Study sites and soil sampling
Our major study sites were located in a shrub-dominated bog13 in the Pocosin Lakes National Wildlife Refuge, NC, USA and a Sphagnum-dominated bog47 in the Marcell Experimental Forest, MN, USA (Supplementary Tables 1 and 2). Three sites (>1 km apart) around Pungo Lake including Pungo West, Pungo Southwest, and Pungo East were selected at the shrub bogs in North Carolina. Ilex glabra and Lyonia lucida cover about 85% and 10%, respectively at Pungo West. Ilex glabra and Lyonia lucida also dominate Pungo Southwest but distribute evenly, also there are many Woodwardia virginica ferns during the growing season. The water level at Pungo Southwest is always higher than at Pungo West. Both Pungo West and Pungo Southwest have prescribed light fire every 4–5 years. There has been no fire disturbance at the Pungo East site over last 30 years, where more dominant plant species exist, including Lyonia lucida, Ilex glabra, Zenobia pulverulenta, Gaylussacia frondosa, Vaccinium formosum.
One hollow and one hummock were selected at the Sphagnum-dominated bogs in Minnesota. A lot of mature trees including Picea mariana, Pinus resinosa, Larix laricina with different bryophytes and shrubs grow at both the hollows and the hummocks. S. fallax dominates the bryophyte layer at the hollows, and S. angustifolium and S. magellanicum dominate at the hummocks. The understory has a layer of ericaceous shrubs including Rhododendron groenlandicum, Chamaedaphne calyculata, Vaccinium oxycoccos at the hummocks, however, only scattered shrubs present in the hollows. Other site information is described in Supplementary Tables 1 and 2. We took three soil cores at each sites (with a distance >4 m from each other), and each soil core was sliced to four subsamples (0–5, 5–10, 10–15, and 15–20 cm). Big roots were removed in lab. The hair roots of all plants were included in the soil samples.
Additionally, we took three soil cores at depth 0–10 cm in the shrub-dominated area in Dajiuhu peatlands in Shennongjia, China (31°29′N, 109°59′E) in May 2017. The dominant shrub at Dajiuhu is Betula albosinensis and Spiraea salicifolia with a dense Sphagnum layer (detailed plant information is described in Supplementary Tables 1 and 2). The samples were transported to the laboratory in iceboxes. Half of the samples were frozen at −80 °C for DNA isolation; the other half was stored at 4 °C for chemical analysis.
Soil chemistry analysis
We used the deionized water extraction of fresh soil for DOC and soluble phenolics measurements. DOC was measured as the difference between total C and inorganic C with a total C analyzer (Shimadzu 5000 A, Kyoto, Japan). Soluble phenolics were measured by following the Folin-Ciocalteu procedure50. Inorganic nitrogen (NH4+–N and NO3−–N + NO2−–N) extract with 2 M KCl was determined colorimetrically on a flow-injection analyzer (Lachat QuikChem 8000, Milwaukee, WI, USA). Total carbon and nitrogen in soil were analyzed with combustion CN soil analyzer equipped with a TCD detector (ThermoQuest Flash EA1112, Milan, Italy). A 1:10 soil/water solution was used to measure soil pH.
DNA extraction, PCR, and sequencing
Genomic DNA was extracted from 0.25 g (fresh weight) of each homogenized soil sample using the PowerSoil DNA isolation kit (Mo Bio Laboratories, Carlsbad, CA, USA). DNA of each replicate was extracted 3 times and homogenized together as one DNA template. For Pocosin and Minnesota samples, a set of fungus-specific primers, ITS1F (3′-CTTGGTCATTTAGAGGAAGTAA-5′) and ITS4 (3′-TCCTCCGCTTATTGATATGC-5′), were used to amplify the internal transcribed spacer (ITS) region using barcoded ITS1F primers. For Dajiuhu samples, ITS1F and ITS2 (3′-GCTGCGTTCTTCATCGATGC-5′) were used. All PCR reactions were repeated in triplicate, together with the negative controls in which the template DNA was replaced with deionized H2O. The amplicon concentration of each sample was determined after purification using Qubit® 2.0 Fluorometer (Invitrogen, Grand Island, NY, USA), samples pooled at equimolar concentrations, purified using AMPure Bead cleanup. The amplicons from Pocosin, Minnesota and Dajiuhu samples were submitted to the core facility at Duke University (Durham, NC, USA) and Allwegene Tech Beijing (Beijing, China) for sequencing using Illumina MiSeq (Illumina, San Diego, CA, USA), respectively.
Bioinformatics processing
Sequence data of Pocosins and Minnesota samples were obtained from both ITS1 and ITS2 gene regions. ITS sequences were quality filtered and processed using the standard QIIME pipeline, with each fungal taxon represented by an OTU at the 97% sequence similarity level. Singleton OTUs were omitted51, and OTUs classified taxonomically using a QIIME-based wrapper of BLAST against the UNITE database52,53 (see Supplementary Methods for further details). The quality and depth of coverage of both primers’ reads were not significantly different, thus libraries from ITS4 reads were used for further analysis of fungal communities. Taxonomic-based alpha diversity was calculated as the total number of phylotypes (richness) and Shannon’s diversity index (H′). A total of 150,967 ITS sequences from ITS2 region passed quality control criteria in the Pocosin and Minnesota sites. These sorted into 590 OTUs. Following the same procedure, a total of 115,936 ITS1 sequences from Dajiuhu samples were assigned into 307 OTUs. Following the processing procedure described by Wilson et al.47, relative abundance of beta-proteobacteria at the controlled site in the boreal Sphagnum site was recalculated from Wilson and others’ sequence data34 available from the National Center for Biotechnology Information at SRP071256. Relative abundance of fungi from a bog forest at the Calvert Island in Canada was recalculated from the raw amplicon reads in the European Nucleotide Archive, ITS (ERS1798771-ERS1799064).
Lab incubations
The decomposing capability of microbes in the Sphagnum- and shrub-dominated peatlands
We tested the decomposing capability of microbes in the Sphagnum- and shrub-dominated peatlands by amending peat inocula from both sites in North Carolina and Minnesota to their peats and labile carbon-enriched mineral soil. Fresh Sphagnum- and shrub-formed peat inocula were prepared by mixing 0.5 kg of each type of fresh peat (10–20 cm) with 2 L of deionized water. After 1 h of stirring and 1-day settlement, the suspension liquid inoculum was filtered through a Buchner funnels (without filter, pore size 0.25–0.5 mm). We added 2 g of glucose to 50 g of nutrient-poor mineral soil (initially 0.05% total nitrogen, 0.64% total soil carbon) to produce a mineral soil medium with high labile carbon content. All incubation media (peat and mineral soil) and jars were sterilized by an autoclave before inoculation. About 30-g fresh Sphagnum-formed peat (2.5–2.8 g in dry weight) or shrub-formed peat (9.1–9.3 g in dry weight), or 50-g mineral soil with 2-g glucose was placed in Mason jars (triplicate, 8-cm diameter, 12-cm height, vacuum seal lid with a stainless-steel fitting with sampling septum), then 20 ml of its own or other’s inoculum was added to the peat media, and 5 ml of inoculum from each site was added to the mineral soil. Finally, all samples were aerobically incubated at a constant temperature of 25 °C. We initially used Parafilm M® Laboratory film, which is air permeable but water resistant, to seal the top for 3-day equilibration, afterward we collected gas samples by syringe from the headspace of each jar at the beginning and end of 1-h sealed incubation and used a GC (Varian 450, CA, USA) to analyze CO2 concentration. As microbial biomass itself is a factor regulating soil respiration rates, standardized CO2 emissions at the microbial biomass were calculated based on the elevated CO2 concentration, time, air volume in the jar, and the amount of added MBC from the inoculum. To prevent microbial acclimation to the assay chemistry18,31, we only incubated the soils for a short time. A chloroform fumigation-extraction method (0.5 M K2SO4 to extract biomass C)54 was used to determine soil MBC by the difference in measured carbon contents between fumigated and control replicates of each sample.
Temperature sensitivity
To test temperature sensitivity of soil respiration, nine fresh peat samples (30 g) from each site were added to jars and sealed with Parafilm M® Laboratory film. Triplicate samples were incubated at 4, 25, and 44.5 °C. The highest temperature in this incubation does not match the in situ conditions in our sites, but it may happen shortly in tropical wooded peatlands in the future. After 3-day equilibration, we used the same method as above to measure gas emission and calculated soil respiration based on soil dry weight. We conducted regression analyses for soil from each site using R = αeβT, where R is soil respiration, coefficient α is the intercept of soil respiration when temperature is zero, coefficient β represents the temperature sensitivity of soil respiration, and T is soil temperature.
The relative contributions of fungi and bacteria to peat decomposition
We subsampled 20 g each of our archived material from the Sphagnum-dominated bog in Minnesota and the shrub-dominated peatland in North Carolina, then subsamples were well mixed to make two composite bulk samples (one for Sphagnum-formed peat, one for shrub-formed peat) for the following incubations.
A total of nine broad-spectrum antibiotics were tested either alone or in combination for their inhibition on bacteria or/and fungal respiration using a selective inhibition (SI) technique55 without glucose. The antibiotics include 5 fungicides (cycloheximide, benomyl, nystatin, natamycin, amphotericin B) and 4 bactericides (streptomycin, penicillin, oxytetracycline hydrochloride, neomycin). Both fungicide and bactericide were used alone or combined at concentrations of 0, 10, 20, 100, 500, and 1000 µg g−1 soil for the shrub-formed peat or 0, 35, 71, 357, 1785, and 3571 µg g−1 soil for the Sphagnum-formed peat. Each concentration of antibiotics (triplicate) was added to a 3-g fresh peat placed in a 50-ml tube. Mason jars (8-cm diameter, 12-cm height, vacuum seal lid with a stainless-steel fitting with sampling septum) are used to incubate the treated samples. CO2 accumulation rates over 24 h was measured and calculated as same as testing temperature sensitivity of soil respiration above. We found that all bactericides used in this study increased CO2 emission along with their concentrations. The results suggest that: (1) the contribution of bacteria to peat decomposition in general was simply very little, (2) the bacteria that were inhibited by bactericide contribute negligibly to peat decomposition, (3) the non-targeted bacteria were stimulated after the targeted-bacteria were inhibited, although the bactericides are broad-spectrum antibiotics, they did not inhibit the dominant bacteria at all in our sites, and /or (4) both bacteria and fungi in our sites may utilize these bactericides as a carbon source. As to the fungicide, only cycloheximide at a concentration of 357 µg g−1 soil slightly decrease CO2 emission in the Sphagnum-formed peat, but not the shrub-formed peat. Other fungicides did not suppress the CO2 emission regardless of their concentrations, or increased the CO2 emission along with increase in concentrations of fungicide, which suggest that these fungicides did not inhibit the dominant fungi in our sites. Therefore, we found no evidence that SI technique could detect the relative contribution of bacteria and fungi to peat decomposition in our sites. To further examine our fungal dominance hypothesis, we next used filtration by size to assess dominant decomposers.
According to the literature (e.g., refs. 56,57,58), the average size of most bacteria is between 0.2 and 2.0 µm in diameter, with most of them less than 1.5 µm; while most fungi grow as hyphae in soil, which are cylindrical, thread-like structures 1.5–10 µm in diameter and up to several centimeters in length57,59,60. The sizes of most fungal spore are more than 2.0 µm in diameter61,62,63. Theoretically, porous filters could physically separate bacteria from fungi58. Domeignoz-Horta et al.64 used 0.8-μm filter to exclude fungi successfully64. In our test, filters with pore sizes of 0.22, 0.45, 1.2, and 1.5 μm were selected. The filtrates through 1.2- and 1.5-μm filters contain most of the bacteria, in which a small portion of larger bacteria and small fungi may pass through pores due to a lack of rigidity of their cells58.
Sphagnum- and shrub-formed peat inocula were made by mixing 50 g of each type of fresh peat with 250 ml of sterilized deionized water. After 1 h of stirring and 1-day settlement, the suspension liquid inoculum was first filtered through a Buchner funnels (without filter, pore size 0.25–0.5 mm). The filtrate, we assumed, contain all bacteria and fungi while removing large decomposers like insects and worms. The 0.25–0.5 mm filtrate was used to make other inocula containing no-bacteria/fungi, nanobacteria and non-fungi, and most bacteria and non-fungi by filtering through 0.22- (nylon), 0.45- (nylon), 1.2- (glass fiber), and 1.5-μm (glass fiber) filters, separately. In total, 6 treatments including 5 inocula (filtrates through 0.22, 0.45, 1.2, 1.5, and 250–500-μm filters) and control (sterilized deionized water) were established. Either inoculum or sterilized deionized water was added to a 3-g sterilized Sphagnum- or shrub-formed peat (triplicate) and incubated at 25 °C. CO2 emission was measured within 24 h.
Statistical analysis
One-way ANOVA with Duncan’s multiple-range test was used to compare the means of soil physicochemical parameters. Standard error of the mean was calculated for each mean. The significant level of the test was set at a probability of 0.05. The ANOSIM function in the vegan package in R was used to test statistical significance in fungal composition within and among sites in the shrub- and the Sphagnum-dominated peatlands (999 permutations), which shows that fungal communities were significantly different within sites at the shrub-dominated peatlands (Pungo East, Pungo West, and Pungo Southwest) and at the Sphagnum-dominated peatlands (hollows and hummocks) (Supplementary Fig. 5). Mantel test and redundancy analysis (RDA) were employed to explain the relative roles of soil physicochemical factors in fungal community composition using vegan package in R. The correlation of the redundancy axes with the explanatory matrix was determined with the general permutation test (anova.cca function; 999 permutations). Stepwise regression was further run to test what primarily control the slow-growing versus fast-growing fungi and soil acidity.
Source: Ecology - nature.com
