Climate-induced shifts in sulfate dynamics regulate anaerobic methane oxidation in a coastal wetland

Jaehyun Lee; Yerang Yang; Hojeong Kang; Genevieve L Noyce; J Patrick Megonigal

doi:10.1126/sciadv.ads6093

. 2025 Apr 23;11(17):eads6093. doi: 10.1126/sciadv.ads6093

Climate-induced shifts in sulfate dynamics regulate anaerobic methane oxidation in a coastal wetland

Jaehyun Lee ^1,^2,^*, Yerang Yang ^1,³, Hojeong Kang ³, Genevieve L Noyce ², J Patrick Megonigal ^2,^*

PMCID: PMC12017331 PMID: 40267209

Abstract

Anaerobic methane oxidation (AMO) is a key microbial pathway that mitigates methane emissions in coastal wetlands, but the response of AMO to changing global climate remains poorly understood. Here, we assessed the response of AMO to climate change in a brackish coastal wetland using a 5-year field manipulation of warming and elevated carbon dioxide (eCO₂). Sulfate (SO₄²⁻)–dependent AMO (S-DAMO) was the predominant AMO process at our study site due to tidal inputs of SO₄²⁻. However, SO₄²⁻ dynamics responded differently to the treatments; warming reduced SO₄²⁻ concentration by enhancing SO₄²⁻ reduction, while eCO₂ increased SO₄²⁻ concentration by enhancing SO₄²⁻ regeneration. S-DAMO rates mirrored these trends, with warming decreasing S-DAMO rates and eCO₂ stimulating them. These findings underscore the potential of climate change to alter soil AMO activities through changing SO₄²⁻ dynamics, highlighting the need to incorporate these processes in predictive models for more accurate representations of coastal wetland methane dynamics.

Climate change affects sulfate-dependent anaerobic methane oxidation by shifting sulfur cycling in a coastal wetland.

INTRODUCTION

Coastal wetlands have been traditionally considered a minor source of methane (CH₄) due to the presence of sulfate (SO₄²⁻), which can outcompete methanogenic communities for electron donors (1, 2). However, recent studies have shown that CH₄ emissions in coastal wetlands are highly variable and can often exceed carbon sequestration in terms of CO₂ equivalents (3–6). Despite the significance of CH₄ emissions in the carbon budget of coastal wetlands (7), a considerable degree of uncertainty persists in accurately quantifying their CH₄ emissions (8, 9). Moreover, the increasing threat of climate change presents a substantial challenge to the fragile equilibrium of these ecosystems (10, 11). Warming temperatures, sea level rise, and elevated atmospheric CO₂ are among the numerous climate-induced changes that influence the resilience and greenhouse gas balance of coastal wetlands (10, 12, 13). These changes often disrupt microbial processes that regulate CH₄ dynamics (14–16). In this context, a comprehensive understanding of the CH₄ dynamics in coastal wetlands becomes essential for predicting and managing future contributions to the global CH₄ budget.

CH₄ dynamics in ecosystems are primarily governed by two opposing biogeochemical processes, CH₄ production mediated by methanogens and its subsequent oxidation facilitated by methanotrophs (17). CH₄ oxidation serves as a critical control mechanism, mitigating up to 90% of the CH₄ produced under anoxic conditions in soils before its atmospheric dispersion (18, 19). Oxidation processes vary by the availability of terminal electron acceptors: aerobic oxidation relies on oxygen (O₂), while anaerobic oxidation uses SO₄²⁻ [SO₄²⁻-dependent anaerobic CH₄ oxidation (S-DAMO)], nitrate (NO₃⁻)/nitrite (NO₂⁻) [NO₃⁻/NO₂⁻-dependent anaerobic CH₄ oxidation (N-DAMO)], manganese/iron oxides, or oxidized humic substances (20). In environments abundant in O₂, the aerobic pathway dominates because of the superior free energy yield of O₂ (20). However, in O₂-deprived systems characteristic of coastal zones, rivers, and lakes, anaerobic pathways assume a dominant role in the CH₄ cycle. Anaerobic CH₄ oxidation (AMO) consumes a median of 71% of the CH₄ produced in the anoxic zones of inundated environments such as coastal ecosystems, wetlands, paddy systems, lakes, and rivers, where substantial amounts of CH₄ are emitted into the atmosphere (21).

S-DAMO is performed by anaerobic methanotrophic (ANME) archaea, represented by three different phylogenic clusters (ANME-1, ANME-2, and ANME-3) (21). ANME-1 and ANME-2 are the most abundant group of ANME archaea, which are widely distributed in anoxic environments, while ANME-3 archaea mostly exist in submarine mud volcanoes or marine CH₄ seeps (22, 23). S-DAMO activity is typically observed in marine environments (marine sediment, coastal wetland soil, etc.) and is the dominant AMO pathway in these environments because SO₄²⁻ is the major redox-active compound in seawater (21). A previous study estimated that S-DAMO removes 71 to 96% of CH₄ produced by methanogens in a coastal wetland complex with varying salinities (1.4 to 34.5) (24), fractions that are similar to the limited number of studies on unvegetated marine ecosystems (22). However, S-DAMO can also play an important role in CH₄ cycling in freshwater environments where SO₄²⁻ is commonly depleted (25).

N-DAMO is a more recently found pathway of AMO (26, 27). It plays a crucial role in the biogeochemical cycles of carbon and nitrogen. It couples CH₄ oxidation with the reduction of NO₂⁻ or NO₃⁻ (28, 29) and also facilitates ammonium oxidation linked to the oxidation of organic matter (30). Two microbes have been identified through enrichment cultures: Methylomirabilis oxyfera, which was identified in freshwater sediment and couples AMO to NO₂⁻ reduction (26), and Methanoperedens nitroreducens, which was identified in both freshwater sediment and wastewater sludge, couples NO₃⁻ reduction to AMO (31).

In soil environments, various methanotrophs compete for the limited carbon source, CH₄, using different electron acceptors including O₂, NO₂⁻/NO₃⁻, and SO₄²⁻. Methanotrophic pathways with higher free energy yield are more likely to outcompete others for CH₄ utilization (20). In an anoxic environment where NO₂⁻/NO₃⁻ and SO₄²⁻ coexist, N-DAMO is more likely to occur than S-DAMO, as NO₂⁻/NO₃⁻ is more thermodynamically favored electron acceptors than SO₄²⁻ (20, 32). Therefore, the N-DAMO process is mainly found in freshwater environments such as terrestrial wetlands, rivers, and lakes and is the dominant AMO pathway in these environments (27, 33–35). Meanwhile, in coastal ecosystems with an abundant supply of SO₄²⁻ from seawater, S-DAMO is more likely to be the dominant AMO process (21). An exception is coastal ecosystems where anthropogenic NO₂⁻/NO₃⁻ inputs from rivers support N-DAMO as a more dominant AMO process than S-DAMO. For example, a previous study assessed S-DAMO and N-DAMO separately in the intertidal zone of the East China Sea and found that S-DAMO accounted for 35% of AMO, with the remainder attributed to N-DAMO activity (36). It was also suggested that N-DAMO is the dominant AMO pathway in intertidal flats of China and plays a key role in the nitrogen cycle (37–39).

Climate change phenomena such as warming temperatures and elevated levels of atmospheric CO₂ may substantially influence the rate of AMO in coastal wetlands by changing the cycling and availability of key electron acceptors. For instance, a previous study revealed that warming markedly enhances SO₄²⁻ depletion by increasing SO₄²⁻ reduction rates (15). These changes in SO₄²⁻ dynamics by warming can consequently affect S-DAMO activity. Moreover, warming can reduce the total nitrogen concentration in the soil by accelerating denitrification and the nitrogen turnover rate, as shown in a coastal wetland in the Yangtze Estuary (40), potentially affecting N-DAMO activity. Meanwhile, elevated CO₂ (eCO₂) has been shown to enhance root growth in coastal wetlands, thereby enhancing O₂ transport belowground (16). This process could potentially decrease AMO activity through competition with aerobic methanotrophs or enhance AMO by regenerating NO₂⁻/NO₃⁻ and SO₄²⁻ as AMO substrates. These changes in electron acceptor dynamics driven by climate change could substantially alter AMO rates and, subsequently, CH₄ emissions from coastal wetland ecosystems.

While prior research has elucidated the effects of climate change on AMO and methanogenesis (19, 41–43), our understanding of its influence on AMO remains limited. Despite this gap in knowledge, it is established that AMO substantially influences coastal wetland CH₄ dynamics, removing up to 90% of CH₄ produced by methanogens (22, 24). Therefore, understanding how AMO responds to climate change and the mechanisms driving this response is essential for accurately predicting future CH₄ dynamics in a changing climate (44). Here, we used an in situ climate change manipulation experiment in a coastal wetland to elucidate the response of AMO to warming temperatures and eCO₂. We hypothesized that (i) S-DAMO is the dominant AMO pathway at our study site given the limited availability of NO₂⁻/NO₃⁻; (ii) warming reduces AMO activity due to warming-induced SO₄²⁻ depletion; and (iii) eCO₂ enhances the transport of O₂ belowground, allowing aerobic methanotrophs to outcompete AMO microbes, which, in turn, decreases AMO activity.

RESULTS

The study was conducted at the Smithsonian’s Global Change Research Wetland (GCReW), a brackish high marsh on the Chesapeake Bay, USA (38°55′N, 76°33′W), using the Salt Marsh Accretion Response to Temperature Experiment (SMARTX) (45). Four climate treatments were used to investigate the response of AMO activity and other biogeochemical characteristics to warming temperature and elevated atmospheric CO₂ concentration. Whole-ecosystem temperature (plant canopy and soil to 1.5 m deep) was maintained at ambient levels, which varied naturally, and was instantaneously warmed to +5.1°C above ambient. Atmospheric CO₂ was maintained at ambient concentration and at 350–part per million (ppm) CO₂ above ambient concentration. The four treatments were fully crossed yielding (i) ambient (ambient temperature and CO₂), (ii) eCO₂ (ambient temperature and elevated CO₂), (iii) +5.1°C (+5.1°C warming above ambient temperature), and (iv) +5.1°C + eCO₂ (both warming and elevated CO₂). This full design was applied in a plant community dominated by a C₃ sedge, while a subset of the design involving only the temperature treatments was applied in a plant community dominated by C₄ grasses.

Effect of climate change on SO₄²⁻ concentration, redox potential, and fine-root productivity

Overall, warming led to decreased porewater SO₄²⁻ concentration, whereas the influence of eCO₂ was depth dependent (Fig. 1). In the C₃ community, warming markedly decreased SO₄²⁻ concentration at all measured depths (20, 40, and 80 cm) compared to the ambient conditions. The plots exposed to only eCO₂ showed increased SO₄²⁻ concentration at all measured depths, but this effect was absent in the deeper layers (40 and 80 cm) when crossed with the warming treatment. In the C₄ community, warming led to a significant decrease in SO₄²⁻ concentration at depths of 20 cm (Fig. 1A, P < 0.05) and 40 cm (Fig. 1B, P < 0.01), but the difference in SO₄²⁻ concentration between the warming plots and the ambient plots at 80 cm was more subtle (Fig. 1C). The overall trend of SO₄²⁻ concentration at 20 cm observed from 2017 to 2022 follows a trend similar to that in 2022, where warming led to a reduction in SO₄²⁻ concentration and eCO₂ increased it (fig. S1). SO₄²⁻ depletion exhibited an opposite trend to SO₄²⁻ concentration, with warming increasing SO₄²⁻ depletion, while eCO₂ decreased it (fig. S2).

Redox potential at a depth of 20 cm mirrored the treatment effects on SO₄²⁻ concentration in the C₃ community (redox was not measured in the C₄ community). eCO₂ increased redox potential, while warming decreased it (Fig. 2A, P < 0.001). In addition, the redox potential showed a significant positive correlation with SO₄²⁻ concentration [Fig. 2B, coefficient of determination (R²) = 0.68, P < 0.001]. eCO₂ increased fine-root productivity, while warming showed no effect in the C₃ community in 2022 (Fig. 2C).

Fig. 2. — (A) Monthly average redox potential measured at a depth of 20 cm from May to July 2022 in two warming treatments (ambient and ambient + 5.1°C) crossed with eCO₂ (ambient and ambient + 350-ppm CO₂) in the C₃ community. (B) A positive correlation between redox potential and SO₄²⁻ concentration measured at a depth of 20 cm in the C₃ community. (C) Fine-root productivity (0 to 40 cm in depth) from November 2021 to November 2022. A linear mixed-effects model and one-way analysis of variance (ANOVA) were used to test the difference in redox potential and fine-root productivity, respectively, between the treatments. Error bars indicate the SEM [n = 6 for (A) and n = 3 for (C)].

Response of AMO process to climate change

In the C₃ community, warming reduced S-DAMO rates (0.195 nmol of ¹³CO₂ g_dw⁻¹ day⁻¹) in comparison to the ambient plot (0.905 nmol of ¹³CO₂ g_dw⁻¹ day⁻¹), while eCO₂ increased rates (4.194 nmol of ¹³CO₂ g_dw⁻¹ day⁻¹) (Fig. 3A, P < 0.01). The combination of warming and eCO₂ (+5.1°C + eCO₂) produced rates of S-DAMO higher than both the ambient and the warming-alone treatments (5.33 nmol of ¹³CO₂ g_dw⁻¹ day⁻¹). S-DAMO rates were positively correlated with SO₄²⁻ concentration (Fig. 3B, R² = 0.41, P < 0.05). In the C₄ community, warming also reduced the average S-DAMO activity (0.445 nmol of ¹³CO₂ g_dw⁻¹ day⁻¹) compared to the ambient condition (1.105 nmol of ¹³CO₂ g_dw⁻¹ day⁻¹), but the relationship was weaker (Fig. 3A). Overall, S-DAMO removed 7 and 12% of the CH₄ produced in the C₃ and C₄ communities, respectively (fig. S3B). For the NO₂⁻- and NO₃⁻-DAMO pathways, the ¹³CO₂ production rates from ¹³CH₄ + NO₂⁻ and ¹³CH₄ + NO₃⁻ treatments were not significantly different from the ¹³CO₂ production rate of the ¹³CH₄ treatment alone (fig. S4), indicating that NO₂⁻ and NO₃⁻ do not serve as electron acceptors for the AMO process at our study site.

Fig. 3. — (A) S-DAMO rates in two warming treatments (ambient and ambient + 5.1°C) crossed with eCO₂ (ambient and ambient + 350-ppm CO₂) in C₃ and C₄ communities. (B) A positive correlation between S-DAMO rate and SO₄²⁻ concentration in the C₃ community. A one-way ANOVA and Mann-Whitney U test were used to test the difference in S-DAMO rate between the treatments in C₃ and C₄ communities, respectively. Error bars indicate the SEM (n = 3).

In situ CH₄ emission

In the C₃ community, warming increased June 2022 CH₄ emissions, while eCO₂ reduced them (Fig. 4, P < 0.005). The combined effect of warming and eCO₂ (+5.1°C + eCO₂) resulted in higher CH₄ emissions than ambient but lower than in plots with warming alone. CH₄ emissions from the C₄ community in June 2022 followed a similar pattern, with warming increasing CH₄ emissions (Fig. 4, P < 0.05). Consistent with the June 2022 trend, the average CH₄ emissions from 2017 to 2022 showed increased emissions in warmed plots and decreased emissions in eCO₂ plots (fig. S3A, P < 0.001).

Abundance of ANME-1 and ANME-2c

In the C₃ community, eCO₂ increased the sum of ANME-1 and ANME-2c gene abundance, while warming alone had no effect (Fig. 5A, P = 0.002). Both ANME-1 and ANME-2c exhibited similar patterns (fig. S5, A and B, P < 0.05). A positive correlation was also observed between S-DAMO rate and combined gene abundance of ANME-1 and ANME-2c (Fig. 5B, R² = 0.44, P = 0.014), with a clear separation of abundance at ambient (low) and eCO₂ (high) (Fig. 5A). The abundances of the two genes considered separately were also positively correlated with S-DAMO rate (fig. S5, C and D, R² = 0.28 to 0.48, P = 0.01 to 0.1). In the C₄ community, warming tended to decrease the average abundances of both ANME-1 and ANME-2c (fig. S5, A and B). In addition, the combined gene abundances of ANME-1 and ANME-2c in warming plots were slightly lower compared to those in ambient plots (Fig. 5A).

DISCUSSION

Variation in SO₄²⁻ concentrations across plots is not attributable to differences in SO₄²⁻ inputs, as tidal water is the primary source of SO₄²⁻ across these colocated plots. Rather, differences in SO₄²⁻ concentration across treatments are likely due to shifts in rates of SO₄²⁻ reduction and SO₄²⁻ regeneration through sulfide (H₂S) oxidation. Warming decreased SO₄²⁻ concentration (Fig. 1 and fig. S1) and increased H₂S concentration (fig. S6) in both the C₃ and C₄ communities, suggesting a temperature-driven increase in SO₄²⁻ reduction rates that was not fully compensated by increased H₂S oxidation rates. This response is consistent with previous studies showing an exponential increase in SO₄²⁻ reduction rates with temperature in brackish tidal marshes and intertidal zones (46, 47). This is consistent with a long-term warming experiment in coastal Baltic Sea sediments that related an increase in SO₄²⁻ reduction to an increase in the relative abundance of SO₄²⁻-reducing bacteria (48). The decrease in redox potential observed in warming plots (Fig. 2A) further suggests that reduction processes were favored over oxidation processes under warming. This trend could be due to a higher temperature sensitivity for reduction than for oxidation, as shown in previous work (49), where Fe reduction was more responsive to warming than Fe oxidation. We hypothesize that this pattern extends to other coupled redox processes, such as SO₄²⁻ reduction and oxidation. This view is supported by greater SO₄²⁻ depletion in warming plots (fig. S2), suggesting a net shift toward reduction over oxidation under warming compared to ambient temperature. Thus, we propose that differences in temperature sensitivity between SO₄²⁻ reduction and H₂S oxidation explain some of the observed porewater chemistry responses to warming.

In contrast to the impact of warming, eCO₂ increased SO₄²⁻ concentration (Fig. 1 and fig. S1) and decreased H₂S concentration (fig. S6) in the C₃ community, a response that coincided with increased soil redox potential and fine-root productivity (Fig. 2 and fig. S7). It is well documented that eCO₂ stimulates root productivity in terrestrial ecosystems (16, 50, 51) and enhanced root productivity in this experiment induced by eCO₂ is associated with an increase in soil redox potential, presumably due to greater plant-mediated O₂ transport from the atmosphere into the soil (16). We propose that an increase in the O₂ supply to soils facilitated by the positive C₃ plant growth response to eCO₂ substantially shifted the net balance between SO₄²⁻ reduction and regeneration toward regeneration (52). This interpretation is consistent with the positive correlation between redox potential and SO₄²⁻ concentration across treatments (Fig. 2B).

SO₄²⁻ concentrations in the warming plots were increased by eCO₂ at the 20-cm soil depth but not at deeper depths (Fig. 1). The surficial 0 to 30 cm of the soil profile is also the peak of plant belowground biomass [70 to 95% of root biomass (53)] and soil redox potential [−150 to 150 mV (16)]. Tidal flooding maintains the soil profile at or near saturation to the soil surface continuously, suggesting that plant gas transport is the dominant source of O₂ into the soil profile. eCO₂ stimulation of plant O₂ transport is expected to be dominant at the soil surface layer, leading to an increase in SO₄²⁻ concentration at shallow depths compared to ambient plots. Because deeper soils are less affected by root activity, they are expected to show relatively small plant O₂ transport responses to eCO₂, so the warming-induced stimulation of SO₄²⁻ reduction in deeper soils should favor lower SO₄²⁻ concentrations. The depth dependence of our treatments on SO₄²⁻ dynamics is a specific mechanism by which plant-microbe interactions indirectly regulate greenhouse gas emissions. Considering that contemporary climate change leads to both warming and eCO₂ and most biological activity occurs at the soil surface, the influence of plant-microbe interactions on greenhouse gas emissions operating through redox-active elements is important to elucidate in terrestrial ecosystems generally.

As we hypothesized, S-DAMO was the primary AMO process, whereas N-DAMO played a minor role. The decreased production of ¹³CO₂ in treatments with NO₂⁻ and NO₃⁻ addition (fig. S4) suggests that the addition of NO₂⁻/NO₃⁻ compounds reduced AMO activity. This finding aligns with previous studies indicating an inhibition of S-DAMO by NO₂⁻/NO₃⁻ in marine CH₄ seeps (54) and estuarine sediments (55), as denitrification is more thermodynamically and biochemically favorable than S-DAMO. The addition of NO₂⁻/NO₃⁻ could potentially have decreased the pH and thereby reduced overall AMO activity; however, no significant changes in pH were observed (fig. S8). Meanwhile, this result is opposed to other studies measuring AMO rates in coastal wetlands, where N-DAMO was identified as the dominant process (36, 37, 39, 56). For instance, in the intertidal zones of the East China Sea, N-DAMO accounted for up to 65% of AMO activity, with S-DAMO responsible for the remainder (36). Consequently, much of the prior research focused exclusively on N-DAMO, overlooking the crucial role of S-DAMO in coastal wetland ecosystems (38, 39, 56). These studies were conducted in coastal areas of East China that receive substantial nitrogen inputs from inland sources, including agriculture, industrial emissions, and urban wastewater (57, 58). As a result, these nitrogen inputs provide NO₂⁻/NO₃⁻ substrates for N-DAMO activity, which are thermodynamically favored as electron acceptors over SO₄²⁻ (32). However, not all coastal areas are subjected to severe nitrogen inputs from inland (59). At our study site, NO₂⁻ and NO₃⁻ concentrations in June 2022 were at or below detection limits (fig. S9), likely because of minimal inputs of NO₂⁻/NO₃⁻ from the adjacent estuary and soils that are continuously saturated to the soil surface (60, 61).

The increased O₂ availability triggered by eCO₂ has the potential to suppress AMO activity through toxic effects or competition with aerobic methanotrophs for CH₄ (62), so our initial hypothesis was that eCO₂ would reduce overall AMO activity. Contrary to expectations, eCO₂ instead promoted AMO activity, particularly S-DAMO (Fig. 3A). This suggests that aerobic and anaerobic CH₄ oxidizers are not competing for CH₄, which is likely given the high porewater CH₄ concentrations [~50 to 150 μM (15)] at our study site. Rather, a positive correlation between the S-DAMO rate and the redox potential indicates (fig. S10) that O₂ enhances S-DAMO activity by increasing the SO₄²⁻ concentration and that both aerobic and anaerobic pathways contribute to mitigating CH₄ emissions from tidal wetlands. We did not estimate the contribution of AMO to overall CH₄ oxidation, but S-DAMO contributed up to 5.6% of the total CH₄ oxidation in a coastal wetland of the East China Sea (29).

The stimulation of S-DAMO rates in eCO₂ plots was likely induced primarily by increased rates of H₂S oxidation to SO₄²⁻, regenerating the electron acceptor required for S-DAMO respiration. This increase in S-DAMO activity is evidence that SO₄²⁻ availability limits S-DAMO rates, which is consistent with the relatively low salinity (~8) and associated SO₄ availability at our site. This is supported by the positive correlation between the S-DAMO rate and the SO₄²⁻ concentration (Fig. 3B) in the C₃ community. Furthermore, SO₄²⁻ concentration has been shown to be positively correlated with the OTU number, the Shannon index, and the Chao1 index of ANME archaea in coastal wetlands, further indicating that SO₄²⁻ availability generally limits S-DAMO activity in coastal wetlands (36). While earlier studies have suggested that S-DAMO microbes might also use alternative substrates such as manganese, iron, and organic humic substances when SO₄²⁻ is scarce, these alternatives appear to lead to lower rates of AMO. In the present case, only humic substances could have served as alternative electron acceptors in these highly organic (~80% organic matter) soils.

We observed an increase in the gene abundance of ANME-1 and ANME-2c, microorganisms involved in S-DAMO, under eCO₂ conditions (Fig. 5A and fig. S5). ANME-1 showed a higher abundance and a stronger correlation with S-DAMO rates than ANME-2c. This may reflect ecological distinctions between the two groups. ANME-2c forms stable aggregates with SO₄²⁻-reducing bacteria, facilitating CH₄ oxidation (63, 64). We hypothesize that eCO₂-induced plant O₂ transport suppressed SO₄²⁻-reducing bacteria, which thrive under anaerobic conditions (65), thereby reducing ANME-2c’s S-DAMO capacity. In contrast, ANME-1 uses an independent S-DAMO strategy that does not rely on SO₄²⁻-reducing bacteria (66), making it less affected by O₂ intrusion and giving it a competitive advantage.

As we hypothesized, +5.1°C warming decreased S-DAMO activity compared to ambient conditions (Fig. 3A), likely a consequence of decreased SO₄²⁻ availability. However, when warming was combined with eCO₂ in the C₃ community, S-DAMO activity rebounded to rates similar to those in the ambient temperature treatments, presumably due to increased rates of plant-mediated O₂ transport supporting SO₄²⁻ regeneration. This interpretation is supported by the significant positive correlation between SO₄²⁻ concentration and S-DAMO rate (Fig. 3B). However, the magnitude of the S-DAMO response to our treatments, which are on a log scale, was much larger than the SO₄²⁻ concentration responses (compare Figs. 1A and 3A), and the correlation (Fig. 3B, R² = 0.41) indicated substantial unexplained variation. Because SO₄²⁻ concentration is the balance of two opposing and rapid processes—SO₄²⁻ reduction and H₂S oxidation—it only approximates SO₄²⁻ availability. A more precise covariate for S-DAMO would be the direct measurement of SO₄²⁻ reduction and H₂S oxidation rates.

The response of CH₄ emissions to climate change treatments follows the observed S-DAMO rate responses, suggesting that reduced S-DAMO under warming contributed to higher CH₄ emissions and increased S-DAMO under eCO₂ contributed to lower CH₄ emissions (Fig. 4 and fig. S3A). These results suggest that S-DAMO plays a crucial role in regulating CH₄ emissions in coastal wetlands. In the relatively low salinity (~8) setting of our study site, we estimated that S-DAMO removes 7 and 12% of CH₄ produced by methanogenesis in the C₃ and C₄ communities, respectively (fig. S3B), a meaningful fraction given the large sustained global warming potential of CH₄ (67). However, given estimates from other sites that S-DAMO can consume up to 90% of CH₄ production in some tidal ecosystems (22), the potential for even larger climate change effects in the greenhouse gas balance of coastal wetlands is substantial.

Most previous studies on SO₄²⁻ regulation of ecosystem CH₄ emissions focus on competitive interactions between SO₄²⁻-reducing bacteria and methanogens. Our study offers the perspective that SO₄²⁻ availability can also modulate ecosystem CH₄ emissions by regulating S-DAMO activity (Fig. 6). We previously reported that warming substantially increased CH₄ emissions by stimulating methanogenic activity, while eCO₂ reduced it by promoting O₂ transport belowground where it supports aerobic methanotrophs (16). Our findings add an anaerobic oxidation mechanism to explain these observations, which is that warming increases CH₄ emissions by reducing S-DAMO activity, while eCO₂ decreases CH₄ emissions by stimulating S-DAMO activity. This mechanism is consistent with our previous hypothesis (16) that eCO₂ enhances CH₄ oxidation through increased plant-mediated O₂ transport but through more complex mechanisms that link carbon cycling to sulfur cycling. The relative contributions of aerobic and anaerobic methanotrophy to this important CH₄ sink remain to be determined, along with related questions about the fate of O₂ in the plant rhizosphere where there are multiple competing chemical and biological sinks for O₂. While the present study linked plant trait effects on CH₄ oxidation to sulfur oxidation, the mechanism for these plant-microbe interactions is transferable to other wetland ecosystems where the stimulation of plant-mediated O₂ transport by eCO₂ or other means would instead increase the availability of oxidants such as NO₃⁻, Fe(III), or oxidized humic substances (49, 68). Understanding these dynamics and integrating them into predictive models are essential for forecasting the future impact of coastal wetlands on global CH₄ budgets and formulating strategies to mitigate CH₄ emissions in the context of climate change.

Fig. 6. — Warming and eCO₂ influence CH₄ emissions through changes in O₂ transport and SO₄²⁻ dynamics. The size of the arrows indicates the magnitude of the rate, and the size of the circles indicates the size of the pool. Thermometer icon indicates the effect of the warming temperature treatment.

MATERIALS AND METHODS

Site description and experimental design

The study was conducted at the Smithsonian’s GCReW, a brackish high marsh located on the western shore of the Chesapeake Bay, USA (38°55′N, 76°33′W), using the SMARTX (45). This comprehensive experiment includes 30 plots distributed over six warming transects; each plot is 2 m by 2 m and is encircled by a 0.2-m buffer zone to minimize edge effects. Half of the transects are located in a high-elevation area dominated by Spartina patens and Distichlis spicata (referred to as the C₄ community), which experiences flooding during 10 to 20% of high tides. The remaining transects are located in a low-elevation area dominated by Schoenoplectus americanus (referred to as the C₃ community) with flooding occurring during 30 to 60% of high tides. Soils are highly organic (<80% organic matter) to a depth of 5 m, which is a characteristic common in high marshes of the Chesapeake Bay and other regions (15). The low mineral content (<20%) influences CH₄ dynamics due to the negligible competition between methanogens and iron-reducing bacteria for electron donors, attributed to the lack of a substantial amount of poorly crystalline iron oxides (69), as has been previously observed at this site (70). Species that dominate the two communities represent two fundamental photosynthetic pathways that respond either weakly (C₄) or strongly (C₃) to eCO₂. For that reason, the C₃ community has an additional eCO₂ treatment.

In this study, a subset of 18 plots was used, including 12 from the C₃ community and 6 from the C₄ community. The C₃ community uses a complete factorial design, featuring two temperature levels (ambient and +5.1°C warming) and two CO₂ levels (ambient and +350 ppm). The C₄ community consists of two temperature levels (ambient and +5.1°C). Each combination of treatment conditions is replicated three times.

Warming in the plots is achieved using infrared heaters to increase aboveground plant-surface temperature and vertical resistance cables to raise soil temperature to a depth of 1.5 m (15, 16). Temperature control is maintained through an integrated microprocessor-based feedback system (16, 71). In addition, the eCO₂ plots are equipped with 2-m-diameter open-top chambers, allowing for independent CO₂ concentration control within each chamber. The warming began in June 2016 and operates continuously throughout the year, while the eCO₂ treatment started in April 2017, applied only during daylight hours in the growing season (April to November).

Porewater chemistry and fine-root productivity

Porewater samples were collected in May and July 2022 through stainless-steel “sippers” installed permanently in each plot in 2016 (15). In each plot, duplicate clusters of sippers were installed at depths of 20, 40, 80, and 120 cm below the soil surface. On collection days, the stagnant porewater within the sippers was initially expelled, followed by the extraction of 60 ml of porewater from each specified depth (30 ml from each sipper) and stored in syringes fitted with three-way stopcocks. From each sample, a 10-ml aliquot was passed through a prerinsed 0.45-μm syringe-mounted filter, preserved with 5% zinc acetate and sodium hydroxide, and frozen for future SO₄²⁻ and chloride (Cl⁻) analysis.

The concentrations of SO₄²⁻ and Cl⁻ were analyzed using a Dionex Integrion system, equipped with an A11 4-μm fast column operated with a 35 mM KOH eluent. The degree of SO₄²⁻ depletion was computed from the porewater concentrations of SO₄²⁻ (SO4_pw) and Cl⁻ (Cl_pw), using the constant molar ratio of Cl⁻ to SO₄²⁻ in surface seawater at the study site (R_sw = 6.84) as per the equation: SO₄²⁻ depletion = Cl_pw/R_sw – SO4_pw (72). Normally, if influenced solely by seawater contribution, then the Cl to SO₄²⁻ ratio stays unchanged. However, in coastal wetland ecosystems, SO₄²⁻ reduction by SO₄²⁻-reducing bacteria and regeneration of SO₄²⁻ by H₂S oxidation may modify this balance, making SO₄²⁻ depletion a useful indicator of the in situ rates of SO₄²⁻ dynamics.

The redox potential in the C₃ community was measured using an automated redox system (16). Briefly, six redox probes with platinum bands were installed at a depth of 20 cm in each plot. Measurements were taken every 30 min, and data from May to July 2022 were used in this study. Replicate measurements within a plot were averaged for each time point (n = 6) and then averaged again across plots (n = 48) to obtain a daily mean per plot. For statistical analysis, daily means were averaged per plot from May to June 2022.

Fine-root productivity was measured using yearlong root ingrowth cores (0 to 40 cm in depth), following the method described previously (45), with three replicate cores per plot. Briefly, roots and rhizomes were collected, sorted by functional groups, oven-dried at 60°C, and weighed.

Potential AMO, CH₄ production, and in situ CH₄ emission

Potential AMO activity was evaluated using the ¹³C stable isotope technique (28). Soil samples were collected from each plot in June 2022, at depths between 15 and 30 cm. On the day of collection, slurries were prepared by mixing 15 g of soil from each plot with 30 ml of porewater, sourced from near the SMARTX at a depth of 20 cm, and these were then placed into 120-ml vials. Before its use, the porewater was passed through a 0.2-μm membrane filter and degassed with N₂. These vials were purged with N₂ and were subjected to a preincubation for 5 days in a shaker at 150 rpm and 20°C in darkness, a process designed to acclimate the microbial communities to the ambient temperature and to eliminate any residual O₂ and NO_x⁻.

Following the preincubation, the vials were again purged with N₂ and organized into five distinct experimental groups: (i) ¹²CH₄, (ii) ¹³CH₄ (99.9% ¹³C; Sigma-Aldrich, DE), (iii) ¹³CH₄ + SO₄²⁻ (final SO₄²⁻ concentration of initial porewater + 30 mM), (iv) ¹³CH₄ + NO₂⁻ (final NO₂⁻ concentration of 0.5 mM), and (v) ¹³CH₄ + NO₃⁻ (final NO₃⁻ concentration of 5 mM). In each vial, 20 μl of Na₂SO₄, NaNO₂, or NaNO₃ was added, as applicable. Moreover, 80 μl of CH₄ [¹²CH₄ for group i and ¹³CH₄ for groups ii to v] were infused to reach a target headspace CH₄ concentration of 1% (v/v). Each treatment was performed in triplicate. Additional vials were set up to monitor the headspace O₂ concentration. Five days after the start of incubation, the headspace from each vial was collected and transferred to 12-ml evacuated double-wadded exetainers (Labco, UK) for analysis. Except for the N₂ purging, all procedures were conducted in an anaerobic chamber with an atmosphere of 97% N₂ and 3% H₂. The total CO₂ concentration was measured using gas chromatography (Varian, USA), and the δ¹³C ratio of CO₂ was measured using an isotope ratio mass spectrometer (Thermo Fisher Scientific, Germany) at the University of California Davis Stable Isotope Facility. In addition, the headspace CH₄ concentration of control treatments was measured using gas chromatography (Varian, USA) to determine the potential CH₄ production rate. Using the rate, we calculated the proportion of S-DAMO to gross CH₄ production.

The potential activities of S-DAMO, NO₂⁻-DAMO, and NO₃⁻-DAMO were quantified on the basis of ¹³CO₂ production during incubation. Specifically, the S-DAMO rate was determined by the difference in ¹³CO₂ production between ¹³CH₄-only and ¹³CH₄ + SO₄²⁻ treatments. NO₂⁻-DAMO and NO₃⁻-DAMO rates were determined by the ¹³CO₂ production difference between ¹³CH₄ and ¹³CH₄ + NO₂⁻ and ¹³CH₄ + NO₂⁻ and ¹³CH₄ + NO₃⁻ treatments, respectively.

In situ CH₄ emissions were measured as described previously (15). Briefly, CH₄ fluxes were measured from March to November from 2017 to 2022 using static chambers, and fluxes were calculated as the linear rate of change in CH₄ concentration within the chamber headspace over 5 min.

DNA extraction and quantitative polymerase chain reaction

Microbial DNA and RNA were coextracted from 2 g of soil samples using the RNeasy PowerSoil Total RNA Kit and the RNeasy PowerSoil DNA Elution Kit according to the manufacturer’s instructions (QIAGEN, Hilden, Germany), and only the extracted DNA was used in this study. The final DNA pellet was delicately suspended in 30 μl of deoxyribonuclease-free water. Last, the quantity and purity of DNA were assessed using the Qubit 4.0 fluorometer and NanoDrop ND-1000 spectrometer (Thermo Fisher Scientific, Waltham, USA).

The abundances of ANME archaea were estimated using quantitative polymerase chain reaction (qPCR) with SYBR Green Real-Time PCR Master Mix (Toyobo, Osaka, Japan) and CFX Opus 96 Real-Time PCR System (Bio-Rad, CA, USA), targeting small subunit ribosomal RNA genes for ANME-1 and ANME-2c. Primers specific to each gene are detailed in table S1. Each reaction mixture, with a total volume of 10 μl, was composed of 3.6 μl of distilled water, 5 μl of SYBR Green Master Mix, 0.2 μl of each forward and reverse primer (0.2 μM), and 1 μl of DNA solution. The copy number of genes was calculated using standard curves derived from serial 10-fold dilutions of gene fragments. For all qPCR reactions, the standard curves exhibited an efficiency greater than 98% and a R² higher than 0.99. Amplification specificity for each qPCR reaction was confirmed through the analysis of melting curves and 1.3% agarose gel electrophoresis.

Statistical analysis

All statistical analyses were performed using R (version 4.3.3). Linear mixed-effects models were used to evaluate the relationships between the S-DAMO rate and the abundance of ANME-1, the abundance of ANME-2, the combined abundance of ANME-1 and ANME-2c, CH₄ emission, and between redox potential, soil pH, H₂S concentration, and SO₄²⁻ concentration in the C₃ community. Climate factors (ambient, +5.1°C, eCO₂, and +5.1°C + eCO₂) were incorporated as random effects to account for between-treatment variability. An exponential regression analysis was used to test the relationship between the S-DAMO rate and the SO₄²⁻ concentration, as well as between the S-DAMO rate and the SO₄²⁻ depletion. Linear mixed-effects models were used to assess the effect of warming and eCO₂ on SO₄²⁻ concentration, SO₄²⁻ depletion, and redox potential in the C₃ community. Climate factors were used as categorical variables, and month was used as random effects. One-way analysis of variance (ANOVA) was used to test the difference in S-DAMO rate, the abundance of ANME-1, ANME-2c, fine-root productivity, and combined abundance of ANME-1 and ANME-2c between the treatments in the C₃ community. Mann-Whitney U tests were used to test the difference in S-DAMO rate, abundance of ANME-1 and ANME-2c, combined abundance of ANME-1 and ANME-2c, soil pH, H₂S concentration, SO₄²⁻ concentration, SO₄²⁻ depletion, fine-root productivity, and CH₄ emission between the treatments in the C₄ community. We did not include post hoc labels in the figure to indicate significant differences between treatments, as the large variability and small sample size reduced statistical power, making it difficult to detect true differences (73).

Acknowledgments

Funding: Funding for this project was provided by the US Department of Energy; the Office of Science; the Office of Biological and Environmental Research; the Environmental System Science program under awards DE-SC0014413, DE-SC0019110, and DE-SC0021112; the National Science Foundation Long-Term Research in Environmental Biology Program (DEB-0950080, DEB-1457100, DEB-1557009, and DEB-2051343); the Ministry of Environment of Korea (RS-2023-00232066); the National Research Foundation of Korea (RS-2024-00335917 and RS-2024-00393713); and the Smithsonian Institution.

Author contributions: Writing—original draft: J.L. and Y.Y. Writing—review and editing: J.L., G.L.N., Y.Y., H.K., and J.P.M. Conceptualization: J.L., Y.Y., and J.P.M. Investigation: J.L. and Y.Y. Methodology: J.L., G.L.N., Y.Y., and H.K. Resources: J.L., G.L.N., Y.Y., and H.K. Funding acquisition: J.L., G.L.N., H.K., and J.P.M. Data curation: J.L., G.L.N., and Y.Y. Validation: J.L., Y.Y., and H.K. Supervision: J.L., G.L.N., H.K., and J.P.M. Formal analysis: J.L. and Y.Y. Software: J.L. Project administration: J.L., G.L.N., and H.K. Visualization: J.L., G.L.N., and Y.Y.

Competing interests: The authors declare that they have no competing interests.

Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. The datasets of the study are available in the Smithsonian Institution figshare repository (https://smithsonian.figshare.com) under https://doi.org/10.25573/serc.27855327.

Supplementary Materials

This PDF file includes:

Figs. S1 to S10

Table S1

References

sciadv.ads6093_sm.pdf^{(1.7MB, pdf)}

REFERENCES AND NOTES

1.Bridgham S. D., Megonigal J. P., Keller J. K., Bliss N. B., Trettin C., The carbon balance of North American wetlands. Wetlands 26, 889–916 (2006). [Google Scholar]
2.Paudel R., Mahowald N. M., Hess P. G. M., Watts J. D., Kimball J. S., Poulter B., Bousquet P., Canadell J. G., Ciais P., Peregon A., Arora V. K., Beerling D. J., Brovkin V., Jones C. D., Joos F., Peng C., Peng S., Prigent C., Schroeder R., Riley W. J., Saito M., Global wetland contribution to 2000–2012 atmospheric methane growth rate dynamics. Environ. Res. Lett. 12, 094013 (2017). [Google Scholar]
3.Bueno de Mesquita C. P., Hartman W. H., Ardón M., Tringe S. G., Disentangling the effects of sulfate and other seawater ions on microbial communities and greenhouse gas emissions in a coastal forested wetland. ISME Commun. 4, ycae040 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]
4.Bueno de Mesquita C. P., Hartman W. H., Ardón M., Bernhardt E. S., Neubauer S. C., Weston N. B., Tringe S. G., Microbial ecology and site characteristics underlie differences in salinity-methane relationships in coastal wetlands. J. Geophys. Res. Biogeosci. 129, e2024JG008133 (2024). [Google Scholar]
5.Rosentreter J. A., Maher D. T., Erler D. V., Murray R. H., Eyre B. D., Methane emissions partially offset “blue carbon” burial in mangroves. Sci. Adv. 4, eaao4985 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]
6.Oreska M. P. J., McGlathery K. J., Aoki L. R., Berger A. C., Berg P., Mullins L., The greenhouse gas offset potential from seagrass restoration. Sci. Rep. 10, 7325 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
7.Kirwan M. L., Megonigal J. P., Noyce G. L., Smith A. J., Geomorphic and ecological constraints on the coastal carbon sink. Nat. Rev. Earth Environ. 4, 393–406 (2023). [Google Scholar]
8.Holmquist J. R., Windham-Myers L., Bernal B., Byrd K. B., Crooks S., Gonneea M. E., Herold N., Knox S. H., Kroeger K. D., McCombs J., Megonigal J. P., Lu M., Morris J. T., Sutton-Grier A. E., Troxler T. G., Weller D. E., Uncertainty in United States coastal wetland greenhouse gas inventorying. Environ. Res. Lett. 13, 115005 (2018). [Google Scholar]
9.Al-Haj A. N., Fulweiler R. W., A synthesis of methane emissions from shallow vegetated coastal ecosystems. Glob. Change Biol. 26, 2988–3005 (2020). [DOI] [PubMed] [Google Scholar]
10.Schuerch M., Spencer T., Temmerman S., Kirwan M. L., Wolff C., Lincke D., McOwen C. J., Pickering M. D., Reef R., Vafeidis A. T., Hinkel J., Nicholls R. J., Brown S., Future response of global coastal wetlands to sea-level rise. Nature 561, 231–234 (2018). [DOI] [PubMed] [Google Scholar]
11.Macreadie P. I., Anton A., Raven J. A., Beaumont N., Connolly R. M., Friess D. A., Kelleway J. J., Kennedy H., Kuwae T., Lavery P. S., Lovelock C. E., Smale D. A., Apostolaki E. T., Atwood T. B., Baldock J., Bianchi T. S., Chmura G. L., Eyre B. D., Fourqurean J. W., Hall-Spencer J. M., Huxham M., Hendriks I. E., Krause-Jensen D., Laffoley D., Luisetti T., Marbà N., Masque P., McGlathery K. J., Megonigal J. P., Murdiyarso D., Russell B. D., Santos R., Serrano O., Silliman B. R., Watanabe K., Duarte C. M., The future of blue carbon science. Nat. Commun. 10, 3998 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]
12.Saintilan N., Horton B., Törnqvist T. E., Ashe E. L., Khan N. S., Schuerch M., Perry C., Kopp R. E., Garner G. G., Murray N., Rogers K., Albert S., Kelleway J., Shaw T. A., Woodroffe C. D., Lovelock C. E., Goddard M. M., Hutley L. B., Kovalenko K., Feher L., Guntenspergen G., Widespread retreat of coastal habitat is likely at warming levels above 1.5°C. Nature 621, 112–119 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
13.Langley J. A., McKee K. L., Cahoon D. R., Cherry J. A., Megonigal J. P., Elevated CO₂ stimulates marsh elevation gain, counterbalancing sea-level rise. Proc. Natl. Acad. Sci. U.S.A. 106, 6182–6186 (2009). [DOI] [PMC free article] [PubMed] [Google Scholar]
14.Mueller P., Mozdzer T. J., Langley J. A., Aoki L. R., Noyce G. L., Megonigal J. P., Plant species determine tidal wetland methane response to sea level rise. Nat. Commun. 11, 5154 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
15.Noyce G. L., Megonigal J. P., Biogeochemical and plant trait mechanisms drive enhanced methane emissions in response to whole-ecosystem warming. Biogeosciences 18, 2449–2463 (2021). [Google Scholar]
16.Noyce G. L., Smith A. J., Kirwan M. L., Rich R. L., Megonigal J. P., Oxygen priming induced by elevated CO₂ reduces carbon accumulation and methane emissions in coastal wetlands. Nat. Geosci. 16, 63–68 (2023). [Google Scholar]
17.Serrano-Silva N., Sarria-Guzmán Y., Dendooven L., Luna-Guido M., Methanogenesis and methanotrophy in soil: A review. Pedosphere 24, 291–307 (2014). [Google Scholar]
18.Le Mer J., Roger P., Production, oxidation, emission and consumption of methane by soils: A review. Eur. J. Soil Biol. 37, 25–50 (2001). [Google Scholar]
19.Megonigal J. P., Schlesinger W. H., Methane-limited methanotrophy in tidal freshwater swamps. Global Biogeochem. Cycles 16, 35-1–35-10 (2002). [Google Scholar]
20.Guerrero-Cruz S., Vaksmaa A., Horn M. A., Niemann H., Pijuan M., Ho A., Methanotrophs: Discoveries, environmental relevance, and a perspective on current and future applications. Front. Microbiol. 12, 678057 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
21.Gao Y., Wang Y., Lee H.-S., Jin P., Significance of anaerobic oxidation of methane (AOM) in mitigating methane emission from major natural and anthropogenic sources: A review of AOM rates in recent publications. Environ. Sci. Adv. 1, 401–425 (2022). [Google Scholar]
22.Knittel K., Boetius A., Anaerobic oxidation of methane: Progress with an unknown process. Annu. Rev. Microbiol. 63, 311–334 (2009). [DOI] [PubMed] [Google Scholar]
23.Meulepas R. J. W., Jagersma C. G., Gieteling J., Buisman C. J. N., Stams A. J. M., Lens P. N. L., Enrichment of anaerobic methanotrophs in sulfate-reducing membrane bioreactors. Biotechnol. Bioeng. 104, 458–470 (2009). [DOI] [PubMed] [Google Scholar]
24.La W., Han X., Liu C.-Q., Ding H., Liu M., Sun F., Li S., Lang Y., Sulfate concentrations affect sulfate reduction pathways and methane consumption in coastal wetlands. Water Res. 217, 118441 (2022). [DOI] [PubMed] [Google Scholar]
25.Mostovaya A., Wind-Hansen M., Rousteau P., Bristow L. A., Thamdrup B., Sulfate- and iron-dependent anaerobic methane oxidation occurring side-by-side in freshwater lake sediment. Limnol. Oceanogr. 67, 231–246 (2022). [Google Scholar]
26.Ettwig K. F., Butler M. K., Le Paslier D., Pelletier E., Mangenot S., Kuypers M. M. M., Schreiber F., Dutilh B. E., Zedelius J., De Beer D., Gloerich J., Wessels H. J. C. T., Van Alen T., Luesken F., Wu M. L., Van De Pas-Schoonen K. T., Op Den Camp H. J. M., Janssen-Megens E. M., Francoijs K. J., Stunnenberg H., Weissenbach J., Jetten M. S. M., Strous M., Nitrite-driven anaerobic methane oxidation by oxygenic bacteria. Nature 464, 543–548 (2010). [DOI] [PubMed] [Google Scholar]
27.Raghoebarsing A. A., Pol A., Van De Pas-Schoonen K. T., Smolders A. J. P., Ettwig K. F., Rijpstra W. I. C., Schouten S., Sinninghe Damsté J. S., Op Den Camp H. J. M., Jetten M. S. M., Strous M., A microbial consortium couples anaerobic methane oxidation to denitrification. Nature 440, 918–921 (2006). [DOI] [PubMed] [Google Scholar]
28.Hu B. L., Shen L. D., Lian X., Zhu Q., Liu S., Huang Q., He Z. F., Geng S., Cheng D. Q., Lou L. P., Xu X. Y., Zheng P., He Y. F., Evidence for nitrite-dependent anaerobic methane oxidation as a previously overlooked microbial methane sink in wetlands. Proc. Natl. Acad. Sci. U.S.A. 111, 4495–4500 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]
29.Wang J., Cai C., Li Y., Hua M., Wang J., Yang H., Zheng P., Hu B., Denitrifying anaerobic methane oxidation: A previously overlooked methane sink in intertidal zone. Environ. Sci. Technol. 53, 203–212 (2019). [DOI] [PubMed] [Google Scholar]
30.Rios-Del Toro E. E., Valenzuela E. I., López-Lozano N. E., Cortés-Martínez M. G., Sánchez-Rodríguez M. A., Calvario-Martínez O., Sánchez-Carrillo S., Cervantes F. J., Anaerobic ammonium oxidation linked to sulfate and ferric iron reduction fuels nitrogen loss in marine sediments. Biodegradation 29, 429–442 (2018). [DOI] [PubMed] [Google Scholar]
31.Haroon M. F., Hu S., Shi Y., Imelfort M., Keller J., Hugenholtz P., Yuan Z., Tyson G. W., Anaerobic oxidation of methane coupled to nitrate reduction in a novel archaeal lineage. Nature 500, 567–570 (2013). [DOI] [PubMed] [Google Scholar]
32.Segarra K. E. A., Comerford C., Slaughter J., Joye S. B., Impact of electron acceptor availability on the anaerobic oxidation of methane in coastal freshwater and brackish wetland sediments. Geochim. Cosmochim. Acta 115, 15–30 (2013). [Google Scholar]
33.Ettwig K. F., Shima S., van de Pas-Schoonen K. T., Kahnt J., Medema M. H., Op den Camp H. J. M., Jetten M. S. M., Strous M., Denitrifying bacteria anaerobically oxidize methane in the absence of archaea. Environ. Microbiol. 10, 3164–3173 (2008). [DOI] [PubMed] [Google Scholar]
34.Ettwig K. F., van Alen T., van de Pas-Schoonen K. T., Jetten M. S. M., Strous M., Enrichment and molecular detection of denitrifying methanotrophic bacteria of the NC10 phylum. Appl. Environ. Microbiol. 75, 3656–3662 (2009). [DOI] [PMC free article] [PubMed] [Google Scholar]
35.Shen L., Wu H., Liu X., Li J., Cooccurrence and potential role of nitrite- and nitrate-dependent methanotrophs in freshwater marsh sediments. Water Res. 123, 162–172 (2017). [DOI] [PubMed] [Google Scholar]
36.Wang J., Hua M., Cai C., Hu J., Wang J., Yang H., Ma F., Qian H., Zheng P., Hua B., Spatial-temporal pattern of sulfate-dependent anaerobic methane oxidation in an intertidal zone of the East China Sea. Appl. Environ. Microbiol. 85, e02638-18 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]
37.Chen F., Zheng Y., Hou L., Zhou J., Yin G., Liu M., Denitrifying anaerobic methane oxidation in marsh sediments of Chongming eastern intertidal flat. Mar. Pollut. Bull. 150, 110681 (2020). [DOI] [PubMed] [Google Scholar]
38.Chen F., Zheng Y., Hou L., Niu Y., Gao D., An Z., Zhou J., Yin G., Dong H., Han P., Liang X., Liu M., Microbial abundance and activity of nitrite/nitrate-dependent anaerobic methane oxidizers in estuarine and intertidal wetlands: Heterogeneity and driving factors. Water Res. 190, 116737 (2021). [DOI] [PubMed] [Google Scholar]
39.Zheng Y., Hou L., Chen F., Zhou J., Liu M., Yin G., Gao J., Han P., Denitrifying anaerobic methane oxidation in intertidal marsh soils: Occurrence and environmental significance. Geoderma 357, 113943 (2020). [Google Scholar]
40.Song S., Zhang C., Gao Y., Zhu X., Wang R., Wang M., Zheng Y., Hou L., Liu M., Wu D., Responses of wetland soil bacterial community and edaphic factors to two-year experimental warming and Spartina alterniflora invasion in Chongming Island. J. Clean. Prod. 250, 119502 (2020). [Google Scholar]
41.Liu Y., Liu X., Cheng K., Li L., Zhang X., Zheng J., Zheng J., Pan G., Responses of methanogenic and methanotrophic communities to elevated atmospheric CO₂ and temperature in a paddy field. Front. Microbiol. 7, 1895 (2016). [DOI] [PMC free article] [PubMed] [Google Scholar]
42.Zhu Y., Purdy K. J., Eyice Ö., Shen L., Harpenslager S. F., Yvon-Durocher G., Dumbrell A. J., Trimmer M., Disproportionate increase in freshwater methane emissions induced by experimental warming. Nat. Clim. Change 10, 685–690 (2020). [Google Scholar]
43.Wang Y., Hu Z., Shen L., Liu C., Islam A. R. M. T., Wu Z., Dang H., Chen S., The process of methanogenesis in paddy fields under different elevated CO₂ concentrations. Sci. Total Environ. 773, 145629 (2021). [DOI] [PubMed] [Google Scholar]
44.Ward N. D., Megonigal J. P., Bond-Lamberty B., Bailey V. L., Butman D., Canuel E. A., Diefenderfer H., Ganju N. K., Goñi M. A., Graham E. B., Hopkinson C. S., Khangaonkar T., Langley J. A., McDowell N. G., Myers-Pigg A. N., Neumann R. B., Osburn C. L., Price R. M., Rowland J., Sengupta A., Simard M., Thornton P. E., Tzortziou M., Vargas R., Weisenhorn P. B., Windham-Myers L., Representing the function and sensitivity of coastal interfaces in Earth system models. Nat. Commun. 11, 2458 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
45.Noyce G. L., Kirwan M. L., Rich R. L., Megonigal J. P., Asynchronous nitrogen supply and demand produce nonlinear plant allocation responses to warming and elevated CO₂. Proc. Natl. Acad. Sci. U.S.A. 116, 21623–21628 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]
46.Miley G. A., Kiene R. P., Sulfate reduction and porewater chemistry in a gulf coast Juncus roemerianus (Needlerush) marsh. Estuaries 27, 472–481 (2004). [Google Scholar]
47.Robador A., Brüchert V., Jørgensen B. B., The impact of temperature change on the activity and community composition of sulfate-reducing bacteria in arctic versus temperate marine sediments. Environ. Microbiol. 11, 1692–1703 (2009). [DOI] [PubMed] [Google Scholar]
48.Seidel L., Sachpazidou V., Ketzer M., Hylander S., Forsman A., Dopson M., Long-term warming modulates diversity, vertical structuring of microbial communities, and sulfate reduction in coastal Baltic Sea sediments. Front. Microbiol. 14, 1099445 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
49.Bullock A. L., Sutton-Grier A. E., Megonigal J. P., Anaerobic metabolism in tidal freshwater wetlands: III. Temperature regulation of iron cycling. Estuar. Coast. 36, 482–490 (2013). [Google Scholar]
50.Langley J. A., Mozdzer T. J., Shepard K. A., Hagerty S. B., Megonigal J. P., Tidal marsh plant responses to elevated CO₂, nitrogen fertilization, and sea level rise. Glob. Change Biol. 19, 1495–1503 (2013). [DOI] [PubMed] [Google Scholar]
51.Nie M., Lu M., Bell J., Raut S., Pendall E., Altered root traits due to elevated CO₂: A meta-analysis. Glob. Ecol. Biogeogr. 22, 1095–1105 (2013). [Google Scholar]
52.Connell W. E., Patrick W. H., Sulfate reduction in soil: Effects of redox potential and pH. Science 159, 86–87 (1968). [PubMed] [Google Scholar]
53.J. P. Megonigal, J. R. Holmquist, Dataset: 1999 CO2xCommunity experiment belowground biomass, Smithsonian Environmental Research Center (2021); 10.25573/serc.13073249. [DOI]
54.Beal E. J., House C. H., Orphan V. J., Manganese- and iron-dependent marine methane oxidation. Science 325, 184–187 (2009). [DOI] [PubMed] [Google Scholar]
55.Zhang Y., Zhang X., Wang F., Xia W., Jia Z., Exogenous nitrogen addition inhibits sulfate-mediated anaerobic oxidation of methane in estuarine coastal sediments. Ecol. Eng. 158, 106021 (2020). [Google Scholar]
56.Wang Z., Li J., Xu X., Li K., Chen Q., Denitrifying anaerobic methane oxidation and mechanisms influencing it in Yellow River Delta coastal wetland soil, China. Chemosphere 298, 134345 (2022). [DOI] [PubMed] [Google Scholar]
57.Liu X., Beusen A. H. W., Van Beek L. P. H., Mogollón J. M., Ran X., Bouwman A. F., Exploring spatiotemporal changes of the Yangtze River (Changjiang) nitrogen and phosphorus sources, retention and export to the East China Sea and Yellow Sea. Water Res. 142, 246–255 (2018). [DOI] [PubMed] [Google Scholar]
58.Wang J., Beusen A. H. W., Liu X., Van Dingenen R., Dentener F., Yao Q., Xu B., Ran X., Yu Z., Bouwman A. F., Spatially explicit inventory of sources of nitrogen inputs to the Yellow Sea, East China Sea, and South China Sea for the period 1970–2010. Earth’s Future 8, e2020EF001516 (2020). [Google Scholar]
59.Beusen A. H. W., Doelman J. C., Van Beek L. P. H., Van Puijenbroek P. J. T. M., Mogollón J. M., Van Grinsven H. J. M., Stehfest E., Van Vuuren D. P., Bouwman A. F., Exploring river nitrogen and phosphorus loading and export to global coastal waters in the shared socio-economic pathways. Glob. Environ. Change 72, 102426 (2022). [Google Scholar]
60.Velinsky D. J., Paudel B., Quirk T., Piehler M., Smyth A., Salt marsh denitrification provides a significant nitrogen sink in Barnegat Bay, New Jersey. J. Coast. Res. 78, 70–78 (2017). [Google Scholar]
61.Jordan T. E., Correll D. L., Continuous automated sampling of tidal exchanges of nutrients by brackish marshes. Estuar. Coast. Shelf Sci. 32, 527–545 (1991). [Google Scholar]
62.Thamdrup B., Steinsdóttir H. G. R., Bertagnolli A. D., Padilla C. C., Patin N. V., Garcia-Robledo E., Bristow L. A., Stewart F. J., Anaerobic methane oxidation is an important sink for methane in the ocean’s largest oxygen minimum zone. Limnol. Oceanogr. 64, 2569–2585 (2019). [Google Scholar]
63.Michaelis W., Seifert R., Nauhaus K., Treude T., Thiel V., Blumenberg M., Knittel K., Gieseke A., Peterknecht K., Pape T., Boetius A., Amann R., Jørgensen B. B., Widdel F., Peckmann J., Pimenov N. V., Gulin M. B., Microbial reefs in the black sea fueled by anaerobic oxidation of methane. Science 297, 1013–1015 (2002). [DOI] [PubMed] [Google Scholar]
64.Stams A. J. M., Plugge C. M., Electron transfer in syntrophic communities of anaerobic bacteria and archaea. Nat. Rev. Microbiol. 7, 568–577 (2009). [DOI] [PubMed] [Google Scholar]
65.Muyzer G., Stams A. J. M., The ecology and biotechnology of sulphate-reducing bacteria. Nat. Rev. Microbiol. 6, 441–454 (2008). [DOI] [PubMed] [Google Scholar]
66.Bertram S., Blumenberg M., Michaelis W., Siegert M., Krüger M., Seifert R., Methanogenic capabilities of ANME-archaea deduced from ¹³C-labelling approaches. Environ. Microbiol. 15, 2384–2393 (2013). [DOI] [PubMed] [Google Scholar]
67.Neubauer S. C., Megonigal J. P., Moving beyond global warming potentials to quantify the climatic role of ecosystems. Ecosystems 18, 1000–1013 (2015). [Google Scholar]
68.Waqas M. A., Li Y., Ashraf M. N., Ahmed W., Wang B., Sardar M. F., Ma P., Li R., Wan Y., Kuzyakov Y., Long-term warming and elevated CO₂ increase ammonia-oxidizing microbial communities and accelerate nitrification in paddy soil. Appl. Soil Ecol. 166, 104063 (2021). [Google Scholar]
69.Roden E. E., Wetzel R. G., Organic carbon oxidation and suppression of methane production by microbial Fe(III) oxide reduction in vegetated and unvegetated freshwater wetland sediments. Limnol. Oceanogr. 41, 1733–1748 (1996). [Google Scholar]
70.Weiss J. V., Emerson D., Megonigal J. P., Geochemical control of microbial Fe(III) reduction potential in wetlands: Comparison of the rhizosphere to non-rhizosphere soil. FEMS Microbiol. Ecol. 48, 89–100 (2004). [DOI] [PubMed] [Google Scholar]
71.Rich R. L., Stefanski A., Montgomery R. A., Hobbie S. E., Kimball B. A., Reich P. B., Design and performance of combined infrared canopy and belowground warming in the B4WarmED (Boreal Forest Warming at an Ecotone in Danger) experiment. Glob. Change Biol. 21, 2334–2348 (2015). [DOI] [PubMed] [Google Scholar]
72.Keller J. K., Wolf A. A., Weisenhorn P. B., Drake B. G., Megonigal J. P., Elevated CO₂ affects porewater chemistry in a brackish marsh. Biogeochemistry 96, 101–117 (2009). [Google Scholar]
73.Amrhein V., Greenland S., McShane B., Scientists rise up against statistical significance. Nature 567, 305–307 (2019). [DOI] [PubMed] [Google Scholar]
74.Lloyd K. G., Alperin M. J., Teske A., Environmental evidence for net methane production and oxidation in putative anerobic methanotrophic (ANME) archaea. Environ. Microbiol. 13, 2548–2564 (2011). [DOI] [PubMed] [Google Scholar]
75.Vigneron A., Cruaud P., Pignet P., Caprais J.-C., Cambon-Bonavita M.-A., Godfroy A., Toffin L., Toffin, archaeal and anaerobic methane oxidizer communities in the Sonora Margin cold seeps, Guaymas Basin (Gulf of California). ISME J. 7, 1595–1608 (2013). [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Figs. S1 to S10

Table S1

References

sciadv.ads6093_sm.pdf^{(1.7MB, pdf)}

[R1] 1.Bridgham S. D., Megonigal J. P., Keller J. K., Bliss N. B., Trettin C., The carbon balance of North American wetlands. Wetlands 26, 889–916 (2006). [Google Scholar]

[R2] 2.Paudel R., Mahowald N. M., Hess P. G. M., Watts J. D., Kimball J. S., Poulter B., Bousquet P., Canadell J. G., Ciais P., Peregon A., Arora V. K., Beerling D. J., Brovkin V., Jones C. D., Joos F., Peng C., Peng S., Prigent C., Schroeder R., Riley W. J., Saito M., Global wetland contribution to 2000–2012 atmospheric methane growth rate dynamics. Environ. Res. Lett. 12, 094013 (2017). [Google Scholar]

[R3] 3.Bueno de Mesquita C. P., Hartman W. H., Ardón M., Tringe S. G., Disentangling the effects of sulfate and other seawater ions on microbial communities and greenhouse gas emissions in a coastal forested wetland. ISME Commun. 4, ycae040 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]

[R4] 4.Bueno de Mesquita C. P., Hartman W. H., Ardón M., Bernhardt E. S., Neubauer S. C., Weston N. B., Tringe S. G., Microbial ecology and site characteristics underlie differences in salinity-methane relationships in coastal wetlands. J. Geophys. Res. Biogeosci. 129, e2024JG008133 (2024). [Google Scholar]

[R5] 5.Rosentreter J. A., Maher D. T., Erler D. V., Murray R. H., Eyre B. D., Methane emissions partially offset “blue carbon” burial in mangroves. Sci. Adv. 4, eaao4985 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]

[R6] 6.Oreska M. P. J., McGlathery K. J., Aoki L. R., Berger A. C., Berg P., Mullins L., The greenhouse gas offset potential from seagrass restoration. Sci. Rep. 10, 7325 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]

[R7] 7.Kirwan M. L., Megonigal J. P., Noyce G. L., Smith A. J., Geomorphic and ecological constraints on the coastal carbon sink. Nat. Rev. Earth Environ. 4, 393–406 (2023). [Google Scholar]

[R8] 8.Holmquist J. R., Windham-Myers L., Bernal B., Byrd K. B., Crooks S., Gonneea M. E., Herold N., Knox S. H., Kroeger K. D., McCombs J., Megonigal J. P., Lu M., Morris J. T., Sutton-Grier A. E., Troxler T. G., Weller D. E., Uncertainty in United States coastal wetland greenhouse gas inventorying. Environ. Res. Lett. 13, 115005 (2018). [Google Scholar]

[R9] 9.Al-Haj A. N., Fulweiler R. W., A synthesis of methane emissions from shallow vegetated coastal ecosystems. Glob. Change Biol. 26, 2988–3005 (2020). [DOI] [PubMed] [Google Scholar]

[R10] 10.Schuerch M., Spencer T., Temmerman S., Kirwan M. L., Wolff C., Lincke D., McOwen C. J., Pickering M. D., Reef R., Vafeidis A. T., Hinkel J., Nicholls R. J., Brown S., Future response of global coastal wetlands to sea-level rise. Nature 561, 231–234 (2018). [DOI] [PubMed] [Google Scholar]

[R11] 11.Macreadie P. I., Anton A., Raven J. A., Beaumont N., Connolly R. M., Friess D. A., Kelleway J. J., Kennedy H., Kuwae T., Lavery P. S., Lovelock C. E., Smale D. A., Apostolaki E. T., Atwood T. B., Baldock J., Bianchi T. S., Chmura G. L., Eyre B. D., Fourqurean J. W., Hall-Spencer J. M., Huxham M., Hendriks I. E., Krause-Jensen D., Laffoley D., Luisetti T., Marbà N., Masque P., McGlathery K. J., Megonigal J. P., Murdiyarso D., Russell B. D., Santos R., Serrano O., Silliman B. R., Watanabe K., Duarte C. M., The future of blue carbon science. Nat. Commun. 10, 3998 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]

[R12] 12.Saintilan N., Horton B., Törnqvist T. E., Ashe E. L., Khan N. S., Schuerch M., Perry C., Kopp R. E., Garner G. G., Murray N., Rogers K., Albert S., Kelleway J., Shaw T. A., Woodroffe C. D., Lovelock C. E., Goddard M. M., Hutley L. B., Kovalenko K., Feher L., Guntenspergen G., Widespread retreat of coastal habitat is likely at warming levels above 1.5°C. Nature 621, 112–119 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]

[R13] 13.Langley J. A., McKee K. L., Cahoon D. R., Cherry J. A., Megonigal J. P., Elevated CO₂ stimulates marsh elevation gain, counterbalancing sea-level rise. Proc. Natl. Acad. Sci. U.S.A. 106, 6182–6186 (2009). [DOI] [PMC free article] [PubMed] [Google Scholar]

[R14] 14.Mueller P., Mozdzer T. J., Langley J. A., Aoki L. R., Noyce G. L., Megonigal J. P., Plant species determine tidal wetland methane response to sea level rise. Nat. Commun. 11, 5154 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]

[R15] 15.Noyce G. L., Megonigal J. P., Biogeochemical and plant trait mechanisms drive enhanced methane emissions in response to whole-ecosystem warming. Biogeosciences 18, 2449–2463 (2021). [Google Scholar]

[R16] 16.Noyce G. L., Smith A. J., Kirwan M. L., Rich R. L., Megonigal J. P., Oxygen priming induced by elevated CO₂ reduces carbon accumulation and methane emissions in coastal wetlands. Nat. Geosci. 16, 63–68 (2023). [Google Scholar]

[R17] 17.Serrano-Silva N., Sarria-Guzmán Y., Dendooven L., Luna-Guido M., Methanogenesis and methanotrophy in soil: A review. Pedosphere 24, 291–307 (2014). [Google Scholar]

[R18] 18.Le Mer J., Roger P., Production, oxidation, emission and consumption of methane by soils: A review. Eur. J. Soil Biol. 37, 25–50 (2001). [Google Scholar]

[R19] 19.Megonigal J. P., Schlesinger W. H., Methane-limited methanotrophy in tidal freshwater swamps. Global Biogeochem. Cycles 16, 35-1–35-10 (2002). [Google Scholar]

[R20] 20.Guerrero-Cruz S., Vaksmaa A., Horn M. A., Niemann H., Pijuan M., Ho A., Methanotrophs: Discoveries, environmental relevance, and a perspective on current and future applications. Front. Microbiol. 12, 678057 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]

[R21] 21.Gao Y., Wang Y., Lee H.-S., Jin P., Significance of anaerobic oxidation of methane (AOM) in mitigating methane emission from major natural and anthropogenic sources: A review of AOM rates in recent publications. Environ. Sci. Adv. 1, 401–425 (2022). [Google Scholar]

[R22] 22.Knittel K., Boetius A., Anaerobic oxidation of methane: Progress with an unknown process. Annu. Rev. Microbiol. 63, 311–334 (2009). [DOI] [PubMed] [Google Scholar]

[R23] 23.Meulepas R. J. W., Jagersma C. G., Gieteling J., Buisman C. J. N., Stams A. J. M., Lens P. N. L., Enrichment of anaerobic methanotrophs in sulfate-reducing membrane bioreactors. Biotechnol. Bioeng. 104, 458–470 (2009). [DOI] [PubMed] [Google Scholar]

[R24] 24.La W., Han X., Liu C.-Q., Ding H., Liu M., Sun F., Li S., Lang Y., Sulfate concentrations affect sulfate reduction pathways and methane consumption in coastal wetlands. Water Res. 217, 118441 (2022). [DOI] [PubMed] [Google Scholar]

[R25] 25.Mostovaya A., Wind-Hansen M., Rousteau P., Bristow L. A., Thamdrup B., Sulfate- and iron-dependent anaerobic methane oxidation occurring side-by-side in freshwater lake sediment. Limnol. Oceanogr. 67, 231–246 (2022). [Google Scholar]

[R26] 26.Ettwig K. F., Butler M. K., Le Paslier D., Pelletier E., Mangenot S., Kuypers M. M. M., Schreiber F., Dutilh B. E., Zedelius J., De Beer D., Gloerich J., Wessels H. J. C. T., Van Alen T., Luesken F., Wu M. L., Van De Pas-Schoonen K. T., Op Den Camp H. J. M., Janssen-Megens E. M., Francoijs K. J., Stunnenberg H., Weissenbach J., Jetten M. S. M., Strous M., Nitrite-driven anaerobic methane oxidation by oxygenic bacteria. Nature 464, 543–548 (2010). [DOI] [PubMed] [Google Scholar]

[R27] 27.Raghoebarsing A. A., Pol A., Van De Pas-Schoonen K. T., Smolders A. J. P., Ettwig K. F., Rijpstra W. I. C., Schouten S., Sinninghe Damsté J. S., Op Den Camp H. J. M., Jetten M. S. M., Strous M., A microbial consortium couples anaerobic methane oxidation to denitrification. Nature 440, 918–921 (2006). [DOI] [PubMed] [Google Scholar]

[R28] 28.Hu B. L., Shen L. D., Lian X., Zhu Q., Liu S., Huang Q., He Z. F., Geng S., Cheng D. Q., Lou L. P., Xu X. Y., Zheng P., He Y. F., Evidence for nitrite-dependent anaerobic methane oxidation as a previously overlooked microbial methane sink in wetlands. Proc. Natl. Acad. Sci. U.S.A. 111, 4495–4500 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]

[R29] 29.Wang J., Cai C., Li Y., Hua M., Wang J., Yang H., Zheng P., Hu B., Denitrifying anaerobic methane oxidation: A previously overlooked methane sink in intertidal zone. Environ. Sci. Technol. 53, 203–212 (2019). [DOI] [PubMed] [Google Scholar]

[R30] 30.Rios-Del Toro E. E., Valenzuela E. I., López-Lozano N. E., Cortés-Martínez M. G., Sánchez-Rodríguez M. A., Calvario-Martínez O., Sánchez-Carrillo S., Cervantes F. J., Anaerobic ammonium oxidation linked to sulfate and ferric iron reduction fuels nitrogen loss in marine sediments. Biodegradation 29, 429–442 (2018). [DOI] [PubMed] [Google Scholar]

[R31] 31.Haroon M. F., Hu S., Shi Y., Imelfort M., Keller J., Hugenholtz P., Yuan Z., Tyson G. W., Anaerobic oxidation of methane coupled to nitrate reduction in a novel archaeal lineage. Nature 500, 567–570 (2013). [DOI] [PubMed] [Google Scholar]

[R32] 32.Segarra K. E. A., Comerford C., Slaughter J., Joye S. B., Impact of electron acceptor availability on the anaerobic oxidation of methane in coastal freshwater and brackish wetland sediments. Geochim. Cosmochim. Acta 115, 15–30 (2013). [Google Scholar]

[R33] 33.Ettwig K. F., Shima S., van de Pas-Schoonen K. T., Kahnt J., Medema M. H., Op den Camp H. J. M., Jetten M. S. M., Strous M., Denitrifying bacteria anaerobically oxidize methane in the absence of archaea. Environ. Microbiol. 10, 3164–3173 (2008). [DOI] [PubMed] [Google Scholar]

[R34] 34.Ettwig K. F., van Alen T., van de Pas-Schoonen K. T., Jetten M. S. M., Strous M., Enrichment and molecular detection of denitrifying methanotrophic bacteria of the NC10 phylum. Appl. Environ. Microbiol. 75, 3656–3662 (2009). [DOI] [PMC free article] [PubMed] [Google Scholar]

[R35] 35.Shen L., Wu H., Liu X., Li J., Cooccurrence and potential role of nitrite- and nitrate-dependent methanotrophs in freshwater marsh sediments. Water Res. 123, 162–172 (2017). [DOI] [PubMed] [Google Scholar]

[R36] 36.Wang J., Hua M., Cai C., Hu J., Wang J., Yang H., Ma F., Qian H., Zheng P., Hua B., Spatial-temporal pattern of sulfate-dependent anaerobic methane oxidation in an intertidal zone of the East China Sea. Appl. Environ. Microbiol. 85, e02638-18 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]

[R37] 37.Chen F., Zheng Y., Hou L., Zhou J., Yin G., Liu M., Denitrifying anaerobic methane oxidation in marsh sediments of Chongming eastern intertidal flat. Mar. Pollut. Bull. 150, 110681 (2020). [DOI] [PubMed] [Google Scholar]

[R38] 38.Chen F., Zheng Y., Hou L., Niu Y., Gao D., An Z., Zhou J., Yin G., Dong H., Han P., Liang X., Liu M., Microbial abundance and activity of nitrite/nitrate-dependent anaerobic methane oxidizers in estuarine and intertidal wetlands: Heterogeneity and driving factors. Water Res. 190, 116737 (2021). [DOI] [PubMed] [Google Scholar]

[R39] 39.Zheng Y., Hou L., Chen F., Zhou J., Liu M., Yin G., Gao J., Han P., Denitrifying anaerobic methane oxidation in intertidal marsh soils: Occurrence and environmental significance. Geoderma 357, 113943 (2020). [Google Scholar]

[R40] 40.Song S., Zhang C., Gao Y., Zhu X., Wang R., Wang M., Zheng Y., Hou L., Liu M., Wu D., Responses of wetland soil bacterial community and edaphic factors to two-year experimental warming and Spartina alterniflora invasion in Chongming Island. J. Clean. Prod. 250, 119502 (2020). [Google Scholar]

[R41] 41.Liu Y., Liu X., Cheng K., Li L., Zhang X., Zheng J., Zheng J., Pan G., Responses of methanogenic and methanotrophic communities to elevated atmospheric CO₂ and temperature in a paddy field. Front. Microbiol. 7, 1895 (2016). [DOI] [PMC free article] [PubMed] [Google Scholar]

[R42] 42.Zhu Y., Purdy K. J., Eyice Ö., Shen L., Harpenslager S. F., Yvon-Durocher G., Dumbrell A. J., Trimmer M., Disproportionate increase in freshwater methane emissions induced by experimental warming. Nat. Clim. Change 10, 685–690 (2020). [Google Scholar]

[R43] 43.Wang Y., Hu Z., Shen L., Liu C., Islam A. R. M. T., Wu Z., Dang H., Chen S., The process of methanogenesis in paddy fields under different elevated CO₂ concentrations. Sci. Total Environ. 773, 145629 (2021). [DOI] [PubMed] [Google Scholar]

[R44] 44.Ward N. D., Megonigal J. P., Bond-Lamberty B., Bailey V. L., Butman D., Canuel E. A., Diefenderfer H., Ganju N. K., Goñi M. A., Graham E. B., Hopkinson C. S., Khangaonkar T., Langley J. A., McDowell N. G., Myers-Pigg A. N., Neumann R. B., Osburn C. L., Price R. M., Rowland J., Sengupta A., Simard M., Thornton P. E., Tzortziou M., Vargas R., Weisenhorn P. B., Windham-Myers L., Representing the function and sensitivity of coastal interfaces in Earth system models. Nat. Commun. 11, 2458 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]

[R45] 45.Noyce G. L., Kirwan M. L., Rich R. L., Megonigal J. P., Asynchronous nitrogen supply and demand produce nonlinear plant allocation responses to warming and elevated CO₂. Proc. Natl. Acad. Sci. U.S.A. 116, 21623–21628 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]

[R46] 46.Miley G. A., Kiene R. P., Sulfate reduction and porewater chemistry in a gulf coast Juncus roemerianus (Needlerush) marsh. Estuaries 27, 472–481 (2004). [Google Scholar]

[R47] 47.Robador A., Brüchert V., Jørgensen B. B., The impact of temperature change on the activity and community composition of sulfate-reducing bacteria in arctic versus temperate marine sediments. Environ. Microbiol. 11, 1692–1703 (2009). [DOI] [PubMed] [Google Scholar]

[R48] 48.Seidel L., Sachpazidou V., Ketzer M., Hylander S., Forsman A., Dopson M., Long-term warming modulates diversity, vertical structuring of microbial communities, and sulfate reduction in coastal Baltic Sea sediments. Front. Microbiol. 14, 1099445 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]

[R49] 49.Bullock A. L., Sutton-Grier A. E., Megonigal J. P., Anaerobic metabolism in tidal freshwater wetlands: III. Temperature regulation of iron cycling. Estuar. Coast. 36, 482–490 (2013). [Google Scholar]

[R50] 50.Langley J. A., Mozdzer T. J., Shepard K. A., Hagerty S. B., Megonigal J. P., Tidal marsh plant responses to elevated CO₂, nitrogen fertilization, and sea level rise. Glob. Change Biol. 19, 1495–1503 (2013). [DOI] [PubMed] [Google Scholar]

[R51] 51.Nie M., Lu M., Bell J., Raut S., Pendall E., Altered root traits due to elevated CO₂: A meta-analysis. Glob. Ecol. Biogeogr. 22, 1095–1105 (2013). [Google Scholar]

[R52] 52.Connell W. E., Patrick W. H., Sulfate reduction in soil: Effects of redox potential and pH. Science 159, 86–87 (1968). [PubMed] [Google Scholar]

[R53] 53.J. P. Megonigal, J. R. Holmquist, Dataset: 1999 CO2xCommunity experiment belowground biomass, Smithsonian Environmental Research Center (2021); 10.25573/serc.13073249. [DOI]

[R54] 54.Beal E. J., House C. H., Orphan V. J., Manganese- and iron-dependent marine methane oxidation. Science 325, 184–187 (2009). [DOI] [PubMed] [Google Scholar]

[R55] 55.Zhang Y., Zhang X., Wang F., Xia W., Jia Z., Exogenous nitrogen addition inhibits sulfate-mediated anaerobic oxidation of methane in estuarine coastal sediments. Ecol. Eng. 158, 106021 (2020). [Google Scholar]

[R56] 56.Wang Z., Li J., Xu X., Li K., Chen Q., Denitrifying anaerobic methane oxidation and mechanisms influencing it in Yellow River Delta coastal wetland soil, China. Chemosphere 298, 134345 (2022). [DOI] [PubMed] [Google Scholar]

[R57] 57.Liu X., Beusen A. H. W., Van Beek L. P. H., Mogollón J. M., Ran X., Bouwman A. F., Exploring spatiotemporal changes of the Yangtze River (Changjiang) nitrogen and phosphorus sources, retention and export to the East China Sea and Yellow Sea. Water Res. 142, 246–255 (2018). [DOI] [PubMed] [Google Scholar]

[R58] 58.Wang J., Beusen A. H. W., Liu X., Van Dingenen R., Dentener F., Yao Q., Xu B., Ran X., Yu Z., Bouwman A. F., Spatially explicit inventory of sources of nitrogen inputs to the Yellow Sea, East China Sea, and South China Sea for the period 1970–2010. Earth’s Future 8, e2020EF001516 (2020). [Google Scholar]

[R59] 59.Beusen A. H. W., Doelman J. C., Van Beek L. P. H., Van Puijenbroek P. J. T. M., Mogollón J. M., Van Grinsven H. J. M., Stehfest E., Van Vuuren D. P., Bouwman A. F., Exploring river nitrogen and phosphorus loading and export to global coastal waters in the shared socio-economic pathways. Glob. Environ. Change 72, 102426 (2022). [Google Scholar]

[R60] 60.Velinsky D. J., Paudel B., Quirk T., Piehler M., Smyth A., Salt marsh denitrification provides a significant nitrogen sink in Barnegat Bay, New Jersey. J. Coast. Res. 78, 70–78 (2017). [Google Scholar]

[R61] 61.Jordan T. E., Correll D. L., Continuous automated sampling of tidal exchanges of nutrients by brackish marshes. Estuar. Coast. Shelf Sci. 32, 527–545 (1991). [Google Scholar]

[R62] 62.Thamdrup B., Steinsdóttir H. G. R., Bertagnolli A. D., Padilla C. C., Patin N. V., Garcia-Robledo E., Bristow L. A., Stewart F. J., Anaerobic methane oxidation is an important sink for methane in the ocean’s largest oxygen minimum zone. Limnol. Oceanogr. 64, 2569–2585 (2019). [Google Scholar]

[R63] 63.Michaelis W., Seifert R., Nauhaus K., Treude T., Thiel V., Blumenberg M., Knittel K., Gieseke A., Peterknecht K., Pape T., Boetius A., Amann R., Jørgensen B. B., Widdel F., Peckmann J., Pimenov N. V., Gulin M. B., Microbial reefs in the black sea fueled by anaerobic oxidation of methane. Science 297, 1013–1015 (2002). [DOI] [PubMed] [Google Scholar]

[R64] 64.Stams A. J. M., Plugge C. M., Electron transfer in syntrophic communities of anaerobic bacteria and archaea. Nat. Rev. Microbiol. 7, 568–577 (2009). [DOI] [PubMed] [Google Scholar]

[R65] 65.Muyzer G., Stams A. J. M., The ecology and biotechnology of sulphate-reducing bacteria. Nat. Rev. Microbiol. 6, 441–454 (2008). [DOI] [PubMed] [Google Scholar]

[R66] 66.Bertram S., Blumenberg M., Michaelis W., Siegert M., Krüger M., Seifert R., Methanogenic capabilities of ANME-archaea deduced from ¹³C-labelling approaches. Environ. Microbiol. 15, 2384–2393 (2013). [DOI] [PubMed] [Google Scholar]

[R67] 67.Neubauer S. C., Megonigal J. P., Moving beyond global warming potentials to quantify the climatic role of ecosystems. Ecosystems 18, 1000–1013 (2015). [Google Scholar]

[R68] 68.Waqas M. A., Li Y., Ashraf M. N., Ahmed W., Wang B., Sardar M. F., Ma P., Li R., Wan Y., Kuzyakov Y., Long-term warming and elevated CO₂ increase ammonia-oxidizing microbial communities and accelerate nitrification in paddy soil. Appl. Soil Ecol. 166, 104063 (2021). [Google Scholar]

[R69] 69.Roden E. E., Wetzel R. G., Organic carbon oxidation and suppression of methane production by microbial Fe(III) oxide reduction in vegetated and unvegetated freshwater wetland sediments. Limnol. Oceanogr. 41, 1733–1748 (1996). [Google Scholar]

[R70] 70.Weiss J. V., Emerson D., Megonigal J. P., Geochemical control of microbial Fe(III) reduction potential in wetlands: Comparison of the rhizosphere to non-rhizosphere soil. FEMS Microbiol. Ecol. 48, 89–100 (2004). [DOI] [PubMed] [Google Scholar]

[R71] 71.Rich R. L., Stefanski A., Montgomery R. A., Hobbie S. E., Kimball B. A., Reich P. B., Design and performance of combined infrared canopy and belowground warming in the B4WarmED (Boreal Forest Warming at an Ecotone in Danger) experiment. Glob. Change Biol. 21, 2334–2348 (2015). [DOI] [PubMed] [Google Scholar]

[R72] 72.Keller J. K., Wolf A. A., Weisenhorn P. B., Drake B. G., Megonigal J. P., Elevated CO₂ affects porewater chemistry in a brackish marsh. Biogeochemistry 96, 101–117 (2009). [Google Scholar]

[R73] 73.Amrhein V., Greenland S., McShane B., Scientists rise up against statistical significance. Nature 567, 305–307 (2019). [DOI] [PubMed] [Google Scholar]

[R74] 74.Lloyd K. G., Alperin M. J., Teske A., Environmental evidence for net methane production and oxidation in putative anerobic methanotrophic (ANME) archaea. Environ. Microbiol. 13, 2548–2564 (2011). [DOI] [PubMed] [Google Scholar]

[R75] 75.Vigneron A., Cruaud P., Pignet P., Caprais J.-C., Cambon-Bonavita M.-A., Godfroy A., Toffin L., Toffin, archaeal and anaerobic methane oxidizer communities in the Sonora Margin cold seeps, Guaymas Basin (Gulf of California). ISME J. 7, 1595–1608 (2013). [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

Climate-induced shifts in sulfate dynamics regulate anaerobic methane oxidation in a coastal wetland

Jaehyun Lee

Yerang Yang

Hojeong Kang

Genevieve L Noyce

J Patrick Megonigal

Roles

Abstract

INTRODUCTION

RESULTS

Effect of climate change on SO₄²⁻ concentration, redox potential, and fine-root productivity

Fig. 1. Porewater SO₄²⁻ concentration in ambient and warmed plots with and without eCO₂ across the different depths.

Fig. 2. Porewater redox potential and fine-root productivity in ambient and warmed plots with and without eCO₂ in the C₃ community.