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Quantifying the spatiotemporal patterns of the coordination between ecosystem service supply and demand is vital for regional sustainable development. To reveal the dynamic pattern of the coordination of ecosystem service (ES) supply and demand in the Lhasa River Basin, we quantified the supply of the following four ESs using the InVEST model from 2000 to 2018: carbon sequestration (CS), water conservation (WC), habitat quality (HQ), and soil conservation (SC). Using socio-economic data, including land development degree, GDP, and population density, the ES demand was quantified. The ES supply–demand ratio (ESDR) and coupling coordination degree (CCD) model were used to evaluate the coupling relationship and coordination of ES supply and demand. The spatial autocorrelation analysis was used to determine the spatial correlation and changes in the ES supply–demand coupling coordination degree. The results indicate that the distribution of ESDR exhibited significant spatial heterogeneity. The area with ES supply far greater than demand was always in the upstream area of the Lhasa River, while the ES demand of Chengguan District far exceeded supply. Grasslands and forests were the main contributors to ESDRs, providing positive ESDRs for three services, SC, HQ, and WC, with a total proportion above 80%. From 2000 to 2018, the mismatch between ES supply and demand was gradually spreading upstream, while the upstream areas had a relatively high CCD. The spatial correlations of the CCD in the Lhasa River basin all showed statistically significant differences (p < 0.01). The high–high aggregation areas were concentrated in the northeast of the Lhasa River basin, while the low–low aggregation areas were centered around Chengguan District. This study provides reference values for optimizing the land use spatial patterns in ecologically vulnerable areas with the goal of sustainable development.

Ulcerative colitis (UC) has attracted much attention for its negative influence on quality of life and increased risk of colorectal cancer. Chemical and biological drugs are currently the usual treatment for UC. These drugs always induce severe side effects, or patients might become resistant to these therapies. Therefore, new therapeutic options for UC are urgently needed. In this study, we discovered the inhibitory activity of the intestinal tryptophan metabolite indole-3-carboxaldehyde (3-IAld) in dextran sulfate sodium salt (DSS)-induced UC mice by targeting the TLR4/NF-κB/p38 signaling pathway. This compound effectively protected against colon length shortening and damage induced by DSS in the colon, notably reducing the severity of inflammation. The production of inflammatory factors of TNF-α, IL-6, and IL-1β was significantly attenuated when treating with 3-IAld in vivo and vitro. This might be attributed to inhibition of the TLR4/NF-kB/p38 signaling pathway. Moreover, 3-IAld could up-regulate the expression of ZO-1 and Occludin in vivo and vitro. Meanwhile, liquid chromatography mass spectrometry (LC-MS) results showed that 3-IAld could balance the aspartate and glutamate metabolism and the lysine degradation metabolism in the serum of DSS-induced colitis mice. In conclusion, 3-IAld ameliorated the intestinal barrier dysfunction and inflammatory response in DSS-induced UC mice, balanced amino acid metabolism, and inhibited the activation of the TLR4/NF-kB/p38 signaling pathway, thereby protecting mice with colitis.

The effectiveness of piperacillin/tazobactam for managing nosocomial pneumonia caused by extended-spectrum β-lactamase (ESBL)-producing Enterobacteriaceae is unknown. To answer this question, we conducted a retrospective cohort study in two tertiary teaching hospitals of patients admitted between January 2018 and July 2021 with a diagnosis of nosocomial pneumonia caused by ESBL-producing K. pneumoniae receiving either piperacillin/tazobactam or carbapenems within 24 h from the onset of pneumonia for at least 72 h. Clinical outcomes, including 28-day mortality and 14-day clinical and microbiological cure, were analyzed. Of the 136 total patients, 64 received piperacillin/tazobactam and 72 received carbapenems. The overall 28-day mortality was 19.1% (26/136). In the inverse probability of treatment weighted cohort, piperacillin/tazobactam therapy was not associated with worse clinical outcomes, as the 28-day mortality (OR, 0.82, 95% CI, 0.23–2.87, p = 0.748), clinical cure (OR, 0.94, 95% CI, 0.38–2.35, p = 0.894), and microbiological cure (OR, 1.10, 95% CI, 0.53–2.30, p = 0.798) were comparable to those of carbapenems. Subgroup analyses also did not demonstrate any statistical differences. In conclusion, piperacillin/tazobactam could be an effective alternative to carbapenems for treating nosocomial pneumonia due to ESBL-producing K. pneumoniae when the MICs are ≤8 mg/L.

When PINNs solve the Navier–Stokes equations, the loss function has a gradient imbalance problem during training. It is one of the reasons why the efficiency of PINNs is limited. This paper proposes a novel method of adaptively adjusting the weights of loss terms, which can balance the gradients of each loss term during training. The weight is updated by the idea of the minmax algorithm. The neural network identifies which types of training data are harder to train and forces it to focus on those data before training the next step. Specifically, it adjusts the weight of the data that are difficult to train to maximize the objective function. On this basis, one can adjust the network parameters to minimize the objective function and do this alternately until the objective function converges. We demonstrate that the dynamic weights are monotonically non-decreasing and convergent during training. This method can not only accelerate the convergence of the loss, but also reduce the generalization error, and the computational efficiency outperformed other state-of-the-art PINNs algorithms. The validity of the method is verified by solving the forward and inverse problems of the Navier–Stokes equation.

Ocean satellite data are often impeded by intrinsic limitations in resolution and accuracy. However, conventional data reconstruction approaches encounter substantial challenges when facing the nonlinear oceanic system and high-resolution fusion of variables. This research presents a Discrete Satellite Gridding Neural Network (DSGNN), a new machine learning method that processes satellite data within a discrete grid framework. By transforming the positional information of grid elements into a standardized vector format, the DSGNN significantly elevates the accuracy and resolution of data fusion through a neural network model. This method’s innovative aspect lies in its discretization and fusion technique, which not only enhances the spatial resolution of oceanic data but also, through the integration of multi-element datasets, better reflects the true physical state of the ocean. A comprehensive analysis of the reconstructed datasets indicates the DSGNN’s consistency and reliability across different seasons and oceanic regions, especially in its adept handling of complex nonlinear interactions and small-scale oceanic features. The DSGNN method has demonstrated exceptional competence in reconstructing global ocean datasets, maintaining small error variance, and achieving high congruence with in situ observations, which is almost equivalent to 1/12° hybrid coordinate ocean model (HYCOM) data. This study offers a novel and potent strategy for the high-resolution reconstruction and fusion of ocean satellite datasets.

The precise interpolation of oceanic temperature and salinity is crucial for comprehending the dynamics of marine systems and the implications of global climate change. Prior neural network-based interpolation methods face constraints related to their capacity to delineate the intricate spatio-temporal patterns that are intrinsic to ocean data. This research presents an innovative approach, known as the Discretized Spatial Encoding Neural Network (DSE-NN), comprising an encoder–decoder model designed on the basis of deep supervision, network visualization, and hyperparameter optimization. Through the discretization of input latitude and longitude data into specialized vectors, the DSE-NN adeptly captures temporal trends and augments the precision of reconstruction, concurrently addressing the complexity and fragmentation characteristic of oceanic data sets. Employing the North Atlantic as a case study, this investigation shows that the DSE-NN presents enhanced interpolation accuracy in comparison with a traditional neural network. The outcomes demonstrate its quicker convergence and lower loss function values, as well as the ability of the model to reflect the spatial and temporal distribution characteristics and physical laws of temperature and salinity. This research emphasizes the potential of the DSE-NN in providing a robust tool for three-dimensional ocean temperature and salinity reconstruction.

P-wave first-motion polarity is important for the inversion of earthquake focal mechanism solutions. The focal mechanism solution can further contribute to our understanding of the source rupture process, the fault structure, and the regional stress field characteristics. By using the abundant focal mechanism solutions of small and moderate earthquakes, we can deepen our understanding of fault geometry and the seismogenic environment. In this paper, we propose an automatic workflow, FocMech-Flow (Focal Mechanism-Flow), for identifying P-wave first-motion polarity and focal mechanism inversion with deep learning and applied it to the 2021 Yangbi earthquake sequence. We use a deep learning model named DiTingMotion to detect the P-wave first-motion polarity of 2389 waveforms, resulting in 98.49% accuracy of polarity discrimination compared with human experts. The focal mechanisms of 112 earthquakes are obtained by using the CHNYTX program, which is 3.7 times more than that of the waveform inversion method, and the results are highly consistent. The analysis shows that the focal mechanisms of the foreshock sequence of the Yangbi earthquake are highly consistent and are all of the strike-slip type; the focal mechanisms of the aftershock sequence are complex, mainly the strike-slip type, but there are also reverse and normal fault types. This study shows that the deep learning method has high reliability in determining the P-wave first-motion polarity, and FocMech-Flow can obtain a large number of focal mechanism solutions from small and moderate earthquakes, having promising application in fine-scale stress inversion.

The precipitation changes induced by climate warming have substantially increased extreme precipitation and seasonal drought events. Different plant functional types (PFTs) could exert an important role in resisting extreme climate. However, the patterns of plant water uptake in different PFTs remain uncertain, especially under different magnitudes of rainfall events. Here, we employed a stable hydrogen isotope (δD) to determine the water sources of different PFTs, including Castanopsis chinensis in the canopy layer, Schima superba in the canopy sublayer, Psychotria asiatica in the shrub layer, and Blechnum orientale on the forest floor in the monsoon evergreen broad-leaved forest in Dinghushan Biosphere Reserve, China. We further used a two-end linear mixing model to explore the water utilization among different PFTs. Our results revealed that precipitation and soil water before rainfall were the water sources of different PFTs. Furthermore, the proportions of precipitation utilized by S. superba in the canopy sublayer under light and moderate rainfalls were 6.9%–59.4% and 30.5%–66.3%, respectively, which were significantly higher than those of other species in both the dry and wet seasons. After heavy rainfall, the proportion of precipitation utilized by S. superba was the lowest (4.7%–26.5%), while B. orientale had the highest proportion of precipitation utilization (31.6%–91.5%), whether in the dry or wet season. These findings imply that different PFTs would compete with one another for water uptake. Especially under climate warming, the uneven distribution of precipitation would intensify the water competition among species, ultimately resulting in the plant community structure becoming much more unstable than before.

Evapotranspiration (ET) is the primary mechanism of water transformation between the land surface and atmosphere. Accurate ET estimation given complex terrain conditions is essential to guide water resource management in mountainous areas. This study is based on the ETWatch model driven by Sentinel-2 remote sensing data at a spatial resolution of 10 m incorporating a net radiation model considering the impact of a complex terrain. We tested our model with two years of data in two regions with a high relief near the Huairou (2020) and Baotianman (2019) weather stations. Regarding the validation results of the ET model, the coefficient of determination (R2) reached 0.84 in Huairou and 0.86 in Baotianman, while the root mean square error (RMSE) value reached 0.59 mm in Baotianman and 0.82 mm in Huairou. The validation results indicated that the model is applicable in regions with a complex terrain, and the ET results can capture topographic textures. In terms of the slope aspect, the ET value on south-facing slopes is higher than that on north-facing slopes in both study areas. Accurate ET monitoring in mountainous regions with a high relief yields a profound meaning in obtaining a better understanding of the characteristics of heat and water fluxes at different vegetation growth stages and underlying surface types, which can provide constructive suggestions for water management in mountainous areas.

Low light intensity can lead to a decrease in photosynthetic capacity. However, could N-fixing species with higher leaf N contents mitigate the effects of low light? Here, we exposed seedlings of Dalbergia odorifera and Erythrophleum fordii (N-fixing trees), and Castanopsis hystrix and Betula alnoides (non-N-fixing trees) to three irradiance treatments (100%, 40%, and 10% sunlight) to investigate the effects of low irradiance on leaf structure, leaf N allocation strategy, and photosynthetic physiological parameters in the seedlings. Low irradiance decreased the leaf mass per unit area, leaf N content per unit area (Narea), maximum carboxylation rate (Vcmax), maximum electron transport rate (Jmax), light compensation point, and light saturation point, and increased the N allocation proportion of light-harvesting components in all species. The studied tree seedlings changed their leaf structures, leaf N allocation strategy, and photosynthetic physiological parameters to adapt to low-light environments. N-fixing plants had a higher photosynthesis rate, Narea, Vcmax, and Jmax than non-N-fixing species under low irradiance and had a greater advantage in maintaining their photosynthetic rate under low-radiation conditions, such as under an understory canopy, in a forest gap, or when mixed with other species.

Impacts of drought events and nitrogen (N) deposition on forests are increasingly concerning in the context of global climate change, but their effects, in particular, their interactive effects on soil respiration and its components remain unclear. A two-factor random block field experiment was conducted at a subtropical Moso bamboo forest in Southwest China to explore the response of soil respiration (Rs), autotrophic respiration (Ra), and heterotrophic respiration (Rh) to throughfall re-duction and N addition. Our results showed that throughfall reduction significantly decreased Rs, which is mainly attributed to the decrease in Ra as a result of the decline in fine roots biomass. The N addition led to microbial carbon limitation hence significantly decreased Rh, and thus Rs. We also observed the negative effect of throughfall reduction on Rs was exacerbated by N addition, which is attributed to the significant reduction in Ra under the interaction between throughfall reduction N addition. Our findings suggest that Ra tended to respond more sensitively to potential drought, while Rh responds more sensitively to N deposition, and consequently, increased soil N availability caused by N deposition might aggravate the negative effect of expected drought on soil carbon cycling.

Global climate models project more frequent drought events in Central China. However, the effect of seasonal drought on ecosystem water use efficiency (WUE) and water regulation strategy in Central China’s natural forests is poorly understood. This study investigated variations in WUE associated with drought in a natural oak (Quercus aliena) forest in Central China from 2017 to 2020 at several timescales based on continuous CO2 and water vapor flux measurements. Results showed that the 4-year mean gross ecosystem production (GEP), evapotranspiration (ET) and WUE of the natural oak forest was 1613.2 ± 116 g Cm−2, 637.8 ± 163.3 mm and 2.6 ± 0.68 g Ckg−1 H2O, with a coefficient of variation (CV) of 7.2%, 25.6% and 26.4%, respectively. The inter-annual variation in WUE was large, primarily due to the variation in ET caused by seasonal drought. Drought increased WUE distinctly in summer and decreased it slightly in autumn. During summer drought, surface conductance (gs) usually decreased with an increase in VPD, but the ratios of stomatal sensitivity (m) and reference conductance (gsref) were 0.21 and 0.3 molm−2s−1ln(kPa)−1 in the summer of 2019 and 2020. Strong drought can also affect ecosystem WUE and water regulation strategy in the next year. Decrease in precipitation in spring increased annual WUE. These results suggested that drought in different seasons had different effects on ecosystem WUE. Overall, our findings suggest that the natural oak forest did not reduce GEP by increasing WUE (i.e., reducing ET) under spring and summer drought, which could be due to its typical anisohydric characteristics, although it can also reduce stomatal opening during long-term drought.

The unknown NOx distributions inside large-scale CFB (circulating fluidized bed) boilers have always hindered the economy of the SNCR (selective non-catalytic reduction) process. In this study, field tests were carried out on a typical 300 MW CFB boiler, where multi-level 316 L-made probe and Ecom-J2KN/Testo 350 analyzers were used to perform detailed two-dimensional distributions of flue gas composition at SNCR inlets for the first time. The penetration depth inside the horizontal flue pass was up to 7 m. The NOx distributions were analyzed in detail combining with the auxiliary test in the dilute phase zone. Key results show that the average O2 concentrations in #A and #C regions were 6.52% and 0.95%, respectively. The vertical NOx distributions of #A and #C SNCR inlets were similar, showing a trend of first increasing and then decreasing with peak value all appeared at 5 m depth, while the NOx distribution of #B SNCR inlet was basically increasing. Some local areas with extremely high NOx concentration (over 2000 mg/m3) were observed near the inclined edge of SNCR inlets, which has never been reported before. Based on this, the optimization of urea injections was conducted, which could save 15.7% of the urea solution consumption while ensuring ultra-low emission of NOx.

Prolonged drought results in serious ecological consequences in forest ecosystems, particularly for soil microbial communities. However, much is unknown about soil microbial communities in their response to long-term consecutive droughts in warm-temperate forests. Here, we conducted a 7-year manipulated throughfall reduction experiment (TFR) to examine the responses of bacterial and fungal communities in terms of richness and networks. Our results show that long-term TFR reduced bacterial, but not fungal, richness, with rare bacterial taxa being more sensitive to TFR than dominant taxa. The bacterial network under the TFR treatment featured a simpler network structure and fewer competitive links compared to the control, implying weakened interactions among bacterial species. Bacterial genes involved in xenobiotic biodegradation and metabolism, and lignin-degrading enzymes were enhanced under TFR treatment, which may be attributed to TFR-induced increases in fine root biomass and turnover. Our results indicate that soil bacterial communities are more responsive than fungi to long-term TFR in a warm-temperate oak forest, leading to potential consequences such as the degradation of recalcitrant organics in soil.

The dispersion characteristics of fuel particles over the bed have always been a key consideration in the design of fluidized beds. However, the lateral fuel dispersion coefficients (Dsr) reported in the previous literature widely ranged from 10−4 to 10−1 m2/s, which were hard to be directly applied in large-scale CFB (circulating fluidized bed) boilers with wider bed width (close to 30 m) and variable coal feeding modes. To solve this problem, field tests were conducted on the first 600 MW CFB boiler in this paper, and the distributions of flue gas composition and flue gas temperature were obtained near the coal feeding port under four working conditions. The dispersion characteristics of fuel particles were analyzed in detail combined with the dispersion model. In addition, a new method based on bed heat balance was also proposed to estimate Dsr and applied in a 300 MW CFB boiler with a different coal feeding mode. The results revealed that Dsr through the local heat balance method ranged from 0.10–0.35 m2/s, which were 9–18% higher than the values through the dispersion model. Compared with the coal feeding port immersed in the bed, Dsr of the fuel particles fed into the splash zone increased by about 34.7%. Dsr under the coal feeding mode of a screw feeder with pressurized air ranged from 0.12–0.16 m2/s, which were lower than Dsr under the coal feeding method of importing fuel into circulating ash. The method and results in this paper could expand the applicability of fuel dispersion, and provide the most direct guidance for the design and optimization of coal feeding ports in large-scale CFB boilers.

Zinc finger BED-type containing 6 (ZBED6), a highly conservative transcription factor of placental mammals, has conservative interaction of insulin-like growth factor 2 (IGF2) based on the 16 bp binding sites of ZBED6 on the IGF2 sequence. IGF2 is related to embryo growth and cell proliferation. At the same time, its functions in muscle and adipose in mammals have been widely mentioned in recent studies. To further investigate the mechanism of ZBED6 on IGF2, we detected the expression of IGF2 and related genes in ZBED6 single allele knockout (ZBED6-SKO) pig tissues and analyzed the transcriptome of ZBED6-SKO pig liver. Through RNA-seq, we captured nine up-regulated genes and eight down-regulated genes which related to lipid metabolism. The results showed that the mRNA of IGF2 had an upward trend after the partial knockout of ZBED6 in liver and had no significant difference in protein expression of IGF2. In summary, ZBED6-SKO could affect the secretion of IGF2 in pig liver and its own lipid metabolism. Our research has provided basic information for revealing the regulatory mechanism of the interaction between ZBED6 and IGF2 in mammals.

The GH growth axis plays an important role in the growth and development of animals and runs through the whole life of animals. Many studies have shown that molecular mutations in key genes of the GH axis will affect the growth and development of animals. The purpose of this study was to explore the distribution characteristics of InDels of GHR, GHRH, and GHRHR in seven Chinese sheep populations, and to further explore the relationship between InDels and sheep growth traits. GHR showed high variation in Chinese sheep, and GHR-53 showed the highest minimum allele frequency (MAF). There was only one InDel mutation site in both GHRH and GHRHR. The genotype frequencies of Hu sheep (HS), Tong sheep (TS), and Lanzhou fat-tail sheep (LFTS) were quite different from other breeds. The association between GHR, GHRH, and GHRHR InDels and body size traits in seven varieties were analyzed. The results showed that there was no significant relationship between GHRH and body size traits in the seven sheep populations. There was a positive association between GHR-21 and hip height of LFSH (p < 0.05). GHR-43 reduced body height and chest depth of Small tail han sheep (STHS) and hip width of TS. GHR-44 significantly affected the body weight of HS, the body height of STHS and the head depth of TS. GHR-53 significantly reduced cannon girth of HS, chest of STHS and forehead width of TS. GHRHR-2 significantly reduced the body weight of LFHS. To sum up, this study revealed the effects of GHR, GHRH, and GHRHR InDels on sheep phenotypic traits, which indicated their potential application prospects in the genetic improvement of mutton sheep.

The Sanbao Mn–Ag (Zn-Pb) deposit located in the Laojunshan ore district is one of the most important deposits that has produced most Ag and Mn metals in southeastern Yunnan Province, China. Few studies are available concerning the distribution and mineralization of Ag, restricting further resource exploration. In this study, detailed mineralogy, chronology, and geochemistry are examined with the aim of revealing Ag occurrence and its associated primary base-metal and supergene mineralization. Results show that manganite and romanèchite are the major Ag-bearing minerals. Cassiterite from the Mn–Ag ores yielded a U–Pb age of 436 ± 17 Ma, consistent with the Caledonian age of the Nanwenhe granitic pluton. Combined with other geochemical proxies (Zn-Pb-Cu-Sn), the Sanbao Mn–Ag deposit may originally be of magmatic hydrothermal origin, rather than sedimentary. The Ag-rich (Zn-Pb (Sn)-bearing) ore-forming fluids generated during the intrusion of the granite flowed through fractures and overprinted the earlier Mn mineralization. Secondary Ag (and possibly other base-metals) enrichment occurred through later supergene weathering and oxidation.

Quantifying the impact of forest management on carbon (C) stock is important for evaluating and enhancing the ability of plantations to mitigate climate change. Near natural forest management (NNFM) through species enrichment planting in single species plantations, structural adjustment, and understory protection is widely used in plantation management. However, its long-term effect on forest ecosystem C stock remains unclear. We therefore selected two typical coniferous plantations in southwest China, Pinus massoniana (Lamb.) and Cunninghamia lanceolate (Lamb.) Hook., to explore the effects of long-term NNFM on ecosystem C storage. The C content and stock of different components in the pure plantations of P. massoniana (PCK) and C. lanceolata (CCK), and their corresponding near natural managed forests (PCN and CCN, respectively), were investigated during eight years of NNFM beginning in 2008. In 2016, there was no change in the vegetation C content, while soil C content in the 0−20 cm and 20−40 cm layers significantly increased, compared to the pure forests. In the P. massoniana and C. lanceolata plantations, NNFM increased the ecosystem C stock by 31.8% and 24.3%, respectively. Overall, the total C stock of soil and arborous layer accounted for 98.2%−99.4% of the whole ecosystem C stock. The increase in the biomass of the retained and underplanted trees led to a greater increase in the arborous C stock in the near natural forests than in the controls. The NNFM exhibited an increasingly positive correlation with the ecosystem C stock over time. Long-term NNFM enhances ecosystem C sequestration by increasing tree growth rate at individual and stand scales, as well as by likely changing the litter decomposition rate resulting from shifts in species composition and stand density. These results indicated that NNFM plays a positive role in achieving multi-objective silviculture and climate change mitigation.

Quantification of the temporal and spatial variations of soil respiration is an essential step in modeling soil carbon (C) emission associated with the spatial distribution of plants. To examine the temporal and spatial variations of soil respiration and its driving factors, we investigated soil respiration, microclimate, and understory vegetation in a 50 m × 70 m plot in a climatic transitional zone oak forest in Central China. The temporal variation of soil respiration based on the 21 measurements ranged from 15.01% to 30.21% across the 48 subplots. Structural equation modeling showed that soil temperature and understory shrub biomass had greater positive effects on the seasonal variability of soil respiration. The spatial variation of soil respiration of the 48 subplots varied from 3.61% to 6.99% during the 21 measurement campaigns. Understory shrub biomass and belowground fine root biomass positively regulated the spatial variation of soil respiration. Soil respiration displayed strong spatial autocorrelation, with an average spatial correlation length of 20.1 m. The findings highlight the importance of understory shrub and belowground biomass in regulating the temporal and spatial heterogeneity of soil respiration in forest ecosystems, and the need to carefully address it to robustly estimate the contribution of soil C emission in terrestrial C cycling.

Tropical forests are frequently disturbed by extreme weather events including tropical cyclones and cold waves, which can not only yield direct impact on hydrological processes but also produce indirect effect on hydrology by disturbing growth and structures of tropical forests. However, the hydrological response to extreme weather-induced forest disturbances especially in tropical forested watersheds has been less evaluated. In this study, a tropical experimental watershed in Hainan Province, China, was selected to investigate the hydrological responses to extreme weather-induced forest disturbances by use of a single watershed approach and the paired-year approach. Key results are: (1) extreme weather-induced forest disturbances (e.g., typhoon and cold wave) generally had a positive effect on streamflow in the study watershed, while climate variability either yielded a negative effect or a positive effect in different periods; (2) the response of low flows to forest discussion was more pronounced; (3) the relative contribution of forest disturbances to annual streamflow (48.6%) was higher than that of climate variability (43.0%) from 1995 to 2005. Given the increasing extreme weather with climate change and their possible catastrophic effects on tropical forests and hydrology in recent decades, these findings are essential for future adaptive water resources and forest management in the tropical forested watersheds.

We have investigated the selective epitaxial growth of GeSi bulk material on silicon-on-insulator substrates by reduced pressure chemical vapor deposition. We employed AFM, SIMS, and Hall measurements, to characterize the GeSi heteroepitaxy quality. Optimal growth conditions have been identified to achieve low defect density, low RMS roughness with high selectivity and precise control of silicon content. Fabricated vertical p-i-n diodes exhibit very low dark current density of 5 mA/cm2 at −1 V bias. Under a 7.5 V/µm E-field, GeSi alloys with 0.6% Si content demonstrate very strong electro-absorption with an estimated effective ∆α/α around 3.5 at 1,590 nm. We compared measured ∆α/α performance to that of bulk Ge. Optical modulation up to 40 GHz is observed in waveguide devices while small signal analysis indicates bandwidth is limited by device parasitics.

Methane (CH4) is a vital greenhouse gas with a 28-fold higher global warming potential than carbon dioxide when considering a molar basis for the time horizon of 100 years. Here, we investigated the variation of soil CH4 fluxes, soil physiochemical properties, and CH4-related bacteria community composition of two forests in China. We measured CH4 fluxes using static chambers and analyzed soil bacterial communities using next-generation high-throughput sequencing in a temperate broad-leaved deciduous forest at Baotianman Nature Reserve (TBDF-BTM) and a tropical rainforest at Jianfengling National Natural Reserve (TRF-JFL). Our results showed that the soils from both sites were CH4 sinks. Significant variation in soil CH4 fluxes was found at TBDF-BTM exclusively, while no seasonal variation in the CH4 uptake was observed at TRF-JFL. The CH4 fluxes at TBDF-BTM were substantially higher than those at TRF-JFL during all seasons. One genus of methanotrophs and three genera of methylotrophs were detected at both sites, though they had no direct relationship with soil CH4 fluxes. Water-filled pore space and soil total carbon content are the main factors controlling the soil CH4 fluxes at TBDF-BTM. At TRF-JFL, the soil CH4 fluxes showed no significant correlations with any of the soil properties. This study improves our understanding of soil CH4 fluxes and their influencing factors in forests in different climatic zones and provides a reference for future investigation of forest soil CH4 fluxes, the forest ecosystem carbon cycle, and the forest CH4 model.

Greenhouse gases are the main cause of global warming, and forest soil plays an important role in greenhouse gas flux. Near natural forest management is one of the most promising options for improving the function of forests as carbon sinks. However, its effects on greenhouse gas emissions are not yet clear. It is therefore necessary to characterise the effects of near natural forest management on greenhouse gas emissions and soil carbon management in plantation ecosystems. We analysed the influence of near natural management on the flux of three major greenhouse gases (carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O)) in Pinus massoniana Lamb. and Cunninghamia lanceolata (Lamb.) Hook. plantations. The average emission rates of CO2 and N2O in the near natural plantations were higher than those in the corresponding unimproved pure plantations of P. massoniana and C. lanceolata, and the average absorption rate of CH4 in the pure plantations was lower than that in the near natural plantations. The differences in the CO2 emission rates between plantations could be explained by differences in the C:N ratio of the fine roots. The differences in the N2O emission rates could be attributed to differences in soil available N content and the C:N ratio of leaf litter, while the differences in CH4 uptake rate could be explained by differences in the C:N ratio of leaf litter only. Near natural forest management negatively affected the soil greenhouse gas emissions in P. massoniana and C. lanceolata plantations. The potential impact of greenhouse gas flux should be considered when selecting tree species for enrichment planting.

Extensive studies on hydrological responses to forest change have been published for centuries, yet partitioning the hydrological effects of forest change, climate variability and other factors in a large watershed remains a challenge. In this study, we developed a single watershed approach combining the modified double mass curve (MDMC) and the time series multivariate autoregressive integrated moving average model (ARIMAX) to separate the impact of forest change, climate variability and other factors on dry season runoff variation in two large watersheds in China. The Zagunao watershed was examined for the deforestation effect, while the Meijiang watershed was examined to study the hydrological impact of reforestation. The key findings are: (1) both deforestation and reforestation led to significant reductions in dry season runoff, while climate variability yielded positive effects in the studied watersheds; (2) the hydrological response to forest change varied over time due to changes in soil infiltration and evapotranspiration after vegetation regeneration; (3) changes of subalpine natural forests produced greater impact on dry season runoff than alteration of planted forests. These findings are beneficial to water resource and forest management under climate change and highlight a better planning of forest operations and management incorporated trade-off between carbon and water in different forests.