Invasive Spartina anglica Greatly Alters the Rates and Pathways of Organic Carbon Oxidation and Associated Microbial Communities in an Intertidal Wetland of the Han River Estuary, Yellow Sea

Introduction

Organic materials deposited in marine sediments are quickly mineralized by hydrolysis, fermentation, and a variety of processes that use different terminal-electron acceptors, including O₂, NO₃^–, Mn(IV), Fe(III), and SO₄^2– (Froelich et al., 1979; Canfield et al., 2005; Jørgensen, 2006). In organic-rich coastal sediments, where oxygen penetration is limited to a depth of a few mm, sulfate reduction (SR) dominates the anaerobic organic carbon (C_org) oxidation process (Howarth and Giblin, 1983; Hines et al., 1989). However, in coastal areas where rapid iron cycling occurs, microbial Fe(III) reduction (FeR) becomes a significant anaerobic C_org oxidation pathway (Kostka et al., 2002a, b; Jensen et al., 2003; Hyun et al., 2007, 2009; Kristensen et al., 2011). Because of the abundance and highly reactive properties of iron and sulfur in marine sediments, the partitioning of C_org oxidation by FeR and SR has a profound influence on the distribution and behavior of redox-sensitive metals and nutrients (Jensen et al., 1995; Dollhopf et al., 2005; Quintana et al., 2015; An et al., 2019; Mok et al., 2019). Therefore, elucidation of the relative significance of FeR and SR in C_org oxidation can improve our understanding of biogeochemical processes in sediments (King et al., 2001; Koretsky et al., 2003; Hyun et al., 2009; Luo et al., 2016; An et al., 2019).

In sediment that experiences rapid turnover of elements, the dynamics (i.e., production or consumption) of chemical constituents can hardly be interpreted by geochemical analyses alone (Jørgensen, 2006). In such conditions, the composition and diversity of microbial communities are among the most sensitive and rapid bio-indicators of environmental change because microorganisms with fast growth rates respond quickly to changes in environmental conditions (Lovell, 2005; Bertics and Ziebis, 2009; Choi et al., 2018). Therefore, it is highly relevant to combine biogeochemical process analysis with microbiological information to confirm if certain C_org oxidation pathways occur or dominate under specific conditions, where the geochemical evidence is less informative in complex environments (Weiss et al., 2003; Dollhopf et al., 2005; Vandieken et al., 2012; Choi et al., 2018).

Intertidal sediments in coastal ecosystems are biogeochemical hot spots where organic material and inorganic nutrients turn over rapidly along the land-sea continuum (Alongi, 1998; Odum, 2000; Cook et al., 2004; Hyun et al., 2009; McLeod et al., 2011). In this respect, the Ganghwa intertidal wetland in Gyeonggi-Incheon Province in the mid-west of the Korean peninsula (Figure 1a) is a significant environmental buffer, mineralizing organic matter that arrives via the Han River, which passes through the Seoul-Gyeonggi-Incheon metropolitan area, where more than 25 million people reside (Hyun et al., 2009). The native marsh plant Suaeda japonica (Figures 1b,d), which has thrived extensively in this area, plays a significant role in regulating the rates and pathways of C_org oxidation (Hyun et al., 2009). However, since it was first reported in the area in 2015, the invasive plant Spartina anglica C. E. Hubbard has rapidly displaced native S. japonica (Figures 1b,c), expanding its coverage by a factor of 80 from approximately 400 m² in 2015 to 31,181 m² in 2018 (KOEM, 2018). Spartina species, due to their relatively greater biomass, longer growing season, and higher photosynthetic rate compared with native species, are regarded as competitive invaders (Liao et al., 2007; Jiang et al., 2009; Li et al., 2009). Because biogeochemical processes in sediment are directly or indirectly coupled with the oxidation of organic materials (Fenchel et al., 1998; Canfield et al., 2005), it is particularly important to determine the rates and partitioning of C_org oxidation to better evaluate the impact of an invasive plant on biogeochemical processes in coastal ecosystems.

FIGURE 1

Figure 1. A map showing sampling sites inhabited by Spartina anglica (SA) and Suaeda japonica (SJ) and the unvegetated mud flat (UMF) of the Ganghwa intertidal wetland (a,b). Shaded area and the lines between land and island in (a) denote the intertidal wetlands and bridges, respectively. Note that the height of the SA shoot reaches 170 cm (c) whereas that of the SJ reaches approximately 30 cm (d). Crabs (Macrophthalmus japonicus) are the dominant macrofauna in the UMF site (e).

Previous studies have reported that invasion of Spartina species remarkably altered sedimentary biogeochemical cycles (Liao et al., 2007; Cheng et al., 2008; Zhang et al., 2017; Wang et al., 2019), physico-chemical properties of sediment (Yang et al., 2013; Bu et al., 2015; Zhang et al., 2019), and microbial communities in sediments associated with nitrification and denitrification (Dollhopf et al., 2005; Zhang et al., 2013; Gao et al., 2019), sulfur-oxidizing and reducing processes (Thomas et al., 2014; Cui et al., 2017) and CH₄ emissions (Yuan et al., 2016). However, little is known about the impact of these invading salt marsh plants on biogeochemical processes and associated microbial communities in the Ganghwa intertidal flats of the Han River estuary in the Yellow Sea. The objectives of this study were: (1) to evaluate the impact of invasive S. anglica on sediment biogeochemistry, with a special emphasis on the rates and partitioning of C_org oxidation coupled with FeR and SR; and (2) to elucidate major microbial consortia associated with the major biogeochemical processes in the rhizosphere of the two vegetated sediments. Our biogeochemical process studies, combining comprehensive geochemical analysis and microbial metabolic rate measurements with molecular microbiological analysis, revealed that the expansion of invasive S. anglica has profound impacts on biogeochemical C–Fe–S cycles and associated microbial communities in the Ganghwa intertidal wetlands.

Materials and Methods

Study Area

The Ganghwa intertidal wetland, with an area of 244 km² (Figure 1a; Woo and Je, 2002), represents the largest portion of the intertidal mud flats (875 km²) in the mideastern portion of the Yellow Sea¹. An exceptionally large tidal range (±6.5 m on average) exposes extensive intertidal areas during low tide. Invasive S. anglica in Ganghwa intertidal sediment shows rapid growth from May to August, exceeding heights of 1 m (Figure 1c), and typically flowers from September to October (Kim et al., 2015; Kim, 2016). Several rhizomes connected to stems spread out in shallow sediment, and extend sideways or to depths of 20 cm or more. These species have a fibrous, radiate root system within the top 10 cm of the surface sediment (Kim et al., 2015). Native S. japonica, in contrast, are highly salt-tolerant annual plants, and flower from August to September (Bang and Lee, 2019). They can reach a height of approximately 20 cm (Figure 1d), and major rhizospheres occur between depths of 3 and 8 cm. In vegetated sediments, most burrowing activity occurs in shallow sediment, and burrows are generally smaller than those found in unvegetated areas because the roots of actively growing plants prevent burrowing activity of macrofauna (Gribsholt and Kristensen, 2003; Koo et al., 2007). In unvegetated mud flats, bioturbation by various macrofauna, such as crabs (Macrophthalmus japonicus) (Figure 1e) and worms (Perinereis aibuhitensis), plays a significant role in replenishing oxidants in sediment deeper than 30 cm (Koo et al., 2005, 2007; Hyun et al., 2009).

Sampling and Handling

Sediment samples for biogeochemical analysis, molecular microbiological analysis and metabolic rate measurements were collected on September 19, 2017, at three contrasting sites: (1) sediments inhabited by exotic S. anglica (Site SA); (2) sediments inhabited by the indigenous salt marsh plant S. japonica (Site SJ); and (3) unvegetated mud flats (Site UMF) (Figure 1). Sampling was performed randomly at a few cm away from plant shoots or burrows at all sites. Sediment samples for geochemical analysis were taken in triplicate from each site using acrylic cores (40 cm length, 6 cm internal diameter) that were immediately sealed with butyl rubber stoppers. Within 3 h of sampling, the cores were transferred to a N₂-filled glove bag (AtmosBag, Sigma-Aldrich Ltd., United States), and sectioned in the laboratory at 2 cm intervals down to a depth of 14 cm, and then at 4 cm intervals down to 30 cm. Sectioned sediments were transferred into polypropylene conical tubes in the same N₂-filled glove bag. The tubes were then tightly capped and sealed with rubber tape, and centrifuged at 2,600 g for 10 min. After reintroduction to the N₂-filled glove bag, supernatant pore water was sampled from the top and filtered through a 0.2 μm cellulose acetate syringe filter (Advantec, Toyo Rashi Kaisha, Ltd., Japan). To determine NH₄⁺ and PO₄^3– concentrations, aliquots of 1–2 mL of pore water were frozen until analysis. To determine the dissolved Fe²⁺ and SO₄^2–, 2 mL of pore water was preserved with 12 N HCl (final conc. 0.1 N) and then stored at 4°C. Dissolved sulfide (H₂S) was precipitated with a zinc acetate solution (20%) and kept frozen. Pore-water was extracted using Rhizon samplers (Rhizosphere Research Products B.V, Wageningen, Netherlands) at depth intervals of 0–4, 4–8, 8–12, and 12–20 cm for an analysis of dissolved organic carbon (DOC). To prevent microbial activity, the DOC samples were acidified to a pH < 2 with 6 M HCl and preserved at 4°C until further analysis. Sediment samples for solid-phase analysis were kept frozen until processed in the laboratory. Additional sediment samples were collected to determine the major microbial communities associated with iron and sulfur cycles in the rhizosphere of the two vegetated sites. Two sediment cores of each Spartina and Suaeda, were collected using acrylic cores (40 cm length, 6 cm internal diameter). The rhizosphere within the sediment core was easily identified by the clusters of rhizome (Figure 2). The sediment loosely attached to the root was carefully scraped off from rhizosphere layer using a sterilized spatula, mixed well in the sterilized plastic bag, and immediately frozen at −80°C.

FIGURE 2

Figure 2. Vertical profiles of NH₄⁺ (a,f,k), PO₄^3– (b,g,l), Fe²⁺ (c,h,m), SO₄^2– (d,i,n), and H₂S (e,j,o) in the pore water at the Spartina anglica (SA), Suaeda japonica (SJ) sites and the unvegetated mud flat (UMF) site. Error bars indicate a mean ± 1 SD from duplicate or triplicate cores. The rightmost figures indicate the size of root systems of S. anglica and S. japonica, and the burrows formed by macrofauna in the UMF site.

Pore-Water Analysis

Dissolved NH₄⁺ and PO₄^3– in pore water were measured using a continuous-flow nutrient analyzer (QuAAtro, Seal Analytical GmbH, Norderstedt, Germany), and a certified reference material from MOOS-3 (National Research Council, Canada) was included in each batch of nutrient samples. Reproducibility was generally within ±7%. Dissolved Fe²⁺ in pore water was determined by colorimetry with a ferrozine solution (detection limit: 1 μM; Stookey, 1970). SO₄^2– concentration was measured using ion chromatography (detection limit: 0.03 mM; 819 IC detector using an A-Supp5 column, Metrohm, Swiss). H₂S in the pore water was determined using methylene blue (detection limit: 3 μM; Cline, 1969). The concentrations of pore-water DOC were measured using a TOC-V_CPH analyzer (Shimadzu, Japan).

Solid-Phase Analysis

Total oxalate-extractable Fe, hereafter TFe_(oxal), was extracted from air-dried sediment in a 0.2 M oxic oxalate solution (pH 3) for 4 h (Thamdrup and Canfield, 1996), while oxalate-extractable Fe(II), hereafter Fe(II)_(oxal), was extracted from frozen sediment in anoxic oxalate (Phillips and Lovley, 1987). The TFe_(oxal) and Fe(II)_(oxal) were determined as described for the pore-water analysis of Fe²⁺. Oxalate-extractable Fe(III), hereafter Fe(III)_(oxal), was calculated from the difference between TFe_(oxal) and Fe(II)_(oxal). This fraction represents amorphous or poorly crystalline Fe(III) forms (Kostka and Luther, 1994). Total reduced inorganic sulfur (TRIS) in the sediments, which included both acid-volatile sulfide (AVS = FeS + H₂S) and chromium-reducible sulfur (CRS = S⁰ + FeS₂), was determined after two-step distillation with cold 12 M HCl and boiling 0.5 M Cr²⁺ solution (Fossing and Jørgensen, 1989), and sulfide was determined according to the method of Cline (1969). Elemental sulfur (S⁰) that is the sulfur extracted with methanol (high-performance liquid chromatography [HPLC] grade) from sediment samples was measured as cyclo-S₈ by reversed-phase HPLC (Zopfi et al., 2004). The content of particulate organic carbon (POC) and total nitrogen (TN) was analyzed using a vario PYRO cube elemental analyzer (Elementar Analysensysteme GmbH, Germany) after removal of CaCO₃. Chlorophyll a (Chl-a) concentrations in surface sediment (0–2 cm) were determined using spectrophotometry according to Parsons et al. (1984).

Rates of Anaerobic Carbon Oxidation, Iron Reduction and Sulfate Reduction

To determine anaerobic C_org oxidation rates and dissimilatory Fe(III) reduction rates (FeRR), sediment from a depth of 0–10 cm was collected using acrylic cores (20 cm length, 10 cm internal diameter) that were immediately sealed with butyl rubber stoppers. Sediment cores were transferred to a N₂-filled glove bag and sliced in 2 cm intervals to a depth of 10 cm. Sediment was homogenized and loaded into 50 mL centrifuge tubes and these tubes were incubated at in situ temperatures (ca. 20–22°C) in the dark. At regular intervals, two tubes were sacrificed and the pore waters were extracted by centrifugation and filtered as described above in sediment handling. For total dissolved inorganic carbon (DIC) analysis, we collected 1.8 mL aliquots in glass vials without head space, fixed with 18 μL of saturated HgCl₂ (125 mM), and analyzed them as soon as possible using flow injection analysis with conductivity detection (detection limit for DIC is 1 mM; Hall and Aller, 1992). Anaerobic C_org oxidation rates were determined from the linear regression of the DIC accumulation with time. After pore-water retrieval from the anaerobic C_org mineralization incubation experiment, the remaining sediment was homogenized under a N₂ atmosphere, and Fe(II) was extracted in oxalate as described above in solid-phase analysis. FeRRs were determined by linear regression of the increase in solid-phase Fe(II)_(oxal) content with time during incubations for the anaerobic C_org oxidation (Kostka et al., 2002a; Hyun et al., 2017).

Sulfate reduction rates (SRRs) were determined using the radiotracer method of Jørgensen (1978). Duplicate or triplicate intact cores (20 cm long with 2.5 cm i.d.) were collected at each site. Two μCi of ³⁵S-SO₄^2– (NEX041H005MC, PerkinElmer, United States) were injected into the injection port at 1 cm intervals, and the cores were incubated for 1–2 h at in situ temperatures. The sediment was sliced into sections, fixed in zinc acetate (20%), and frozen until processed in the laboratory. The reduced ³⁵S was recovered using distillation with a boiling acidic Cr²⁺ solution according to Fossing and Jørgensen (1989). The radioactivity of the reduced ³⁵S was quantified using a liquid scintillation counter (Tri-Carb 2910 TR; PerkinElmer, Waltham, MA, United States). SRR detection limits estimated from double-standard deviation of the blank value (Fossing et al., 2000) ranged from 0.72 to 5.75 nmol cm^–3 d^–1.

Partitioning of Organic Carbon Oxidation

The relative significance of FeR and SR in anaerobic C_org oxidation was estimated after converting the FeR and SR to carbon units (see Hyun et al., 2017). Briefly, to calculate the C_org oxidation by microbial FeR, the 4Fe: 1C stoichiometry of FeR coupled with C_org oxidation was used from the stoichiometric equation (Canfield et al., 1993): CH₂O + 4FeOOH + 8H⁺ = CO₂ + 4Fe²⁺ + 7H₂O. To calculate the contribution of SR in anaerobic carbon oxidation, the SRRs were converted to carbon oxidation using a stoichiometric equation (Thamdrup and Canfield, 1996): 2CH₂O + SO₄^2– + 2H⁺ = 2CO₂ + H₂S + 2H₂O.

DNA Extraction, Sequencing, and Sequence Analyses

To support the results on biogeochemical process associated with Fe–S cycles in the rhizosphere, additional microbial community analysis was conducted using a sediment core collected at SA and SJ. Total genomic DNA was extracted using a Powersoil DNA Isolation kit (Mo Bio Laboratories, Carlsbad, CA, United States), following the manufacturer’s instructions. 16S rRNA genes amplification for sequencing was performed with the primers containing the Illumina adaptor sequences and universal V3-V4 region of the 16S rRNA gene (341F: CCTACGGGNGGCWGCAG and 805R: GACTACHVGGGTATCTAATCC). Sequencing of 16S rRNA gene amplicons was performed by the Illumina MiSeq platform at Macrogen Inc. (Seoul, South Korea) according to the manufacturer’s instructions. Sequences were clustered into operational taxonomic units (OTUs), which met a 97% similarity threshold, using the multi-step pipeline CD-HIT-OTU tool and rDnaTools (Schloss et al., 2009; Li et al., 2012). Chimeric sequences were identified and removed by rDnaTools. The 16S rRNA gene sequences were identified by comparing the datasets against the Ribosomal Database Project (RDP) Classifier tool. Alpha diversity indices were created using QIIME software (Caporaso et al., 2010). Raw sequence data have been submitted to the National Center for Biotechnology Information under study accession number PRJNA565620.

Plant Biomass

Above- and below-ground biomass (AGB and BGB, respectively) and shoot density of both S. anglica and S. japonica was determined by harvesting all materials in five randomly selected 25 × 25 cm² frames. Plant shoots for measuring AGB were cut at the sediment surface, and the sediment for estimating BGB were moved to the laboratory. The plant materials and detritus were washed carefully with tap water and rinsed twice with distilled water. Belowground tissues were washed using 500 μm sieve to avoid the loss of small roots. They were separated into leaves, stems and below-ground material, and then dried at 60°C for > 48 h to determine dry weight.

Data Analysis

Depth-integrated analysis was conducted for the quantitative comparison of geochemical parameters and rate measurements at the SA, SJ, and UMF sites. A one-way analysis of variance was performed to identify significant differences among different sampling sites. Tukey’s honestly significant difference post hoc test was used to determine statistically significant differences between stations. If homogeneity of variances (Levene’s test) were not obtained, a non-parametric Kruskal–Wallis test was used, both at a critical level of 0.05. Statistical analyses were performed using SPSS ver. 21 (SPSS for Windows, SPSS, Inc.).

Results

Sediment Properties

Physico-chemical and ecological properties obtained at the three sampling sites are presented in Table 1. Porosity ranged from 0.56 to 0.61, and water content varied from 33.9 to 35.9% among the sites. POC and TN in the sediments ranged from 0.72 to 1.01%, and 0.11 to 0.12%, respectively. The POC at SA patch was slightly higher than those of other sites. The above- and below-ground biomass at SA patch (AGB = 2021 g m^–2, BGB = 1358 g m^–2) were 7- and 10-fold, respectively, greater than that of SJ patch (AGB = 281 g m^–2, BGB = 138 g m^–2).

TABLE 1

Table 1. Physico-chemical and ecological parameters in the surface sediments (0–10 cm).

Pore-Water Constituents

NH₄⁺ concentrations at SA and UMF sites were constantly low at entire depth (Figures 2a,k), whereas it increased steeply below 10 cm depth at SJ (Figure 2f). The depth-integrated concentration (0–30 cm) of NH₄⁺ at SJ site was 3.3- and 5.1-fold higher than at UMF and SA sites, respectively (F₂,₃₀ = 8.73, p = 0.001; Table 2). PO₄^3– in the pore water showed similar vertical distribution patterns with the NH₄⁺ concentrations (Figures 2b,g,l). The depth-integrated concentrations of PO₄^3– were 2.5- and 8.3-fold higher at SJ than at SA and UMF, respectively, although the difference was not significant (p = 0.182; Table 2). Dissolved Fe²⁺ concentrations differed greatly among the sites (p = 0.001; Table 2). The highest Fe²⁺ concentration (486 μM) was observed at a depth of 2–4 cm at the SJ site (Figure 2h), and the concentration decreased below 1.80 μM at a depth of 26–30 cm. The Fe²⁺ peak (225 μM) observed at the 8–10 cm depth of SA site (Figure 2c) decreased slightly with increasing depth, whereas the Fe²⁺ concentrations were low at all depths at UMF site (Figure 2m). Depth-integrated inventories of Fe²⁺ at SA and SJ were 19 times greater than at UMF site (Table 2). SO₄^2– concentrations were similar (>21 mM) between the three sites (Figures 2d,i,n). Dissolved sulfide concentrations were close to the detection limit (<3 μM) at all sites (Figures 2e,j,o). SO₄^2– and H₂S concentrations did not differ significantly between the sites (p = 0.34 and p = 0.19, respectively). Pore-water DOC at the SA site was constantly within 6 cm, but increased rapidly with depth from 7.1 mM at 16 cm depth (Figure 3). At SJ site, DOC concentrations increased slightly with increasing depth from 1.3 mM to 3.5 mM, whereas UMF was almost constant with depth (Figure 3).

TABLE 2

Table 2. Depth-integrated inventories (mmol m^–2) of pore-water constituents and solid-phase constituents (n = 3).

FIGURE 3

Figure 3. Vertical profiles of dissolved organic carbon (DOC) in sediment vegetated by Spartina anglica (SA) and Suaeda japonica (SJ) and unvegetated mud flats (UMF). Error bars indicate a mean ± 1 SD from triplicate cores.

Solid-Phase Iron and Sulfur

Vertical distributions of solid-phase iron and sulfur in sediment are presented in Figure 4. The concentrations of Fe(II)_(oxal) increased slightly with depth at SA and SJ sites (Figures 4a,g), but Fe(III)_(oxal) concentrations gradually decreased with increasing depth (Figures 4b,h). The Fe(II)_(oxal) at UMF was lowest at all depths, except for 28–30 cm (Figure 4m). The depth-integrated (0–30 cm) amount of Fe(III)_(oxal) was 1.7 times greater at UMF site than at other sites, and most solid-phase iron consisted of reactive Fe(III) (>60% of the total iron), which accounted for > 90% at UMF (Table 2). Most of the TRIS forms at the Ganghwa intertidal sediment was preserved in the CRS form (S⁰ + FeS₂) (>95% of TRIS), while the concentrations of AVS (H₂S + FeS) were near depletion at all sites (<1 μmol cm^–3). CRS concentrations were almost constant with depth at all three sites, although small peak concentrations (26.2–30.9 μmol cm^–3) were observed at the 6–12 cm depth of SA site (Figure 4e). The depth-integrated (0–20 cm) CRS pool was greater at SA (4198 mmol m^–2) than at the other two sites (SJ; 2690 mmol m^–2, UMF; 2597 mmol m^–2) (p < 0.001; Table 2). S⁰ concentration was more abundant at SA than SJ and UMF (p < 0.05; Table 2), and higher concentrations of S⁰ were observed at the 8–14 cm depth at SA site (Figure 4f).

FIGURE 4

Figure 4. Vertical profiles of oxalate-extractable Fe(II) (a,g,m), Fe(III) (b,h,n), total Fe (TFe) (c,i,o), acid-volatile sulfur (AVS) (d,j,p), chromium-reducible sulfur (CRS) (e,k,q), and elemental sulfur (S⁰) (f,l,r) in sediment vegetated by Spartina anglica (SA) and Suaeda japonica (SJ) and unvegetated mud flats (UMF). Error bars indicate the mean ± 1 SD from duplicate or triplicate cores.

Rate Measurements

Depth-integrated (0–10 cm) anaerobic C_org oxidation at SA (88.7 mmol C m^–2 d^–1) was two-fold greater than that of SJ (48.8 mmol C m^–2 d^–1) and UMF sites (47.5 mmol C m^–2 d^–1) (Table 3). Anaerobic C_org oxidation rates were highest at the rhizosphere (4–8 cm) of SA site (1183–1205 nmol C cm^–3 d^–1), approximately 2–3 times higher than those measured at SJ (395–398 nmol C cm^–3 d^–1) and at a depth similar to that of UMF (351–609 nmol C cm^–3 d^–1) (Figures 5a,d,g). The depth-integrated (0–10 cm) FeRR at SA was twice as high as SJ and UMF site (Table 3). Similar to the anaerobic C_org oxidation rates, FeRRs were higher at the rhizosphere of SA (4–8 cm, 3084–3986 nmol Fe cm^–3 d^–1) compared with that measured at SJ (468–931 nmol Fe cm^–3 d^–1) and at a depth range similar to that of UMF site (912–1397 nmol Fe cm^–3 d^–1) (Figures 5b,e,h). The depth-integrated (0–10 cm) SRR (29.0 mmol S m^–2 d^–1) at SA was twice that at SJ (13.7 mmol S m^–2 d^–1) and more than 4.4 times higher than at the UMF site (6.58 mmol S m^–2 d^–1) (Table 3). SRR at SA increased from 222 nmol m^–3 d^–1 at the surface to 453 nmol m^–3 d^–1 at 2–4 cm, and then decreased continuously to 65.8 nmol m^–3 d^–1 at a depth of 18 cm (Figure 5c), while the rates remained relatively constant with depth at SJ and UMF sites (Figures 5f,i).

TABLE 3

Table 3. Partitioning of sulfate reduction (SRR) and Fe(III) reduction (FeRR) in C_org oxidation, and turnover rates of Fe(III).

FIGURE 5

Figure 5. Vertical profiles of anaerobic C_org oxidation rates (a,d,g), iron reduction rates (FeRR) (b,e,h), and sulfate reduction rates (SRR) (c,f,i) in the sediments vegetated by Spartina anglica (SA) and Suaeda japonica (SJ) and unvegetated mud flats (UMF). Error bars in SRR indicate the mean ± 1 SD from triplicate cores.

Bacterial Communities

To further assess the impact of invasive S. anglica on biogeochemical processes, microbiological analyses of bacterial community structures were conducted at the rhizosphere of the SA and SJ sites. A total of 23,935 reads, with an average length of 440 base pairs, were obtained after excluding 865 sequences of the cyanobacterial 16S rRNA genes. Chao1 index and OTU_0.97 counts of bacterial 16S rRNA gene sequences were lower in the sediment at SA than at SJ. Of the 19 identified phyla of bacteria, Proteobacteria, comprising 71.9–79.5% of the total reads, represented the most predominant microbial group (Figure 6 and Table 4). Among the Proteobacteria, Deltaproteobacteria (21.8–26.4%) and Gammaproteobacteria (43.7–44%) dominated both sites (Figure 6 and Table 4). Bacteria belonging to Bacteroidetes appeared to be the second most dominant, comprising 13.2 and 8.53% of total reads at SA and SJ sites, respectively. Bacterial populations belonging to Actinobacteria (0.64–1.39%), Firmicutes (0.75–4.17%), Fusobacteria (1.26–3.59%), and Verrucomicrobia (0.57–1.50%) were minor bacterial groups (Table 4).

FIGURE 6

Figure 6. Relative abundance of major bacterial phyla (bar chart) and families in Delta- and Gammaproteobacteria (pie chart) within a depth of 4–8 cm of the sediment inhabited by invasive Spartina anglica (SA) and native Suaeda japonica (SJ).

TABLE 4

Table 4. Phylogenetic composition and diversity indices of 16S rRNA genes in the 4–8 cm depth of the Ganghwa intertidal sediments.

Major subgroups at the family level in Deltaproteobacteria and Gammaproteobacteria showed different distribution at SA and SJ sites (Figure 6 and Supplementary Table S1). At SA, more than half of the deltaproteobacterial sequences (51.1% in the Deltaproteobacteria) were affiliated with Desulfuromonadaceae, including several iron-and elemental sulfur–reducing bacteria. The second dominant bacterial group in the deltaproteobacterial sequences was affiliated with Desulfobulbaceae (28.2% in the Deltaproteobacteria), which are well known as sulfate-reducing bacteria (Figure 6). In contrast, the relative contribution of Desulfuromonadaceae, thriving most abundantly at SA, appeared to be lower at SJ (32.2%) (Figure 6). Sulfate-reducing Desulfobulbaceae were more dominant at SJ (46.0% in the Deltaproteobacteria) than at SA (28.2%).

The distribution of major family groups for Gammaproteobacteria and Epsilonproteobacteria varied considerably with sites as well. Among Gammaproteobacteria, the family Woeseiaceae, facultatively anaerobic and heterotrophic marine bacteria (Du et al., 2016) were the most frequent at both sites, comprising 21.7–45.8% in total gammaproteobacterial sequences (Figure 6). The abundance of family Thioprofundaceae appeared to be the highest at SA (23.3% in the Gammaproteobacteria), but decreased to 7.52% at SJ (Figure 6). Likewise, members of the family Halieaceae in Gammaproteobacteria were also detected at a high proportion (12.8% in Gammaproteobacteria) at SA site, compared with those at SJ site (0.97%) (Figure 6). Meanwhile, the family Psychromonadaceae occupied the most abundant proportion in total gammaproteobacterial sequences (52%) at SJ (Figure 6 and Supplementary Table S1). The relative abundance of Sulfurovum in epsilonproteobacterial sequences was higher at SJ (84.2% in Epsilonproteobacteria) compared with SA (66.8%) (Supplementary Table S1).

Discussion

Influence of Invasive S. anglica on C_org Oxidation

The rates and pathways of C_org oxidation in sediments are largely regulated by the availability of electron donors (i.e., labile organic matters) and acceptors (Canfield et al., 2005). In coastal sediments, various physico-chemical and biological factors such as vegetation, bioturbation, freshwater runoff, tidal inundation, and anthropogenic activities are responsible for availability of the electron donors and acceptors for microbial metabolic activities (Alongi et al., 1999; Kristensen and Kostka, 2005; Hyun et al., 2009; An et al., 2019; Mok et al., 2019). Of all the environmental factors, marsh plants significantly affect biogeochemical properties by translocating organic matter via roots and rhizomes (Armstrong et al., 2000; Lee, 2003; Sundby et al., 2003; Koop-Jakobsen et al., 2018). For example, exudates from the roots of marsh plants provide bacteria with a large amount of labile organic carbon, enhancing microbial respiration in vegetated sediments (Hines et al., 1989; Gribsholt and Kristensen, 2002; Hyun et al., 2007). Furthermore, the rhizosphere appears to be a zone of intense re-oxidation of reduced solutes, such as Fe²⁺ and H₂S, which results in a rapid regeneration of Fe(III) and sulfate for re-stimulating FeR and SR, respectively (Hines et al., 1989; Gribsholt et al., 2003; Hyun et al., 2009; Luo et al., 2018).

In the present study, total anaerobic C_org oxidation rate, FeR, and SR were consistently higher at SA than at SJ and UMF (Figure 4 and Table 3). Exceptionally enhanced metabolic activities were observed at the rhizosphere (4–8 cm depth) of SA. The results are consistent with previous studies conducted in salt marsh sediment vegetated by Spartina (Hines, 1991; Hines et al., 1994; Gribsholt et al., 2003; Luo et al., 2018). More than half of the photosynthetically fixed carbon by S. anglica is allocated in the below-ground root system (Hemminga et al., 1996). Spartina roots therefore provide substantial amounts of labile organic compounds (i.e., DOC) (Bu et al., 2015; Cheng et al., 2008; Zhang et al., 2017), which fuel anaerobic respiration in the sediment (Hines et al., 1989; Hines, 1991; Kostka et al., 2002a; Koretsky et al., 2008). Indeed, depth-integrated (0–20 cm) DOC concentrations at SA (560 mmol m^–2) were 2.2 times and 2.9 times higher than that measured at SJ (258 mmol m^–2) and UMF (192 mmol m^–2), respectively (Table 2). Specially, DOC concentrations at the rhizosphere depth (10–15 cm) of SA site were 3-times greater than that measured at the rhizosphere depth (3–6 cm) of SJ and at the entire depth of UMF sites (Figure 3). The results indicated that invasive Spartina species possessing 10 times the below-ground biomass of native S. japonica (Figure 3 and Table 1) exudates more labile dissolved organic matter into sediments, thereby stimulating the microbial metabolic activities.

Partitioning of C_org Oxidation and Associated Microbial Communities in Rhizosphere

In addition to stimulating metabolic activities, the invasion of S. anglica in Ganghwa intertidal sediment exerted a profound influence on sediment biogeochemistry associated with the partitioning of C_org oxidation. SR appeared to be the dominant anaerobic respiration pathway at 0–10 cm depth of the vegetated SA and SJ sediments, comprising 65.3 and 56.3% of anaerobic C_org oxidation, respectively (Table 3). However, in the rhizosphere layers of SA (4–8 cm) and SJ (2–6 cm), the contribution of FeR to C_org oxidation was higher than that of the SR, comprising approximately 70 and 60% of anaerobic C_org oxidation, respectively (Table 3). Together with the exceptionally high FeR (Figure 5b), the higher contribution of FeR in C_org oxidation at the rhizosphere of SA indicated that the large root system of invasive S. anglica greatly accelerates iron cycling in the sediment. Indeed, the iron turnover rates at the rhizosphere depth of SA site (0.063 d^–1 in average) were 3–5 times higher than that measured at the rhizosphere depth at SJ (0.023 d^–1 in average) and UMF (0.013 d^–1 in average), respectively (Table 3). In the Georgia salt marsh, Hyun et al. (2007) reported that FeR represented 21–69% of C_org oxidation due to rapid regeneration of Fe(III) by root of S. alterniflora. Gribsholt and Kristensen (2002) also found that FeR accounts for the majority of C_org oxidation in the mesocosms manipulated with S. anglica by supplying Fe(III) through downward translocation of oxygen, which leads to the re-oxidation of Fe(II).

The dominance of FeR in C_org oxidation at SA was further supported by the relative abundance of microbial consortia in the rhizosphere. At SA, the genera Desulfuromonas, Pelobacter, and Desulfuromusa in the family Desulfuromonadaceae among Deltaproteobacteria appeared to be the dominant bacterial groups. They reportedly oxidize organic matter using various electron acceptors such as Mn(IV), Fe(III), S⁰, and S₂O₃^2– in anoxic conditions (Liesack and Finster, 1994; Vandieken et al., 2006; Haveman et al., 2008). Considering that FeR is a dominant C_org oxidation pathway in the rhizosphere of SA (Table 3), supply of Fe(III) via rapid iron turnover in the presence of the extensive root system of S. anglica ultimately provides a favorable condition for Fe(III) reduction by Desulfuromonadaceae. The high abundance of Desulfuromonadaceae that use both Fe(III) and S⁰ as electron acceptors was further supported by high S⁰ concentrations in rhizosphere of SA (Figure 4f).

On the other hand, in unvegetated UMF site, Fe(III) appears to be the most influential electron acceptor for C_org oxidation (Figure 4n, Table 2). Accordingly, FeR accounted for 45.3% of anaerobic C_org oxidation, whereas SR only accounted for 29% (Table 3). The burrows constructed by macrofauna foster relatively oxidized conditions by increasing the area of the sediment-water interface at UMF site (Koo et al., 2007). Under these conditions, reactive Fe(III) is readily supplied via macrofaunal burrowing activities, thereby allowing FeR to outcompete SR in anaerobic C_org oxidation processes at UMF (Table 3, Gribsholt et al., 2003; Kristensen and Alongi, 2006).

Biogeochemical and Microbiological Evidence for a Profound Influence of S. anglica on Iron and Sulfur Cycles

Microbial metabolic activities by SR and FeR ultimately produce H₂S and Fe²⁺, respectively (Eqs. 1–2). However, despite high SRR and FeRR at the rhizosphere of SA (Figures 5b,c and Table 3), H₂S in the pore water of SA was depleted (Figure 2e), and the accumulation of Fe²⁺ was smaller at SA site (Figure 2c) than at SJ site (Figure 2h). These discrepancies can be explained by sulfur oxidation coupled with abiotic reduction of Fe(III) and re-oxidation of Fe²⁺ within the root zone, respectively. Because S. anglica has a well-developed aerenchyma system and denser root systems, a large amount of O₂ can be readily supplied to deeper layers of SA sediment, stimulating re-oxidation of reduced compounds in the rhizosphere (i.e., Maricle and Lee, 2002; Koop-jakobsen and Wenzhöfer, 2015). Under this relatively sub-oxic condition, H₂S derived from SR (Eq. 1) is quickly oxidized by Fe(III) to form S⁰ (Eq. 3, Ferreira et al., 2007; Jian et al., 2017). Simultaneously, the Fe²⁺ generated by microbial FeR (Eq. 2) and abiotic FeR (Eq. 3) is efficiently precipitated as FeS in the presence of H₂S (Eq. 4), which is then transformed to thermodynamically more stable pyrite (FeS₂) (Eq. 5; Canfield et al., 2005). The distribution of Fe–S compounds in pore water and the solid phase of the rhizosphere of SA were characterized by higher amounts of CRS and S⁰ than those measured at SJ and UMF sites (Figures 2, 3). These results are consistent with the findings of Jian et al. (2017), who reported active sulfur oxidation in the rhizosphere of a mangrove system.

$$2CH{}_{2}O+SO{}_4{}^{2-}+2H{}^{+}=2CO{}_2+H{}_{2}S+2H{}_{2}O(1)$$

$$CH{}_{2}O+4FeOOH+8H{}^{+}=CO{}_2+4Fe{}^2{}^{+}+7H{}_{2}O(2)$$

$$4FeOOH+3H{}_{2}S=4Fe{}^2{}^{+}+S{}^0+S{}_{2}O{}_3{}^{2-}+4H{}_{2}O(3)$$

$$Fe{}^2{}^{+}+H{}_{2}S=FeS+2H{}^{+}(4)$$

$$FeS+S{}^0=FeS{}_{2}orFeS+H{}_{2}S=FeS{}_2+H{}_2(5)$$

Depletion of H₂S coupled with the reduction of FeOOH via Eq. 3 at the rhizosphere of SA could also be explained by the abundance of sulfur-oxidizing bacteria (SOB) using S⁰ as electron donors. Among the SOB, Thioprofundaceae in Gammaproteobacteria (γ-SOB), which use O₂ and NO₃^– as electron acceptors and reduced sulfur (e.g., S⁰, S₂O₃^2–, and S₄O₆^2–) as an electron donor, was predominant at SA, whereas Sulfurovum in Epsilonproteobacteria (ε-SOB) dominated at SJ (Supplementary Table S1). These notable differences suggest that the two SOB groups have distinctly different metabolic strategies for sulfur oxidation. The γ-SOB have a relatively narrow habitat zone because both oxygen and reduced sulfur are steadily supplied in their energy-producing pathway (Yamamoto and Takai, 2011; Ihara et al., 2017). In contrast, ε-SOB have versatile energy metabolisms in more reduced conditions. Thus, ε-SOB adapt to more dynamic and transient environmental conditions, such as hydrothermal system (Yamamoto and Takai, 2011; Ihara et al., 2017) and sulfidic finfish farm sediments (Choi et al., 2018). It is therefore plausible to identify γ-SOB dominating at the rhizosphere of SA, where both oxygen and reduced sulfur compounds (i.e., S⁰ and S₂O₃^2–) are steadily supplied via aerenchyma of S. anglica and via Eq. (3) into rhizosphere, respectively.

Implications Associated With Climate Change

Temperature rise as a consequence of climate change has a significant impact on native and non-native plants in terms of photosynthesis, biomass allocation, and nutrient uptake in costal marshes and estuaries (Gray and Mogg, 2001; Loebl et al., 2006; Nehring and Hesse, 2008; Hulme, 2014). Because of a higher phenotypic plasticity compared with native plants, invasive plants would likely adapt more effectively to variations in environmental conditions resulting from climate change (Loebl et al., 2006; Charles and Dukes, 2009; Hulme, 2014; Grewell et al., 2016). For example, Loebl et al. (2006) suggested that the spread of invasive S. anglica was most likely triggered by temperature increase due to improved seed development. Similarly, Kirwan et al. (2009) demonstrated that an increase in annual temperature of 2–4°C would cause S. alterniflora productivity to increase by up to approximately 10–40%.

During the last 2–3 decades (1982–2006), warming rates (1°C per decade) of sea surface temperatures in the East Asian marginal seas, including the Yellow Sea and East China Sea, have been approximately 8 times faster than the global mean rate of 0.13°C per decade (Belkin, 2009). As a result, the current expansion of S. anglica observed in the Ganghwa intertidal sediments could be directly associated with the phenotypic plasticity of S. anglica under this climate change–induced warming trend. Our biogeochemical process studies combining microbiological analyses suggest that the invasion of S. anglica, which may displace native S. japonica, greatly alters the biogeochemical C–Fe–S cycles and associated microbial communities, which ultimately generates multi-directional variations in the ecological and biogeochemical processes of the coastal wetlands inhabited by native S. japonica. Our results provide scientific information that should be considered by decision-makers responsible for protecting estuarine and coastal environments in which invasive exotic plants have been established.

Data Availability Statement

The datasets generated for this study can be found in the NCBI/PRJNA565620 (https://www.ncbi.nlm.nih.gov/bioproject/PRJNA565620/).

Ethics Statement

Written informed consent was obtained from the individuals for the publication of any potentially identifiable images or data included in this article.

Author Contributions

S-UA, HC, and J-HH designed the study and wrote the manuscript. S-UA, U-JJ, BK, and HL collected the samples and performed most laboratory analysis. All the authors contributed to the discussion of the results and to the final version of the manuscript.

Funding

This research was supported by the Korean Long-term Marine Ecological Researches (K-LTMER) funded by the Korean Ministry of Oceans and Fisheries, and by the Mid-career Scientist Research Program funded by the Korean Ministry of Science and ICT (No. 2018R1A2B2006340).

Conflict of Interest

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.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fmars.2020.00059/full#supplementary-material

Footnotes

1. ^ http://www.kosis.kr

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