Environ. Sci. Technol. 2007, 41, 4032-4037
Global Methane Emissions from Terrestrial Plants CHRISTOPHER L. BUTENHOFF* AND M. ASLAM KHAN KHALIL Department of Physics, Portland State University, P.O. Box 751, Portland, Oregon 97207
Recent measurements suggest that the terrestrial plant community may be an important source of methane with global contributions between 62 and 236 Tg CH4 y-1. If true, terrestrial plants could rival wetlands as being the largest global source of methane forcing us to rethink the methane budget. While further measurements are needed to confirm the methane release rates from this source and their dependencies, in this work we use the preliminary measurements to assess the potential impact of the methane release from this source globally. Using novel techniques we extrapolate the initially reported chamber measurements to the global scale and calculate the global methane emissions from the terrestrial plant community to be in the range 20 to 69 Tg CH4 y-1. The spread in emissions is largely due to the sensitivity of the global flux to the prescribed temperature dependence of the plant emission rate, which is largely unknown. The spread of calculated emissions is in good agreement with the upper limit imposed on the source during the late pre-industrial period, which we estimate to range from 25 to 54 Tg CH4 y-1 during the years 0 to 1700 A.D. using the published atmospheric δ13CH4 record. In addition, if we assume that plant emissions have been constant at the mean value of 45 Tg CH4 y-1, we find that the methane release from wildfires and biomass burning during the pre-industrial span 0-1000 A.D. must be near 12 Tg CH4 y-1, which would be in better agreement with previous estimates of the pyrogenic source during this time than a methane budget missing the plant source. We conclude that methane release from the terrestrial plant community as presently understood does not require major innovations to the global methane budget.
1. Introduction Methane is an important radiative and reactive gas and is second only to carbon dioxide among trace gases that perturb the atmosphere’s radiation balance (1). Presently, its globally averaged mixing ratio is nearly 1800 ppb, which is over two and half times larger than its pre-industrial value, raising concerns about its future (2). Though the global burden of methane continues to rise, its rate of increase has decreased from nearly 20 ppb y-1 in 1980 to its present day rate of about 3 ppb y-1 (3, 4). The decreasing trend may represent an approach to steady state, as methane emissions have likely been stable over the last 20 years (3, 4). Methane is released from a well-studied and diverse set of sources, which together emit some 500-600 Tg CH4 y-1 (2). Of this total, about 70% of emissions come from a * Corresponding author e-mail:
[email protected]. 4032
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specialized group of bacteria that release methane as a byproduct of their metabolism in anaerobic environments, including flooded soils, landfills, wastewater lagoons, and the digestive tracts of animals. Wetlands are thought to be the single largest source, contributing 100-200 Tg CH4 to the annual budget (2). Considering that the methane budget is balanced within the uncertainties of its sources and sinks, it came as a surprise in early 2006 when researchers reported measuring emissions of methane from C3 and C4 plants under aerobic conditions (5). The experiments were performed on detached plant leaves and intact plants both in the field and in the laboratory using a wide variety of plants including grass, tree, and crop species. Release rates from the detached leaves ranged from 0.2 to 3 ng CH4 per g (dry weight) h-1 and from 12 to 370 ng CH4 per g (dry weight) h-1 for the intact plants. The release rates were found to be temperature and sunlight dependent. As a natural source of methane, these emissions are unusual since such emissions are typically mediated by bacteria under anaerobic conditions (6). In addition, initial estimates put annual emissions from this source between 62 and 236 Tg CH4, which would rival wetlands as the largest methane source (5). If global plant emissions are near the mean of this range (149 Tg CH4 y-1), we are forced to rethink the methane budget. Extrapolation of the chamber studies to the global scale is difficult due to the limited plant emission measurements and the spatial and temporal variability of global vegetation. The original extrapolation used annual net primary production (NPP) as the scaling proxy (5). We feel this is not appropriate for a number of reasons. First, NPP is the rate of accumulation of organic carbon in the tissues of plants and includes the accumulated carbon content in all compartments of the plant; roots, woody tissues, foliage, etc. The fraction of NPP in the below-ground compartments can be as high as 70% in grasslands and typically around 40% in boreal, temperate, and tropical forests (7). Since Keppler et al. measured emissions coming from both detached leaves and intact leafy plants, it seems likely that a plant’s standing foliage biomass is a better indicator of the plant’s emissions. The standing foliage biomass also depends on the rate of loss to litterfall and herbivores, which is not considered in the plant’s NPP. Second, plants may have significant standing foliage at the same time their net primary production is small or zero. Such is the case during the dormant season of evergreen species when low temperature or aridity limits photosynthesis. Leaf emissions based on NPP during these times may be underestimated. Third, even if NPP represented foliage biomass, the use of annual NPP in (5) overestimates the emissions, since their calculation assumes that the entire annual production of biomass is available throughout the growing season as a source of emissions, when actually the standing biomass slowly accumulates over the growing season and will be typically smaller than the annual sum throughout. That is, if f is the emission factor that converts NPP to methane flux (Tg CH4 per Pg C dry plant biomass y-1), the annual emissions S (Tg CH4) as calculated by (5) are given by
S ) ∆tgrow × (f * NPPannual) ) ∆tgrow × f *
∫
∆tgrow
NPP(t)dt (1)
where NPPannual is the integrated annual production (Pg C dry plant biomass), ∆tgrow is the growing season length (y), and NPP(t) describes how NPP changes throughout the 10.1021/es062404i CCC: $37.00
2007 American Chemical Society Published on Web 04/25/2007
growing season (Pg C y-1). More appropriately, the annual emissions should be found by
S′ ) f
∫
t′)tend
t′)to
B(t′)dt′ ) f
∫
t′)tend
t′)to
∫
t)t′
t)to
NPP(t)dtdt′ (2)
Here, the emissions at any time t′ during the growing season are based on the standing plant biomass, B(t′), available at that time. The standing biomass is specified in the calculation as the integrated production from the beginning of the growing season (to) to the current time t′. It is these emissions then that are integrated over the entire growing season to form the annual sum. We can estimate the difference between S and S′ by using as an example the average seasonal cycle of NPP from Brasilia, Brazil, as the function NPP(t) in the equations above. This site is chosen as representative of the region that dominates the global NPP. We find that emissions calculated using eq 1 are nearly 1.75 times larger than those using the correct procedure in eq 2. Clearly the large methane source predicted by (5) is suspect and is partly due to this miscalculation. Recent papers have recognized the improper use of NPP and have re-estimated global plant emissions using the foliage biomass by biome as the scaling factor (8, 9). Parsons et al. applied the measured sunlit and non-sunlit emission rates (5) to foliage and non-foliage biomass, respectively, and estimated global plant emissions to be 52 Tg CH4 y-1 (9). Using both foliage biomass and photosynthetic activity, Kirschbaum et al. estimate global emissions to be between 10 and 60 Tg CH4 y-1 (8). These estimates are consistent with top-down constraints from the atmospheric methane and δ13CH4 record (10, 11). In the current work, we model monthly plant emissions on a 0.5 × 0.5° grid based upon the temperature- and sunlightdependent emission rates determined by Keppler et al. Sunlight exposure is determined not only by day length, but also by cloud cover and canopy-shading. Calculations are performed on a per cell basis to allow variations across vegetation biomes. We feel this is the most complete bottomup estimate done to date of the plant emissions. We use two distinct methods to derive our foliage biomass distribution to assess uncertainty. We also verify that our bottom-up estimates are consistent with the pre-industrial methane record, which forces global plant emissions to be significantly smaller than the original estimate.
Method The results from the plant emissions study relevant to the current work are the following. First, emissions were detected from both detached and intact leaves, though emissions from the former were insignificant compared to the latter (8.7 vs 374 ng CH4 per g (dry matter) h-1, mean values reported here). Since emissions from detached leaves are marginal, we ignore emissions from the leaf litter in our calculation below. Second, emissions were sensitive to daylight. When intact leaves were exposed to sunlight they released on average three times more methane than when kept in the dark. Finally, emissions from the detached leaves were strongly temperature dependent, increasing by a factor of 6 when temperatures were increased by a factor of 2.3. It is speculative to extend this conclusion to intact leaves since all experiments performed on live plants were at ambient temperatures near 21 °C. Nonetheless, the detached leaf measurements suggest that methane emissions diminish with decreasing temperature and we assume a threshold temperature of 20 °C, consistent with the original study. In the work below, we find that global emissions are sensitive to the threshold temperature over a moderate range of values.
Method 1: Leaf Area Index. The primary driver of the proposed vegetation source is the magnitude of the global reservoir of terrestrial foliage. Of additional concern is its spatial and temporal distribution since the measurements indicate methane release from plants is sensitive to temperature and exposure to direct sunlight. We use two independent methods to construct time- and space-dependent foliage biomass maps. In method 1 we use globally gridded, quarter-degree resolution maps (later degraded to half-degree to match resolution of meta-data) of leaf area index derived from the MODIS satellite products. The LAI is the ratio between the one-sided area of the leaf and the area it projects on the ground. These maps are constructed from the 1 km, sine projection standard product and available every 8 days from the year 2000 to the present (12, 13). We convert them to maps of foliage biomass (FM) through
FMi ) LAIi × Ai × SLAi
(3)
where Ai is the grid cell area and SLAi is the specific leaf area given by 0.0001(6.24 × LAI + 19.86) if foliage biomass is expressed in grams and cell area is expressed in square meters (14). This method produces an annually averaged global foliar biomass of 49 Pg C. Method 2: Above-Ground Net Primary Production. In our second method, we use monthly gridded maps of global net primary production. Though a plant’s total NPP is a poor proxy for its foliage biomass for reasons discussed above, its aboveground NPP is correlated with the plant’s annual peak foliage (15). The fraction of NPP that is aboveground varies with vegetation type but on average is close to 50% (7). Typically a greater fraction of a forest’s NPP goes to aboveground components than does grass and shrublands. We create global maps of ANPP by scaling each grid cell in the NPP maps by the appropriate ANPP/NPP ratio determined by the vegetation type of the grid cell (16). For a wide range of vegetation types, the annual aboveground NPP is correlated with the annual peak foliage mass. To determine the peak foliage mass of each grid cell we annually integrate the ANPP over each cell and apply the relation (15)
PFMi ) 0.44Ai × (2 × ANPPiannual)1.08
(4)
where the peak foliage mass (PFM) has units of g y-1. Though this calculation gives only the peak amount of foliage mass, we create a seasonal time series of foliage mass by assuming that foliage mass scales with LAI. This is reasonable since when a plant’s leaf area is large, so too in general will its leaf biomass. We average the seasonality of LAI over all years of data and scale it by the factor PFMi/LAImax, which is the ratio between a cell’s peak foliage mass and the maximum value of LAI through the average seasonal cycle. This is based on the assumption that the peak leaf mass coincides with the peak leaf area. The global foliage biomass calculated using this method is sensitive to the input NPP. Though NPP can be measured directly on small scales by field studies, global NPP is routinely estimated in carbon cycle and terrestrial ecosystem models. Annual global NPP from such models typically range from 40 to 70 Pg C y-1 (17). For the current work we use a model (18) that estimates annual NPP is 60 Pg C y-1. This is at the upper end of the range and is chosen to produce the highest reasonable emissions of methane using this method. According to eq 4 we estimate global foliage mass is 26 Pg C y-1. From the range of annual NPP quoted above, a reasonable range of foliage biomass based on this method is about 1730 Pg C y-1. This is about half the global value estimated using the LAI method. The reasons for the discrepancies are VOL. 41, NO. 11, 2007 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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FIGURE 1. Gridded monthly methane emissions (0.5 × 0.5°) from the plant leaf source using method 1. Units on the color bar are Gg CH4: (a) January; (b) April; (c) July; (d) October. If the emissions are integrated over the entire grid, the monthly totals range from 2 to 4 Tg CH4. unclear, but not unexpected considering the two disparate approaches used. It is possible that the foliar biomass estimated using method 1 is overestimated since the specific leaf area relation used is biased toward needle-bearing trees, which tend to have lower SLA than broadleaf trees (9). Methane Emissions from Foliage Biomass. We transform the foliage biomass into methane emissions using the emission rates of (5). There are two important results of their work that we consider in the transformation. First, emissions nearly triple when the leaves are exposed to direct sunlight, and second, there appears to be a threshold temperature below which the plants do not produce emissions. To take into account the first observation we separate each 24-hr day into nighttime and daylight hours and additionally separate daylight hours into overcast (i.e., indirect sunlight) and cloud-free (direct sunlight) hours using monthly cloud climatology (19). We also differentiate the fraction of the leaf canopy that is in direct sunlight from the fraction that is shaded during daylight hours using a time-dependent vegetation canopy model (20) and apply the appropriate methane emission rate to each fraction. Preliminary measurements suggest that plant emission rates are temperature-dependent though the functional relation is unknown (5). Initial results indicate emission rates approach zero near 20 °C. As a first order approach we take this to be the minimum threshold for emissions and test the sensitivity of the global emissions to this requirement. Though the minimum temperature required for emissions to occur is perhaps unknown, it seems reasonable to assess the sensitivity of emissions to temperature as the responsible emission mechanism, be it biological, chemical, or physical, is likely to be temperature dependent. 4034
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Results and Discussions Applying the considerations above, we calculate daily plant emissions over a 0.5 × 0.5° grid for all terrestrial land surfaces. The respective integrated annual emissions are 36 and 20 Tg CH4 y-1 from methods 1 and 2 when we use the mean sunlit and shaded emission rates of 374 and 119 ng CH4 per g (dry weight) h -1 reported in (5). If we include the reported ranges in the emission rates, which largely reflect variability between plant species, our respective plant emissions from methods 1 and 2 span 14-60 and 8-34 Tg CH4 y-1. These are significantly smaller than the range estimated in the original study (62-236 Tg CH4 y-1) but similar to the range reported by a recent study (10-60 Tg CH4 y-1) (8). Emissions are lower using method 2 since the foliar biomass estimated using this method is smaller than using method 1. If we lower the threshold temperature in method 1 to 15, 10, and 5 °C, the mean global emissions are 52, 60, and 66 Tg CH4 y-1, respectively. If we further reduce the temperature to 0 °C, perhaps a less controversial minimum temperature, global emissions increase only slightly more to 69 Tg CH4 y-1. Using our extrapolation scheme, this then appears to be the maximum emissions we can expect from this source. When we use 0 °C as the minimum temperature in method 2, emissions increase from 20 to 36 Tg CH4 y-1. Whether such a minimum temperature exists and what its value may be is one of the largest sources of uncertainty in our extrapolation process. The sensitivity of the emissions to this temperature indicates that this needs to be a focus of future work. In the remainder of the paper we take the minimum temperature to be 20 °C.
FIGURE 2. Distribution of the methane emissions from the plant source calculated using method 1 binned monthly and in latitude (5° bins). The heavy line shows the distribution of the tabulated annual emissions.
FIGURE 3. Distribution of annual plant emissions according to vegetation type. Vegetation classifications are from (11): BEF ) broadleaf evergreen forest; CEF ) coniferous evergreen forest; HDF ) high-latitude deciduous forest; CFW ) coniferous evergreen forest and woodland; WGR ) wooded grassland; GRA ) grassland; BAG ) bare ground; SHG ) shrubs and bare ground; CRP ) cultivated crops; BDF ) broadleaf deciduous forest and woodland. The spatial and temporal patterns of emissions are shown for method 1 in Figures 1 and 2. The emissions estimated using method 2 are similar in pattern but differ quantitatively. We see immediately from Figure 1 that the bulk of the emissions occur in the tropics, with concentrations in the Amazonian Basin, equatorial Africa, and the Indonesian archipelago. We estimate that 84% of all emissions occur between latitudes of (30° (if we drop the threshold temperature to 0 °C, this percentage drops to 64%). This is consistent with reports that suggest there may be a missing methane source over this region (21). Global emissions peak during the northern hemisphere summer due to its greater continental landmass and foliage biomass. During the months of June, July, and August, the northern hemisphere’s continental landmasses (>30° N) contribute nearly 40% of the global emissions, but they contribute less than 15% of the world’s annual emissions (Figure 2). During the winter months in each hemisphere, emissions are restricted to latitudes lower than 30°, while in the summer, emissions in the northern hemisphere extend northwards of 60°. The latitudinal cutoff in emissions is largely a consequence of our choice to define a minimum temperature, below which we assume plant emissions do not occur. The smaller leaf biomass during the winter months also limits
the latitudinal extent of the emissions, but this plays only a secondary role since the evergreen coniferous forest prevalent at high latitudes still contributes leaf matter during the winter months. If we categorize the emissions based on land cover type (Figure 3), 41% of the total are from grasslands and wooded grasslands, while another 32% are from broadleaf evergreen forests. The only other land type of major significance is croplands, which contributes 10% of the global emissions. There are small differences between these values and those calculated using method 2: 31%, 42%, and 12%, respectively. These distributions are comparable to those found by Keppler et al. (5), who estimate tropical forests (roughly equal to our broadleaf evergreen forests) and grasslands respectively contribute about 50% and 26% of the total. Emissions from Non-Wetlands. The possibility exists that if this novel plant source is real, it may already be partly included in the flux from wetlands and rice paddies. According to this thought, only a fraction of the calculated emissions should be considered new, with the remaining fraction folded into the previously known and measured emissions. We estimate what the upper limit to this latter fraction may be by tallying the plant emissions that occur on land areas designated as either wetlands or rice paddies. We VOL. 41, NO. 11, 2007 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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FIGURE 4. Sensitivity of the historic pyrogenic source (Sp) to the strength of the plant leaf flux (SL). Pyrogenic sources are calculated for the time period 1700-1800 A.D. from the ice core methane record assuming different annual emissions from the plant source. If plant emissions exceed 64 Tg CH4 y-1, pyrogenic emissions are forced below zero, which is evident if we assume plant emissions are 149 Tg CH4 y-1. It is likely that pyrogenic emissions are near 10 Tg CH4 y-1 during this time, which constrains the plant emissions to be no larger than 25 Tg CH4 y-1. This agrees with our mean bottom-up estimate from methods 1 and 2 using a threshold temperature of 20 °C. use the one-degree gridded natural wetland and rice paddy areas that are included in the IGBP global emissions inventory (GEIA) (22, 23). Using the emissions from method 1 we find that 8.8 Tg CH4 out of the annual 36 Tg CH4 is from these land areas, which leaves a minimum of 27 Tg CH4 or 76% of the total plant emissions that are not included in the global budget. This percentage increases to 78% if we use the emissions estimated using a minimum temperature of 0 °C as only 15 Tg CH4 out of 69 Tg CH4 lie within these regions. Thus, even if the measured methane release from rice fields and wetlands already includes flux from the plant source, the majority of this source is still unaccounted for in the present methane budget as it is released from non-flooded regions. Historical Constraints from the Ice Core Record. Measurements of δ13CH4 in the Law Dome ice-core of Antarctica have recently been used to constrain the pyrogenic and biogenic sources of methane during the late preindustrial Holocene (0 to 1700 A.D.) (24). Based on these isotope measurements and the cotemporaneous atmospheric methane record, pyrogenic and biogenic emissions are estimated to be 25 and 195 Tg CH4 y-1, respectively, during the period 0 to 1000 A.D (24). The strength of the pyrogenic emissions is somewhat surprising as it is nearly twice the size of previous estimates (25, 26) but falls to 15 Tg CH4 y-1 by the year 1700 A.D. How do these emissions change if we now consider the terrestrial vegetation source and include it in the source reconstruction during this time? Following (24) we use a onebox nonequilibrium atmosphere model (27) to estimate δ13C of the global methane source from the ice-core measurements. The model includes isotopic fractionation due to differences between the reaction rates of OH with 12CH4 and 13CH . To ensure that differences between the pyrogenic and 4 biogenic emissions computed here and those reported above are due only to the inclusion of the plant emissions, we adopt model parameter values from Ferretti et al. (24): k13/k12 ) 0.9926, τ ) 7.6 y, SF ) 20 Tg y-1, δ13Cbiogenic) -60‰ (-57 to -63‰), δ13Cpyrogenic ) -20‰ (-12 to -25‰, for C4 and C3 plants respectively, C3/C4 ) 60:40), and δ13Cfossil ) -40‰ (-35 to -40‰), where kn is the rate coefficient between OH and isotope nCH4, τ is the methane atmospheric lifetime, SF is the late pre-industrial Holocene rate of methane emissions from fossil fuels, δ13Cx is the δ13C value for source x, and the δ13C ranges in parentheses are uncertainty ranges. We add to this mix δ13Cleaf ) -50‰, which is the reported weighted mean δ13C value for leaf emissions assuming a C3/C4 plant 4036
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ratio of 60:40 (5). We parameterize the isotope and atmospheric methane ice-core records with fits that produce correlation coefficients better than 0.99 and use these as inputs to the model. Over the period 0 to 1000 A.D., the fit to the isotope record is near constant at δ13C ) -47.3‰. During this same period the modeled δ13CH4 of the global methane source is -54‰. If we set the plant emissions to zero and run the model, the respective pyrogenic and biogenic emissions are 24 and 192 Tg CH4 y-1 (during 0 to 1000 A.D.), nearly identical to the above emissions as required. As we increase the plant emissions from zero, the pyrogenic and biogenic emissions decrease as necessary to balance the source and isotope budget. In fact, as we continue to increase the plant emissions above a time-dependent threshold, the budgets can only be satisfied if the pyrogenic emissions dip to below zero. This is so because plant emissions are enriched in 13CH4 relative to the global source, which requires a concurrent reduction in the even more enriched pyrogenic source. To satisfy this constraint and ensure pyrogenic emissions are positive, we estimate plant emissions must be less than 90 Tg CH4 y-1 during the period 0-1000 A.D and less than 64 Tg CH4 y-1 during 1700-1800 A.D., when 13CH4 is most depleted (Figure 4). Furthermore, it is more reasonable to constrain plant emissions to rates that produce pyrogenic emissions of at least 10 Tg CH4 y-1 and not zero, since pre-industrial biomass burning and wildfires are thought to contribute at least this amount (25, 26). With this new constraint, annual emissions from plants cannot exceed 28 (54) Tg CH4 y-1 during 17001800 (0-1000) A.D. (Figure 4) and certainly must be lower than the initial range of 62-236 Tg CH4 y-1 (5). If we assume plant emissions are the mean of this latter range (149 Tg CH4 y-1) the predicted pyrogenic emissions drop to -21 Tg CH4 y-1, which is clearly unphysical as it turns the pyrogenic source to a sink. Our constraints are consistent with those estimated by Ferretti et al. (11) (46 Tg CH4 y-1) who use the same methane record, but assume weaker fractionation for the OH sink (k13/k12 ) 0.9939), which would tend to explain their larger plant emissions. This also explains in large part the higher emissions (85 Tg CH4 y-1) estimated by Houweling et al. (10) during this period, who use k13/k12 ) 0.9961 for their model calculations. We find then that using the most stringent of the δ13CH4 constraints, that plant emissions cannot exceed 25 Tg CH4 y-1. The results of our re-analysis of the ice core record also corroborate our bottom-up estimates (20-69 Tg CH4 y-1)
from above. In addition, if we set plant emissions to be the mean of this range (45 Tg CH4 y-1) and run the atmospheric model over the steady-state years of 0-1000 A.D., the predicted pyrogenic emissions during this time are 12 Tg CH4 y-1. This compares better to the expected flux of 15 Tg CH4 y-1 (26) relative to the predicted flux from a model run with no plant source (24 Tg CH4 y-1). It is possible that not only is the magnitude of the plant flux consistent with the known methane budget, but it also brings the budget into better agreement with expectations. The predicted biogenic emissions, which include contributions from wetlands, termites, ruminants, and rice agriculture, are 170 Tg CH4 y-1, which is consistent with estimates of this source (25, 26). Thus these results combined with those from our extrapolations support the view that emissions from terrestrial plants are modest and can be readily accommodated in the methane budget.
Acknowledgments We thank the members of the Global Change Research Program at Portland State University for valuable discussions. We thank Wenze Yang at Boston University for the use and support of the MODIS LAI data sets. The net primary production maps were acquired from the University of New Hampshire, EOS-WEBSTER Earth Science Information Partner (ESIP). This research was supported by the Office of Science (BER), U.S. Department of Energy, Grant No. DEFG02-04ER63913.
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Received for review October 6, 2006. Revised manuscript received March 9, 2007. Accepted March 26, 2007. ES062404I
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