Peatlands Have the Potential to Emerge as Significant Contributors to Future Climate Warming

Introduction. Methane and carbon dioxide are the most important greenhouse gases, the increase in the concentration of which in the atmosphere is the main cause of climate change [Taylor and Penner, 1994; Drösler et al., 2014; Hoegh-Guldberg et al., 2019]. In addition to relatively constant sources of methane and carbon dioxide into the atmosphere (such as oligotrophic bogs of the boreal zone), there are sporadic sources (SS): intermittently flooded floodplains, boreal swamp forests, some intermittently swamp forests, etc. Despite the variability of SS as sources of methane, CH4 fluxes in floodplains and in swamp forests can reach 0.1–12.5 [Whalen et al., 1991; Van Huissteden et al., 2005; Terentieva et al., 2019] and 0.7 – 17.1 mgC m-2 h-1 [Moore and Knowles, 1990; Ambus and Christensen, 1995; Aronson et al., 2012; Koskinen et al., 2016; Glagolev et al., 2018], respectively. These values are comparable, and exceed those observed in bogs under certain conditions (a combination of soil moisture and temperature, and other factors) [Gulledge and Schimel, 2000; Vasconcelos et al., 2004; Ullah and Moore, 2011; Shoemaker et al., 2014; Christiansen et al., 2017; Torga et al., 2017; Glagolev et al., 2018; Mochenov et al., 2018]. Unfortunately, in Russia, studies of CH4 and CO2 fluxes from sporadic sources are extremely limited (one-time measurements were performed without reference to spatial, seasonal, and interannual variability of conditions) and were carried out mainly in Western Siberia [Sabrekov et al., 2013; Mochenov et al., 2018; Glagolev et al., 2018; Terentieva et al., 2019] and the European part of Russia [Kuznetsov and Bobkova, 2014; Ivanov et al., 2018; Glukhova et al., 2021; Glukhova et al., 2022]. In general, medium-scale (at the Federal subject level) studies of bogs and forests in Russia have not been carried out in all regions, although they are of particular interest due to the possibility of maintaining a balance between the detailing of estimates and the magnitude of spatiotemporal coverage [Zatsarinnaya and Volkova, 2011; Grishutkin et al., 2013; Baisheva et al., 2015; Ilyasov et al., 2019; Suslova, 2019]. Besides, estimates made throughout the country require clarification at the regional level [Vompersky et al., 2005]. The aim of our work was the simplest inventory of swamp forests of the Moscow region as sources of CH4 and CO2 using GIS mapping and field measurements.
 Objects and methods. The basis for the map of swamp forests of the Moscow region (hereinafter, by this term we mean the total territory of Moscow and the Moscow region) was a mosaic of 6 Landsat-8 satellite images. The mapping was carried out using the Supervised Classification algorithm in the Multispec program (Purdue Research Foundation, USA). For each decryption class, at least 7 training polygons were set and the classification module was launched using the maximum likelihood estimation. After the classification, the decryption classes were combined into typological ones: “forest” (automorphic forests), “water surfaces” (rivers, lakes, other water bodies), “swamp forest” (excessively moist forests with a water table level (WTL), predominantly located on the soil surface or close to it) and “wet forest” (excessively moist forests with predominant WTL below the soil surface). We considered the classes of swamp forests and wet forests, regardless of the presence or absence of peat layer in them: the key criterion was WTL. To assess the accuracy of the classification, an error matrix was compiled. For that purpose, on the resulting map, the first operator identified 75 points evenly distributed in space within each typological class; the coordinates of these points without specifying the belonging to the class were randomly sorted and passed to the second operator. Further, the points were assigned to one of the mapped classes based on “blind” visual expert interpretation using ultra-high resolution satellite images. The overall classification accuracy was determined as the ratio of the sum of points, whose mapped and real classes coincide, to the total number of points (Table 1).
 Measurements of carbon dioxide and methane fluxes were carried out from 2019 to 2022 in the Dorokhovo mixed black alder moist grass forest, located 66 km west of the border of Moscow, using the static chamber method [Hutchinson and Mosier, 1981; Terent'eva et al., 2017]. Opaque chambers were used in the measurements, so the term “CO2 flux” used in the paper implies the sum of the respiration of the soil-grass-moss cover. The calculation of the annual flux of methane and carbon dioxide from the swamp forests of the Moscow region was performed seasonally using the simplest inventory method [Glagolev, 2010]:
 ФОРМУЛА НЕ РИСУНОК
 where Aij – is the area (m2) occupied by the i-th source type in the j-th region; fi – is the surface flux density (mgC m-2 h-1), characteristic of the i-th source type; Tj – is the duration of the emission period (hour), characteristic of the j-th region. The duration of the methane emission period within individual seasons was taken on the basis of hydrothermal coefficients and the radiation index as follows: summer – 122 days (from June to September inclusive), autumn – 76 days (from October to mid-December), winter – 90 days (from mid-December to mid-March), spring – 77 days (from mid-March to the end of May). The surface flux density was calculated as the median (and also 1Q, 3Q) for the considered season based on all observations.
 Results. The resulting map of swamp forests of the Moscow region is shown in Figure 1 and is characterized by the following areas of typological classes: “forest” - 2,157,716 ha, “water surfaces” 45,693 - ha, “swamp forest” - 58,384 ha, “wet forest” - 233,865 ha. Thus, the total share of forest ecosystems that are able to function as sources of methane - swamp forests and wet forests - is 1.2 and 5.0% of the region's area, respectively (in total 292,249 ha). According to the map, swamp forests are predominantly small ecosystems (from small ones with an area of 3-5 ha, which are extremely widespread, to larger ones, with an area of 30-50 ha, which are somewhat less common), which are exposed to excessive moisture as a result of their location on the outskirts of wetland massifs, near river floodplains, in small local relief depressions, as well as in elements of a ravine-gully planting (mainly in the southern part of the Moscow region). Wet forests are located in more drained areas, often associated with swamp forests in a single landscape structures, but they are much more widespread, and often occupy significantly larger areas: from 10–50 to 100–500 ha.
 The error matrix of the resulting map is presented in Table. 1. The overall classification accuracy (the ratio of the sum of the elements of the main diagonal of the error matrix to the sum of checkpoints by class) is 76%. Water surfaces with the highest possible producer’s accuracy (100%) are most accurately identified. The “other” class has the same user’s accuracy as water surfaces (93%), but poorly less producer’s accuracy (74%). In general, the classes of swamp and wet forests are the least accurately defined (36–46%): they have significant intersections with all classes except that for the open water surface, and, most importantly, with each other. In order to achieve a reasonable classification accuracy and to make further calculations of the regional flow, we combined the “swamp forest” and “wet forest” classes into one: in this case, the user’s accuracy of the combined class was 65%, and the producer’s accuracy was 74%, which allows us to fairly accurately predict the location of forests of varying degrees of waterlogging when they are considered together.
 Generalized results of measurements of methane and carbon dioxide fluxes by seasons and their brief statistical characteristics are presented in Table. 2. The simplest inventory based on the proposed approach makes it possible to estimate the methane flux from the soils of swamp forests with different degrees of waterlogging at 6666 tC yr-1 (1Q – 407; 3Q – 38790); carbon dioxide at 1.5 MtC yr-1 (1Q – 0.6; 3Q – 2.7). Taking into account the 100-year global warming potential for methane equal to 28 [Drösler et al., 2014], the total emission of methane and carbon dioxide from the soils of swamp forests with different degrees of waterlogging was 5.7 MtCO2-eq yr-1 (1Q – 2.2; 3Q – 11.4)[1]. More detailed information obtained on the basis of the simplest inventory presents in table 3.
 Discussion. According to the data of the Great Russian Encyclopedia [Osipov et al., 2004], the area of automorphic forests in the Moscow region in 2015 amounted to 1,896,000 ha, which is in good agreement with the data obtained based on the current classification (the area of the “forest” class amounted to 2,157,716 ha). The distribution of swamp forests in the north of the Moscow region, observed on the resulting map, corresponds to swamp black alder, downy birch forests, as well as forests with gray alder on the map of G.N. Ogureeva et al. [1996]. In the southeastern part of the Moscow region, the areas occupied by swamp forests, according to the results of satellite data classification, are identical to the distribution of downy birch and pine-spruce-long-moss-sphagnum forests along the edges of wetlands. Wet forests are located to the south of the Ruza Reservoir correspond to spruce forests with gray alder, whereas those located to the northwest of the town of Klin are associated with black alder forests and pine-spruce forests with black alder (Ogureeva et al., 1996). The area occupied by swamp and wet forests identified in the current work is comparable to that of distribution of forests with black and gray alder (5.01 and 1.44% of the area of the region) provided in (Kotlov and Chernenkova, 2020), which indirectly confirms the assessment adequacy of the share of the territory occupied by wetland forest ecosystems identified in our work.
 One of the main problems of GIS cartography based on remote sensing data is the poor availability of ground-based data or the inability to check map errors by field methods due to the wide coverage of the study area. However, the classification accuracy of 60-70% is the rule rather than the exception [Kotlov and Chernenkova, 2020] and is considered satisfactory. We anticipate that GIS mapping that combines multiple cartographic sources at its core (for example, by calculating a median estimate based on multiple maps) will improve the final result in the future.
 Conclusion. The total area of swamp forests and wet forests in the Moscow Region is 292,249 ha. The emission of methane from these ecosystems is 0.25 (1Q – 0.02; 3Q – 1.45) MtCO2-eq per year, whereas that of carbon dioxide is 5.40 (1Q – 2.16; 3Q – 9.92) MtCO2 per year. The highest total emission of methane and carbon dioxide from wetlands is observed in the summer-autumn period, gradually decreasing by the beginning of winter and increasing again (to the level of autumn values) in spring. The value of the total emission of the main carbon-containing gases from the soils of swamp forests of the European part of the Russian Federation should be taken into account when quantifying all significant sources and sinks.
 
 [1] The annual total methane flux was calculated as follows: the median of measurements for each of the season (0.14, 0.74, 0.02 and 0.25 mgC m-2 h-1, for summer, autumn, winter and spring, respectively) was multiplied by the number of hours in days, by the corresponding length of the season (122, 76, 90 and 77 days), then by the wetland forest area (2.922×109 m2), and finally by a correction factor (10-9) to convert mgC to tC. The annual total carbon dioxide flux was calculated in a similar way (the difference was in the value of the correction factor, which was 10–15 for converting mgC to MtC). When converting the CH4 flux (expressed in tC yr-1) to MtCO2-eq yr-1, the original value was multiplied by 16/12 (the ratio of the molar mass of CH4 to the molar mass of C), then by 28 (100-year global warming potential) and, finally, by a correction factor (10-6) to convert tons to megatons. To calculate the total flux consisting of emissions of CH4 (MtCO2-eq year-1) and CO2 (MtC year-1), the latter was multiplied by 44/12 (the ratio of the molar mass of CO2 to the molar mass of C) and added.

Phosphate oxygen isotope evidence for methylphosphonate sources of methane and dissolved inorganic phosphate

Identifying the sources and sinks of methane and carbon dioxide is important for understanding processes within the Earth's climate system. This paper attempts to use back trajectories to identify sources of atmospheric methane and carbon dioxide as measured by high resolution in situ gas analyzers during aircraft ascents and descents in Southern Australia. Results from the back trajectory analysis were confirmed by also performing a forward trajectory analysis on some of the data. The in situ aircraft measurements were part of a joint Japanese‐Australia field campaign in March and April 2007 near Adelaide, South Australia. The vertical profiles showed considerable variation in methane and carbon dioxide content above the planetary boundary layer. We used back trajectories based on an atmospheric transport model to derive the origin of the air masses which enabled speculation about sources of the gases. We were thus able to identify emission from the volcanoes on Réunion Island in the Indian Ocean and the seafloor hydrothermal activity in the Southeast Indian Ridge, confirming speculations published earlier by other research teams.

Methane emission from wetland trees is an overlooked source of methane, with poor resolution of their global significance and mechanisms. Our ongoing work in the Amazon basin has revealed that wetland trees are the largest source of methane, emitting the equivalent of all the methane emitted from the Arctic. Factors controlling and mechanisms driving these emissions remain unclear. Tree stem surfaces are no longer considered passive conduits for soil-produced methane; instead, they are active surfaces driving both methane production and oxidation.Over the past five years, using methane flux measurements, wood incubation experiments, stable carbon isotopic composition of methane measurements and wood structure and traits analysis, we attempt to unravel the following questions:  Where is methane produced? How is methane transported and emitted from the tree stems? What controls the flux strength of methane eventually released at the stem surface?So far, results suggest that soil is the predominant source of tree stem-released methane; however, certain tree species display strong internal methane production, increasing from the wet to dry season. The methane transport pathway is also tree species-specific, with some trees showing strong evidence of diel variability and others displaying minimal to zero diel variability. Internal wood methane concentration and stable isotopic measurements corroborate this. A strong presence of tree-methane oxidation was observed, which again was tree species-specific, despite the net fluxes measured at the stem surface always being positive. Methane oxidation within the tree stems was dominant, with methane oxidation in the bark only playing a minor role. Wood structure and traits analysis revealed that wood density could be used as a proxy to predict stem methane fluxes at an ecosystem level. However, species-level variability was controlled by other species-specific wood traits, making it harder to fully explain the variability we observe in methane emitted at the stem surface. 

Terrestrial ecosystems currently sequester about one third of anthropogenic CO2 emissions each year, an important ecosystem service that dampens climate change. The future fate of this net uptake of CO2 by land based ecosystems is highly uncertain. Most ecosystem models used to predict the future terrestrial carbon cycle share a common architecture, whereby carbon that enters the system as net primary production (NPP) is distributed to plant compartments, transferred to litter and soil through vegetation turnover and then re-emitted to the atmosphere in conjunction with soil decomposition. However, while all models represent the processes of NPP and soil decomposition, they vary greatly in their representations of vegetation turnover and the associated processes governing mortality, disturbance and biome shifts. Here we used a detailed second generation dynamic global vegetation model with advanced representation of vegetation growth and mortality, and the associated turnover. We apply an emulator that describes the carbon flows and pools exactly as in simulations with the full model. The emulator simulates ecosystem dynamics in response to 13 different climate or Earth system model simulations from the Coupled Model Intercomparison Project Phase 5 ensemble under RCP8.5 radiative forcing. By exchanging carbon cycle processes between these 13 simulations we quantified the relative roles of three main driving processes of the carbon cycle; (I) NPP, (II) vegetation dynamics and turnover and (III) soil decomposition, in terms of their contribution to future carbon (C) uptake uncertainties among the ensemble of climate change scenarios. We found that NPP, vegetation turnover (including structural shifts, wild fires and mortality) and soil decomposition rates explained 49%, 17% and 33%, respectively, of uncertainties in modelled global C-uptake. Uncertainty due to vegetation turnover was further partitioned into stand-clearing disturbances (16%), wild fires (0%), stand dynamics (7%), reproduction (10%) and biome shifts (67%) globally. We conclude that while NPP and soil decomposition rates jointly account for 83% of future climate induced C-uptake uncertainties, vegetation turnover and structure, dominated by biome shifts, represent a significant fraction globally and regionally (tropical forests: 40%), strongly motivating their representation and analysis in future C-cycle studies.

Marine hydrocarbon seeps are sources of methane and carbon dioxide to the ocean, and potentially to the atmosphere, though the magnitude of the fluxes and dynamics of these systems are poorly defined. To better constrain these variables in natural environments, we conducted the first high-resolution measurements of sea surface methane and carbon dioxide concentrations in the massive natural seep field near Coal Oil Point (COP), California. The corresponding high resolution fluxes were calculated, and the total dissolved phase air-sea fluxes over the surveyed plume area (∼363 km(2)) were 6.66 × 10(4) to 6.71 × 10(4) mol day(-1) with respect to CH4 and -6.01 × 10(5) to -5.99 × 10(5) mol day(-1) with respect to CO2. The mean and standard deviation of the dissolved phase air-sea fluxes of methane and carbon dioxide from the contour gridding analysis were estimated to be 0.18 ± 0.19 and -1.65 ± 1.23 mmol m(-2) day(-1), respectively. This methane flux is consistent with previous, lower-resolution estimates and was used, in part, to conservatively estimate the total area of the dissolved methane plume at 8400 km(2). The influx of carbon dioxide to the surface water refutes the hypothesis that COP seep methane appreciably influences carbon dioxide dynamics. Seeing that the COP seep field is one of the biggest natural seeps, a logical conclusion could be drawn that microbial oxidation of methane from natural seeps is of insufficient magnitude to change the resulting plume area from a sink of atmospheric carbon dioxide to a source.

Abstract. The source and sinks of carbon dioxide (CO2) and methane (CH4) due to anthropogenic and natural biospheric activities were estimated for the South Asian region (Bangladesh, Bhutan, India, Nepal, Pakistan and Sri Lanka). Flux estimates were based on top-down methods that use inversions of atmospheric data, and bottom-up methods that use field observations, satellite data, and terrestrial ecosystem models. Based on atmospheric CO2 inversions, the net biospheric CO2 flux in South Asia (equivalent to the Net Biome Productivity, NBP) was a sink, estimated at −104 ± 150 Tg C yr−1 during 2007–2008. Based on the bottom-up approach, the net biospheric CO2 flux is estimated to be −191 ± 193 Tg C yr−1 during the period of 2000–2009. This last net flux results from the following flux components: (1) the Net Ecosystem Productivity, NEP (net primary production minus heterotrophic respiration) of −220 ± 186 Tg C yr−1 (2) the annual net carbon flux from land-use change of −14 ± 50 Tg C yr−1, which resulted from a sink of −16 Tg C yr−1 due to the establishment of tree plantations and wood harvest, and a source of 2 Tg C yr−1 due to the expansion of croplands; (3) the riverine export flux from terrestrial ecosystems to the coastal oceans of +42.9 Tg C yr−1; and (4) the net CO2 emission due to biomass burning of +44.1 ± 13.7 Tg C yr−1. Including the emissions from the combustion of fossil fuels of 444 Tg C yr−1 for the 2000s, we estimate a net CO2 land–atmosphere flux of 297 Tg C yr−1. In addition to CO2, a fraction of the sequestered carbon in terrestrial ecosystems is released to the atmosphere as CH4. Based on bottom-up and top-down estimates, and chemistry-transport modeling, we estimate that 37 ± 3.7 Tg C yr−1 were released to atmosphere from South Asia during the 2000s. Taking all CO2 and CH4 fluxes together, our best estimate of the net land–atmosphere CO2-equivalent flux is a net source of 334 Tg C yr−1 for the South Asian region during the 2000s. If CH4 emissions are weighted by radiative forcing of molecular CH4, the total CO2-equivalent flux increases to 1148 Tg C yr−1 suggesting there is great potential of reducing CH4 emissions for stabilizing greenhouse gases concentrations.

The quasi-two-dimensional mean effective concentration fields and mean effective fields of methane and carbon dioxide sources and sinks in the region of the Kara and Barents seas are analyzed. The fields were retrieved using the instrumental and computational atmospheric fluid-location technology (passive remote sensing using wind) based on measurements of the surface concentrations on the island of Belyi during the summer months of 2016 and 2017. The concept of the emission and uptake flux disbalance index is introduced, which quantitatively characterizes a degree of the impact of the regional greenhouse gas sources and sinks on the climate system. Estimates of the index are performed for two greenhouse gases for the region of the Barents and Kara seas, which was an emitter of methane (the flux disbalance index is 2.15 and 1.61, respectively) and a sink of carbon dioxide (0.75 and 0.92, respectively), in the summers of 2016 and 2017.

Abstract. Natural peatlands are important carbon sinks and sources of methane (CH4). In contrast, drained peatlands turn from a carbon sink to a carbon source and potentially emit nitrous oxide (N2O). Rewetting of peatlands thus potentially implies climate change mitigation. However, data about the time span that is needed for the re-establishment of the carbon sink function by restoration are scarce. We therefore investigated the annual greenhouse gas (GHG) balances of three differently vegetated sites of a bog ecosystem 30 years after rewetting. All three vegetation communities turned out to be sources of carbon dioxide (CO2) ranging between 0.6 ± 1.43 t CO2 ha−2 yr−1 (Sphagnum-dominated vegetation) and 3.09 ± 3.86 t CO2 ha−2 yr−1 (vegetation dominated by heath). While accounting for the different global warming potential (GWP) of CO2, CH4 and N2O, the annual GHG balance was calculated. Emissions ranged between 25 and 53 t CO2-eq ha−1 yr−1 and were dominated by large emissions of CH4 (22–51 t CO2-eq ha−1 yr−1), with highest rates found at purple moor grass (Molinia caerulea) stands. These are to our knowledge the highest CH4 emissions so far reported for bog ecosystems in temperate Europe. As the restored area was subject to large fluctuations in the water table, we assume that the high CH4 emission rates were caused by a combination of both the temporal inundation of the easily decomposable plant litter of purple moor grass and the plant-mediated transport through its tissues. In addition, as a result of the land use history, mixed soil material due to peat extraction and refilling can serve as an explanation. With regards to the long time span passed since rewetting, we note that the initial increase in CH4 emissions due to rewetting as described in the literature is not inevitably limited to a short-term period.

What mechanisms mediate the flow of energy and cycling of nutrients during ecological succession? Are they linked in time and across space? In 1969, Eugene P. Odum proposed a series of hypotheses that caused the ecological community to think critically about patterns and processes (sensu Watt 1947) during ecological succession and how they might be linked in a causal manner. Odum’s perspective on the process of succession, or “the strategy of ecosystem development” as he termed it, was undoubtedly shaped by the intellectual influence of his mentor, Victor Shelford, as well as Shelford’s contemporaries such as Fredrick Clements. They shared the idea that ecological communities possessed emergent properties, wherein the whole is greater than the sum of its parts (sensu Phillips 1934). Inasmuch, the 24 hypotheses Odum (1969) articulated were an amalgam of holism and reductionism that created his rationale for the way energy flows and nutrients cycle within ecosystems. It is within this context that Peter Vitousek and Bill Reiners derived ideas that are fundamental to our understanding of energy flow and nutrient cycling in terrestrial ecosystems, ideas that have profoundly shaped my thinking as an ecologist.

We investigated whether rates of net primary production (NPP) and biomass turnover of floating grasses in a central Amazon floodplain lake (Lake Calado) are consistent with published evidence that CO2 emissions from Amazon rivers and floodplains are largely supplied by carbon from C4 plants. Ground‐based measurements of species composition, plant growth rates, plant densities, and areal biomass were combined with low altitude videography to estimate community NPP and compare expected versus observed biomass at monthly intervals during the aquatic growth phase (January–August). Principal species at the site were Oryza perennis (a C3 grass), Echinochloa polystachya, and Paspalum repens (both C4 grasses). Monthly mean daily NPP of the mixed species community varied from 50 to 96 g dry mass m−2 day−1, with a seasonal average (±1SD) of 64±12 g dry mass m−2 day−1. Mean daily NPP (±1SE) for P. repens and E. polystachya was 77±3 and 34±2 g dry mass m−2 day−1, respectively. Monthly loss rates of combined above‐ and below‐water biomass ranged from 31% to 75%, and averaged 49%. Organic carbon losses from aquatic grasses ranged from 30 to 34 g C m−2 day−1 from February to August. A regional extrapolation indicated that respiration of this carbon potentially accounts for about half (46%) of annual CO2 emissions from surface waters in the central Amazon, or about 44% of gaseous carbon emissions, if methane flux is included.

PDF HTML阅读 XML下载 导出引用 引用提醒 新疆天山高寒草原不同放牧管理下的CO2,CH4和N2O通量特征 DOI: 10.5846/stxb201209221338 作者: 作者单位: 中国科学院干旱区生物地理与生物资源重点实验室 中国科学院新疆生态与地理研究所;中国科学院研究生院;中国农业大学资源与环境学院,中国科学院干旱区生物地理与生物资源重点实验室 中国科学院新疆生态与地理研究所,中国科学院干旱区生物地理与生物资源重点实验室 中国科学院新疆生态与地理研究所,中国科学院干旱区生物地理与生物资源重点实验室 中国科学院新疆生态与地理研究所,中国科学院新疆生态与地理研究所 中国农业大学资源与环境学院,中国科学院干旱区生物地理与生物资源重点实验室 中国科学院新疆生态与地理研究所,中国科学院干旱区生物地理与生物资源重点实验室 中国科学院新疆生态与地理研究所 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金资助项目（41005001）；国家重点基础研究发展计划（973）资助项目（2009CB825103）；中国科学院百人计划资助项目（304）资助 The fluxes of carbon dioxide, methane and nitrous oxide in alpine grassland of the Tianshan Mountains, Xinjiang Author: Affiliation: Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences,,,,Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences. College of Resources and Environmental Sciences, China Agricultural University.,, Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:以中国科学院新疆巴音布鲁克草原生态站为依托，于2010年5月-2011年10月利用静态箱-气相色谱法对短期禁牧（2005年围封）、长期禁牧（1984年围封）和自由放牧（冬季放牧）3种草地的CO2、CH4、N2O气体通量进行了野外连续试验研究。结果表明：新疆天山高寒草原对CO2，CH4和N2O通量表现出明显的季节排放特点。在植物的生长季（5-10月），新疆天山高寒短期禁牧、长期禁牧和自由放牧草原的CO2通量平均值分别为：（89.8±49.3）、（52.8±28.7）、（57.0±30.7）mg · m-2 · h-1，CH4通量平均值分别为：（-66.3±21.3）、（-104.5±32.8）、（-103.0±39.0）μg · m-2 · h-1，N2O通量平均值分别为：（21.2±11.8）、（13.6±6.9）、（13.2±6.2）μg · m-2 · h-1；短期禁牧草原与长期禁牧和自由放牧草原CH4平均通量具有显著性差异（P < 0.05），但CO2和N2O差异不显著（P > 0.05）。在植物的非生长季（11月-翌年4月），新疆天山高寒短期禁牧、长期禁牧以及自由放牧草原的3种温室气体的通量较低且差异均不显著。 Abstract:With growing concerns on impacts of human activities and global warming on Alpine grasslands, comprehensive understanding of the sources and sinks of greenhouse gases becomes increasingly more important. The understanding is closely related to the progress on biogeochemical cycles of carbon and nitrogen in terrestrial ecosystems. Carbon dioxide, methane and nitrous oxide are the three most important greenhouse gases, which are considered to account for 80% contribution to global warming potential. The alpine grassland of Xinjiang is a typical temperate arid region of grasslands. The study was conducted at the Bayinbuluk Grassland Eco-system Research Station, Chinese Academy of Sciences(83°43'E,42°54'N). Bayinbuluk alpine grassland is located in the southern Tianshan mountains. Xinjiang Uygur AutonoMous Region, central Asia and covers a total area of approximately 2.3×104 km2. Bayinbuluk alpine grassland is the typical temperate arid alpine grassland, which is the second largest grassland of China after Inner Mongolia Grassland. As we all know, the grassland ecosystem has degenerated seriously and grazing prohibition is a frequently-used solution to prevent grass grassland degradation. While, it is still unknown that grazing prohibition impacts greenhouse gases fluxes in some degree. The study of carbon dioxide, methane and nitrous oxide of long-term grazing-prohibition grass(1984), short-term grazing-prohibition grass(2005) and free grazing grass in Bayinbuluk alpine grassland is meaningful, which will deepen our understanding of greenhouse gases fluxes in the alpine grassland ecosystem, help us assess global warming, parameterize Earth System models and get more comprehensive grasp of the impact of grazing prohibition on the grassland ecosystem. Using opaque, static, manual stainless steel chambers and gas chromatography, the fluxes of carbon dioxide, methane and nitrous oxide of long-term grazing-prohibition grass, short-term grazing-prohibition grass and free grazing grass were measured through the continuous experiment in situ from May 2010 to October 2011(no sampling in January and February 2011 because of the very low temperatures, about -40℃). Four times per month during the growing season(from May to October) and twice per month during non-growing (from November to next year April) season at all sites. According to the results of field experiment, the alpine grassland of Xinjiang is the sources of carbon dioxide and nitrous oxide; it is the sinks of methane. In the growing season, CO2 average fluxes of short-term grazing-prohibition, long-term grazing-prohibition and free grazing are (89.8±49.3),(52.8±28.7), (57.0±30.7)mg · m-2 · h-1; CH4 fluxes averaged out to (-66.3±21.3), (-104.5±32.8), (-103.0±39.0) μg · m-2 · h-1; CH4 fluxes averaged out to (21.2±11.8), (13.6±6.9), (13.2±6.2) μg · m-2 · h-1. Our results indicated that: (1) Nitrous oxide fluxes showed a significant correlation with carbon dioxide fluxes in three kinds of grasslands. (2) In the growing season, the difference of greenhouse gases fluxes between long-term grazing-prohibition grass and free grazing grass were not significant, while short-term grazing-prohibition grass has higher fluxes of carbon dioxide and nitrous oxide and lower fluxes of methane. (3) In growing season, the fluxes of methane of short-term grazing-prohibition grass showed significant difference with long-term grazing-prohibition grass and free grazing grass. But the difference of growing-season average carbon dioxide and nitrous oxide fluxes did not reach the significance level of 0.05. (4) In non-growing season, no significant differences between the fluxes of carbon dioxide, methane and nitrous oxide were found in long-term grazing-prohibition grassland, short-term grazing-prohibition grassland and free grazing grassland. 参考文献 相似文献 引证文献

Spatial variability in rates of net primary production (NPP) and onset of the spring bloom in Greenland shelf waters

We present a model for prediction of pedogenic environments and soil properties based on energy input to the soil system. The model estimates rates of precipitation and net primary production (NPP) energy input using the Parameter‐Regression Independent Slope Model (PRISM) climate data, and a parent material index (PMI). Soil order, soil C, and clay data from the State Soil Geographic (STATSGO) database were compared with rates of NPP and precipitation energy input for major geographic regions of the continental USA, including California, Oregon, Washington, Texas, North Dakota, Alabama, Pennsylvania, and New Hampshire. Soil orders in all states show differences in total energy input ( E in , kJ m −2 yr −1 ) and the percentage of E in from NPP (% E npp ) (e.g., Ultisols E in = 29915, % E npp = 49%; Mollisols E in = 5880, % E npp = 90%). Using linear regression models, rates of NPP estimated ( R 2 = 0.82***) trends in soil C content in western states, but failed to estimate soil C in other geographic areas. Parent material index adjusted energy flux estimated soil clay content for the majority (99.5%) of igneous parent materials in California and Oregon ( R 2 = 0.67**), the only states with digital geologic data. The model underestimated clay content in steeply sloping Inceptisols and Andisols (0.5% of igneous land area). Results suggest that rates of NPP may be used to estimate soil C for climate regimes with steep environmental gradients. Landscape age and stability components might improve clay prediction in young and erosive landscapes. Modeled energy input provides a tool for estimating pedogenic environments, soil order, and soil properties. Energy input parameters may aid efforts to pre‐map broad landscape units for soil survey.

Methane is a powerful greenhouse gas and is estimated to be responsible for approximately one-fifth of man-made global warming. Per kilogram, it is 25 times more powerful than carbon dioxide over a 100-year time horizon -- and global warming is likely to enhance methane release from a number of sources. Current natural and man-made sources include many where methane-producing micro-organisms can thrive in anaerobic conditions, particularly ruminant livestock, rice cultivation, landfill, wastewater, wetlands and marine sediments. This timely and authoritative book provides the only comprehensive and balanced overview of our current knowledge of sources of methane and how these might be controlled to limit future climate change. It describes how methane is derived from the anaerobic metabolism of micro-organisms, whether in wetlands or rice fields, manure, landfill or wastewater, or the digestive systems of cattle and other ruminant animals. It highlights how sources of methane might themselves be affected by climate change. It is shown how numerous point sources of methane have the potential to be more easily addressed than sources of carbon dioxide and therefore contribute significantly to climate change mitigation in the 21st century.