The sunny side of greenhouse gas emissions – quantifying the contribution of aerobic methane production to global methane budgets
Bibliographic record
Abstract
Over the last three decades, two global-scale issues, namely depletion of stratospheric ozone and global climate change, have dominated both the science and the politics of the environment. While the success of political responses to the two remain starkly different at present, from the scientific perspective both have required the development of new understanding of the complex interplay between atmospheric composition, radiation balance and the biosphere. More recently, this new understanding has revealed that ozone depletion and climate change are linked at a range of scales. For example, chlorofluorocarbons are major greenhouse gases, and by controlling their release, the Montreal Protocol has made a major contribution to meeting the terms of the Kyoto Protocol (Velders et al., 2007; Andrady et al., 2010). Increased concentrations of greenhouse gases, while leading to warming of the troposphere, lead to cooling of the stratosphere, which is expected to delay recovery of the ozone column at high latitudes (Rex et al., 2006). At low latitudes, the already high intensity of solar ultraviolet (UV) radiation reaching the biosphere is expected to increase further because of changes in the distribution of stratospheric ozone resulting from climate change (Hegglin & Shepherd, 2009; Kazantzidis et al., 2010). Climate change will also influence the intensity of solar UV radiation reaching the biosphere through mechanisms other than changing ozone. In particular, cloud and aerosols have major effects on the penetration of UV radiation to the Earth’s surface (McKenzie et al., 2007; Andrady et al., 2010). Conversely, UV-B radiation can influence the concentrations of several compounds that contribute to the production of atmospheric aerosols and cloud, including dimethylsulphide from the oceans and isoprene from terrestrial ecosystems (Zepp et al., 2007). Finally, solar UV-B radiation is a driver for many elements of atmospheric chemistry, including the photolysis of tropospheric ozone and the production of hydroxyl radicals that play a key role in the degradation of atmospheric pollutants (Wilson et al., 2007). ‘Is it time to draw a line under the aerobic methane emissions?’ The study of Bloom et al. (pp. 417–425) in this issue of New Phytologist highlights a further interaction between solar UV radiation and climate change, namely the capacity of UV radiation to affect methane (CH4) emissions from vegetation. Methane is a major greenhouse gas (see Forster et al., 2007), and methane production from human activities now exceeds that from natural sources (reviewed by Denman et al., 2007), but the single largest source in the global methane budget is production from wetlands, as a result of anaerobic microbial respiration in water-saturated soils (Denman et al., 2007). While the main elements of methane budgets are generally well defined, uncertainties remain, including the causes of significant between-year variation in methane production and the magnitude of methane sources in tropical terrestrial systems (Denman et al., 2007). So, where is the connection between methane emissions and solar UV radiation? Before 2006, the only defined link was evidence that increased UV-B radiation could reduce emissions of methane from wetlands, probably by altering plant morphology in ways that reduced the movement of methane from the soil to the atmosphere (Niemi et al., 2002). In 2006, Keppler et al. published novel observations showing that methane could be produced by plants growing in well-aerated soils. The same authors also showed that methane was produced at a much higher rate in sunlight than in the dark (Keppler et al., 2006). These observations, and especially the authors’ estimate that the aerobic production of methane from vegetation might contribute up to 30–40% of global methane production, proved highly controversial. The controversy lay not only in the size of the contribution of aerobic methane production to global budgets but also the more fundamental question of whether aerobic methane production was a real biological process at all (e.g. Dueck et al., 2007). However, aerobic methane production has now been reported from a number of laboratories using a range of biological systems, and with rigorous attention to avoiding measurement artifacts (reviewed by Bloom et al.). In addition, there is now a solid mechanistic understanding of the process. UV-B radiation produces methane from plant material under aerobic conditions through a nonenzymatic photochemical degradation of the methyl pectins that form a significant component of cell walls (Keppler et al., 2008; Messenger et al., 2009). That process is based on the generation of reactive oxygen species (ROS) by UV-B radiation, and the same mechanism has now been demonstrated in response to other factors that generate ROS, including high temperature and disease (McLeod et al., 2008; Messenger et al., 2009). While not all researchers may agree, in my view, the process of aerobic methane is now sufficiently well documented to be considered proven, which focuses attention on the question of how large a contribution it makes to global methane budgets. It is answering this question that is the foundation of the recent study of Bloom et al. One key step in extrapolating from the mechanistic understanding of UV-B-induced methane production at the laboratory scale to global methane budgets was the publication of the action spectrum for aerobic methane production (McLeod et al., 2008). An action spectrum describes the quantitative relationship between the wavelength of radiation and a response, regardless of whether that response is pigment accumulation in plants, sunburn in human skin, or methane production (McKenzie et al., 2007). Understanding the appropriate action spectrum for a particular process is vital for any consideration of the effects of UV-B radiation in nature, because it allows a common basis of ‘weighting’ radiation from any source in a way that is relevant to a specific process. For example, without such weighting it is impossible to compare the UV radiation produced from lamps with that present in sunlight. Similarly, action spectra allow account to be made for the changes in the solar UV spectrum that result from ozone depletion, and also from time of day, season and latitude (McKenzie et al., 2007). Bloom et al. use this approach to model global variation in ‘methane-effective radiation’, based primarily on solar elevation, atmospheric ozone column, cloud cover and aerosols. The resulting global ‘methane UV climatology’ shows the expected pattern with maximum irradiances in the tropics, especially in tropical mountains (see Fig. 1 in Bloom et al.). This model for ‘methane-effective radiation’ is then combined with estimates of the amount of target material determined from the typical pectin contents of plant material and the global distribution of plant biomass (derived from satellite data of leaf area index), to predict aerobic methane emissions from different regions and different types of vegetation, and finally to estimate total global emissions from this source of methane. These calculations produce an interesting pattern of geographical variation in aerobic methane emissions. The authors point out high annual production rates in the rainforests of tropical Africa and northern Australia, but there are also seasonal peaks outside the tropics, for example, in the south-west of North America, Mediterranean Europe, southern Asia and south-east Africa (see Fig. 2 in Bloom et al.). The maximum rates of aerobic methane emission are in the order of 15–20 mg CH4 m−2 yr−1. It is worth considering these annual emission rates in the context of methane production from ‘conventional’ anaerobic sources, which may reach 200–1000 mg CH4 m−2 d−1 in natural wetlands and rice paddies (e.g. Yan et al., 2003; Nahlik & Mitsch, 2010). In terms of total global production, Bloom et al. estimate that UV-driven aerobic production of CH4 from vegetation might total 0.2–1.0 Tg CH4 yr−1 compared with total emissions of c. 550 Tg CH4 yr−1. This latest estimate of the magnitude of aerobic methane emissions, of < 1.0 Tg yr−1, is clearly a long way from the original suggestion that such emissions might be as high as 236 Tg yr−1 (Keppler et al., 2006). Bloom et al. rightly acknowledge the uncertainties in their model, and others will surely further refine their values, but the inescapable conclusion of the current estimate is that aerobic methane production is only a minor contributor to the global methane budget. So, is it time to draw a line under the aerobic methane emissions? I suspect that there will be many views on that question, but in my opinion the study of Bloom et al. has highlighted a point with wider relevance than simply quantifying methane emissions. The magnitude of UV radiation-driven aerobic methane production alone may be too small to lead to significant climate feedbacks, but UV radiation also drives photochemical carbon monoxide production from plant litter (Schade & Crutzen, 1999) and the direct photochemical degradation of litter to release CO2 (Brandt et al., 2009; Austin & Ballare, 2010), as well as having diverse effects on atmospheric chemistry and the biosphere. Are there possible feedbacks here, as changing cloud, aerosols and ozone distribution affect future UV climates? The ecological and biogeochemical effects of solar UV radiation are still too often seen only in the context of stratospheric ozone depletion. By recognizing UV radiation as a dynamic component of the global environment, Bloom et al. have demonstrated the value of incorporating UV radiation into models of global-scale biogeochemistry, and pointed the way for the wider inclusion of ‘ambient UV’ in the assessment of global change processes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".