Surface sediments are the inner source of contaminations in aquatic systems and usually maintain aerobic conditions. As the key participators of nitrification process, little is known about the activities and contributions of ammonia-oxidizing archaea (AOA) and bacteria (AOB) in the surface sediments. In this study, we determined the net and potential nitrification rates and used 1-octyne as an AOB specific inhibitor to detect the contributions of AOA and AOB to nitrification in surface sediments of Danjiangkou reservoir, which is the water source area of the middle route of South-to-North Water Diversion Project in China. Quantitative PCR and Illumina high-throughput sequencing were used to evaluate the abundance and diversity of the amoA gene. The net and potential nitrification rates ranged from 0.42 to 1.93 and 2.06 to 8.79 mg N kg(-1) dry sediments d(-1), respectively. AOB dominated in both net and potential nitrification, whose contribution accounted for 52.7-78.6% and 59.9-88.1%, respectively. The cell-specific ammonia oxidation rate calculation also revealed the cell-specific rates of AOB were higher than that of AOA. The Spearman's rank correlation analysis suggested that ammonia accumulation led to the AOB predominant role in net nitrification activity, and AOB abundance played the key role in potential nitrification activity. Furthermore, phylogenetic analysis suggested AOB were predominantly characterized by the Nitrosospira cluster, while AOA by the Nitrososphaera and Nitrososphaera sister clusters. This study will help us to better understand the contributions and characteristics of AOA and AOB in aquatic sediments and provide improved strategies for nitrogen control in large reservoirs.
Surface sediments are the inner source of contaminations in aquatic systems and usually maintain aerobic conditions. As the key participators of nitrification process, little is known about the activities and contributions of ammonia-oxidizing archaea (AOA) and bacteria (AOB) in the surface sediments. In this study, we determined the net and potential nitrification rates and used 1-octyne as an AOB specific inhibitor to detect the contributions of AOA and AOB to nitrification in surface sediments of Danjiangkou reservoir, which is the water source area of the middle route of South-to-North Water Diversion Project in China. Quantitative PCR and Illumina high-throughput sequencing were used to evaluate the abundance and diversity of the amoA gene. The net and potential nitrification rates ranged from 0.42 to 1.93 and 2.06 to 8.79 mg N kg−1 dry sediments d−1, respectively. AOB dominated in both net and potential nitrification, whose contribution accounted for 52.7–78.6% and 59.9–88.1%, respectively. The cell-specific ammonia oxidation rate calculation also revealed the cell-specific rates of AOB were higher than that of AOA. The Spearman's rank correlation analysis suggested that ammonia accumulation led to the AOB predominant role in net nitrification activity, and AOB abundance played the key role in potential nitrification activity. Furthermore, phylogenetic analysis suggested AOB were predominantly characterized by the Nitrosospira cluster, while AOA by the Nitrososphaera and Nitrososphaera sister clusters. This study will help us to better understand the contributions and characteristics of AOA and AOB in aquatic sediments and provide improved strategies for nitrogen control in large reservoirs.
Location specific perceptual learning can transfer to a new location if the new location is trained with a secondary task that by itself does not impact the performance of the primary learning task (double training). Learning may also transfer to other locations when double training is performed at the same location. Here we investigated the mechanisms underlying double-training enabled learning and transfer with an external noise paradigm. Specifically, we measured the Vernier thresholds at various external noise contrasts before and after double training. Double training mainly vertically downshifts the TvC functions at the training and transfer locations, which may be interpreted as improved sampling efficiency in a linear amplifier model or a combination of internal noise reduction and external noise exclusion in a perceptual template model at both locations. The change of the TvC functions appears to be a high-level process that can be remapped from a training location to a new location after double training.
Abstract Aim Is high diversity in tropical and subtropical mountains due to topographical complexity alone or a combination of topography and temperature seasonality? Here, we aim to assess the contribution of these two factors on Rhododendron diversity in China. Specifically, we evaluate how low temperature seasonality in subtropical China jointly with heterogeneous environment accounts for increased species diversity across montane landscapes relative to those of the more seasonal temperate zone in north China. Location China. Methods We compiled distributional data for all Rhododendron species in China and then estimated the species richness patterns of rare versus common species, and of shrubs versus trees at spatial resolutions of 50 × 50 km. Bivariate regressions were performed to evaluate the effects of environmental variables on species richness followed by stepwise regression to select the best set of predictors. Results The variables of habitat heterogeneity and climate seasonality were consistently the strongest predictors of species richness for all species groups, while the contribution of water and energy variables was proportionately much lower. Winter coldness had very low predictive power, which indicated that unlike other woody plants, the northward dispersal of Rhododendron is not limited by cold winter temperature. Main conclusions High Rhododendron diversity in south-west China appears to be influenced jointly by the climatic gradients induced by topographical complexity and temperature seasonality as suggested by Janzen's hypothesis. The increased topographical complexity in combination with low temperature seasonality in south-west China might have promoted species accumulation by offering more niche space, preventing extinction and providing increased opportunities for allopatric speciation. While our findings strongly indicate the effect of habitat heterogeneity on species diversity, they also suggest the role of seasonal uniformity of temperature for increased diversity towards the tropics. The effect of seasonality may, however, be more pronounced in plants because of their limited ability to use behaviour to avoid environmental influences.
Thermal emission from objects tends to be spectrally broadband, unpolarized, and temporally invariant. These common notions are now challenged with the emergence of new nanophotonic structures and concepts that afford on-demand, active manipulation of the thermal emission process. This opens a myriad of new applications in chemistry, health care, thermal management, imaging, sensing, and spectroscopy. Here, we theoretically propose and experimentally demonstrate a new approach to actively tailor thermal emission with a reflective, plasmonic metasurface in which the active material and reflector element are epitaxially grown, high-carrier-mobility InAs layers. Electrical gating induces changes in the charge carrier density of the active InAs layer that are translated into large changes in the optical absorption and thermal emission from metasurface. We demonstrate polarization-dependent and electrically controlled emissivity changes of 3.6%P (6.5% in relative scale) in the mid-infrared spectral range.
Coastal estuaries and bays are exposed to both natural and anthropogenic environmental changes, inflicting intensive stress on the microbial communities inhabiting these areas. However, it remains unclear how microbial community diversity and their eco-functions are affected by anthropogenic disturbances rather than natural environmental changes. Here, we explored sediment microbial functional genes dynamics and community interaction networks in Hangzhou Bay (HZB), one of the most severely polluted bays on China’s eastern coast. The results indicated key microbial functional gene categories, including N, P, S, and aromatic compound metabolism, and stress response, displayed significant spatial dynamics along environmental gradients. Sensitive feedbacks of key functional gene categories to N and P pollutants demonstrated potential impacts of human-induced seawater pollutants to microbial functional capacity. Seawater ammonia and dissolved inorganic nitrogen (DIN) was identified as primary drivers in selecting adaptive populations and varying community composition. Network analysis revealed distinct modules that were stimulated in inner or outer bay. Importantly, the network keystone species, which played a fundamental role in community interactions, were strongly affected by N-pollutants. Our results provide a systematic understanding of the microbial compositional and functional dynamics in an urbanized coastal estuary, and highlighted the impact of human activities on these communities.
Conventional wisdom has long held that a composite particle behaves just like an ordinary Newtonian particle. In this paper, we derive the effective dynamics of a type-I Wigner crystal of composite particles directly from its microscopic wave function. It indicates that the composite particles are subjected to a Berry curvature in the momentum space as well as an emergent dissipationless viscosity. While the dissipationless viscosity is the Chern-Simons field counterpart for the Wigner crystal, the Berry curvature is a feature not presented in the conventional composite fermion theory. Hence, contrary to general belief, composite particles follow the more general Sundaram-Niu dynamics instead of the ordinary Newtonian one. We show that the presence of the Berry curvature is an inevitable feature for a dynamics conforming to the dipole picture of composite particles and Kohn's theorem. Based on the dynamics, we determine the dispersions of magnetophonon excitations numerically. We find an emergent magnetoroton mode which signifies the composite-particle nature of the Wigner crystal. It occurs at frequencies much lower than the magnetic cyclotron frequency and has a vanishing oscillator strength in the long-wavelength limit.
SCOPE: Effects of dairy consumption on body weight and body composition have been inconsistently observed in randomized control trials (RCTs). Our meta-analysis aims to systematically evaluate the effects of dairy consumption on body weight and body composition among the adults. METHODS AND RESULTS: We conducted a comprehensive search of the Cochrane Library, PubMed, and Embase databases of the relevant studies from 1966 to Mar 2017 regarding dairy consumption on body weight and body composition including body fat, lean mass, and waist circumference (WC). The summary results are pooled by using a random-effects meta-analysis. Thirty-seven RCTs with 184 802 participants are included in this meta-analysis. High dairy intervention increased body weight (0.01, 95% CI: -0.25, 0.26, I(2) = 78.3%) and lean mass (0.37, 95% CI: 0.11, 0.62, I(2) = 83.4%); decreased body fat (-0.23, 95% CI: -0.48, 0.02, I(2) = 78.2%) and WC (-1.37, 95% CI: -2.28, -0.46, I(2) = 98.9%) overall. In the subgroup analysis, we found that consumption of dairy products increases body weight (0.36, 95% CI: 0.01, 0.70, I(2) = 83.1%) among participants without energy restriction. Dairy consumption decreases body weight (-0.64, 95% CI: -1.05, -0.24, I(2) = 60.2%), body fat (-0.56, 95%CI: -0.95, -0.17, I(2) = 66.6%), and waist circumference (-2.18, 95%CI: -4.30, -0.06, I(2) = 99.0%) among the adults with energy restriction. CONCLUSIONS: This meta-analysis suggests a beneficial effect of energy-restricted dairy consumption on body weight and body composition. However, high dairy consumption in the absence of caloric restriction may increase body weight.
China is an agricultural country with the largest population in the world. However, intensification of droughts and floods has substantial impacts on agricultural production. For effective agricultural disaster management, it is significant to understand and quantify the influence of droughts and floods on crop production. Compared with droughts, the influence of floods on crop production and a comprehensive evaluation of effects of droughts and floods are given relatively less attention. The impact of droughts and floods on crop production is therefore investigated in this study, considering spatial heterogeneity with disaster and yield datasets for 1949-2015 in China mainland. The empirical relationships between drought and flood intensity and yield fluctuation for grain, rice, wheat, maize and soybean are identified using a Bayesian hierarchical model. They are then used to explore what social-economic factors influenced the grain sensitivity to droughts and floods by the Pearson's coefficient and locally weighted regression (LOSEE) plots. The modeling results indicate that: (a) droughts significantly reduce grain yields in 28 of 31 provinces and obvious spatial variability in drought sensitivity exists, with Loess Plateau having highest probability of crop failure caused by droughts; (b) floods significantly reduce grain yield in 20 provinces, while show positive effect in the northwestern and southwestern China; (c) the spatial patterns of influence direction of droughts and floods on rice, maize and soybean are consistent with the grain's results; and (d) promoting capital investments and improving access to technical inputs (fertilizer, pesticide, and irrigation) can help effectively buffer grain yield lose from droughts.