Climate warming perturbs ecosystem carbon (C) cycling, causing both positive
and negative feedbacks on greenhouse gas emissions. In 2016, we began a
tidal marsh field experiment in two vegetation communities to investigate
the mechanisms by which whole-ecosystem warming alters C gain, via
plant-driven sequestration in soils, and C loss, primarily via methane
(CH4) emissions. Here, we report the results from the first 4 years.
As expected, warming of 5.1 ∘C more than doubled CH4
emissions in both plant communities. We propose this was caused by a
combination of four mechanisms: (i) a decrease in the proportion of CH4
consumed by CH4 oxidation, (ii) more C substrates available for
methanogenesis, (iii) reduced competition between methanogens and sulfate-reducing bacteria, and (iv) indirect effects of plant traits. Plots
dominated by Spartina patens consistently emitted more CH4 than plots dominated by
Schoenoplectus americanus, indicating key differences in the roles these common wetland plants play
in affecting anaerobic soil biogeochemistry and suggesting that plant
composition can modulate coastal wetland responses to climate change.
Introduction
Methane (CH4) is a potent greenhouse gas that contributes to 15 %–19 %
of total greenhouse gas radiative forcing (IPCC, 2013) and has a
sustained-flux global warming potential that is 45 times that of CO2 on
a 100-year timescale (Neubauer and Megonigal, 2015). Wetlands are the
largest natural source of CH4 to the atmosphere and were recently
identified as the largest source of uncertainty in the global CH4
budget (Saunois et al., 2016). Recent estimates calculate that CH4
emissions from vegetated coastal wetlands offset 3.6 of the 12.2 million
metric tons (MMT) of CO2 equivalents accumulated by these ecosystems
each year (EPA, 2017). Despite this, there is still a substantial knowledge
gap regarding how global change factors, such as climate warming, will alter
coastal wetland CH4 emissions (Mcleod et al., 2011) even though these
feedbacks have the potential to shift coastal wetlands from being a net sink
of C to a net source (Al-Haj and Fulweiler, 2020; Bridgham et al., 2006).
The net flux of CH4 to the atmosphere from any ecosystem represents the
balance between the amount of CH4 produced (methanogenesis), the
amount of CH4 oxidized (methanotrophy), and the rate of CH4
transport from the soil. In coastal wetlands, methanogenesis occurs through
three pathways: (i) hydrogenotrophic methanogenesis (i.e., CO2
reduction) in which H2 is the electron donor and CO2 is the
electron acceptor; (ii) acetoclastic methanogenesis, in which acetate
(CH4COOH) is split into CH4 and CO2; and (iii) methylotrophic
methanogenesis in which methylated compounds are converted to CH4 and
CO2 (Conrad, 2020; Oremland et al., 1982; Schlesinger and Bernhardt,
2020). Rates of methanogenesis are driven by low-redox conditions and
substrate availability, while aerobic CH4 oxidation requires both
O2 and CH4 as substrates. Roots and rhizomes in wetland ecosystems
influence methane-related substrates through at least two mechanisms: (i) deposition of organic compounds that support multiple pathways of
heterotrophic microbial respiration, including methanogenesis, and (ii) release of O2 that simultaneously promotes CH4 oxidation and
regeneration of competing electron acceptors such as Fe(III) and SO4
(Philippot et al., 2009; Stanley and Ward, 2010). Root exudates, which
typically include low-molecular-weight compounds, may either be more readily
used by microbes than existing soil C (Kayranli et al., 2010; Megonigal et
al., 1999) or prime microbial use of soil C (Basiliko et al., 2012;
Philippot et al., 2009; Robroek et al., 2016; Waldo et al., 2019). Root
exudates can also decrease CH4 oxidation by stimulating use of O2
by other aerobic microbes (Lenzewski et al., 2018; Mueller et al., 2016).
Consequently, wetland CH4 emissions are strongly linked to a wide
variety of plant traits that govern the supply of reductive (organic carbon)
and oxidative (O2) substrates to soils (Moor et al., 2017; Mueller et
al., 2020).
Although it is understood that wetland plants are a primary control on
CH4 emissions and that much of their influence is mediated through
conditions in the rhizosphere (Waldo et al., 2019), there are surprisingly
few data, especially from coastal wetlands, that couple plant responses to
the dynamics of electron donors (organic C), electron acceptors (O2,
SO4), and the rates of competing (sulfate reduction vs. methanogenesis)
or opposing (CH4 production vs. CH4 oxidation) microbial processes.
The general lack of process data on wetland CH4 cycling makes it
difficult to forecast ecosystem responses to climate change. For example,
the well-documented observation that warming increases wetland methane
emissions can be either amplified or dampened depending on changes in plant
activity (e.g., primary production) or plant traits (e.g., community
composition) (Mueller et al., 2020). Vegetation composition has been shown
to be a stronger control on CH4 emissions than ∼ 1 ∘C of warming in northern peatlands (Ward et al., 2013), and Chen
et al. (2017) proposed that warming effects on plant functional types can
drive C flux responses that cannot otherwise be explained by abiotic
conditions. In freshwater marshes, plant species and growth trends have also
been linked to seasonal shifts in pools of dissolved CH4 and dissolved inorganic carbon (DIC; Ding
et al., 2005; Stanley and Ward, 2010) and methanogenesis dynamics (Sorrell
et al., 1997).
Tidal wetlands are particularly good model systems for determining the
mechanisms by which warming alters CH4 emissions. Not only will the
CH4 cycle respond to the direct effects of warming, but the
temperature effects on the outcome of competition for electron acceptors are
relatively easily observed because of the abundance of SO4.
Thermodynamic theory in which terminal electron acceptors (TEAs) are used in
order of decreasing thermodynamic yield is commonly interpreted to mean that
a system will support only one form of anaerobic respiration at a time, with
acetoclastic and hydrogenotrophic methanogenesis occurring only when pools
of more energetically favorable TEAs have been depleted (Conrad, 2020;
Schlesinger and Bernhardt, 2020). However, in real systems with spatial and
temporal variability in the supply of electron donor substrates and TEAs,
all forms of anaerobic metabolism occur simultaneously (Megonigal et al.,
2004; Bridgham et al., 2013). Much of this spatial and temporal variation
arises from the distribution and activity of roots and rhizomes as mediated
by the rhizosphere (Neubauer et al., 2008). Global change factors such as
warming will further affect the spatial distribution of key metabolic
substrates. In addition, the relatively limited species diversity in saline
tidal wetlands allows species-level effects on CH4 cycling to be
delineated more easily than in diverse freshwater wetlands.
Methane flux measurements are a metric of broader shifts in redox potential
and biogeochemical cycling, as they are sensitive to virtually all processes
that regulate availability of electron donors and electron acceptors.
Emissions are commonly predicted to increase with future climate warming,
including from coastal wetlands (Al-Haj and Fulweiler, 2020), but there is
minimal prior understanding of the underlying mechanisms, which was the
focus of this study. Our objectives were to explore the mechanisms that
drive enhanced CH4 emissions under warming. To accomplish this, we
measured monthly CH4 emissions from 2016 through 2019 and coupled these
flux measurements with analysis of porewater biogeochemistry and vegetation
biomass and composition.
Materials and methodsSite description and experimental design
The Salt Marsh Accretion Response to Temperature eXperiment (SMARTX) was
established in the Smithsonian's Global Change Research Wetland (GCReW) in
2016. GCReW is part of Kirkpatrick Marsh, a microtidal, brackish high marsh
on the western shore of the Chesapeake Bay, USA (38∘53′ N,
76∘33′ W). Soils are organic (> 80 % organic
matter) to a depth of 5 m, which is typical of high marshes in the
Chesapeake Bay and elsewhere. The very low mineral content (< 20 %) affects methane dynamics because negligible competition between
methanogens and iron-reducing bacteria for electron donors is expected in
the absence of a significant pool of poorly crystalline iron oxides (Roden
and Wetzel, 1996), as has been documented previously at this site (Weiss et
al., 2004). Soil bulk density in the upper 60 cm averages 0.124 g cm3
and ranges from 0.079 to 0.180 g cm3. The relatively uniform bulk
density of the soil profile reflects the uniform soil organic matter content
and the fact that bulk density becomes largely independent of organic matter
and mineral content once organic matter content exceeds 50 % (Holmquist et
al., 2018). The marsh is typically saturated to within 5–15 cm of the soil
surface, but inundation frequency varies across the site, from 10 %–20 % of
high tides in high-elevation areas to 30 %–60 % of high tides in low-elevation areas.
SMARTX consists of six replicate transects, three located in each of the two
dominant annual plant communities (Fig. S1). In the C3-dominated
community (herein the “C3 community”) the C3 sedge Schoenoplectus americanus (herein
Schoenoplectus) composes more than 90 % of the aboveground biomass (Table 1). In the
C4-dominated community (herein the “C4 community”), 75 % of the
aboveground biomass was initially composed of two C4 grasses (Spartina patens and
Distichlis spicata, herein Spartina and Distichlis, respectively). However, by 2019, Spartina and Distichlis declined to 56 % of
the aboveground biomass (Table 1).
Relative contribution to total aboveground biomass from C3
sedges (Schoenoplectus americanus) and C4 grasses (Spartina patens and Distichlis spicata) in each plant community. Values are
means and SE (n= 12).
Each transect is an active warming gradient consisting of unheated ambient
plots and plots that are heated to 1.7, 3.4, and
5.1 ∘C above ambient. All plots are 2 m× 2 m with a 20 cm-wide buffer around the perimeter. Aboveground plant-surface temperature
is elevated via infrared heaters, and soil temperature is elevated via
vertical resistance cables (Rich et al., 2015). Soils are heated to a depth
of 1.5 m, which is the depth most vulnerable to climate or human disturbance
(Pendleton et al., 2012). Aboveground and belowground temperature variation
are assessed via thermocouples embedded in acrylic plates at plant canopy
level and inserted into the soil, respectively, and the temperature gradient
is maintained by integrated microprocessor-based feedback control (Rich et
al., 2015). Noyce et al. (2019) provide additional details of the heating
system. Warming began on 1 June 2016 and has continued year-round.
Methane flux measurements
Methane emissions were measured monthly year-round from May 2016 to December 2019
using a static chamber system. One permanent 160 cm2 aluminum base was
inserted 10 cm into the soil in each plot in April 2016. On each measurement
date, clear chambers (40 cm × 40 cm × 40 cm) were gently placed on top of each
base and secured with compression clips. Chambers consisted of an aluminum
frame with transparent sides made of polychlorotrifluoroethylene film
(Honeywell International) and closed-cell foam on the base. Depending on the
height of the vegetation at the time of measurement, chambers were stacked
up to four high (total height of 40–160 cm) (Fig. S2). The advantage of
this stacking method is that it uses the minimal chamber volume necessary,
while also allowing for plant growth. After placement, the chambers were
left open for at least 10 min, to minimize disturbance effects and allow
air inside the chamber to return to ambient conditions. During data
collection, chambers were covered with a transparent polycarbonate top
equipped with sampling tubes, a fan to circulate air inside the chambers, a
PAR sensor, and thermocouples. The sealed chamber was covered with a foil
shroud to block out all light and to minimize changes in temperature and
relative humidity during the measurement period. An Ultraportable Greenhouse
Gas Analyzer (Los Gatos Research, CA) was used to measure headspace CH4
concentrations for 5 min. Plots were accessed from permanent boardwalks
elevated 15 cm above the soil surface to avoid compressing the surrounding
peat and altering diffusive CH4 emissions. Fluxes were calculated as
the slope of the linear regression of CH4 concentration over time. The
40 fluxes where p> 0.05 were assigned a value of one-half the
limit of detection of the system (Wassmann et al., 2018; Table S1). This was
1 % of fluxes during the growing season and 4.5 % of fluxes over the
remaining months. For 2017–2019, monthly measurements were scaled to annual
estimates by regressing CH4 emissions against daily mean soil
temperature and day of year (as a proxy for phenological status). Annual
estimates were not calculated for 2016 because flux measurements did not
start until May.
Porewater sampling and analysis
Porewater samples were collected in May, July, and September of each year using
stainless-steel “sippers” permanently installed in each plot. Each sipper
consisted of a length of stainless-steel tubing, crimped and sealed at the
end, with several slits (approximate width 0.8 mm) cut in the bottom 2 cm.
The aboveground portion of each sipper was connected to Tygon
Masterflex® tubing capped with a two-way stopcock. In May 2016,
duplicate clusters of sippers were installed in each of the 30 plots at 20,
40, 80, and 120 cm below the soil surface. An additional set of 10 cm deep
sippers was installed in 2017. In this study we defined samples from 10–20 cm as “rooting zone” samples and samples from 40–120 cm as “deep peat”
samples. On sampling dates, porewater sitting in the sippers was drawn up
and discarded, after which 60 mL of porewater from each depth (30 mL from
each sipper) was withdrawn and stored in syringes equipped with three-way
stopcocks. A 10 mL aliquot of each sample was filtered through a pre-leached
0.45 µm syringe-mounted filter, preserved with 5 % zinc acetate
and sodium hydroxide, and frozen for future SO4 and Cl analysis.
Dissolved CH4 was extracted from 15 mL of porewater in the syringe by
drawing 15 mL of ambient air and shaking vigorously for 2 min to allow the
dissolved CH4 to equilibrate with the headspace. Headspace subsamples
were then immediately analyzed on a Shimadzu GC-14A gas chromatograph
equipped with a flame ionization detector. A total of 3 mL of porewater was used to
measure pH using a Fisher Scientific accumet electrode (13-620-290). The
remaining porewater was used to measure H2S and NH4; those data
are not reported here.
SO4 and Cl were measured on a Dionex ICS-2000 ion chromatography system
(2016–2018) or a Dionex Integrion (2019). On the Dionex ICS-2000 samples
were separated using an A11 column with 30 mM of KOH as eluent; on the
Dionex Integrion samples were separated using an A11 4 µm fast column
with 35 mM KOH. Sulfate depletion (SulfateDep) was calculated based on
measured porewater concentrations of SO4 (SO4pw) and Cl
(Clpw) and the constant molar ratio of Cl to SO4 in surface
seawater (Rsw=19.33; Bianchi, 2006) using the following equation:
SulfateDep= Clpw/Rsw- SO4pw. If driven
only by seawater inputs, the ratio of Cl to SO4 would remain constant,
but under anaerobic conditions SO4 can be reduced by sulfate-reducing
bacteria, altering this ratio. As a result, SO4 depletion can be used
as a proxy for SO4 reduction rates.
Plant biomass measurements
Measurements of Schoenoplectus, Spartina, and Distichlis biomass were conducted during peak biomass of each
year (29 July–2 August) as described by Noyce et al. (2019). Schoenoplectus biomass was
estimated using non-destructive allometric techniques (Lu et al., 2016) in
900 cm2 quadrats, and Spartina and Distichlis biomass were estimated through destructive
harvest of 25 cm2 subplots.
Data analysis
Statistics were conducted in R (version 3.6.3). Methane flux (Fig. S3) and
porewater data were log transformed to become normally distributed prior to
statistical analyses. The “growing season” was defined as May through September
based on Schoenoplectus growth trends (Fig. S4). Pearson's correlations were used to test
the relationships between CH4 flux and soil temperature as well as CH4
flux and plant biomass. Responses of CH4 emissions to vegetation type
and warming treatment were analyzed using linear mixed models with
vegetation community and warming treatment as categorical variables and
plot and year as random effects. P values were calculated using
Satterthwaite's method, and Tukey's post hoc tests were used to compare
individual means. Porewater data were averaged per year and then analyzed
using one-way ANOVAs to determine the effects of warming treatment or plant
community, applying Tukey's HSD test for post hoc analyses.
ResultsEnvironmental conditions, site characteristics, and experiment
performance
The growing season of 2016 was the hottest of the 4 years, with growing
season temperatures averaging > 1 ∘C above the other
3 years (Table 2). While 2017 through 2019 had similar summer
temperatures, they had very different precipitation regimes: 2018 was much
wetter on average and 2019 was slightly drier (Table 2). During all years,
temperatures in the experimental plots were successfully shifted by the
target differentials of +1.7, +3.4, and +5.1 ∘C above the
ambient plots (Fig. 1 (top); Noyce et al., 2019). Porewater pH ranged from
6.4 to 6.8 across the measurement period, with no effect of temperature
treatment (p> 0.1; data not shown). There was no difference in
soil bulk density between the ambient and +5.1 ∘C plots after
4.5 years of warming (p=0.54; data not shown).
Growing season (May–September) temperature and precipitation. Temperature
data are means (SE) of daily averages from ambient plots, and precipitation
is the total from May through September.
Methane emissions increased with soil temperature (R2= 0.41, p<0.001) (Fig. 1). Emissions from all treatments had strong seasonal
trends; fluxes were highest in the C3 community in June through August and
peak fluxes in the C4 community were shifted about a month later to July
through September (Fig. S3). Whole-ecosystem warming increased CH4 emissions
throughout the growing season (F3,400= 5.1, p= 0.002; Fig. 2).
Across all 4 years, 5.1 ∘C of warming more than doubled
growing season emissions, from 624 to 1413 µmol CH4 m-2 d
(padj= 0.02; Fig. 2).
Bottom: CH4 emissions from each plot versus the soil
temperature at the time of measurement. Top: density plot depicting the
range of soil temperatures in each treatment, delineated by color: ambient
(blue), +1.7 (green), +3.4 (yellow),
and +5.1 ∘C (red).
Comparison of CH4 emissions from each warming treatment
during the growing season (May–September). Means include both the C3 and
C4 community and all years of measurement. Error bars indicate SE.
Horizonal bars indicate means that are significantly different and the
corresponding padj.
Mean CH4 emissions were higher from the C4 community than from the
C3 community both during the growing season (F1,22= 13.6, p= 0.001; Fig. 3a) and on an annual basis (F1,22= 8.5, p= 0.008; Fig. 3b). Mean annual CH4 emissions ranged from 58 mmol CH4 (ambient) to 343 mmol CH4 m-2 yr-1 (+5.1 ∘C) in the C3 community and from 55 mmol CH4 (ambient) to 879 mmol CH4 m-2 yr-1 (+5.1 ∘C) in the C4 community (Table S2). Under ambient
conditions, growing season CH4 fluxes were almost twice as large from
C4 plots, whereas under low warming (1.7 to 3.4 ∘C) this
difference increased to more than 3 times as large (Fig. 3a). From
2017–2019, CH4 emissions were positively related to Spartina and Distichlis aboveground
biomass across all warming treatments and negatively related to
Schoenoplectus biomass (Fig. 4a, b). In 2016, however, the direction of those relationships
in both plant communities were the exact opposite, with Spartina and Distichlis biomass
negatively related, and Schoenoplectus biomass positively related, to CH4 emissions
(Fig. 4a, b).
Comparison of CH4 emissions from the C3 community
dominated by Schoenoplectus (open bars) and the C4 community dominated by Spartina and
Distichlis (grey bars). (a) During the growing season (May–September) and (b) scaled to a
year. Means are averaged across all sampling dates for 2017–2019. Error
bars indicate SE. Asterisks indicate significant differences between C3 and C4 means at a given temperature (*padj<0.05, **padj<0.01).
Mean growing season (May–September) CH4 emissions from each plot
versus the biomass of (a) C3 (Schoenoplectus) and (b) C4 (Spartina and Distichlis) plants. All
regressions are significant at p= 0.05.
Porewater chemistry
Under ambient conditions, porewater collected from the C4 community had
more dissolved CH4 (F1,22= 18.4, p<0.001; Fig. 5a, b),
less SO4 (F1,22= 29.1, p<0.001; Fig. 6a), and similar
salinity (p= 0.068) compared to the C3 community. In the C3
community, warming increased dissolved CH4 in both the rooting zone
porewater (10–20 cm) (F3,44= 2.85, p= 0.048; Fig. 5a) and in the
deep peat (40–120 cm) (F3,44= 6.23, p= 0.001; Fig. 5b). Dissolved
CH4 concentrations were relatively similar in the ambient, +1.7,
and +3.4 ∘C treatments but more than doubled
with +5.1 ∘C of warming in both the rooting zone (59 to 125 µmol CH4 L-1, padj<0.001) and the deeper
porewater (43 to 1254 µmol CH4 L-1, padj<0.001). In the C4 community there was minimal effect of warming
treatment on porewater in the rooting zone (F3,44= 0.442, p= 0.72;
Fig. 5a), but all levels of warming decreased dissolved CH4 below 40 cm
(F3,44= 129.3, p<0.001), with concentrations in the +3.4
and +5.1 plots less than a third of the concentrations in the ambient
plots (155 vs. 56 and 40 µmol CH4 L-1, padj<0.001; Fig. 5b).
Comparison of dissolved CH4 from the C3 community
dominated by Schoenoplectus (open bars) and the C4 community dominated by Spartina and
Distichlis (grey bars). (a) In the dominant rooting zone (10–20 cm) and (b) below the
rooting zone (40–120 cm). Means are averaged across all sampling dates for
2016–2019. Error bars indicate SE. Letters indicate temperature
treatments that are significantly different from each other (padj<0.05) within the same plant community.
Comparison of sulfate concentrations and estimated sulfate
depletion from the C3 community dominated by Schoenoplectus (open bars) and the
C4 community dominated by Spartina and Distichlis (grey bars). (a) Sulfate availability
throughout the entire soil profile and (b) sulfate depletion in the rooting
zone. Means are averaged across all sampling dates for 2016–2019. Error
bars indicate SE. Letters indicate temperature treatments that are
significantly different from each other (padj<0.05) within the
same plant community.
In the C3 community, SO4 concentrations decreased with warming
(F3,44= 3.76, p= 0.017), but warming effects on SO4 cycling
in the C4 community were more mixed with +3.4 ∘C
increasing SO4 (padj= 0.048) but no other treatments having
large effects (Fig. 6a). In all plots, the measured concentrations of
rooting-zone SO4 were lower than expected based on salinity (Fig. 6b),
indicating that SO4 reduction occurred. In both plant communities, the
+5.1 ∘C treatments increased this SO4-depletion effect
compared to ambient, though the effect was stronger in the C3 community
(p<0.001) than the C4 community (p= 0.04) (Fig. 6b).
Dissolved CH4 was highest in both plant communities when SO4
concentrations were <5 mmol SO4 L-1 (Fig. S5).
Discussion
Soil temperature (both seasonal and experimental) and plant traits were both
strong drivers of CH4 emissions from this site. This follows prior
field, mesocosm, and incubation studies across a variety of wetlands, in
which temperature has been shown to be a strong predictor of CH4
emissions (e.g., Al-Haj and Fulweiler, 2020; van Bodegom and Stams, 1999;
Christensen et al., 2003; Dise et al., 1993; Fey and Conrad, 2000; Liu et
al., 2019; Ward et al., 2013; Yang et al., 2019; Yvon-Durocher et al., 2014)
and in which plant functional type has an interacting effect (e.g., Chen et
al., 2017; Duval and Radu, 2018; Liu et al., 2019; Mueller et al., 2020;
Ward et al., 2013). Methane emissions are a function of the balance between
methanogenesis, CH4 oxidation, and CH4 transport, so explaining
these results requires some combination of stimulation of methanogenesis,
reduction of CH4 oxidation, or increase in CH4 transport.
Prior data from brackish wetlands are limited, but incubation studies of
freshwater wetland soils typically show large increases in CH4 fluxes
with warming (van Bodegom and Stams, 1999; Duval and Radu, 2018; Hopple et
al., 2020; Inglett et al., 2012; Sihi et al., 2017; Wilson et al., 2016),
indicating that warming alters belowground processes. Though there is some
evidence that rhizosphere temperature alters CH4 transport through rice
aerenchyma (Hosono and Nouchi, 1997), any transport-driven effects in this
ecosystem would be transient unless there were a simultaneous increase in net
CH4 production (i.e., an increase in methanogenesis that was not
completely offset by methanotrophy). Instead, we observed a sustained
increase in CH4 emissions, suggesting large shifts in anaerobic
metabolism, especially with +5.1 ∘C of warming. We propose four
potential and non-exclusive mechanisms to explain the temperature-driven
increase in CH4 emissions: (1) shifted ratios of CH4 production
to oxidation, (2) increased substrate availability, (3) reduced
competition with sulfate reducers for H2 and organic C, and (4) indirect plant trait effects (Fig. 7).
Schematic of mechanisms driving enhanced CH4 emissions in
response to warming. SCAM: Schoenoplectus americanus. SPPA: Spartina patens. (a) Processes under ambient
conditions. Plants add organic compounds to the soil, which are transformed
into other low-molecular-weight organic compounds. This pool, and processed
soil organic matter, support terminal respiration processes dominated by
SO4 reduction over CH4 production in organic-rich brackish marsh
soils. Plants also transport O2, which supports oxidation of a fraction
of the CH4 before it can be transported out of the soil. (b) Processes under warmed conditions. (1) Rates of CH4 production increase
more than rates of CH4 oxidation. (2) Substrate availability increases
as plants add more rhizodeposits and organic matter is more rapidly
fermented to low-molecular-weight organic compounds and H2. (3) The pool
of electron donors available to methanogens increases as SO4 reducers
become SO4 limited. (4) The dominant plant species have different
effects on these processes, with S. americanus driving a net increase in O2 transport
and S. patens driving a net increase in rhizodeposits.
Whole-ecosystem warming promotes methanogenesis over CH4 oxidation
Holding the supply of substrates and transport properties of the system
constant, warming is expected to increase rates of CH4 production
relative to CH4 oxidation due solely to differences in the temperature
dependence of each process (Megonigal et al., 2016). In wetland soils, the
average Q10 of methanogenesis is 4.1 compared to 1.9 for aerobic CH4
oxidation (Segers, 1998), which means that a system starting with a given
initial ratio between the two processes will become increasingly dominated
by methanogenesis as soils warm. A corollary to this expected pattern is
that the ratio of the two processes should be constant if the Q10
responses are similar, an outcome that was supported with in situ measurements of
the two processes in a tidal freshwater forested wetland (Megonigal and
Schlesinger, 2002). We did not quantify the temperature dependence of
CH4 production and oxidation in the present study, but based on the
literature (Segers, 1998) it is likely that methanogenic activity increased
more than aerobic methanotrophic activity in direct response to warming
(Fig. 7, mechanism 1). Evidence for this is that rhizosphere pools of
porewater CH4 were highest in the warmest treatment (Fig. 5a); because
this occurred despite either no change or an increase in aboveground biomass
(Noyce et al., 2019), which would by itself have lowered porewater CH4
due to venting (plant transport), it indicates that CH4 production
increased relative to the sum of aerobic and anaerobic methane oxidation.
Whole-ecosystem warming increases substrate availability for
methanogens
Methanogenesis can be the terminal step of anaerobic decomposition, but a
consortium of microbes is required to break down soil organic matter to
electron donor substrates that methanogens can metabolize. The final step in
any decomposition pathway involves the flow of electrons from organic matter
(electron donors) to a TEA. Under anaerobic conditions, this is accomplished
by microbes that tend to specialize in one TEA and compete for organic C as
an electron donor (Megonigal et al., 2004). Consequently, the supply of both
electron donors and TEAs regulates the multi-step process of anaerobic
decomposition and thus ultimately controls CH4 emissions. For all
pathways, methanogenic activity is typically limited by the supply of
electron donors, including low-molecular-weight organic compounds (e.g.,
acetate; Neubauer and Craft, 2009) and H2, a product of organic matter
fermentation. We propose that whole-ecosystem warming increases the
availability of previously limited C substrates in two aspects (Fig. 7,
mechanism 2).
First, warming may directly influence C availability through biochemical
kinetics. Even if organic inputs remained constant, warming likely
accelerates fermentation of soil organic matter, increasing substrate
availability for methanogens. Second, the warmed plots had longer growing
seasons than the unheated controls (Noyce et al., 2019). This presumably
increased inputs of root exudates and fresh detritus, accelerating all forms
of heterotrophic microbial respiration by providing organic material that is
decomposed into low-molecular-weight organic C compounds and H2
(Philippot et al., 2009), stimulating growing season CH4 emissions from
warmed plots. In 2017, we observed that gross primary production was
positively correlated with CH4 emissions and that this effect increased
with warming (Fig. S6). Prior studies have also linked CH4 production
or emissions to rates of photosynthesis (Vann and Megonigal, 2003), periods
of active growth (Chen et al., 2017; Ward et al., 2013), and plant
senescence, which coincides with a pulse input of labile C from plants to
soils (Bardgett et al., 2005).
Temperature-accelerated biochemical kinetics and increased electron donor
supply are mechanisms that can increase methanogenesis without necessarily
shifting methanogenic pathways. However, shifts in the balance between
hydrogenotrophic, acetoclastic, and methylotrophic methanogenesis pathways
can be expected with warming. For example, in Arctic permafrost,
methylotrophic methanogenesis was found to be more sensitive to warming than
the other pathways (de Jong et al., 2018). Such shifts can be quantified
with future analyses of H2 and low-molecular-weight organic compounds
(e.g., Bridgham et al., 2013; Yang et al., 2016), isotopic tracing of
specific methanogenic pathways (e.g., Blaser and Conrad, 2016; Conrad, 2005;
Neumann et al., 2016; Whiticar, 1999), and molecular community analyses
(e.g., Bridgham et al., 2013; He et al., 2015; Wilson et al., 2016).
Whole-ecosystem warming reduces competition with sulfate
reducers
While low-molecular-weight organic compounds are electron donors for
acetoclastic methanogenic respiration, they are also substrates for other
microbial groups such as SO4 reducers (Megonigal et al., 2004; Ye et
al., 2014). As a result, consumption of the limited organic carbon supply by
SO4 reducers should (and often does) limit methanogenic activity, such
that terminal microbial respiration is typically dominated by SO4
reduction in brackish marshes (Sutton-Grier et al., 2011). Similarly,
SO4 reducers are more efficient than methanogens at competing for the
H2 required for CO2 reduction (Kristjansson et al., 1982). We did
not measure rates of SO4 reduction in this study but can use SO4
depletion as a proxy; more SO4 depletion indicates that more SO4
reduction has occurred. Warming generally increased SO4 depletion,
especially in the plots dominated by Schoenoplectus (Fig. 6b). Differences in SO4
depletion between plots are not driven by SO4 inputs because the only
supply of SO4 is the tidal flow, which is the same for all plots in
each community of the experiment. Instead, higher rates of SO4
reduction are most likely driven by some combination of electron donor
supply and kinetics. While SO4 reducers likely benefited from the
increased availability of electron donors, as described above, the kinetics
of SO4 reduction also respond strongly to temperature (Weston and Joye,
2005).
When SO4 concentrations drop below a threshold concentration,
SO4 reduction becomes SO4-limited, rather than electron-donor-limited (Megonigal et al., 2004). A review of the coastal wetland
CH4 literature estimated this threshold at 4 mmol SO4
(Poffenbarger et al., 2011), a value that is consistent with patterns of
porewater CH4 and SO4 at the GCReW site (Keller et al. 2009). As
SO4 and O2 are the dominant electron-accepting compounds that
suppress methanogenesis in this organic soil, this drawdown then releases
the methanogens from substrate competition (Fig. 7, mechanism 3). Here, we
show that SO4 is typically below 4 mmol in the +5.1 plots in the
C3 community and in all plots in the C4 community (Figs. 6, S5). The drawdown of SO4 may also reduce rates of anaerobic CH4
oxidation (Hinrichs and Boetius, 2003). Van Hulzen et al. (1999) proposed a
multi-phase system in a warming incubation experiment, observing that first
methanogens are outcompeted for substrates by other microbes, next CH4
production increases as the supply of inhibiting TEA decreases, and finally
TEA availability is reduced to the point that methanogenesis is controlled
only by the supply of electron donors. Warming in this study decreased the
time required for the system to pass through the first two phases (van
Hulzen et al., 1999). In our experiment, this final phase of increased
methanogenic activity occurs when SO4 concentrations dip below 4 mmol SO4 L-1, which occurs most often in the +5.1 ∘C
plots, especially in the C3 community. This interpretation is also
supported by the long-term record of porewater chemistry from an allied
experiment at the site, demonstrating that porewater CH4 concentrations
increase as SO4 concentrations decrease (Keller et al., 2009).
Methanogens may also have a competitive advantage over SO4 reducers for
electron donor consumption at warmer temperatures (van Hulzen et al., 1999).
Sulfate reducers and methanogens have very similar KM values for
acetate, but the KM for acetoclastic methanogenesis may decrease with
temperature whereas KM values for SO4 reducers increase with
temperature (van Bodegom and Stams, 1999). If this is the case in our system,
then warming would allow methanogens to use a greater proportion of the
available substrates.
Plant traits modify warming effects on CH4
cycling
The three biogeochemical mechanisms we propose to explain a warming-induced
increase in CH4 emissions should interact strongly with plant responses
to warming. Relationships between plant functional groups and CH4
emissions have been demonstrated through field studies in other wetland
ecosystems such as peatlands (Bubier et al., 1995; Ward et al., 2013) and in
tidal wetland mesocosms (Liu et al., 2019; Martin and Moseman-Valtierra,
2017; Mueller et al., 2020). We provide field evidence that two species with
distinct plant traits – Schoenoplectus and Spartina – have strikingly different effects on
CH4 emissions from brackish wetlands. Spartina-dominated communities had
consistently higher CH4 emissions under both ambient and warmed
conditions (Fig. 3). In most years, Schoenoplectus biomass was negatively correlated with
CH4 emissions, while Spartina and Distichlis biomass was positively correlated. Vegetation
effects are typically strongest during the growing season, when the plants
are actively altering rhizosphere biogeochemistry (van der Nat and
Middelburg, 1998b; Ward et al., 2013), which is consistent with our
observations in this study.
As with warming effects, plant-driven shifts in CH4 emissions are the
result of differing rates of CH4 production, oxidation, transport, or a
combination of these processes, but sustained differences in emissions
cannot be attributed only to transport, as discussed previously. Instead,
the stimulation of CH4 emissions is likely due to changes in the
plant-mediated supply of electron acceptors and electron donors. In a field
environment, differentiating between species-specific effects and underlying
environmental conditions can be difficult, but mesocosm studies that control
all environmental factors have also found species-specific effects on
CH4 cycling (e.g., Liu et al., 2014). Plants can alter CH4 cycling
by adding O2 (electron acceptor) or C substrates (electron donors) to
the rhizosphere, altering the redox state. We propose that Schoenoplectus is a net
oxidizer of the rhizosphere and that Spartina is a net reducer, and thus their
presence and productivity have opposing effects on CH4 emissions (Fig. 7, mechanism 4).
Schoenoplectus oxidizes the rhizosphere, increasing CH4 oxidation
Species vary in their capacity to support aerobic CH4 oxidation (van
der Nat and Middelburg, 1998b), and Schoenoplectus appears to support higher rates of
aerobic CH4 oxidation than Spartina (Mueller et al., 2020). Scirpus lacustris is morphologically
similar to Schoenoplectus americanus studied here and has been demonstrated to have substantial
rhizosphere oxidation capacity, especially during the growing season (van
der Nat and Middelburg, 1998b). Consequently, these plants likely exert
stronger control on rates of CH4 oxidation than rates of methanogenesis
(van der Nat and Middelburg, 1998a). We hypothesize that the relatively high
capacity of Schoenoplectus to transport O2 held the CH4 emissions stimulation
caused by modest levels of warming (+1.7 to +3.4 ∘C) to rates
similar to under ambient conditions (Fig. 3). At high warming (+5.1 ∘C), however, Schoenoplectus community CH4 emissions drastically increase
(Fig. 3). We suggest that this is due to the combined effects of the three
mechanisms discussed previously, namely the differences in the
Q10 values of CH4 production and CH4 oxidation, the increased
supply of organic substrate through plant productivity, and the decrease in
competition for electron donors due to SO4 depletion. Collectively,
when the ecosystem is warmed above current ambient conditions by 5 ∘C or more, enhanced stimulation of CH4 production starts to
offset some of the Schoenoplectus oxidation effect. This also offers an explanation for
the positive correlation between Schoenoplectus biomass and CH4 emissions observed
in 2016 as that was the hottest of the 4 years in this study.
Spartina reduces the rhizosphere, increasing CH4 production
The variability in quality and quantity of root exudates between plant
functional types is well known to affect microbial community composition and
activity (Deyn et al., 2008). Methanogenesis responses to warming in
incubation studies are related to the lignin and cellulose content of the
peat, which in turn depends on the plant functional type from which the peat
developed (Duval and Radu, 2018). Although warming likely increases
substrate availability across the whole experiment, the production of
labile, low-molecular-weight C substrates through fermentation is less
sensitive to temperature above 25 ∘C than below this threshold
(Neubauer and Craft, 2009; Weston and Joye, 2005). Microorganisms may also
preferentially use freshly produced (i.e., labile) organic carbon compounds
as electron donors (DeLaune et al., 2014), and consequently warming effects
on CH4 production should be strongest in a system where rates of root
exudation and turnover are most rapid. We propose that root exudation and
turnover explain the positive correlation between plant biomass and CH4
emissions that we observed in the C4 community. Multiple years of
porewater chemistry at this site show that Spartina-dominated communities have
higher DOC and dissolved CH4 than adjacent Schoenoplectus communities (Keller et al.,
2009; Marsh et al., 2005). Though we did not directly measure root
exudation, porewater DOC is partially derived from root exudates and has
been used as a proxy to understand the responses of root exudates to global
change factors (Dieleman et al., 2016; Fenner et al., 2007; Jones et al.,
2009).
We observed a simultaneous increase in dissolved CH4 at the soil
surface and a decrease in dissolved CH4 at depth in the warmed C4
plots. As with the observed trends in CH4 emissions, there are multiple
mechanisms that could cause a shift in porewater CH4 concentrations. Of
the four mechanisms outlined above, perhaps the simplest explanation is an
increase in labile C at shallow depths and a decrease in deeper soil. This
is consistent with DOC depth profiles from this C4 community in
which porewater DOC increases with warming in shallow samples but decreases
with warming in deep samples (Fig. S7). This shallowing of peak DOC
concentrations could be due to a warming-induced increase in
evapotranspiration, leading to slower downward hydrologic transport of
DOC-rich surface porewater to lower depths, or a warming-induced shallowing
of the root system, leading to a shift in the location of root exudates.
In most years, Spartina biomass was positively correlated with CH4 emissions,
supporting our hypothesis that Spartina favors net CH4 production. However,
in 2016 Spartina biomass and CH4 emissions were negatively correlated. Prior
work at this site has indicated that Spartina and Distichlis biomass is more negatively affected
by hot and dry growing conditions than Schoenoplectus (Noyce et al., 2019) due in part
because the Spartina and Distichlis (C4) communities are less frequently inundated. The 2016
growing season was substantially warmer than average (Table 2), and the
heating treatments were initialized on 1 June of that year, after the annual
plants had already established and may have developed adaptations to
ambient, rather than elevated, temperature conditions. The combination of
these two effects likely led to heat stress, reducing the root exudates
supplied to the rhizosphere microbial community (Heckathorn et al., 2013)
and thus minimizing the Spartina stimulation effect.
Comparisons with prior data
Methane emissions have been measured at the GCReW site previously, but this
study represents the most comprehensive dataset collected to date and is
thus particularly useful for advancing the process-based understanding
needed to improve prognostic models. Overall, our flux estimates are lower
than those reported previously. The earliest CH4 fluxes were measured
in a single month (July) in Schoenoplectus-dominated plots and reported to be 331 to 6883 µmol m-2 d-1 (Dacey et al., 1994), much higher than our
range of 359 to 1651 µmol m-2 d-1 for ambient temperature
Schoenoplectus plots in July. Similarly, Marsh et al. (2005) reported mean growing season
(May–October) CH4 emissions from this site of 846 ± 111 µmol CH4 m-2 d-1, whereas we measured 656 ± 79 µmol CH4 m-2 d-1 over the same months. Finally,
Pastore et al. (2017) estimated average annual fluxes in their
Schoenoplectus-dominated ambient CO2 plots as 3.1 ± 1.7 g CH4 m-2 yr-1, compared to our estimates of 1.6 ± 0.3 g CH4 m-2 yr-1 for Schoenoplectus plots. The different estimates by these studies may be partly
due to interannual variability as demonstrated in our data where 2018 had
substantially higher fluxes than any of the surrounding years (Table S2).
The annual estimates reported here for ambient temperature plots trended
lower than published mean CH4 emissions for mesohaline tidal marshes.
Our plots ranged from 0.7 to 9.3 g CH4 m-2 yr-1 (mean = 9.3), compared to the range of 3.3 to 16.4 g CH4 m-2 yr-1
(mean = 16.4) reported by Poffenbarger et al. (2011). This difference may
be explained by the fact that there was significant within-class variation
in the oligohaline and mesohaline salinity classes that was unexplained, and
their assessment was based on too few data points to fully capture the
variation that is expected to exist in the mesohaline class. Indeed,
subsequent studies have documented fluxes well below 3 g CH4 m-2 yr-1 (Krauss and Whitbeck, 2012) and even negative fluxes
(Al-Haj and Fulweiler, 2020). We hypothesize that the low fluxes measured at
our site reflect Schoenoplectus americanus traits that favor CH4 oxidation more than CH4
production and that the high end of our range was limited by the high soil
elevation (i.e., deep water table) of areas dominated by Spartina patens, offsetting the
influence of S. patens traits that favor CH4 production.
Implications for tidal wetland carbon cycling
Warming accelerates rates of CH4 emissions from brackish marshes,
especially during the growing season. This is driven by both direct and
indirect warming effects and mediated by soil biogeochemistry, but the
magnitude of the warming effect is also dependent on traits of the plant
species that dominate the plant community. Communities dominated by
Spartina patens increase net CH4 emissions in response to smaller increments of
warming than communities dominated by Schoenoplectus americanus. Spartina-dominated sites may thus have a
higher likelihood of shifting from a net C sink to a net C source under
future warming conditions, due to this increased loss of C as CH4.
However, this effect could be mitigated if these high-elevation Spartina marshes
become dominated by Schoenoplectus in response to predicted accelerated sea-level rise
(Kirwan and Guntenspergen, 2012). In addition, Spartina traits are plastic and
influenced by factors such as soil redox conditions (Kludze and DeLaune,
1994), salinity (Crozier and DeLaune, 1996), and water level (Liu et al.,
2019), all of which can be expected to change plant-mediated effects on
CH4 biogeochemistry. Further studies are needed to thoroughly assess
the range of environmental conditions under which Spartina is a net reducer and
Schoenoplectus is a net oxidizer as proposed by the present study.
Data availability
All data are available from the corresponding author upon request.
The supplement related to this article is available online at: https://doi.org/10.5194/bg-18-2449-2021-supplement.
Author contributions
GLN and JPM designed the study, GLN collected and analyzed the data, and GLN
and JPM wrote the paper.
Competing interests
The authors declare that they have no conflict of interest.
Acknowledgements
Roy Rich
designed the warming infrastructure and maintains it with the assistance of
Gary Peresta. We also thank the technicians in the SERC Biogeochemistry Lab for
assistance with porewater collection and analysis.
Financial support
This research has been supported by the US Department of Energy, Office of Science, Office of Biological and Environmental Research program (grant nos. DE-SC0014413 and DE-SC0019110); the National Science Foundation Long-Term Research in Environmental Biology program (grant nos. DEB-0950080, DEB-1457100, and DEB-1557009); and the Smithsonian Institution.
Review statement
This paper was edited by Edzo Veldkamp and reviewed by two anonymous referees.
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