Asian monsoon precipitation changes and the Holocene methane anomaly

Abstract

It has been suggested that late-Holocene human activities caused the increase in atmospheric methane (CH₄) concentration that otherwise would have been a naturally decreasing trend. As one of the places where rice farming originated, China has been considered to play a significant role in pre-industrial changes in atmospheric CH₄ concentrations. To establish the climatic context since the first rice cultivation and to evaluate the relative roles of monsoon climate and rice cultivation on late Holocene CH₄ rise, we synthesized climate data from China to examine the Holocene trends in monsoon precipitation. The results show high monsoon rainfall from 10,000 to 7000 years ago, and declining precipitation in the late Holocene as shown by most reconstructions. The decreasing trend in monsoon precipitation is consistent with that in other north tropical monsoon regions, and is opposite to the trend in CH₄ concentrations. After ruling out several other natural factors and estimating CH₄ emissions from early rice farming, we conclude that the late-Holocene methane increase has been significantly influenced by the expansion of early rice paddy fields during the period of declining monsoon precipitation.

Keywords

anthropogenic hypothesis China Holocene methane monsoon precipitation rice paddies

Introduction

Atmospheric CH₄ concentrations gradually decreased during the early Holocene and then reversed direction ~5000 years ago (Blunier et al., 1995). Based on comparison with CH₄ changes in several former interglacials and rejection of natural forcings, some researchers (Ruddiman, 2003; Ruddiman and Thompson, 2001) suggested that the atmospheric CH₄ concentrations would have declined gradually during the middle and late Holocene as a result of orbital forcing in the absence of anthropogenic intervention.

Because agriculture developed very early in China, and because China has historically been home to a substantial fraction of the world’s population, the early anthropogenic hypothesis proposes that China played a significant role in pre-industrial anthropogenic changes (Ruddiman, 2003, 2007; Ruddiman et al., 2008). Irrigated rice paddies have been proposed as an important anthropogenic source of atmospheric CH₄. By compilation of archaeological sites in rice growing regions of China, our earlier study (Ruddiman et al., 2008) found that between 6000 and 4000 years ago the number of new sites increased almost ten-fold, and spread across most of the area in China where irrigated rice is growing today (Figure 1a). The time coincides with the increase of atmospheric CH₄ concentrations around 5000 years ago. Along the rapid expansion of rice farming in Asia at around 5000 and 3000 years ago (Fuller et al., 2011; Li et al., 2009), the results give strong support to the view that early human activity may have significantly affected atmospheric CH₄ concentrations, although accurate, quantitative estimates of CH₄ emissions are still difficult to establish.

Figure 1.

Maps of archeological sites with rice remains in China and the sites of monsoon rainfall records. (a) Spread of rice remains in China by 4000 years ago (data from Ruddiman et al., 2008). (b) Map showing the location of the sites used in this paper (see Table 1 for site information and references; map modified from Zhou et al., 2008). The discontinuous line indicates the northern front of the summer monsoons.

Rice cultivated in artificial wetlands (paddies), not in natural ones, plays a key role in anthropogenic CH₄ emissions (Zhou and Guo, 2009). If monsoon precipitation declined during the middle to late Holocene, the continuous expansion of rice farming during the period could indicate the development of paddies that would be responsible for increases in anthropogenic CH₄ emissions. So the climatic background is crucial for studying the contribution of early rice farming to the CH₄ increases.

On the other hand, one key premise of Ruddiman’s early anthropogenic hypothesis (Ruddiman, 2003) is that CH₄ changes were mainly controlled by the low-latitude monsoon precipitation. China is located in the largest monsoon region – the Asian monsoon region, which can be divided into the East Asian Monsoon region and the Indian Monsoon region. Variations in monsoon precipitation in different parts of China during the Holocene are considered to have different trends (An et al., 2000; Hong et al., 2005). So an averaged change in trends of monsoon precipitation in China is needed to compare with that in other monsoon regions and to test the hypothesis.

Here we summarize terrestrial records of Holocene monsoon precipitation changes in China, in part to provide a climatic context for anthropogenic developments, and in part to test some aspects of the early anthropogenic hypothesis.

Data and methods

Monsoon rainfall records

Past changes in amounts of monsoon rainfall in China have been reconstructed by using different geologic data, such as loess-paleosol sequences, lacustrine and swamp deposits, cave deposits, ice cores and river delta deposits. The accuracy of the reconstructions can be adversely affected by dating uncertainties and by discontinuities in the records, so records without reliable dating were not used in the present study. All of the records selected are high-resolution and well constrained by ¹⁴C, OSL (optically stimulated luminesence) and Th dating, and span at least 6000 years. The data set includes 17 records of monsoon rainfall available from the published literature. The location of these sites is shown in Figure 1b and listed in Table 1.

Table 1.

List of sites of Holocene monsoon precipitation proxies used.

Site no.	Site name	Latitude	Longitude	Monsoon precipitation proxy	Dating method	Number of dates	Region	References
1	Selincuo Lake	31°45′N	88°51′E	Carbonate δ¹⁸O	¹⁴C	5	Monsoon Margin	Gu et al. (1993)
2	Qinghai Lake	36°53′N	100°10′E	Carbonate δ¹⁸O	AMS ¹⁴C	6	Monsoon Margin	Liu et al. (2007)
				Pollen	AMS ¹⁴C	6		Shen et al. (2005)
3	Hongyuan Peat	32°46′N	102°30′E	Peat cellulose δ¹³C	AMS ¹⁴C	15	Indian Monsoon	Hong et al. (2003)
4	Xingyun Lake	24°20′N	102°47′E	Carbonate δ¹⁸O	AMS ¹⁴C	7	Indian Monsoon	Hodell et al. (1999)
5	Dongge Cave	25°17′N	108°05′E	Stalagmite δ¹⁸O	²³⁰Th	55	Indian Monsoon	Wang et al. (2005); Yuan et al. (2004)
6	Yaoxian	34°53′N	108°45′E	Loess magnetic susceptibility	Optically stimulated luminesence	7	East Asian Monsoon	Zhao et al. (2007)
7	Jiuxian Cave	33°34′N	109°06′E	Stalagmite δ¹⁸O	²³⁰Th	26	East Asian Monsoon	Cai et al. (2010)
8	Shanbao Cave	31°40′N	110°26′E	Stalagmite δ¹⁸O	²³⁰Th	15	East Asian Monsoon	Wang et al. (2008)
9	Heshang Cave	30°27′N	110°25′E	Stalagmite δ¹⁸O	U-Th	21	East Asian Monsoon	Hu et al. (2008)
10	Lianhua Cave	29°29′N	109°32′E	Stalagmite δ¹⁸O	²³⁰Th	10	East Asian Monsoon	Cosford et al. (2009)
11	Daihai Lake	40°35′N	112°40′E	TOC, Pollen	AMS ¹⁴C	8	Monsoon Margin	Xiao et al. (2004, 2006)
12	Bayanchagan Lake	41°65′N	115°21′E	Pollen	AMS ¹⁴C	7	Monsoon Margin	Jiang et al. (2006)
13	Pearl Estuary	22°23′N	113°53′E	Organic matter δ¹³C	AMS ¹⁴C	4	East Asian Monsoon	Zong et al. (2006)
14	Dahu Swamp	24°46′N	115°02′E	Organic matter δ¹³C	¹⁴C	9	East Asian Monsoon	Zhong et al. (2010)
15	Hani Peat	42°13′N	126°31′E	Peat cellulose δ¹³C	AMS ¹⁴C	9	East Asian Monsoon	Hong et al. (2005, 2009)

The selected time series of monsoon rainfall are based on pollen records, total organic carbon (TOC) and carbonate δ¹⁸O record from lake deposits, δ¹³C from organic material in estuarine sediments, stalagmite δ¹⁸O, and other records. All sites are located within the Asian monsoon zone in China (Figure 2). Each proxy is linked to summer-monsoon rainfall variability through various mechanisms, but each is also affected by processes that complicate this interpretation. Although the interpretation of some individual records is still controversial, they have mostly been interpreted as proxies for monsoon precipitation. Some of the factors affecting the reliability of the proxies are discussed briefly below.

Figure 2.

Records of monsoon rainfall used in this paper (see Table 1 for site information and references).

In monsoon regions of China, vegetation is largely correlated with precipitation and temperature. At the margin of the monsoon region, trees are particularly sensitive to variations in monsoon precipitation. Hence, tree pollen percentages at sites on the margins of monsoon influence can be used as good indicators of, or as a basis to reconstruct monsoon rainfall changes (Jiang et al., 2006; Shen et al., 2005). Thus we here selected several pollen records from lake sediments in the monsoon marginal zone, although pollen concentration changes, in the late Holocene, might also have been influenced by human activities. TOC in lake sediment has been interpreted as a proxy for fluvially transported organic matter, which is mainly controlled by monsoon rainfall, and therefore may be used to infer monsoon rainfall changes (Xiao et al., 2006).

Although δ¹⁸O values of lacustrine authigenic carbonates depend on the combination of inflow isotopic composition, evaporation processes from the lake surface and the carbonate crystallization temperature, in the monsoon domain, shifts in δ¹⁸O values have been mainly attributed to monsoon precipitation changes (Wei and Gasse, 1999). Thus three time series have been selected in present study.

In past decades, loess magnetic susceptibility has been widely used as an indicator of monsoon precipitation changes (An et al., 1990), because fine-grained magnetic minerals that enhanced magnetic susceptibility mainly arise from pedogenic processes that are controlled by monsoon precipitation changes (Zhou et al., 1990). Care is needed in interpreting magnetic susceptibility signals from loess solely in climatic terms as they may be complex in origin (Deng et al., 2004). Here, one record with precise dating has been selected.

Because δ¹³C values of Hongyuan peat, Hani peat and Dahu swamp all fall in the range of δ¹³C values for C3 plants (Hong et al., 2003, 2005; Zhong et al., 2010), it has been considered that the Hongyuan peat, Hani peat and Dahu swamp consist of the C3 series plants. The δ¹³C value of C3 plants is dependent on monsoon rainfall in these regions, therefore δ¹³C values of peat cellulose and organic matter have been used as indicators of monsoon rainfall changes (Hong et al., 2003, 2005; Zhong et al., 2010). At the same time, however, the δ¹³C value of C3 plants can also be affected by other factors, such as temperature and atmospheric CO₂ concentrations (Ehleringer et al., 1997).

In the Pearl River Estuary, δ¹³C values of organic matter are controlled by the balance between marine sources with lower δ¹³C values and fresh water aquatic plants with higher δ¹³C values. They can thus be used as indicators of monsoon rainfall changes, which have controlled the freshwater discharge (Zong et al., 2006). This proxy may also have been affected by other factors such as sea level changes.

During recent years stalagmite δ¹⁸O values with precise dating have been widely accepted as proxies for monsoon precipitation changes. The reasons for this are as follows: (1) most of the precipitation influencing the stalagmite δ¹⁸O changes is summer monsoon rainfall (Wang et al., 2001), (2) the effect of temperature on stalagmite δ¹⁸O changes is small (Wang et al., 2001), (3) trends in 50 yr and 150 yr instrumental rainfall records are consistent with the stalagmite δ¹⁸O signals (He et al., 2005; Liu et al., 2008; Zhou et al., 2010), and (4) the dominant 20-ka period on orbital timescale in stalagmite δ¹⁸O records is the typical monsoon rainfall period induced by low-latitude insolation (Wang et al., 2008). Other studies have argued that stalagmite records might be influenced by both summer and winter monsoons (Clemens et al., 2008); however, the proxies they used for comparison are not dated precisely, and so the phase relationship among different proxies requires further study.

Stacking method

The ‘stacking’ method of Clemens and Prell (2003) has been used to extract an estimate of the information common to all the varying climate signals. We use this method here to reconstruct generalized Holocene monsoon rainfall trend in China. The values and trends shown are calculated at 500 yr intervals, using interpolation as required. Each record was also normalized to unit variance. The various time series were then grouped into three major subdivisions within the monsoon regions in China: the East Asian monsoon region, the southwestern Indian monsoon region, and the monsoon margin (Figure 2, Table 1). To equally stack the time series, we first averaged the same type of proxies in each region. The acquired records were afterwards averaged by region to get regional climate signals, which were then normalized and averaged to obtain stacked proxies.

Results

The stacked proxy of monsoon precipitation (see Figure 4a) shows an increasing trend in the early Holocene prior to 10,000–9500 years ago, with maximum values from ~10,000 to 6000 years ago, consistent with the time of the Holocene Optimum in China (Duan et al., 2009). After ~7000 years ago, the monsoon stack record shows a decreasing trend, with some increase during the last 1000 years, as noted by some other studies (Severinghaus et al., 2009). Our new reconstruction is consistent with the earlier synthesized moisture changes inferred from pollen data in eastern monsoonal China (Zhao et al., 2009) and some other monsoon proxies in other monsoonal regions (Fleitmann et al., 2003; Gupta et al., 2003), implying a similar monsoon precipitation trends over large areas.

The records selected also show different trends, especially the timing for the Holocene Optimum (Figure 3), and multiple interpretations have been offered in the literatures (An et al., 2000; Long et al., 2010; Xiao et al., 2008). During the late Holocene, trends from different records are also variable. For example, monsoon precipitation recorded in Lake Bayanchagan and Hani Peat increased in the past 4000 years, but other records show different trends (Figure 3). The results further suggest that the reconstruction of monsoon precipitation would be affected by other factors, such as snow/ice input to lakes (Xiao et al., 2008). However, the ‘stack’ method will highlight the common signal, likely representing monsoon precipitation.

Figure 3.

Comparison of the stacked proxies with other indices and climate forcings. (a) Reconstructed monsoon precipitation trend with ±1 s.d. uncertainty (black thick line with grey shading) compared with synthesized time series of relative moisture changes from fossil pollen data across eastern monsoonal China (dashed line in black, Zhao et al., 2009) and the earlier reconstructions based on data from outside China (dashed line in grey, Fleitmann et al., 2003; solid line in grey, Gupta et al., 2003). (b) Comparison of the reconstructed monsoon precipitation trend (grey shading indicates the ±1 s.d. uncertainty) with the atmospheric CH₄ (solid line in grey, Blunier et al., 1995) and 30°N summer insolation changes (dashed line in grey, Berger, 1978).

Discussion

Monsoon precipitation in China and atmospheric CH₄ concentration

Monsoon intensities, driven by the land–ocean thermal contrast, are controlled by the low-latitude insolation on orbital timescale (Kutzbach et al., 2008; Wang, 2006). Trends of monsoon precipitation changes in the Northern Hemisphere would thus decrease during the middle to late Holocene following the changes of low-latitude Northern Hemispheric insolation. Geological records from Northern Hemispheric monsoon regions consistently show gradually decreasing trend, as is concluded by earlier studies (Burns, 2011; COHMAP Members, 1988), confirming the former inference. In addition, as induced by the more intense and frequent El Niños, the Southeast Asia, a major tropical peatland region, became drought, reinforcing the interpretation of a reduced contribution of tropical wetlands as CH₄ sources (Yu, 2011).

A recent study (Bloom et al., 2010) showed that CH₄ emissions in the tropics are controlled by the water-table depth, so the trend of atmospheric CH₄ changes would follow that of the monsoon precipitation changes, as Guo et al. (2011) proposed. During the interval between 10,000 and 5000 BP, the generally declining trend of our reconstructed monsoon precipitation in China is consistent with that of CH₄. This coherent relationship further supports the view that orbital-scale CH₄ variations are primarily controlled by the strength of tropical monsoons (Blunier et al., 1995; Brook et al., 1996; Chappellaz et al., 1990). So although wetlands in China are not the largest sources of atmospheric CH₄, the decreasing trend of monsoon precipitation in China during the middle to late Holocene can represent the whole Northern Hemisphere with respect to CH₄.

The decreased monsoon precipitation in Northern Hemisphere would thus not have contributed to the increase of atmospheric CH₄ observed during the late Holocene. Thus the CH₄ rise in the late Holocene might instead be ascribed to some other factors.

Rejection of some natural sources

After considering and ruling out several natural sources (e.g. boreal peatlands and tropical natural wetlands), Ruddiman and Thomson (2001) proposed that human activities, especially early rice farming, should be invoked to explain the CH₄ anomaly during the past 5000 years. Although natural forcings have been rejected (Ruddiman, 2005, 2007; Ruddiman and Thomson, 2001; Ruddiman et al., 2008), contrary views have been repeatedly expressed.

Ruddiman and Thomson (2001) had suggested that forcing from northern peatlands growth could be ruled out by the changes in the interpolar CH₄ gradient, which decreased in the late Holocene. Moreover, the slow expansion of wetlands in northern high-latitude regions during the late Holocene further opposed ascribing the CH₄ reversal to circum-Arctic wetlands (MacDonald et al., 2006). But a recent study has shown extensive expansion of high-latitude peatlands from 5000 years ago, suggesting that northern peatlands cannot be neglected when seeking causes for the late-Holocene rise in CH₄ (Korhola et al., 2010). However, this is not supported by a more detailed study of the interpolar CH₄ gradient (Brook and Mitchell, 2007), which decreased post 4800 years ago, confirming the early suggestion that forcing by northern peatland growth could be ruled out as a major contributor to the CH₄ anomaly in the late Holocene.

Recently, the increase of CH₄ during the past 2000 years has been ascribed to the upturn in monsoon precipitation forced by increased May–June 30°N insolation (Severinghaus et al., 2009). But this interpretation is not supported for the following reasons. First, only some of the monsoon proxies show the increasing trend (Figure 3), the causes of which should be further explored. Second, the upturn in atmospheric CH₄ concentrations began about 5000 years ago, 3000 years earlier than that in May–June 30°N insolation. Third, the amplitude of the insolation increase is far smaller than that of the CH₄ changes. Moreover, the slowdown in the rate of natural tropical peatlands expansion during the late Holocene (Yu et al., 2010) suggests that the CH₄ increase should not be attributed to changes in low-latitude insolation. Thus the wetlands in river deltas/coastal regions in northern tropics can also be rejected as major influences on the Holocene CH₄ anomaly, as Ruddiman et al. (2008) concluded.

Generally, monsoon precipitation in the Northern Hemisphere decreased gradually during the late Holocene, but some geological records (Cruz et al., 2005; Partridge et al., 1997) indicate that the south hemispheric monsoon precipitation followed the insolation curve for 30°S, showing an inverse trend to that in the Northern Hemisphere. These results suggest that it is still not clear what role wetlands in the Southern Hemisphere have played in the changes in atmospheric CH₄ concentrations, as noted by Brook (2009). To date, the Southern Hemispheric wetlands still could not be conclusively rejected, as changes in the natural non-peat-forming wetlands are not clear. But the low carbon accumulation of peatlands in the Southern Hemisphere (Yu et al., 2010) indicates that, as suggested by Ruddiman and Thomson (2001), CH₄ emissions from tropical wetlands in the Southern Hemisphere do not provide a plausible explanation for the CH₄ increase of the last 5000 years.

The contribution of early rice farming to atmospheric CH₄ concentration

A recent modeling study using only natural forcing mechanisms has been able to show the increases in CH₄ during the late Holocene, suggesting that early agricultural activities may not be needed to account for the late-Holocene CH₄ increases (Singarayer et al., 2011). As discussed above and noted in earlier studies (Fuller et al., 2011; Li et al., 2009; Ruddiman et al., 2008), the well-known expansion of rice farming in Asia as a source of CH₄ could not be ignored.

Here we estimate the CH₄ emissions from rice paddies in China between 7000 and 3000 years ago by using a simple approach based on human population changes, rice productions and per square meter CH₄ emissions, to further study the contribution of early rice farming to the CH₄ increase. Li et al. (2009) have reconstructed the prehistoric populations in China by data compilation from archaeological sites, and their results are consistent with the earlier studies (Biraben, 2003). So we selected the reconstructed results by Li et al. (2009) as our basis of calculation. According to the spatial and temporal distribution of rice farming (Ruddiman et al., 2008) and the number of archaeological sites (Li et al., 2009), the human populations feed by rice farming were acquired at 500 yr interval. The personal rice acquirement of 216 kg/yr (Wu, 1985) was used to calculate total rice acquirement. Historians and archaeologists have also reconstructed average per-area yield of rice at different times since about 7000 years ago (Wu, 1985; Zhao, 2002). Rice productivity before 3000 years ago can be estimated from these data by a non-linear scaling method, and the areas of rice farming can thus be calculated. Because there was only single harvest rice before about 2000 years ago (Wang, 1982), and the distribution of early rice farming are centered at the lower and middle Yangtze Valley, average CH₄ emission flux from single harvest paddies of seven provinces in these regions was chosen for our estimation.

Our results (Figure 4d) show that CH₄ emissions from paddies in China were less than 0.6 Tg/yr between 7000 and 5000 years ago, then increased abruptly to about 1.8 Tg/yr. The trend is consistent with that of site number of rice remains (Ruddiman et al., 2008) and estimated rice distribution area (Li et al., 2009). The results are also consistent with the reconstructions by Fuller et al. (2011), for China has the largest areas of paddies in prehistorical times (Fuller et al., 2011; Li et al., 2009). However, the slight decreasing of CH₄ emissions between 4500 and 3000 years ago is inconsistent with the expansion of rice farming at that time periods recorded by the historical literatures. The bias might be caused by (1) the imprecision of the estimation of rice productions per area, and (2) the inconsideration of tool using, an important factor affected rice farming areas, as mentioned by Fuller et al. (2011).

Figure 4.

Early rice farming and the late Holocene CH₄ increase. (a) Anthropogenic CH₄ emissions in the late Holocene (modified from Ruddiman, 2007). (b) Estimated yearly CH₄ emissions from paddies (Fuller et al., 2011). (c) Estimated rice distribution area in the Holocene (Li et al., 2009). (d) Estimated prehistorical CH₄ emissions from paddies in China.

According to the early anthropogenic hypothesis (Ruddiman, 2007), the estimated anthropogenic CH₄ emission at around 4000 years ago is about 21 Tg/yr calculated from 70 ppbv atmospheric CH₄. Our estimation of about 1.8 Tg/yr is far less than that the value. However, if the paddy areas in China were about one-third of the global ones at that time, as indicated by Li et al. (2009) and Fuller et al. (2011), the global CH₄ emissions from paddies should be about 5.4 Tg/yr, which is about 25% of the anthropogenic emissions estimated by the early anthropogenic hypothesis (Figure 4a). Inferring the spatial variation of land use efficiency for rice cultivation, Fuller et al. (2011) have estimated CH₄ emissions in the late Holocene by using GIS model, the results suggested that rice CH₄ emissions increased rapidly, especially in the past 3000 years, and reached 8.7–22.5 Tg/yr, about 13% to 36% of the anthropogenic emissions at ad 1000. The results are in good agreement with the possible CH₄ emissions of 18–27 Tg/yr¹ from paddies in ad 1500 in Asia estimated by Ruddiman (2007) by a non-linear tying to human population. Thus the early anthropogenic hypothesis is supported by these estimates.

Other anthropogenic sources, such as livestock, human waste and biomass burning, could also contribute to the CH₄ increase, as inferred by Ruddiman (2003, 2007). In addition, Fuller et al. (2011) also suggested that CH₄ emissions from ungulate livestock could be even larger than rice farming in prehistory. So anthropogenic CH₄ emissions after 5000 years ago would have significant contributions to the atmospheric CH₄ increase. If the early anthropogenic sources are not required to account for the late-Holocene CH₄ increase as Singarayer et al. (2011) indicated, the atmospheric CH₄ concentrations would be higher than what is observed.

As mentioned above, the early rice farming carried out in natural wetlands or paddies is central to reconstructing early anthropogenic CH₄ emissions. The large expansion of rice agriculture occurred during the middle to late Holocene (Figure 1a), but during this time, monsoon precipitation declined. Archaeologists interpret most of the early rice as having been irrigated (Ling et al., 2005) in view of the high water requirements. Without irrigation and paddy formation, the climatic trend (less and less monsoon rainfall) would have been inimical to the early rice farming.

Water-management systems, such as wells and irrigated canals, appeared between 7000 and 6000 years ago (Hunan Provincial Institute of Cultural Relics and Archaeology, 1999; Udatsu et al., 1998). To date, Neolithic paddy-fields have been found not only in the middle and lower valley of the Yangtze River, but also in the lower valley of the Yellow River (Jin et al., 2007; Zhou et al., 2005), where dry farming is observed in modern times. These observations further reinforce the view that the development of irrigated systems of rice farming against a background of declining monsoon rainfall made a significant contribution to the CH₄ increase during the middle to late Holocene.

Conclusions

Our stacked climate records suggest a declining trend in monsoon rainfall in China during the middle to late Holocene. The monsoon weakening in China during the past 10,000 years matches the trend expected from the orbital monsoon hypothesis of Kutzbach (1981), but its continued weakening after 5000 BP, which is consistent with that in northern tropics, is opposed to the trend in CH₄ concentrations. After ruling out several other natural factors and estimating CH₄ emissions from early rice farming, we conclude that the late-Holocene CH₄ anomaly has been significantly influenced by the expansion of early paddy-fields against the background of a weakening monsoon system and declining precipitation.

Footnotes

Acknowledgements

I thank Zhengtang Guo, Bill Ruddiman, Haibin Wu and three anonymous reviewers for detailed comments and suggestions. I also thank Frank Oldfield and Zicheng Yu for useful comments and improving the language.

This work is supported by the Natural Science Foundation of Anhui Province (Grant No. 11040606Q48).

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Asian monsoon precipitation changes and the Holocene methane anomaly

Abstract

Keywords

Introduction

Data and methods

Monsoon rainfall records

Stacking method

Results

Discussion

Monsoon precipitation in China and atmospheric CH4 concentration

Rejection of some natural sources

The contribution of early rice farming to atmospheric CH4 concentration

Conclusions

Footnotes

Acknowledgements

References

Monsoon precipitation in China and atmospheric CH₄ concentration

The contribution of early rice farming to atmospheric CH₄ concentration