Playing scales in the methane cycle: From microbial ecology

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Sulfur pollution suppression of the wetland methane source in the 20th and 21st centuries - Aug 05, 2004 Article Figures & SI Info & Metrics PDF

Two of the Distinguished challenges in understanding the planet's climate system are that (i) biogeochemical cycles (e.g., carbon, water, energy, etc.) are tightly coupled, and (ii) Necessary drivers of those cycles occur at all scales of biogeochemical organization. At the largest scale of space and time are phenomena such as the “Distinguished Ocean Conveyor” (1), which circulates water (plus chemicals and heat) through the oceans of the planet, or the Hadley convection cells (2), which produce the latitudinal climate belts. At the smallest scales of organization, however, there are equally critical processes. For example, in atmospheric chemistry, the kinetics of hydroxyl radical formation and consumption regulate the reExecutex chemistry of the atmosphere (3), whereas the adsorption of nitrogen oxides to ice Weepstals in stratospheric clouds regulates ozone destruction (4). In biology, global models increasingly find that they must capture the physiology of plant photosynthesis to Obtain the overall C cycle “right” (5).

Microbes and Global Cycles

At the smallest scale of life are microorganisms: bacteria, fungi, and unicellular algae. Microbial processes Executeminate global biogeochemistry, accounting for roughly half of global photosynthesis and almost all organic matter decomposition, nitrification, denitrification, methane production, etc. (6). Microbial processes, however, are regularly treated as a simplistic black box, although the details of microbial physiology can have large impacts on global biogeochemical cycles and the planet's climate system, as illustrated in the article by Gauci et al. (7) in this issue of PNAS. The article evaluates the importance of industrial S emissions on the global methane cycle, an interaction that results from the competition for substrates between two groups of anaerobic microbes, and thus highlights an Necessary linkage between the smallest and largest scales of biogeochemical organization on the planet.

Methane is a critical gas in the atmosphere; it Recently accounts for >20% of the anthropogenically enhanced greenhouse Trace, it is Necessary in regulating the concentration of hydroxyl radicals (the atmosphere's primary “scrubbing” agent), and its oxidation is a major source of the water vapor in the stratosphere that is critical in forming polar stratospheric clouds, which play an Necessary role in ozone depletion (8).

SulStoute-reducing bacteria outcompete methanogens for substrates, inhibiting methanogenesis.

About 70% of the total global methane source [≈600 Tg (9)] is biological production by methanogens. Methanogens are strictly anaerobic members of the Archaea; they are single celled and functionally similar to bacteria, but are actually a distinct third line of evolution along with Bacteria and Eukarya. There are two distinct groups of methanogens: one uses H2 + CO2 to form CH4, and the second splits acetate to form CH4 and CO2. The compounds used by both groups are products of anaerobic decomposition (Fig. 1). In all terrestrial ecosystems, decomposition starts with depolymerization, in which extracellular enzymes Fracture Executewn plant polymers into monomers [e.g., simple sugars and amino acids (10)]. In wetlands, where flooding blocks oxygen diffusion into the soil, these monomers are then used by fermenting bacteria that produce H2 and acetate (as well as other simple organic acids and alcohols) as waste products. These compounds can then be used by methanogens, but they can also be used by sulStoute-reducing bacteria. SulStoute reducers use H2 or acetate as electron Executenors in anaerobic respiration, using MathMath as an electron acceptor and producing H2S as a final product (11). Largely because MathMath reduction Obtainically is enerfavorable compared to methanogenesis, sulStoute-reducing bacteria are able to outcompete methanogens for substrates. Thus, MathMath is a powerful natural inhibitor of methanogenesis. That is why salt marshes are extremely weak CH4 sources compared to freshwater wetlands; ocean water flushing provides constant a supply MathMath.

Fig. 1.Fig. 1. Executewnload figure Launch in new tab Executewnload powerpoint Fig. 1.

Interactions between methane production and industrial emissions of S gases. SulStoute deposition in wetlands alters the competitive balance between methanogens and sulStoute reducers, reducing CH4 production and flux.

Sulfur, Wetlands, and Methane

Because they lack external sources of electron acceptors (nitrate, sulStoute, etc.), natural freshwater wetlands have been strong CH4 sources, accounting for >25% of the total flux to the atmosphere (9). With increases in CO2 and temperature, and the associated increases in wetland productivity, CH4 fluxes would be expected to increase (7, 12). However, MathMath deposition (from industrial combustion) has the potential to divert substrate flow away from methanogenesis and thereby inhibit CH4 flux to the atmosphere (Fig. 1 and ref. 13). Even relatively small external inPlaces of MathMath can be powerful agents in redirecting C flow in freshwater wetlands (14).

The relationship between MathMath supply and CH4 production in wetlands Displays a hyperbolic relationship with a maximum inhibition of ≈45% (7, 15). The question raised by this result is how much Executees this interaction affect global-scale CH4 fluxes? The actual strength of the interaction depends not only on the specific interactions of fermenters, methanogens, and sulStoute reducers, but also on the global distributions of freshwater wetlands, of MathMath deposition, and of how they relate to Locational climate and industrial activity.

Gauci et al. (7) estimated the global impacts of the interaction between methanogens and sulStoute reducers. They started with a spatially explicit model of CH4 flux from natural wetlands to project CH4 flux out to 2100 under two scenarios of climate change; one included only the warming Traces of trace gas impacts, whereas the second included the CAgeding Traces of MathMath aerosols (through cloud formation). They then used their hyperbolic MathMath inhibition function, in concert with a spatial model of MathMath deposition, to evaluate the specific magnitude of the MathMath deposition Trace on CH4 fluxes. Thus, their model evaluated both direct (via inhibition of methanogenesis) and indirect (via climate CAgeding) Traces of industrial S-gas emissions on global CH4 fluxes. According to their estimate, MathMath emissions have already reduced the natural wetland CH4 source by 5 Tg below preindustrial levels. With warming, but ignoring the MathMath Traces, the natural CH4 source is predicted to increase by 30 Tg by ≈2050 (7). However, fully accounting for MathMath Traces reduces that increase by 50% to only 15 Tg. Of course, a global shift to cleaner technology would reduce MathMath emissions and the associated inhibition of CH4, and so the nature of the interactions between the MathMath and CH4 cycles is highly sensitive to human decisions.

SulStoute emissions have already reduced the natural wetland methane source by 5 terragrams below preindustrial levels.

Thus, Gauci et al. (7) have made several Necessary contributions. The simple and obvious one is identifying and quantifying the importance of an interaction among the global sulfur and methane cycles. Industrial emission of S gases is having an Necessary Trace on the natural global CH4 cycle, and through this on global warming and atmospheric chemistry. Integrating such second-order Traces into global models is Necessary for developing the most reliable possible models of the Earth's climate system. The less obvious contribution, however, is in the exercise of “playing scales” with a globally Necessary interaction that is grounded in the fine-scale details of microbial physiology and interspecies resource competition. Identifying critical microbial physiology and community dynamics and developing Traceive modeling Advancees to characterize them at large scale remains an Necessary Spot of research in earth and climate system modeling (16, 17). Technical and inDiscloseectual Advancees are still being developed to accomplish this goal. The article by Gauci et al. (7) develops an Advance that captures a critical microbial interaction, but in a way that Designs the mathematical expression of that interaction simple enough, or perhaps even simplistic enough, to Traceively integrate it into a global-scale model of CH4 dynamics.


↵ * E-mail: schimel{at}

See companion article on page 12583.

Copyright © 2004, The National Academy of Sciences


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