;</mml:mo><mml:mtext>&#x000A0;</mml:mtext><mml:msub><mml:mrow><mml:mtext>C</mml:mtext></mml:mrow><mml:mrow><mml:mtext>S</mml:mtext></mml:mrow></mml:msub><mml:mo>/</mml:mo><mml:mn>0</mml:mn><mml:mo>.</mml:mo><mml:mn>9</mml:mn><mml:mo>&#x0002B;</mml:mo><mml:msub><mml:mrow><mml:mtext>C</mml:mtext></mml:mrow><mml:mrow><mml:mtext>C</mml:mtext></mml:mrow></mml:msub></mml:mrow><mml:mo stretchy="false">)</mml:mo></mml:mrow><mml:mo>/</mml:mo><mml:mrow><mml:mo stretchy="false">(</mml:mo><mml:mrow><mml:mn>0</mml:mn><mml:mo>.</mml:mo><mml:mn>08</mml:mn><mml:mtext>&#x000A0;</mml:mtext><mml:mo>&#x000D7;</mml:mo><mml:mtext>&#x000A0;</mml:mtext><mml:mn>1</mml:mn><mml:mo>,</mml:mo><mml:mn>000</mml:mn></mml:mrow><mml:mo stretchy="false">)</mml:mo></mml:mrow></mml:mtd></mml:mtr></mml:mtable></mml:math></disp-formula>
<p>where C<sub>V</sub>, C<sub>S</sub>, and C<sub>C</sub> are the C concentrations in V, S, and C, respectively (&#x003BC;g g<sup>&#x02212;1</sup>). The release coefficients of V, S, and C by CuO oxidation were 0.33, 0.90, and 1.00, respectively (Hautala et al., <xref ref-type="bibr" rid="B11">1997</xref>). The minimum lignin concentration in plant residues of major crops is set to 0.08 (Burgess et al., <xref ref-type="bibr" rid="B3">2002</xref>). One thousand is the conversion coefficient between &#x003BC;g and mg.</p></sec>
<sec>
<title>2.7 Soil microbial traits</title>
<p>The activities of five hydrolases were detected using the 96-well fluorescent plate method according to Saiya-Cork et al. (<xref ref-type="bibr" rid="B39">2002</xref>). These included enzymes for C (&#x003B2;-glucosidase, BG; cellobiohydrolase, CBH), N (N-acetyl-&#x003B2;-glucosaminidase, NAG; leucine aminopeptidase, LAP), and P (acid phosphatase, AP) acquisition. Each replicate of a 1-g fresh sample was mixed with the respective substrates and incubated at 25&#x000B0;C for 4 h in the dark (substrates were presented in <xref ref-type="supplementary-material" rid="SM1">Supplementary Table S1</xref>). The fluorescent plate was reading using a microplate reader to evaluate the enzymatic activities (Synergy H1M, USA, 365 nm excitation and 450 nm emission).</p>
<p>The microbial diversity and composition of were determined through amplicon sequencing. Primers 515F (5&#x02032;-GTGCCAGCMGCCGCGG-3&#x02032;) and 907R (5&#x02032;-CCGTCAATTCMTTTRAGTTT-3&#x02032;) were used to amplify the V3&#x02013;V4 region of the 16S rRNA gene. Primers ITS1F (5&#x02032;-CTTGGTCATTTAGAGGAAGTAA-3&#x02032;) and ITS2R (5&#x02032;-GCTGCGTTCTTCATCGATGC-3&#x02032;) were used to amplify the ITS gene. The 20 &#x003BC;L PCR system contained 4 &#x003BC;L of 5&#x000D7; TransStart FastPfu buffer, 2 &#x003BC;L of 2.5 mM dNTPs, 0.8 &#x003BC;L of each primer, and 0.4 &#x003BC;L TransStart FastPfu DNA polymerase.</p>
<p>PCR products were recovered through 2% agarose gel electrophoresis and purified using the AxyPrep DNA Gel Extraction Kit (Axygen Biosciences, CA, USA). The library was constructed using the NEXTFLEX Rapid DNA-Seq Kit and sequenced using the Miseq platform (Illumina Miseq PE300, USA). Bacteria were classified using the SILVA database (Release 138), while fungi were identified using the UNITE database (Release 8.0) (Quast et al., <xref ref-type="bibr" rid="B38">2012</xref>; Nilsson et al., <xref ref-type="bibr" rid="B35">2018</xref>).</p></sec>
<sec>
<title>2.8 Statistical analysis</title>
<p>Statistical differences in MNC, PNC, BNC, FNC, lignin phenols, SOC, AN, SAP, SM, enzyme activities, &#x003B1;-diversity index and gene abundance (phylum level) among various treatments and soil depths were identified by one-way ANOVA and Duncan&#x00027;s multiple comparisons (<italic>p</italic> &#x0003C; 0.05) in SPSS 19 (IBM, Chicago, IL, USA). The C/V to S/V ratios reflect the intensity of microbial transformation of plant lignin, with a lower ratio indicating a higher transformation intensity (K&#x000F6;gel, <xref ref-type="bibr" rid="B22">1986</xref>). Principal coordinates analysis (PCoA) based on Bray-Curtis distance was employed to assess the dispersion patterns of microbial communities in R (version 4.4.0). Random forest models were used to reveal the influences of soil physical, chemical and microbial traits on soil NC by the &#x0201C;randomForest&#x0201D; and &#x0201C;rfPermute&#x0201D; package according to Archer (<xref ref-type="bibr" rid="B2">2016</xref>) in R (version 4.4.0). Finally, a schematic diagram was used to reveal the potential mechanisms and pathways of MNC and PNC formation in topsoil and subsoil. All figures were prepared using SigmaPlot (version 12.5, Systat Software, Chicago, IL, USA).</p></sec></sec>
<sec id="s3">
<title>3 Results</title>
<sec>
<title>3.1 Variations of MNC and PNC at different substrate matching levels</title>
<p>MNC and PNC concentrations were influenced by SS (<xref ref-type="fig" rid="F1">Figure 1</xref>). Compared to NPS0, NPS3 increased MNC by 7.6%&#x02212;8.4% in the topsoil (days 90 and 150) and by 11.8%&#x02212;18.1% in the subsoil. Concurrently, PNC was reduced by 4.4%&#x02212;17.5% in the topsoil and by 10.6%&#x02212;21.7% in the subsoil (days 90 and 150). Whereas, NPS1 did not significantly affect MNC or PNC. Under the same treatments, MNC and PNC concentrations were higher in the topsoil than in the subsoil. Over time, the contribution of MNC to SOC increased from 52.0% to 66.4% in the topsoil and from 42.9% to 53.2% in the subsoil. The contribution of PNC to SOC decreased from 38.9% to 15.3% in the topsoil and from 39.2% to 13.3% in the subsoil.</p>
<fig id="F1" position="float">
<label>Figure 1</label>
<caption><p>Dynamics of microbial necromass C <bold>(A&#x02013;C)</bold> and plant necromass C <bold>(D&#x02013;F)</bold> in topsoil (0&#x02013;20 cm, blue) and subsoil (20&#x02013;40 cm, orange) under varied substrate stoichiometry on days 30, 90, and 150. Different lowercase or uppercase letters above bars mean significant differences among treatments in topsoil and subsoil, respectively (<italic>p</italic> &#x0003C; 0.05). Asterisk indicates significant difference between topsoil and subsoil (<italic>p</italic> &#x0003C; 0.05). CK, soil only; NPS0, soil &#x0002B; straw; NPS1&#x02013;NPS3, soil &#x0002B; straw &#x0002B; incremental nitrogen, phosphorus, and sulfur addition.</p></caption>
<alt-text>Bar graphs showing microbial and plant necromass carbon content over time at different soil depths and stages: jointing (day 30), florescence (day 90), and maturity (day 150). Microbial necromass is in panels A, B, C; plant necromass is in panels D, E, F. Data is separated by soil depths 0-20 cm (blue) and 20-40 cm (orange). Each panel compares CK, NPS0, NPS1, NPS2, and NPS3 treatments, with letters indicating statistical differences.</alt-text>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmicb-16-1619932-g0001.tif"/>
</fig>
<p>FNC was more responsive to changes in SS than BNC (<xref ref-type="fig" rid="F2">Figure 2</xref>). Compared with NPS0, NPS3 increased FNC by an average of 14.8% in both topsoil and 20.8% in the subsoil. In contrast, NPS3 reduced BNC in the topsoil by 6.0%&#x02212;13.6%, with no change in the subsoil. The FNC and BNC concentrations in the topsoil were 1.4&#x02013;1.7 times and 0.9&#x02013;1.3 times those in the subsoil, respectively. The microbial transformation intensity of phenols gradually increased from NPS0 to NPS3, with the subsoil showing higher intensity than the topsoil (<xref ref-type="fig" rid="F3">Figure 3</xref>).</p>
<fig id="F2" position="float">
<label>Figure 2</label>
<caption><p>Changes in fungal necromass C <bold>(A&#x02013;C)</bold> and bacterial necromass C <bold>(D&#x02013;F)</bold> in topsoil (0&#x02013;20 cm, blue) and subsoil (20&#x02013;40 cm, orange) under different substrate stoichiometries on days 30, 90, and 150. Different lowercase or uppercase letters mean significant differences among treatments in topsoil and subsoil, respectively (<italic>p</italic> &#x0003C; 0.05). Asterisks denote significant differences between topsoil and subsoil (<italic>p</italic> &#x0003C; 0.05). CK, soil only; NPS0, soil &#x0002B; straw; NPS1&#x02013;NPS3, soil &#x0002B; straw &#x0002B; incremental nitrogen, phosphorus, and sulfur addition.</p></caption>
<alt-text>Bar graph showing fungal and bacterial necromass C across different treatments (CK, NPS0, NPS1, NPS2, NPS3) over days 30, 90, and 150. Two depth levels (0-20 cm and 20-40 cm) are compared in panels A-F. Fungal necromass decreases over time, while bacterial necromass remains relatively stable. Statistical significance is indicated by different letters above bars.</alt-text>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmicb-16-1619932-g0002.tif"/>
</fig>
<fig id="F3" position="float">
<label>Figure 3</label>
<caption><p><bold>(A&#x02013;C)</bold> Ratios of cinnamyl to vanillyl phenol (C/V) vs syringyl to vanillyl (S/V) for lignin phenols in topsoil (0&#x02013;20 cm, circle) and subsoil (20&#x02013;40 cm, square)under different substrate stoichiometric ratios on days 30, 90, and 150. Red and blue dashed lines represent the mean values for topsoil and subsoil, respectively (<italic>n</italic> &#x0003D; 3). Asterisks indicate significant differences between topsoil and subsoil (<italic>p</italic> &#x0003C; 0.05). CK, soil only; NPS0, soil &#x0002B; straw; NPS1&#x02013;NPS3, soil &#x0002B; straw &#x0002B; incremental nitrogen, phosphorus, and sulfur addition.</p></caption>
<alt-text>Scatter plots showing C/V versus S/V ratios at three different times: Day 30, Day 90, and Day 150. Each plot compares 0-20 cm and 20-40 cm soil depths using different treatments (NPS0, NPS1, NPS2, NPS3). Markers indicate treatment types with a legend detailing color coding. An arrow labeled &#x0201C;Microbial transformation&#x0201D; points from high to low C/V values across the plots.</alt-text>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmicb-16-1619932-g0003.tif"/>
</fig>
</sec>
<sec>
<title>3.2 Response of soil basic properties to substrate stoichiometry</title>
<p>Compared with NPS0, NPS1&#x02013;NPS3 increased the SM of the subsoil by 8.7%&#x02212;23.6% on day 30, while no change was observed in the topsoil (<xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S2</xref>). The concentrations of AN and SAP increased from NPS1 to NPS3. For instance, the SAP concentration in the topsoil increased from 18.2 mg kg<sup>&#x02212;1</sup> (NPS0) to 32.7 mg kg<sup>&#x02212;1</sup> (NPS3). The activities of BG (NPS3) and AP (NPS0&#x02013;NPS3) were higher in the subsoil than in the topsoil at days 30 and 90 (<xref ref-type="fig" rid="F4">Figure 4</xref>). Compared with NPS0, only NPS3 decreased the Ace of bacteria by 10.6% in the subsoil on day 30, with no change was observed in other treatments or soil layers (<xref ref-type="supplementary-material" rid="SM1">Supplementary Figures S4A</xref>&#x02013;<xref ref-type="supplementary-material" rid="SM1">C</xref>). No change was observed in the Ace of fungi among NPS0&#x02013;NPS3 (<xref ref-type="supplementary-material" rid="SM1">Supplementary Figures S4G</xref>&#x02013;<xref ref-type="supplementary-material" rid="SM1">I</xref>). PCoA analysis showed that the incremental addition of nutrient substrates increased the dispersion degree of both bacterial and fungal communities compared with NPS0 (<xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S5</xref>).</p>
<fig id="F4" position="float">
<label>Figure 4</label>
<caption><p>Activities of enzymes involved in C <bold>(A&#x02013;C)</bold>, N <bold>(D&#x02013;F)</bold>, and P <bold>(G&#x02013;I)</bold> acquisition under different substrate stoichiometries at three sampling times. Different lowercase or uppercase letters mean significant differences among treatments in topsoil and subsoil, respectively (<italic>p</italic> &#x0003C; 0.05). Asterisks indicate significant differences between topsoil and subsoil (<italic>p</italic> &#x0003C; 0.05). BG, &#x003B2;-glucosidase; LAP, L-leucine aminopeptidase; AP, acid phosphatase; CK, soil only; NPS0, soil &#x0002B; straw; NPS1&#x02013;NPS3, soil &#x0002B; straw &#x0002B; incremental nitrogen, phosphorus, and sulfur addition.</p></caption>
<alt-text>Bar charts showing enzyme activity levels (BG, LAP, and AP) at different soil depths (0-20 cm and 20-40 cm) over 150 days. Panels A-C depict BG activity, D-F show LAP, and G-I present AP. Time intervals are Day 30, Day 90, and Day 150. Green dots represent 0-20 cm, and green squares indicate 20-40 cm. Variations in enzyme activity are marked with star symbols and letters indicating statistical significance.</alt-text>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmicb-16-1619932-g0004.tif"/>
</fig>
<p>In the topsoil, <italic>Proteobacteria, Acidobacteriota</italic>, and <italic>Actinobacteriota</italic> predominanted, accounting for 34%&#x02212;44%, 17%&#x02212;22%, and 18%&#x02212;24% of the bacterial community, respectively. In the subsoil, the dominant bacteria were <italic>Actinobacteriota, Proteobacteria</italic>, and <italic>Firmicutes</italic>, accounting for 24%&#x02212;42%, 14%&#x02212;41%, and 8%&#x02212;19%, respectively (<xref ref-type="fig" rid="F5">Figure 5</xref>). Compared to NPS0, NPS1&#x02013;NPS3 enriched the abundances of <italic>Proteobacteria, Planctomycetota</italic>, and <italic>Bacteroidota</italic> in both topsoil and subsoil, while the <italic>Firmicutes</italic> abundance increased only in the subsoil. Fungal compositions were similar between topsoil and subsoil. NPS1 increased <italic>Mortierellomycota</italic> abundance by 61%, but had no effect on Ascomycota. NPS3 increased <italic>Ascomycota</italic> and <italic>Mortierellomycota</italic> abundances by 23% and &#x02212;24.7%, respectively (<xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S6</xref>).</p>
<fig id="F5" position="float">
<label>Figure 5</label>
<caption><p>Bacterial community composition on days 30 and 150 under varying substrate stoichiometries in topsoil and subsoil. Different letters indicate significant differences among treatments (<italic>p</italic> &#x0003C; 0.05). CK, soil only; NPS0, soil &#x0002B; straw; NPS1&#x02013;NPS3, soil &#x0002B; straw &#x0002B; incremental nitrogen, phosphorus, and sulfur addition.</p></caption>
<alt-text>Stacked bar charts show the composition of bacterial communities at depths of 0&#x02013;20 cm and 20&#x02013;40 cm on days 30 and 150 across treatments CK, NPS0, NPS1, NPS2, and NPS3. Different bacterial groups are color-coded, including Proteobacteria, Acidobacteriota, and others. Statistical differences are denoted by letters a, b, c, etc. Annotations highlight enriched and depleted bacteria.</alt-text>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmicb-16-1619932-g0005.tif"/>
</fig></sec>
<sec>
<title>3.3 Control factors over MNC and PNC formation</title>
<p>Seventeen variables were used to reflect the impact of soil physical, chemical and biological parameters on NC (<xref ref-type="fig" rid="F6">Figure 6</xref>). For NPS1, <italic>Planctomycetota</italic>, AN, SM, Ace-Bacteria, and AP were the primary factors regulating MNC changes, with the effects of <italic>Mortierellomycota, Firmicutes</italic>, and SAP on MNC in the subsoil being more pronounced. <italic>Planctomycetota</italic>, Ace-Bacteria, SAP, AP, and SM were the most important factors regulating PNC changes, with the effects of AN and <italic>Firmicutes</italic> being enhanced in the subsoil. For NPS3, MNC changes were more reliant on <italic>Proteobacteria</italic>, AN, SAP, SM, and BG, with the effects of Ace-Bacteria on MNC in the subsoil being more pronounced. PNC changes were predominantly influenced by <italic>Planctomycetota</italic>, AN, Ace-Fungi, BG, and <italic>Mortierellomycota</italic>, with SAP&#x00027;s influence being more pronounced in the subsoil.</p>
<fig id="F6" position="float">
<label>Figure 6</label>
<caption><p>Relative influence of soil variables on microbial and plant necromass C (MNC, PNC) under oligotrophic <bold>(A, C)</bold> and copiotrophic conditions <bold>(B, D)</bold> in topsoil and subsoil by the percentage increase of the mean squared error (MSE). Significant variables are highlighted in green and red for topsoil and subsoil, respectively (<italic>p</italic> &#x0003C; 0.05). SM, soil moisture; AN, soil available nitrogen; SAP, soil available phosphorus; BG, &#x003B2;-glucosidase; AP, acid phosphatase; EV, total explained variance; NPS1, substrate stoichiometry to match fungal needs; NPS3, substrate stoichiometry to match bacterial needs.</p></caption>
<alt-text>Four scatter plots, labeled A to D, show the mean square error (MSE) increase percentage for different microbial taxa in topsoil and subsoil. Topsoil is marked with green triangles, and subsoil with red squares. Each plot is titled (A) MNC-NPS1, (B) MNC-NPS3, (C) PNC-NPS1, and (D) PNC-NPS3. Taxa names are listed on the left: Planctomycetota, Gemmatimonadota, Actinobacteria, and others. Explained variances (EV) for each plot are provided; for example, plot A has EV topsoil = 68 and EV subsoil = 67.</alt-text>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmicb-16-1619932-g0006.tif"/>
</fig>
<p>The schematics of the evolution of NC were constructed by key factors under SS<sub>O</sub> and SS<sub>C</sub> (<xref ref-type="fig" rid="F7">Figure 7</xref>). Under NPS1, dominant bacteria (e.g., <italic>Planctomycetota</italic>), AP, and SM controlled NC changes, with MNC and PNC being more affected by AN and SAP, respectively. <italic>Firmicutes</italic> significantly impacted NC in the subsoil. Under NPS3, a broader range of bacteria, including <italic>Proteobacteria</italic>, were mobilized, with BG and AN playing important roles in NC changes. Fungi and their richness controlled more in the variation of PNC in topsoil.</p>
<fig id="F7" position="float">
<label>Figure 7</label>
<caption><p>Schematic diagram of MNC and PNC formation under substrate stoichiometric matching (oligotrophic to copiotrophic) in topsoil and subsoil. MNC, microbial necromass C; PNC, plant necromass C; FNC, fungal necromass C; BNC, bacterial necromass C; V, S and C, vanillyl, syringyl, and cinnamyl phenols; Nu, nutrient availability; SM, soil moisture; AN, soil available nitrogen; SAP, soil available phosphorus; BG, &#x003B2;-glucosidase; LAP, L-leucine aminopeptidase; AP, acid phosphatase; Ace-B/F, Acetate of bacteria/fungi; Pla, Planctomycetota; Bac, Bacteroidota; Act, Actinobacteriota; Gem, Gemmatimonadota; Aci, Acidobacteriota; Asc, Ascomycota; Mor, Mortierellomycota; Glo, Glomeromycota.</p></caption>
<alt-text>Diagram illustrating microbial interactions at different soil depths: 0 cm, 20 cm, and 40 cm. Shows ex vivo and in vivo environments with bacteria and fungi needs, including chemical symbols N, P, and S. Contains diagrams for microbial community changes, highlighting percentages for MNC and PNC. Elements like AP, Nu, and SM are linked to bacterial or fungal needs, with arrows indicating interaction. Labels include Pla, Gem, Mor, Bac, and Ace-B, with varying organisms within circles at different depths, differentiated into shallow and deep zones.</alt-text>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmicb-16-1619932-g0007.tif"/>
</fig></sec></sec>
<sec id="s4">
<title>4 Discussion</title>
<sec>
<title>4.1 Changes in MNC and PNC in response to substrate stoichiometry</title>
<p>The accumulation of MNC positively responded to the integration of straw with N, P, and S (<xref ref-type="fig" rid="F1">Figures 1A</xref>&#x02013;<xref ref-type="fig" rid="F1">C</xref>), which was consistent with the hypothesis I. Generally, C-rich but nutrient-poor substrates (NPS0) limit microbial anabolism, while C- and nutrient-rich substrates (NPS3) promote anabolic processes by satisfying microbial stoichiometric demands (Heuck et al., <xref ref-type="bibr" rid="B13">2015</xref>). Our previous study also established a positive correlation between microbial C assimilation and nutrient availability (Wu et al., <xref ref-type="bibr" rid="B49">2023</xref>). Optimizing the SS to meet the needs from fungi to bacteria promotes microbial proliferation and accelerates growth cycles, particularly for fungi, thus enhancing MNC accumulation (Liang et al., <xref ref-type="bibr" rid="B28">2007</xref>; Tian et al., <xref ref-type="bibr" rid="B45">2024</xref>). Consistent with the previous findings, this study also found that the MNC concentration in the topsoil was higher than that in the subsoil, primarily due to the frequent input, and decomposition of plant-derived C (Cotrufo et al., <xref ref-type="bibr" rid="B9">2013</xref>; Zhou et al., <xref ref-type="bibr" rid="B55">2023</xref>). The 15% increase of MNC in the subsoil (vs. 8% in the topsoil) highlighted SS&#x00027;s role in overcoming the nutrient limitations in less disturbed subsoil (Zhang et al., <xref ref-type="bibr" rid="B52">2020</xref>). Thus, adjusting SS according to bacterial metabolic needs promoted MNC accumulation in the short-term field trials.</p>
<p>PNC dynamics further underscored this mechanism: its decline under NPS3 (<xref ref-type="fig" rid="F1">Figures 1D</xref>&#x02013;<xref ref-type="fig" rid="F1">F</xref>) revealed a SS-driven shift from <italic>ex vivo</italic> modification to <italic>in vivo</italic> turnover. Upon straw incorporation, microbes and enzymes preferentially decomposed labile C, leaving behind <italic>ex vivo</italic>-modified recalcitrant C and driving PNC accumulation (Liang et al., <xref ref-type="bibr" rid="B27">2017</xref>). However, nutrient supplementation enabled microbes to reuse the remaining C via faster growth cycles, and the C/V and S/V ratios confirmed the gradual microbial transformation of PNC (<xref ref-type="fig" rid="F3">Figure 3</xref>) and the &#x0201C;entombing effect&#x0201D; of MNC (Fang et al., <xref ref-type="bibr" rid="B10">2018</xref>; Tian et al., <xref ref-type="bibr" rid="B45">2024</xref>). The topsoil&#x00027;s lower PNC transformation intensity compared to the subsoil could be linked to the continuous input of plant materials, leading to rapid C component update and reduced metabolic extents (K&#x000F6;gel, <xref ref-type="bibr" rid="B22">1986</xref>; Chen et al., <xref ref-type="bibr" rid="B6">2021</xref>). Moreover, the higher water availability in the subsoil may promote microbial transformation (Matthews et al., <xref ref-type="bibr" rid="B31">2023</xref>). Therefore, nutrient supplementation induced PNC digestion and its potential transfer to MNC.</p>
<p>The dominance of FNC over BNC (<xref ref-type="fig" rid="F2">Figure 2</xref>) indicated the distinct responses of oligotrophs and copiotrophs to SS variations. The oligotrophic nature of fungi meant that improved substrate accessibility both shortened their life cycles and mediated community selection, ultimately promoting FNC accumulation (Fang et al., <xref ref-type="bibr" rid="B10">2018</xref>; Tian et al., <xref ref-type="bibr" rid="B45">2024</xref>). While, bacterial necromass is preferentially dissolved duo to structural weakness, which precisely explains that the contribution of FNC to MNC is greater than that of BNC (Nakas and Klein, <xref ref-type="bibr" rid="B34">1979</xref>). The distribution difference of FNC between topsoil and subsoil was more pronounced, as aerobic topsoil conditions further amplified its accumulation (Moritz et al., <xref ref-type="bibr" rid="B33">2009</xref>). Therefore, the variations of FNC and BNC were influenced by microbial life strategies and environmental conditions, with FNC contributing more to MNC.</p></sec>
<sec>
<title>4.2 Evolutions of biochemical properties in response to substrate stoichiometry</title>
<p>The regulation of SS altered the biochemical properties of both topsoil and subsoil in the short term, highlighting the tightly interplay between soil nutrient dynamics and microbial responses. Soil nutrient capacity especially SAP increase, from NPS0 to NPS3 (<xref ref-type="supplementary-material" rid="SM1">Supplementary Table S2</xref>), was driven not only by direct P amendments but also by the integration of straw, which acts as a conduit for P activation (Wu et al., <xref ref-type="bibr" rid="B50">2022</xref>). Moreover, straw incorporation activated a synergistic action of <italic>Pseudomonas</italic> and phosphatase, substantially improving soil P availability (Hu et al., <xref ref-type="bibr" rid="B15">2018</xref>). The subsoil showed enhanced nutrient buildup relative to the topsoil, resulting from its native nutrient deficiency and oxygen-limited conditions conducive to nutrient retention (Chen et al., <xref ref-type="bibr" rid="B7">2020</xref>). Such conditions, while suppressing aerobic processes, unexpectedly intensify substrate amendment effects, as indirectly evidenced by the sensitive response of microbial community&#x00027;s dispersion degree to substrate addition in the subsoil (<xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S5</xref>). Additionally, water availability regulated NC formation by enhancing subsoil microbial activity and substrate diffusion, thereby supporting microbial growth and subsequent NC production (Matthews et al., <xref ref-type="bibr" rid="B31">2023</xref>).</p>
<p>The hydrolases involved in <italic>ex vivo</italic> modification were significantly influenced by the SS (Liang et al., <xref ref-type="bibr" rid="B27">2017</xref>; Jiang et al., <xref ref-type="bibr" rid="B16">2019</xref>). Our results revealed that optimized SS preferentially stimulated BG and AP activities in the subsoil, exceeding topsoil enzyme levels during early decomposition stages (<xref ref-type="fig" rid="F4">Figure 4</xref>). The enhanced enzymatic activity demonstrated significantly increased substrate decomposition potential and nutrient cycling efficiency in the subsoil, challenging conventional views of subsoil inactivity while highlighting its sensitivity to nutrient amendments. Moreover, the narrow C:N:P acquisition enzyme ratios were observed among different treatments (<xref ref-type="supplementary-material" rid="SM1">Supplementary Table S3</xref>). Such metabolic consistency reflected microbial adaptive strategies that maintain a balanced enzymatic profile to engage in stoichiometric metabolism, ensuring integrated acquisition and utilization of substrate nutrients (Sinsabaugh et al., <xref ref-type="bibr" rid="B42">2009</xref>; Luo et al., <xref ref-type="bibr" rid="B30">2017</xref>). The declining C:N and C:P enzyme activity ratios observed in the topsoil from NPS0 to NPS3 likely resulted from oxygen-replete conditions and enhanced substrate availability, which promoted more efficient C assimilation over nutrient mining (Fang et al., <xref ref-type="bibr" rid="B10">2018</xref>; Chen et al., <xref ref-type="bibr" rid="B4">2018</xref>). This, in turn, promoted the production of nutrient-acquiring enzymes, effectively mitigating microbial biomass stoichiometric imbalances (especially for eutrophic environment). Therefore, microbial communities adjusted their enzymatic strategies in response to SS, with BG and AP serving as key drivers of nutrient cycling.</p>
<p>The primarily microbial taxa that dominated the <italic>in vivo</italic> turnover and promoted microbial biomass assimilation process were significantly influenced by SS (<xref ref-type="fig" rid="F5">Figure 5</xref> and <xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S5</xref>). Eutrophic bacteria (e.g., <italic>Proteobacteria</italic> and <italic>Planctomycetota</italic>), which actively participate in organic matter digestion and assimilation, demonstrated effective mobilization across soil horizons (Fang et al., <xref ref-type="bibr" rid="B10">2018</xref>; Kim et al., <xref ref-type="bibr" rid="B19">2021</xref>). The predominance of <italic>Proteobacteria</italic> in driving both microbial proliferation and necromass accumulation under SS<sub>C</sub> conditions stems from their preferential substrate utilization and central role in microbial assimilation pathways (Kim et al., <xref ref-type="bibr" rid="B19">2021</xref>; Shi et al., <xref ref-type="bibr" rid="B41">2023</xref>). <italic>Firmicutes</italic>, typically deep-seated bacteria, were selectively mobilized in the subsoil, demonstrating notable adaptability for C decomposition and recycling under oxygen- and nutrient-limited conditions (Zhang et al., <xref ref-type="bibr" rid="B53">2021</xref>). Fungal taxa, <italic>Ascomycota</italic> and <italic>Mortierellomycota</italic>, established dominance as primary decomposers across soil layers, exhibiting enzymatic capabilities for labile substrate degradation including sugars and cellulose (Pei et al., <xref ref-type="bibr" rid="B36">2019</xref>). Notably, <italic>Mortierellomycota</italic>, a nutrient-sensitive fungal phylum, demonstrated preferential activity in SS<sub>O</sub> conditions, as evidenced by its relatively high abundance under NPS1 (<xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S6</xref>). Substrate amendments substantially changed <italic>in vivo</italic> microbial turnover through selective mobilization of key taxa (Proteobacteria, Planctomycetota, and Mortierellomycota), which subsequently drived microbial assimilation processes.</p></sec>
<sec>
<title>4.3 Formation of necromass C regulated by substrate stoichiometry</title>
<p>The dynamics of MNC and PNC were influenced by varying factors from SS<sub>O</sub> to SS<sub>C</sub> in our short-term experiment (<xref ref-type="fig" rid="F6">Figure 6</xref>). While P availability selectively affected PNC formation under SS<sub>O</sub>, N availability universally dominated necromass regulation, consistent with its known multifunctional control over C catabolism and anabolism (Vu et al., <xref ref-type="bibr" rid="B46">2022</xref>). Under SS<sub>O</sub>, the catabolism of C source faces with nutrient limitations, particularly P limitation due to its strong adsorption capacity and rapid fixation in soil. To meet microbial substrate decomposition requirements, nutrient acquisition enzymes such as AP are required to release P from plant and soil (Jiang et al., <xref ref-type="bibr" rid="B16">2019</xref>). This explained the marked regulatory effect of AP activity on NC changes under NPS1. Conversely, under SS<sub>C</sub>, BG-mediated processes became the primary driver of NC change, reflecting C anabolism and recycling in bacterial-favoring environments that preferentially rely on C-acquiring enzymatic pathways. As discussed in Section 4.2, the chemotrophic preferences indicated that <italic>Firmicutes</italic> significantly impacted NC under SS<sub>O</sub> (especially in the subsoil), while <italic>Proteobacteria</italic> played an enhanced role under SS<sub>C</sub>. In addition to bacteria, fungi also control over NC variations (<xref ref-type="fig" rid="F6">Figures 6A</xref>, <xref ref-type="fig" rid="F6">D</xref>), particularly through <italic>Mortierellomycota</italic>-mediated mobilization of bioavailable P to maintain microbial stoichiometric balance (Zhang et al., <xref ref-type="bibr" rid="B51">2011</xref>). Thus, SS regulated NC dynamics by integrating the key roles of nutrient availability, enzymatic activities, and microbial strategies.</p>
<p>SS<sub>C</sub> significantly promoted the continuous accumulation of MNC (<xref ref-type="fig" rid="F7">Figure 7</xref>). In SS<sub>O</sub>-treated topsoil, dominant bacteria taxa cooperated with specialized fungal decomposers to employed P-acquiring enzymes to process and assimilate C sources. The availability of water and nutrient (especially N) showed significant positive correlations with this microbial process, underscoring the critical role of nutrient adequacy in regulating microbial metabolic activity. Under SS<sub>C</sub>, both the rate of MNC accumulation and its contribution to SOC showed gradually enhancement, predominantly driven by <italic>Proteobacteria</italic> and BG, alongside an increased incorporation of FNC. Generally, elevated nutrient availability preferentially stimulated copiotrophic bacterial activity, intensifying their contribution to MNC formation through BG-mediated C acquisition pathways, while simultaneously releasing BNC and FNC via turnover processes. The selective suppression of oligotrophic fungal taxa under eutrophic environments resulted in enhanced accumulation of FNC (Jiang et al., <xref ref-type="bibr" rid="B16">2019</xref>; Megyes et al., <xref ref-type="bibr" rid="B32">2021</xref>). Moreover, the structural stabilization of FNC reduces its bioavailability for microbial reuse, thus promoting its contribution to MNC over BNC (Nakas and Klein, <xref ref-type="bibr" rid="B34">1979</xref>). The influence of SS<sub>C</sub> on MNC in the subsoil was similar to that in the topsoil, though with a greater accumulation intensity in the subsoil. This disparity may be attributed to the inherent characteristics of the subsoil, as discussed in Section 4.1. In summary, SS meeting bacterial metabolic needs promoted MNC accumulation, which were mainly associated with dominant bacteria, N and P availability, and C-acquiring enzymes.</p>
<p>SS<sub>C</sub> also enhanced the consumption and transformation of PNC in both topsoil and subsoil. Under SS<sub>O</sub>, dominant bacteria taxa cooperated with certain fungal group to primarily decomposed labile substrates through AP-mediated P acquisition, while recalcitrant macromolecules (e.g., lignin phenols) underwent temporal stabilization, directly contributing to PNC. The availability of P demonstrated a significant positive correlation with this process, highlighting its critical role in facilitating microbial decomposition activities (Wu et al., <xref ref-type="bibr" rid="B49">2023</xref>). Under SS<sub>C</sub>, both PNC concentration and its contribution to SOC showed gradually declines, a pattern closely associated with N availability, BG activity, and <italic>Mortierellomycota</italic> abundance. In such environments, enhanced microbial assimilation of substrates leads to the transformation of plant-derived C to MNC via <italic>in vivo</italic> turnover. Therefore, the requirement for C-acquiring enzymes becomes more critical to convert partly decomposed plant material. Following depletion of labile plant substrates, previously sequestered PNC may undergo progressive microbial reactivation and catabolism (Liang et al., <xref ref-type="bibr" rid="B27">2017</xref>; Chen et al., <xref ref-type="bibr" rid="B6">2021</xref>). Meanwhile, certain fungal taxa, notably <italic>Mortierellomycota</italic>, may regulate bioavailable nutrient fluxes through dormancy or competition, thus influencing the dynamics of PNC (Zhang et al., <xref ref-type="bibr" rid="B51">2011</xref>). The shift from SS<sub>O</sub> to SS<sub>C</sub> attenuated P control over PNC while amplifying N regulation, reflecting SS-driven microbial resource allocation strategies. That is, P plays a central role in microbial catabolism under SS<sub>O</sub>, while microbial C assimilation is more reliant on N availability under SS<sub>C</sub> (Luo et al., <xref ref-type="bibr" rid="B30">2017</xref>; Jiang et al., <xref ref-type="bibr" rid="B16">2019</xref>; Vu et al., <xref ref-type="bibr" rid="B46">2022</xref>). Therefore, SS meeting bacterial demands enhances the transformation of PNC by primarily regulating N availability, dominant fungi and bacteria, and C-acquiring enzymes.</p></sec></sec>
<sec id="s5">
<title>5 Conclusion</title>
<p>This short-term study revealed that aligning substrate stoichiometry (SS) with microbial metabolic requirements induced adaptive shifts in microbial communities, enzymatic activities, and nutrient availability, thereby influencing the formation and transformation of MNC and PNC. Specifically, SS meeting bacterial requirements (SS<sub>B</sub>) enhanced MNC accumulation and accelerated PNC digestion, especially in the subsoil, compared to SS preferred by fungi (SS<sub>F</sub>). This enhancement is attributed to the stoichiometric supply of C, N, P, and S, which meets the metabolic demands of bacteria and supports microbial anabolism. Notably, the preferential release of FNC over BNC emerged as a key driver of MNC accumulation. Consequently, the efficiency and stability of MNC accumulation, particularly FNC, deserve further study to optimize SOC sequestration strategies. The formation of necromass C was predominantly controlled by certain bacteria taxa, such as <italic>Planctomycetota</italic> and <italic>Proteobacteria</italic>, while certain fungi, like <italic>Mortierellomycota</italic>, regulated the release or retention of soil nutrients. Our results highlighted the critical role of P-acquiring enzymes and P availability in microbial catabolism under SS<sub>F</sub>, and the role of C-acquiring enzymes in microbial anabolism under SS<sub>B</sub>. These findings emphasize the importance of aligning straw and nutrient inputs with bacterial metabolic demands to enhance MNC entombment and highlight the potential of subsoil MNC accumulation for C sequestration in the short term.</p></sec>
</body>
<back>
<sec sec-type="data-availability" id="s6">
<title>Data availability statement</title>
<p>The data that support the findings of this study are openly available at <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.5281/zenodo.16310622">https://doi.org/10.5281/zenodo.16310622</ext-link>.</p>
</sec>
<sec sec-type="author-contributions" id="s7">
<title>Author contributions</title>
<p>HW: Formal analysis, Writing &#x02013; original draft, Writing &#x02013; review &#x00026; editing, Investigation. LW: Data curation, Writing &#x02013; review &#x00026; editing, Investigation. XL: Methodology, Writing &#x02013; review &#x00026; editing, Software. WW: Writing &#x02013; review &#x00026; editing, Methodology, Data curation. CL: Conceptualization, Writing &#x02013; review &#x00026; editing. WD: Funding acquisition, Writing &#x02013; review &#x00026; editing, Resources, Supervision.</p>
</sec>
<sec sec-type="funding-information" id="s8">
<title>Funding</title>
<p>The author(s) declare that financial support was received for the research and/or publication of this article. This work was financially supported by the National Key R&#x00026;D Program of China (2022YFD1500600, 2023YFD1902600), the Natural Science Foundation of Hebei Province (D2024503009), and the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA28020300).</p>
</sec>
<ack><p>We thank LetPub (<ext-link ext-link-type="uri" xlink:href="https://www.letpub.com">www.letpub.com</ext-link>) for its linguistic assistance during the preparation of this manuscript.</p>
</ack>
<sec sec-type="COI-statement" id="conf1">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec sec-type="ai-statement" id="s9">
<title>Generative AI statement</title>
<p>The author(s) declare that no Gen AI was used in the creation of this manuscript.</p></sec><sec sec-type="disclaimer" id="s10">
<title>Publisher&#x00027;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
<sec sec-type="supplementary-material" id="s11">
<title>Supplementary material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fmicb.2025.1619932/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fmicb.2025.1619932/full#supplementary-material</ext-link></p>
<supplementary-material xlink:href="Data_Sheet_1.docx" id="SM1" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document" xmlns:xlink="http://www.w3.org/1999/xlink"/></sec>
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