Rapid climate change and intensified human activities have resulted in water table lowering (WTL) and enhanced nitrogen (N) deposition in Tibetan alpine wetlands. These changes may alter the magnitude and direction of greenhouse gas (GHG) emissions, affecting the climate impact of these fragile ecosystems. We conducted a mesocosm experiment combined with a metagenomics approach (GeoChip 5.0) to elucidate the effects of WTL (-20 cm relative to control) and N deposition (30 kg N ha-1 yr-1 ) on carbon dioxide (CO2 ), methane (CH4 ) and nitrous oxide (N2 O) fluxes as well as the underlying mechanisms. Our results showed that WTL reduced CH4 emissions by 57.4% averaged over three growing seasons compared with no-WTL plots, but had no significant effect on net CO2 uptake or N2 O flux. N deposition increased net CO2 uptake by 25.2% in comparison with no-N deposition plots and turned the mesocosms from N2 O sinks to N2 O sources, but had little influence on CH4 emissions. The interactions between WTL and N deposition were not detected in all GHG emissions. As a result, WTL and N deposition both reduced the global warming potential (GWP) of growing season GHG budgets on a 100-year time horizon, but via different mechanisms. WTL reduced GWP from 337.3 to -480.1 g CO2 -eq m-2 mostly because of decreased CH4 emissions, while N deposition reduced GWP from 21.0 to -163.8 g CO2 -eq m-2 , mainly owing to increased net CO2 uptake. GeoChip analysis revealed that decreased CH4 production potential, rather than increased CH4 oxidation potential, may lead to the reduction in net CH4 emissions, and decreased nitrification potential and increased denitrification potential affected N2 O fluxes under WTL conditions. Our study highlights the importance of microbial mechanisms in regulating ecosystem-scale GHG responses to environmental changes.
Abstract Subsoils contain >50% of soil organic carbon (SOC) globally yet remain under‐investigated in terms of their response to climate changes. Recent evidence suggests that warmer, drier conditions in alpine grasslands induce divergent responses in SOC decomposition and carbon accrual in top‐ versus subsoils. However, longer term effects on microbial activity (i.e., catabolic respiration vs. anabolic growth) and belowground carbon cycling are not well understood. Here we utilized a field manipulation experiment on the Qinghai‐Tibetan Plateau and conducted a 110‐day soil incubation with and without 13 C‐labeled grass litter to assess microbes' role as both SOC “decomposers” and “contributors” in the top‐ (0–10 cm) versus subsoils (30−40 cm) after 5 years of warming and drought treatments. Microbial mineralization of both SOC and added litter was examined in tandem with potential extracellular enzyme activities, while microbial biomass synthesis and necromass accumulation were analyzed using phospholipid fatty acids and amino sugars coupled with 13 C analysis, respectively. We found that warming and, to a lesser extent, drought decreased the ratio of inorganic nitrogen (N) to water‐extractable organic carbon in the subsoil, intensifying N limitation at depth. Both SOC and litter mineralization were reduced in the subsoil, which may also be related to N limitation, as evidenced by lower hydrolase activity (especially leucine aminopeptidase) and reduced microbial efficiency (lower biomass synthesis and necromass accumulation relative to respiration). However, none of these effects were observed in the topsoil, suggesting that soil microbes became inactive and inefficient in subsoil but not topsoil environments. Given increasing belowground productivity in this alpine grassland under warming, both elevated root deposits and diminished microbial activity may contribute to new carbon accrual in the subsoil. However, the sustainability of plant growth and persistence of subsoil SOC pools deserve further investigation in the long term, given the aggravated N limitation at depth.
Abstract Evidence for ungauged large freshwater palaeofloods in valley‐confined landscapes frequently includes giant flow‐eddy bars, deposited in alcoves along the floodway margins. Elevations of the bar tops commonly are used to define the minimum water level for computational flood simulations. Field study has shown that giant bar stratigraphy and sedimentology can be distinctive; identifying the alluvial signature of large palaeofloods where the morphological evidence may be less clear. However, whether the shape and stratigraphy of eddy bars provide indicators as to the nature of the floodwaves has not been considered widely. Flood hydrographs might be dam‐break surge waves, gradually varied, or steady flows, for example. Yet, if bar form and stratigraphy vary systematically with the nature of the flood wave, then bars have additional value in defining the style of unrecorded floodwaves for environmental interpretation and flood modelling purposes. An experimental water flume was used to reproduce three styles of scaled floodwave that might be associated with sudden and more protracted releases of water from upstream reservoirs. Discharge was through a channel consisting of a series of contractions and expansions. Eddy bars were deposited within the flow separation zones that formed at each flow expansion. The basic hydraulic characteristics of the floodwaves were recorded and the form of the bars and the stratigraphy were examined. The results indicate that each style of flood deposited a distinctive barform and related stratigraphy. In this manner, we demonstrate that the examination of the form and stratification of giant bars in the natural environment can provide information on the style of the palaeoflood – sudden release or protracted flow – that was responsible for the deposition of the bars. Such information assists with the identification and interpretation of the nature and source of the floodwater as well as informing attempts to model hydrograph shapes.
Abstract The vast wetlands on the Tibetan Plateau are expected to be an important natural source of methane (CH 4 ) to the atmosphere. The magnitude, patterns and environmental controls of CH 4 emissions on different timescales, especially during the nongrowing season, remain poorly understood, because of technical limitations and the harsh environments. We conducted the first study on year‐round CH 4 fluxes in an alpine wetland using the newly developed LI‐COR LI‐7700 open‐path gas analyzer. We found that the total annual CH 4 emissions were 26.4 and 33.8 g CH 4 m −2 in 2012 and 2013, respectively, and the nongrowing season CH 4 emissions accounted for 43.2–46.1% of the annual emissions, highlighting an indispensable contribution that was often overlooked by previous studies. A two‐peak seasonal variation in CH 4 fluxes was observed, with a small peak in the spring thawing period and a large one in the peak growing season. We detected a significant difference in the diurnal variation of CH 4 fluxes between the two seasons, with two peaks in the growing season and one peak in the nongrowing season. We found that the CH 4 fluxes during the growing season were well correlated with soil temperature, water table depth and gross primary production, whereas the CH 4 fluxes during the nongrowing season were highly correlated with soil temperature. Our results suggested that the CH 4 emission during the nongrowing season cannot be ignored and the vast wetlands on the Tibetan plateau will have the potential to exert a positive feedback on climate considering the increasing warming, particularly in the nongrowing season in this region.
Land use/cover (LUC) datasets are the basis of global change studies and cross-scale land planning. Data fusion is an important direction for correcting errors and improving the reliability of multisource LUC datasets. In this study, a new fusion method based on Bayesian fuzzy probability prediction was developed, and a case study was conducted in five countries of the Indochina Peninsula to form a fusion dataset with a resolution of 30 m in 2020 (BeyFusLUC30). After precision and uncertainty analysis, it was found that: (1) using accuracy validation information as prior knowledge and considering spatial relations can be well applied to LUC data fusion. (2) When compared to the four source datasets (LSV10, GLC_FCS30, ESRI10, and Globeland30), the accuracy indices of BeyFusLUC30 are all optimal. The average overall consistency increased by 6.42–13.61%, the overall accuracy increased by 4.84–7.11%, and the kappa coefficient increased by 4.98–7.60%. (3) The accuracy of the fusion result improved less for land types with good original accuracy (cropland, forest, water area, and built-up land), and the improved range of F1 score was at least 0.40–2.29%, and at most 6.66–9.88%. For the land types with poor original accuracy (grassland, shrubland, wetland, and bare land), the accuracy of the fusion result improved more, and the F1 score improved by at least 4.02–5.82%, and at most 14.41–48.35%. The LUC dataset fusion and quality improvement method developed in this study can be applied to other regions of the world as well. BeyFusLUC30 can provide reliable LUC data for scientific research and government applications in the peninsula.
Abstract To explore the rheology of dolomite and investigate recent findings regarding the so‐called inversion of activation energy between dislocation and diffusion creep, we compressed medium‐grained Fangshan dolomite (113 ± 42 µm) at effective confining pressures of 50–300 MPa, temperatures of 27°C–900°C, and strain rates of 10 −6 to 2 × 10 −4 s −1 using a Paterson gas‐medium apparatus. Two end‐member deformation regimes with corresponding diagnostic flow laws and microstructures were identified. At temperatures ≤500°C, low‐temperature plasticity (LTP), which is characterized by microstructures of predominant abrupt undulatory extinctions and f‐twins, was determined to dominate the deformation of Fangshan dolomite. The corresponding flow behavior can be described by an with and (Regime 1). At temperatures ≥800°C, dislocation creep, which shows characteristic microstructures of smooth undulating extinction and new recrystallized grains, dominated the deformation of Fangshan dolomite. The corresponding flow behavior can be expressed by a power law equation, with , , and (Regime 2). At temperatures between ∼500 and 800°C, a transition regime between LTP and dislocation creep was identified (Regime 3) with the dependence of flow stress on strain rate increasing gradually with increasing temperature. When extrapolated to natural conditions, our flow law of dislocation creep for dolomite in combination with that of diffusion creep reported by Davis et al. (2008) suggests that the dislocation creep regime of dolomite is limited to a relatively narrow region of high temperature and relatively high stress, whereas the diffusion creep regime dominates the deformation of dolomite in tectonic settings with low stress levels.
Correct simulation of overwinter condition is important for the growth of winter crops and for initial growth of spring crops. The objective of this study was to investigate overwinter soil water and temperature dynamics with the simultaneous heat and water (SHAW) model and with its linkage to the root zone water quality model (RZWQM), a hybrid model of RZWQM and SHAW (RZ-SHAW) in a Siberian wildrye grassland under two irrigation treatments (non-irrigation and pre-winter irrigation) in two seasons (2005–2006 and 2006–2007). Experimental results showed that pre-winter irrigation considerably increased soil water content for the top 60-cm soil profile in the following spring, but had little effect on soil temperature. Both SHAW and RZ-SHAW simulated these irrigation effects equally well, which demonstrated a correct linkage between RZWQM and SHAW. Across the treatments and years, the average root mean square deviation (RMSD) for simulated total soil water content (liquid plus frozen) was 0.031 m3 m−3 for both RZ-SHAW and SHAW models, and that for liquid water content alone was 0.028 m3 m−3 for both models. Both models provided better simulation of total and liquid soil water contents under non-irrigation condition than under pre-winter irrigation conditions. On average, RZ-SHAW simulated soil temperature slightly better with an average RMSD of 1.4°C compared to that of 1.8°C by SHAW. Both RZ-SHAW and SHAW simulated the soil freezing process well, but were less accurate in simulating the soil thawing processes, where further improvements are desirable. These simulation results show that the SHAW model is correctly implemented in RZWQM (RZ-SHAW), which adds the capability of RZWQM in simulating overwinter soil conditions that are critical for winter crops.
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