Calcium promotes persistent soil organic matter by altering microbial transformation of plant litter

doi:10.21203/rs.3.rs-2606058/v1

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Calcium promotes persistent soil organic matter by altering microbial transformation of plant litter

https://doi.org/10.21203/rs.3.rs-2606058/v1

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published 19 Oct, 2023

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Calcium (Ca) can increase soil organic carbon (SOC) persistence by mediating physico-chemical interactions between organic compounds and minerals. Yet, Ca is also crucial for microbial adhesion, potentially affecting colonization of plant and mineral surfaces. The relative importance of Ca as a mediator of microbe-mineral-organic matter interactions and resulting SOC transformation has hereto been overlooked. We incubated ⁴⁴Ca labeled soils with ¹³C¹⁵N labeled leaf litter to study the effects of Ca on microbial transformation of plant litter and formation of mineral associated organic matter. Ca additions promoted hyphae-forming bacteria, which often specialize in colonizing surfaces, increased incorporation of plant litter into microbial biomass by 20% and carbon use efficiency by 40%, and reduced cumulative CO₂ emission by 5%, while promoting associations between minerals and microbial byproducts of plant litter. These findings expand the role of Ca in SOC persistence from solely a driver of physico-chemical reactions to a mediator of coupled abiotic-biotic cycling of SOC.

Earth and environmental sciences/Biogeochemistry/Carbon cycle

Earth and environmental sciences/Biogeochemistry/Element cycles

Globally, there is a positive correlation between exchangeable calcium (Ca), mostly found on clay minerals, and soil organic carbon (SOC) content in slightly acidic to alkaline soils^1,2. The conventional explanation for this relationship is that soil Ca can reduce SOC bioavailability, and increase SOC stocks, by driving physico-chemical associations between organic compounds and minerals, such as sorption^3–5, co-precipitation and complexation^6,7, and occlusion within mineral aggregates⁸. These mechanisms produce what is operationally defined as mineral-associated organic matter (MAOM), which has been shown to persist for longer timescales than bulk SOC^9–13.

MAOM is comprised mainly of microbial products, and its formation is therefore often conceptualized as a two-step process: (1) microbial transformation and assimilation of plant C, the principal source of SOC¹⁴, and (2) association of microbial products with soil minerals. The current paradigm for how Ca affects SOC accumulation overlooks its potential influence over the first step, microbial transformation of plant C, which is affected by its C:N, the microbial C use efficiency (CUE), and abiotic conditions (e.g., soil moisture and pH)^15–17. Plant C transformation may also be impacted by soil Ca content^18,19, since Ca is a key factor in microbial surface adhesion, such as to particulate organic substrates and soil minerals, biofilm development²⁰, and growth of surface-associated bacteria^21–23. Enrichment in bacterial taxa that attach to particulate C sources (i.e., plant litter or MAOM) may limit SOC gain due to enhanced litter mineralization¹⁹, or conversely, may enhance SOC gain by limiting litter decomposition¹⁸. This trade-off can be reflected in the quality and quantity of microbial biomass and metabolic by-products generated during litter decomposition, potentially impacting their downstream interactions with minerals, and SOC accrual²⁴.

Direct evidence for the effects of Ca on microbial SOC cycling are available from ecosystem scale liming experiments performed in acidic, organic forest soils^{18, 25–27}. Such liming experiments produce concomitant changes in soil pH and Ca whose effects can be difficult to disentangle. Nonetheless, addition of wollastonite (CaSiO₃) or calcitic lime (CaCO₃) has been found to decrease SOC mineralization rates, and an associated long-term accumulation of C in organic soil horizons^{18, 26–28}. While some laboratory experiments have shown that elevated Ca has contrasting effects on litter or SOC mineralization^18,19,29, others have shown that lime and gypsum additions can alter the soil microbiome and increase SOC content^30,31. Thus, despite evidence suggesting an underlying role of Ca in limiting decomposition^18,25,28, the specific roles of Ca in microbial transformation of plant C, and subsequent transfer of microbial products to MAOM, remain unclear.

Here, we tested the hypothesis that Ca promotes SOC persistence by altering microbiome structure and function in ways that govern plant litter degradation, and by altering the formation of microbial products available for stabilization on mineral surfaces. Specifically, we asked (1) whether Ca treatment will select for microbial taxa that specialize in a surface-attached lifestyle, (2) what effects this shift has on CUE and microbial uptake of litter, and (3) how Ca-induced changes to the microbiome affect the formation of newly formed MAOM, and what are the specific spatial and chemical roles that Ca plays in these organo-mineral interactions. To address these questions, we used microcosm experiments to determine whether adding Ca to soil favors microbial transformation of plant litter into microbial biomass and MAOM. We incubated a ⁴⁴CaCl₂-labeled Mollic Endoaqualf silt-loam soil from a fallow agricultural field, with ¹³C¹⁵N-labeled willow leaf litter for ~ 4 months, during which we measured total CO₂ and litter-derived ¹³CO₂ production. The microcosms were sampled at 4 days and ~ 4 months to determine the effects of elevated Ca on bacterial community and the transfer of leaf litter into microbial biomass and MAOM. FTIR-spectromicroscopy was used to study the formation of organo-mineral associations at the micron scale, while bulk Near Edge X-ray Absorption Fine Structure (NEXAFS) spectroscopy was used to evaluate the chemical speciation of C and Ca. Leveraging ⁴⁴Ca-labeling, we used nano-scale secondary ion mass spectrometry (NanoSIMS) to quantify the spatial co-localization of ⁴⁴Ca, ¹⁵N, and minerals in intact soil aggregates, to evaluate the effect of Ca on the formation of MAOM. Our results show a hitherto overlooked mechanism of Ca-driven changes to the soil microbiome which alter the conversion of plant-derived C into more persistent MAOM fractions.

Calcium alters microbial respiration, litter metabolism, and conversion to MAOM

Calcium addition reduced cumulative CO₂ production at T_beg (after 4 days; P = 0.011 and P = 0.064 under high and low water contents, respectively) and at T_end (after ~ 4 months; P = 0.017 and P = 0.033 under high and low water content, respectively) (Fig. 1A). However, Ca addition did not affect the proportion of CO₂ mineralized from litter (Fig. 1B). Soils treated with KCl, instead of CaCl₂, and incubated with litter for 16 days had similar mineralization rates to control soils, suggesting that the effects of the CaCl₂ treatment were due to Ca (Supplementary Fig. 1). We did not observe a significant interaction between water content and Ca addition (Supplementary Tables 2, 3, 4), and so we present results of combined data (low- and high-water content) in the main text and include the full results separately in the Supplementary information section (Supplementary Fig. 5).

Ca addition altered microbial growth and metabolism. Ca addition increased microbial CUE at T_beg (P < 0.001) (Fig. 1C) and increased the amount of ¹³C transferred from litter to microbial biomass at T_beg (P < 0.001) (Fig. 1D), though no significant effect was found at T_end (Supplementary Table 2). Total MBC and dissolved organic carbon (DOC) were not affected by Ca addition at either T_beg or T_end (Supplementary Fig. 6).

The effects of Ca on litter decomposition influenced the transfer of litter into the MAOM fraction. At T_beg, the proportion of litter-derived C and N in the MAOM fractions was lower in Ca-treated than control soils (P = 0.014 for C; P = 0.043 for N) (Fig. 1E, Supplementary Table 3). By T_end, there was no difference in MAOM between treatments (Fig. 1E, Supplementary Table 3). However, at T_end, the C:N ratio of litter-derived ¹³C¹⁵N on the MAOM fraction in Ca-treated soil was lower than control (P = 0.002) (Fig. 1F, Supplementary Table 3). The amount of occluded particulate organic matter (oPOM) was slightly higher in control than Ca-treated soils at T_end (Supplementary Table 4), but, overall, Ca treatment did not affect the proportion of litter-¹³C or ¹⁵N in free particulate organic matter (fPOM) and oPOM fractions (Supplementary Table 5). This finding suggests that occlusion of litter within aggregates was not an important mechanism by which Ca reduced respiration or altered microbial litter metabolism in our experiment.

Calcium-induced shifts in bacterial community composition

Bacterial community composition was significantly impacted by all treatment factors at both time points, as evidenced in the clustering of samples in a t-SNE ordination (Fig. 2A). At T_Beg, Ca and litter addition explained 28% and 32% of the variation among bacterial communities, respectively. At T_end, Ca addition explained an increasing proportion of variation in bacterial community composition (32%), more than explained by litter amendment (18%) (Fig. 2B). Moisture had a significant effect on bacterial community composition, but it explained less variation than Ca or litter (Fig. 2B). Ca addition brought about an immediate and enduring enrichment of many bacterial species identified as Firmicutes (class Bacilli) and Actinobacteria (classes Actinobacteria and Thermoleophilia) as well as select members of Proteobacteria (Supplementary Fig. 7). While most Proteobacteria declined in relative abundance in response to Ca addition, especially members of the Gammaproteobacteria (orders Burkholderiales and Pseudomonadales) and Alphaproteobacteria (Caulobacterales), a few groups were favored by Ca (orders Rhizobiales, Xanthomonadales). Ca caused a decline in relative abundance of those populations that were enriched in response to litter (see arrows in Fig. 2C), suggesting an effect of Ca on putative decomposers populations. A complete list of ASVs that were differentially abundant according to treatment factors, as well as further characterizations of the changes in the soil microbiome are provided as Supplementary Information (Supplementary Figs. 7–10).

Ca influences SOC chemical composition and spatial distribution

The effects of Ca on microbial community structure and utilization of litter affected bulk SOC composition, as measured by C K-edge NEXAFS spectroscopy. At T_beg, SOC composition was similar across treatments, but by T_end (after > 40% of the litter had been mineralized), Ca-treated soils showed a greater relative decrease in O-alkyl C content (289.4 eV) and a higher relative increase in aromatic-C and substituted aromatic-C content (285.3 and 286.7 eV, respectively) than controls, indicating greater decomposition of the carbohydrate component of litter in Ca treated soil (Fig. 3, Supplementary Table 5). This is consistent with the results that show enhanced incorporation of litter into microbial biomass (Fig. 1D).

We found that Ca affected the formation of organo-mineral associations using infrared spectromicroscopy (Fig. 4). The spatial co-localization of clay minerals and three organic functional groups (aromatic, aliphatic, and carboxylic) across intact microaggregate sections were higher in the Ca treated soil, as indicated by the higher coefficients of determination (R² values) both at T_beg and at T_end (Fig. 4B-D, 4F-H). Microaggregates from Ca treated soils also had greater organic loading per unit mineral content, as indicated by higher regression coefficients, and greater clay mineral abundances (greater absorbance at 3590–3700 cm^− 1). Lastly, we found that both R² and coefficients in regression models for carboxylic-C and aromatic-C in microaggregates from Ca treated soils, increased from T_beg to T_end, while these values decreased for aliphatic-C (Fig. 5B-D). In contrast, the greatest increase in R² and regression coefficient values in regression models of controls soils was in the relationship between clay minerals and aliphatic C (Fig. 5F-H). This is consistent with lower litter-derived C:N value of MAOM fractions in Ca-treated soils (Fig. 1F). These findings reflect Ca-driven formation of organo-mineral associations with microbial transformation products rich in carboxylic and aromatic functional groups.

We further investigated the role of Ca in MAOM formation by tracking litter-derived ¹⁵N on mineral surfaces using NanoSIMS with soils sampled at T_end (Fig. 5). NanoSIMS images reveal a heterogeneous arrangement of minerals, pores, and organic matter within sections of intact aggregates (Supplementary Fig. 11). Widespread ⁴⁴Ca enrichment was observed across both mineral- and organic matter-dominated regions (49.2 atom % at organic matter; 42.6 at mineral surfaces (Supplementary Fig. 11D). Images were segmented into mineral-dominated and organic matter-dominated regions (Fig. 5A) and each region was further classified as dominated by Ca, aluminum (Al), or iron (Fe) (Fig. 5B). Calcium addition increased co-localization of Ca with organic matter regions from 67.8–89.8% (Fig. 5D) and increased Ca co-localization with mineral regions from 10.7–13.9% (Fig. 5E). The effect of Ca addition on Ca co-localization with organic matter was greater when Ca and litter were added together compared to when only Ca was added (Supplementary Fig. 12A). Enrichment in ¹⁵N and CN:C ratio (the reciprocal of C:N ratio) were higher in Ca-dominated segments of mineral regions of Ca-treated soils compared to control soils (Fig. 5F, 5G, Supplementary Fig. 12F), which indicates that Ca addition enhanced mineral association with N-rich organic compounds. These micron-scale observations were consistent with bulk measurements which showed lower C:N from litter-derived ¹⁵N and ¹³C on the MAOM fraction of Ca-treated soils (Fig. 1D). Furthermore, when Ca was added, the ratio of Ca:CN at the mineral surface doubled compared to control (Fig. 5H), highlighting the interactions of mineral-bound Ca with N-rich OM, some of which was co-localized with litter-derived ¹⁵N (Fig. 5C). These results show, through evident co-localization, that Ca interacted at the mineral-litter interface, especially when Ca and litter were applied together, and enhanced deposition of litter transformation products onto mineral surfaces, forming potentially new organic-mineral associations.

Current conceptual frameworks assign the influence of Ca on SOC persistence solely to physico-chemical mechanisms such as sorption, co-precipitation, and occlusion of organic matter ^2,6,32. Our findings show that Ca addition exerted an immediate and prolonged influence on microbial community structure and litter metabolism, revealing upstream Ca effects on the biological properties of SOC cycling. We observed that Ca addition decreased soil respiration and increased the efficiency of litter C assimilation and subsequent transfer of highly processed litter C and N into the MAOM fraction. Our results support the hypothesis that Ca affects microbial community structure, altering microbial products derived from litter, and promoting enhanced stabilization of these products through Ca driven organo-mineral interactions. Here, we discuss the potential mechanisms underlying the changes in litter C cycling caused by Ca additions.

We observed two major trends in the effects of Ca on the bacterial community. First, Ca had a disproportionately large negative effect on ASVs favored by litter addition (Fig. 2C). This observation suggests that Ca treatment had a strong impact on decomposer communities, and that reduced net respiration resulted to some extent from a change in decomposer populations. However, we cannot test this relationship directly, as we lack information about changes in the absolute abundance of these populations. Second, Ca treatment enhanced the relative abundance of surface-colonizing bacterial taxa, including actinobacteria that form mycelia such as Nocardioides, Rhodococcus, Leifsonia, Streptomyces, Cellulomonas, Agromyces, and Pseudonocardia^33–36, and surface motile or surface-adhering populations such as Devosia, Hyphomicrobium, Haliangium, Sorangium, members of Fibrobacterota, Asticcacaulis, Luteimonas, and Adhaeribacter^37–44 (Supplementary Figs. 7, 8). Many of the same taxa were also similarly favored in a study of forest soil amended with calcitic lime, especially Nocardioides, Devosia, Haliangium, and Hyphomicrobium²⁶, suggesting that the observed shift in surface-colonizing bacteria is associated with Ca-driven processes.

The selection for surface-adhering bacterial populations can be explained by the fact that Ca is a critical co-factor in many modes of bacterial attachment (see Supplementary Information for more details) and biofilm production^20–23. We anticipate that surface-attached populations will exhibit differences in metabolism from those bacteria better adapted for growth in pore water, favoring slower growth rates, higher CUE, and an increase in microbial products that facilitate surface interactions (e.g., adhesive proteins and extracellular polymeric substances).

The Ca-induced shift in microbial processing of litter had a cascading effect on the C and N occurring as MAOM. In the Ca-treated soils, a larger fraction of MBC was derived from litter-C than in control soils, indicating that more litter was cycled through microbial biomass. This result was supported by the observation that MAOM consisted of compounds that were more microbially processed (lower C:N) in Ca-treated than control soil (Fig. 2F). Our data also show that Ca plays a direct role in the transfer of litter-derived decomposition products into the MAOM fraction – forming new organo-mineral associations. When Ca was added, we observed higher co-localization between clay minerals and organic compounds, greater organic loading, and increased clay mineral particle aggregation at sub-micron scales (Fig. 4). This is consistent with other studies who have shown that Ca can play an important role in mediating organo-mineral interactions^5,7,45. Furthermore, we found that the amount and co-localization of carboxylic-C and aromatic-C with clay minerals in Ca-treated soils increased with incubation time. This result indicates that organic matter accumulated in spatially constrained hotspots (Fig. 4), as suggested by recent studies^46,47, which may reflect the activity of microbial surface colonies which produce and deposit metabolic by-products on mineral surfaces. This observation is consistent with NanoSIMS measurements which showed increased Ca and litter-derived ¹⁵N co-localization on mineral surfaces (Fig. 5F).

Reduced C bioavailability due to Ca-driven sorption or precipitation of DOC did not appear to be the direct cause of lower mineralization rates since DOC concentrations were comparable in Ca-treated and control soils (Supplementary Fig. 6). Preliminary observations ruled out the effects of transient increase in soil salinity on mineralization with a KCl control (Supplementary Fig. 1), supporting our conclusion that Ca was solely responsible for the changes to mineralization, bacterial community composition, and C metabolism. Furthermore, if lower bioavailability of DOC or saline conditions were limiting factors, litter transformation in Ca-treated soils would also be reduced, which was not the case (Fig. 1D, Fig. 3).

Taken together, our results support our hypotheses that Ca additions affect microbial community structure, altering microbial products derived from litter, and promoting enhanced stabilization of these products through Ca-driven organo-mineral interactions. The Ca addition increased an already high exchangeable-Ca content (from 85–92% of the soil’s cation exchange capacity - CEC) (Supplementary Table 1) but did not change Ca speciation (Supplementary Figs. 2, 3), which raises the question: how did a minor increase in exchangeable Ca bring about a major change in both microbial processing and MAOM formation?

Based on our findings we conclude that the most likely mechanism (Fig. 6) was that Ca addition displaced other exchangeable cations, providing pristine sites for microbial attachments and adsorption of litter transformation products. Additionally, the elevated concentration of soluble Ca ions likely caused changes in microbial cell regulation which triggered a switch to surface colonization, as previously reported^48–51. Subsequently, surface-attached microbial cells, microbial by-products and necromass may have been deposited at greater loadings on mineral surfaces^52,53. Ca-driven organo-mineral associations of highly processed organic molecules likely reduced microbial access, increasing their persistence in soil. The latter explanation indicates that the biotic effect of Ca on microbial C cycling preceded the abiotic effect. Regardless, both scenarios suggest that even small changes in the concentration of soluble Ca can influence SOC cycling and persistence, whether through cation exchange processes on mineral surfaces or biochemical regulation of surface-attaching behavior.

Our study revealed the influence of Ca on previously overlooked biological mechanisms that affect MAOM formation. While the extent that Ca drives biotic controls over SOC cycling will be soil dependent, our findings suggest that amendments which raise soluble Ca content can increase the conversion of organic inputs to MAOM, a more persistent form of SOC. These observations raise the possibility that Ca additions may be used to manage SOC in agroecosystems. For example, Ca-containing soil amendments, like gypsum and lime, are commonly added to manage soil fertility, while basalt rock (calcium silicate) is applied to sequester inorganic C through enhanced rock weathering. These amendments may concomitantly impact SOC due to effects on microbial C cycling, especially when coupled with organic matter amendments. Understanding the nature of the soil Ca pools responsible for coupling biotic-abiotic SOC cycling processes will help optimize the management of Ca amendments and SOC stocks for more climate-smart soils.

Soil sampling

A Mollic Endoaqualf silt loam was collected at 0–15 cm from a fallow subplot located in an experimental bioenergy feedstock field trial in Ithaca, NY (42º N 28.20', 76º W 25.94'). The mean annual temperature and precipitation at the site were 10°C and 940 mm, respectively. Soil was air-dried, sieved to 2 mm, and visible plant detritus removed. The soil texture is 22.5% sand, 57.5% silt, and 20.0% clay. Soil total C and N contents are 3.66% and 0.36%, and δ¹³C and δ¹⁵N values are 27.6‰ and 5.3‰, respectively. Soil pH and electrical conductivity are 6.1 and 184 µS/cm, respectively, in a 1:2.5 soil:water extract (Supplementary Table 1). Exchangeable cations were extracted using 1 N ammonium acetate at pH 7 and measured on an inductively coupled plasma spectrometer (iCAP 6000 series, Thermo Fisher Scientific, Waltham, MA, USA). Soil water filled pore space (WFPS) was determined as previously described⁵⁴.

Experimental design

For reference, an overview of the three-factor factorial experimental design is provided in Fig. 7. A CaCl₂ solution at a concentration 200 meq/L (Ca treatment) or deionized water (control treatment) were added to the soil to reach a water content of 60%WFPS. Soils were then pre-incubated for one week at 20°C in Mason jars, after which all soils were leached on a filter funnel fitted with filter paper with consecutive 50-mL portions of deionized water until leachate electric conductivity was < 100 µS/cm, then soils were allowed to air dry. This method was chosen over shaking a soil slurry with a CaCl₂ solution ²⁵ to minimize impact on soil structure. The effect of salinity during Ca treatment on subsequent C dynamics was tested in a preliminary experiment in which soils were treated with KCl (200 meq/L) as above, incubated with plant litter for 16 days, and heterotrophic respiration was measured (Supplementary Fig. 1). Treatment with CaCl₂ resulted in a ~ 10% increase in exchangeable Ca, but did not change soil pH, EC, or aggregate slaking value compared to control (Supplementary Table 1). Based on Ca L-edge NEXAFS spectroscopy of the soil samples, Ca treatment did not alter Ca speciation and there was no evidence of excess CaCl₂ (Supplementary Figs. 2, 3, 4) (See Supplementary Information for details).

Soil microcosms consisted of air-dry soil (9 g, < 2 mm) mixed with labeled plant litter (2% by weight, < 1 mm) in 60-mL Qorpak vials. Litter was ¹³C¹⁵N-labeled (1.895 atom% ¹³C; 8.203 atom% ¹⁵N) willow leaves (Salix viminalis x S.miyabeana)⁵⁴. Calcium content in the willow leaves was ~ 15 mg/g dry weight, as determined using acid digestion. Litter addition to soil corresponded to 1.56 ± 0.03 meq Ca/100 g soil, or ~ 10% of initial exchangeable Ca after Ca treatment. Samples were wetted with deionized water and incubated (20°C) in a 2-by-2 factorial design with pre-incubation (Ca vs control) and water content, ‘low’ (40% WFPS) or ‘high’ (60% WFPS) as treatments. Soil microcosms without litter were included for each treatment combination. Moisture was included as a factor since it strongly influences both substrate availability and biotic activity^55,56.

Six jars were prepared for each treatment and the whole sample set was duplicated and destructively sampled after four days (T_beg) and at the end of the incubation (T_end), after 112 days (for high water content) or 135 days (for low water content). For NanoSIMS analysis (see below), a third set of microcosms was incubated with 1 g of soil treated with ⁴⁴CaCl₂ solution (97 atom%, Sigma Aldrich), and ¹³C¹⁵N labelled litter (2% w/w) at low or high water content and sampled only at T_end. Headspace CO₂ concentrations on the first two sets of microcosms were measured using KOH traps on days 1, 2, 3, 4, 6, 8, 11, 15, 21, 30, 44, 61, 91, and T_end, as previously described⁵⁷. Integrated measurement of ¹³CO₂ in days 0–4 (T_beg) and 5-112 (high WFPS) or 5-135 (low WFPS) (T_end) was obtained using the Ba¹³CO₃ method⁵⁸. We ended the incubation after a calculated 41.0% and 47.5% of the litter was mineralized under low or high water content, respectively. To estimate litter mineralization, we assumed that the difference in CO₂ between microcosms with and without litter (for each treatment and water content) was entirely contributed by litter mineralization.

Microbial biomass

For microbial biomass C (MBC) analysis, the six microcosms were randomly paired and composited into triplicate samples. MBC was measured following a standard fumigation-extraction method⁵⁹. Briefly, one subsample (1.33 g dry wt. equivalent) was immediately extracted by agitating for one hour in K₂SO₄ (0.05 M, 10 mL), while the other subsample was fumigated for 24 hours with ethanol-free chloroform (0.4 mL) prior to extraction with K₂SO₄. The extracts were passed through filter paper (0.45 µm, Advantec) and dissolved organic C was measured by combustion catalytic oxidation (TOC-VCPN TOC analyzer Shimadzu, Japan). A portion of the extract was freeze-dried, and total C and δ¹³C of the freeze-dried residue were measured using isotope ratio mass spectrometry (Delta V, Thermo Scientific, Germany) coupled to an elemental analyzer (NC2500, Carlo Erba, Italy).

Soil organic matter fractionation

We modified a procedure⁵⁷ for fractionating soils according to size and density to characterize the effects of Ca on operationally defined soil organic matter fractions relevant to SOC cycling, namely: free and occluded particulate organic matter, and mineral-associated organic matter (fPOM, oPOM, and MAOM, respectively). fPOM and oPOM contain mostly plant matter at different degrees of decomposition, while MAOM contains silt- and clay-size primary particles and organo-mineral complexes as well as < 53 µm microaggregates. Briefly, sodium polytungstate (1.65 g cm^− 3) was added to soil samples to isolate the floating material (fPOM) after centrifugation and filtration. Next, soils were shaken end-to-end in fresh sodium polytungstate solutions (1.65 g cm^− 3) for 18 hours with 3 mm glass beads to disrupt aggregates, and the floating material (oPOM) was collected. The remaining materials was shaken end-to-end in sodium hexametaphosphate (0.5% w/w) for 18 hours and sieved (53 µm) to separate sand from silt + clay sized particles (MAOM). All fractions were washed with deionized water, dried at 60°C, weighed, and ball milled. The mean mass recovery was 102%; C recovery ranged from 96 to 109%, and N recovery ranged from 98 to 106%. Six replicates were randomly paired and measured, along with bulk soils, for total C, N, δ¹³C, and δ¹⁵N, as above. We assumed total C equaled organic C since these soils did not contain carbonates, as previously determined⁶⁰.

C K-edge and Ca L-edge near edge X-ray adsorption fine structure (NEXAFS) spectroscopy

The chemical composition of SOC and soil Ca was determined by NEXAFS which was acquired at the C K-edge (270–320 eV) and Ca L-edge (340–360 eV) on composited (n = 6) bulk soils and reference materials at the spherical grating monochromator (SGM) beamline of the Canadian Light Source (Saskatoon, SK). For C analysis, spectra were deconvoluted into Gaussian functions that constitute contributions from aromatic-C, substituted aromatic-C, alkyl-C, carboxyl-C, O-alkyl C, and carbonyl-C⁶¹. For Ca analysis, the position of the two main peaks (L₂ at 349.4 and L₃ 352.6 eV), and the L_2/3 split ratio, which reflects Ca crystallinity, were compared among soils samples and to a set of reference Ca-containing materials which were measured in parallel to the soil samples: calcite, Ca-smectite, CaCl₂, CaSO₄, Ca-acetate, Ca-formate, and Ca-citrate. Full details are provided in the Supplementary Information section.

Mid infrared spectromicroscopy

We used FTIR spectromicroscopy to study the spatial distribution of organo-mineral associations. At least 8 sections (500 nm thick) of intact microaggregates (53–250 µm) were collected from samples composited for each treatment factor using a published protocol ⁶² and analyzed at the Mid Infrared Spectromicroscopy (Mid-IR) beamline of the Canadian Light Source (Saskatoon, SK) on an Agilent Cary 670 FTIR interferometer and an Agilent Cary 620 microscope. Full details on sample preparation, and data collection and analysis are provided in the Supplementary Information. Briefly, spectral maps (8–10 from each intact microaggregate) were created for the absorbance at 3620 (O-H groups of clay minerals), 2829–2920 (aliphatic-C), 1620 (aromatic-C), and 1413 cm^− 1 (carboxylic-C). We acknowledge that the band defined as aromatic-C^62–64, which spans from 1477 to 1756 cm^− 1, may also contain peaks contributed by N-H bending and C = N stretching (~ 1545 cm^− 1) and C = O stretching (~ 1650 cm^− 1). We did not analyze the polysaccharide peak at 900–1290 cm^− 1 since it overlaps with Si-O vibrations from clay minerals. The absorbance values were used to construct linear models to quantify the co-localization of organic chemical groups and clay minerals. We interpret linear models as follows: 1) absorbance values reflect chemical abundance, 2) coefficients of determination (R²) indicate co-localization, and 3) regression coefficients (β) quantify organic content per unit clay mineral. Due to beamtime limitations, only soils incubated at low water content at T_beg and at T_end were analyzed.

NanoSIMS

A NanoSIMS 50L (Cameca, Gennevilliers, France) was used to analyze the spatial distribution of litter-derived ¹³C¹⁵N, ⁴⁴Ca, and soil minerals on intact aggregates. A total of 37 measurements (4–7 per treatment) were collected with the O⁻ RF plasma source⁶⁵ to measure the spatial distribution of ²³Na⁺, ²⁴Mg⁺, ²⁷Al⁺, ³⁹K⁺, ⁴⁰Ca⁺, ⁴⁴Ca⁺, and ⁵⁶Fe⁺. The Cs⁺ source was used to conduct 37 measurements (4–9 per treatment) to measure the spatial distribution of ¹⁶O⁻, ¹²C₂⁻, ¹³C¹²C⁻, ¹²C¹⁴N⁻, ¹²C¹⁵N⁻, ²⁸Si⁻, and ⁴⁴Ca¹⁶O⁻. We focused on ¹²C¹⁵N⁻ as a fingerprint for ¹⁵N-enriched litter since the high enrichment of litter-N enabled more accurate isotopic analysis. Both primary ion sources were tuned to match an imaging resolution of approximately 120 nm with a field of view of 30 µm at 256 pixels with 30–40 consecutive planes. The dwell time was 1 ms pixel^− 1 at a primary current of 2 pA. Further details about sample preparation, and image processing and segmentation are provided in the Supplementary Information.

Bacterial community structure

Bacterial community structure was determined by 16S rRNA gene amplicon sequencing as previously described⁶⁶. A full description is available in the Supplementary Information. In brief, DNA was extracted from 0.25 g of freeze-dried soil sample using the Qiagen PowerSoil kits, according to the manufacturer’s protocol, and PCR was used to amplify the 16S rRNA gene (V4 region; 515f/806r). All sample metadata and raw sequencing data was archived under the NCBI BioProject accession: PRJEB48763. Sequencing data was processed using QIIME2 (v. 2020.2)⁶⁷ with a dependency on DADA2 (v. 1.10)⁶⁸ to assign sequences to amplicon sequence variants (ASVs). Taxonomic classification was performed using the QIIME2 ‘q2-feature-classifier’ trained on the Silva database (v. 138)⁶⁹. All counts were normalized by proportion of total reads and presented as counts per thousand reads.

Data analysis and statistics

The proportion of litter-derived C and N in soil and soil fractions, and C in microbial biomass C and CO₂, was determined from isotope data by applying a two-source mixing model,

$${f}_{litter}= \left(\frac{{at\%}_{sample}- {at\%}_{control}}{{at\%}_{litter}- {at\%}_{control}}\right)$$

where, ${f}_{litter}$ is the proportion of litter-derived C or N in a sample, ${at\%}_{sample}$ is the atom% ¹³C or ¹⁵N value of a sample (incubated with litter), ${at\%}_{control}$ is the atom% ¹³C or ¹⁵N value in the control sample (incubated without litter) and ${at\%}_{litter}$ is the atom% ¹³C or ¹⁵N of the labelled litter. ${f}_{litter}$ was multiplied by C or N concentration in each pool to calculate litter-derived C or N in µg C g^− 1 soil or µg N g^− 1 soil.

${f}_{litter}$ in microbial biomass was calculated as:

$${atom\%}^{13}{\text{C}}_{mic} =\frac{{at\%}^{13}{C}_{f}*{C}_{f}-at\%{C}_{nf}*{C}_{nf}}{{C}_{f}-{C}_{nf}}$$

Where ${at\%}^{13}{C}_{f}$ and ${at\%}^{13}{C}_{nf}$ are the ${at\%}^{13}$ values of the fumigated and non-fumigated samples and ${C}_{f}$ and ${C}_{nf}$ are the extracted C contents (µg C g^− 1 soil) of the corresponding samples. The control and treatment values for ${atom\%}^{13}{\text{C}}_{mic}$ were incorporated into the two-source mixing model to calculate the fraction of litter incorporated into the microbial biomass, then multiplied by the MBC pool size (µg MBC g^− 1) to calculate the mass of substrate incorporated into the biomass (MB¹³C).

Microbial carbon use efficiency (CUE) was calculated as:

$$CUE= \frac{\text{M}{B}^{13}\text{C}}{\text{M}{B}^{13}\text{C}+{}_{ }{}^{13}C{O}_{2}}$$

All statistical analyses were performed in R v4.0.4. The effects of Ca treatment, water content, and sampling time, and their interactions on cumulative CO₂ mineralization, microbial biomass C and CUE, total C and N, and proportion of labeled litter in CO₂ and soil fractions, were evaluated with an ANOVA using the aov function. Differences among treatments were evaluated using the emmeans function with a Tukey HSD correction for multiple comparisons. Linear regressions between peak heights obtained from FTIR spectromicroscopy were done using the lm function.

The alpha- and beta-diversity of bacterial communities were analyzed using the following approaches. PERMANOVA testing was performed using ‘adonis’ from the vegan package (v. 2.5.7) based on the Bray-Curtis dissimilarity calculated from bacterial community composition. The differential abundance of ASVs between contrasting treatments (± litter, ± calcium, and high / low moisture) were identified using the R package DESeq2 (v. 1.30.1). Non-significant indicator ASVs (p_adj < 0.05) and those which were less than 3-fold differentially abundant were excluded from analyses. The similarity among bacterial communities was visualized using t-distributed stochastic neighbor embedding (t-SNE) with Rtsne (v. 0.15). The main effects and interactions among treatments were determined by fitting to fixed effects linear models (‘lm’ function). Significant effects are denoted by asterisk: p < 0.05 (*), p < 0.01 (**), and p < 0.001 (***). Analyses were performed in R with a general dependency on the following packages: phyloseq (v. 1.34)

Acknowledgements

This work was supported by BARD, the United States - Israel Binational Agricultural Research and Development Fund, Vaadia-BARD Postdoctoral Fellowship Award No. FI-573-2018, and the U.S. Department of Energy, Office of Biological & Environmental Research Genomic Science Program Award No. DE-SC0016364. Part of the research described in this paper was performed at the Canadian Light Source, a national research facility of the University of Saskatchewan, which is supported by the Canada Foundation for Innovation (CFI), the Natural Sciences and Engineering Research Council (NSERC), the National Research Council (NRC), the Canadian Institutes of Health Research (CIHR), the Government of Saskatchewan, and the University of Saskatchewan.

Author contributions

I.A.S drafted and wrote the manuscript, designed and conducted experiments, and collected and analyzed data; R.C.W wrote the manuscript, collected and analyzed data, and provided critical revision of the article; and S.A.S. collected and analyzed data, and provided critical revision of the article; C.H. collected and analyzed data; D.H.B supported data collection and provided critical revision of the article; J.L. aided in designing the experiments, and provided critical revisions to the article. All authors have approved the final version for publication.

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Calcium promotes persistent soil organic matter by altering microbial transformation of plant litter

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Abstract

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Introduction

Results

Calcium alters microbial respiration, litter metabolism, and conversion to MAOM

Calcium-induced shifts in bacterial community composition

Ca influences SOC chemical composition and spatial distribution

Discussion

Methods

Soil sampling

Experimental design

Microbial biomass

Soil organic matter fractionation

C K-edge and Ca L-edge near edge X-ray adsorption fine structure (NEXAFS) spectroscopy

Mid infrared spectromicroscopy

NanoSIMS

Bacterial community structure

Data analysis and statistics

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References

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