Global patterns, trends, and drivers of water use efficiency from 2000 to 2013

Water use efficiency (WUE; gross primary production [GPP]/evapotranspiration [ET]) estimates the tradeoff between carbon gain and water loss during photosynthesis and is an important link of the carbon and water cycles. Understanding the spatiotemporal patterns and drivers of WUE is helpful for projecting the responses of ecosystems to climate change. Here we examine the spatiotemporal patterns, trends, and drivers of WUE at the global scale from 2000 to 2013 using the gridded GPP and ET data derived from the Moderate Resolution Imaging Spectroradiometer (MODIS). Our results show that the global WUE has an average value of 1.70 g C/kg H2O with large spatial variability during the 14-year period. WUE exhibits large variability with latitude. WUE also varies much with elevation: it first remains relatively constant as the elevation varies from 0 to 1000 m and then decreases dramatically. WUE generally increases as precipitation and specific humidity increase; whereas it decreases after reaching maxima as temperature and solar radiation increases. In most land areas, the temporal trend of WUE is positively correlated with precipitation and specific humidity over the 14-year period; while it has a negative relationship with temperature and solar radiation related to global warming and dimming. On average, WUE shows an increasing trend of 0.0025 g C·kg−1 H2O·yr−1 globally. Our global-scale assessment of WUE has implications for improving our understanding of the linkages between the water and carbon cycles and for better projecting the responses of ecosystems to climate change

A Trust Model Based on Cloud Model and Bayesian Networks

Abstractthe Internet has been becoming the most important infrastructure for distributed applications which are composed of online services. In such open and dynamic environment, service selection becomes a challenge. The approaches based on subjective trust models are more adaptive and efficient than traditional binary logic based approaches. Most well known trust models use probability or fuzzy set theory to hold randomness or fuzziness respectively. Only cloud model based models consider both aspects of uncertainty. Although cloud model is ideal for representing trust degrees, it is not efficient for context aware trust evaluation and dynamic updates. By contrast, Bayesian network as an uncertain reasoning tool is more efficient for dynamic trust evaluation. An uncertain trust model that combines cloud model and Bayesian network is proposed in this paper

Characterization of Shewanella sp. Isolated from Cultured Loach Misgurnus anguillicaudatus

Shewanella infection of fish has become a significant problem in aquaculture. In September 2014, a disease was seen in cultured loach (Misgurnus anguillicaudatus) in Xuzhou, central China. A gram-negative bacillus was isolated from the diseased loaches and was tentatively named strain MS1, which was then identified as Shewanella sp. by physiological and biochemical characteristics analysis. The strain MS1 showed highest 16S rRNA sequence identities (98.93%, 98.87%) with the latest two species listed (Shewanella sp. MR7, Shewanella sp. MR4). The phylogenetic tree constructed on the basis of 16S rRNA gene sequences strongly indicated that the strain MS1 is most closely related to the new Shewanella strains MR7 and MR4. The isolate MS1 was confirmed as the pathogen of the infected loaches by experimental reinoculation. The strain was susceptible to most antimicrobial agents tested, but resistant to glycopeptides (vancomycin, teicoplanin) and lincosamide (lincomycin, clindamycin). This is the second report on Shewanella sp. isolated from the diseased loach

Global patterns of woody residence time and its influence on model simulation of aboveground biomass

Woody residence time (τw) is an important parameter that expresses the balance between mature forest recruitment/growth and mortality. Using field data collected from the literature, this study explored the global forest τw and investigated its influence on model simulations of aboveground biomass (AGB) at a global scale. Specifically, τw was found to be related to forest age, annual temperature, and precipitation at a global scale, but its determinants were different among various plant function types. The estimated global forest τw based on the filed data showed large spatial heterogeneity, which plays an important role in model simulation of AGB by a dynamic global vegetation model (DGVM). The τw could change the resulting AGB in tenfold based on a site-level test using the Monte Carlo method. At the global level, different parameterization schemes of the Integrated Biosphere Simulator using the estimated τw resulted in a twofold change in the AGB simulation for 2100. Our results highlight the influences of various biotic and abiotic variables on forest τw. The estimation of τw in our study may help improve the model simulations and reduce the parameter\u27s uncertainty over the projection of future AGB in the current DGVM or Earth System Models. A clearer understanding of the responses of τw to climate change and the corresponding sophisticated description of forest growth/mortality in model structure is also needed for the improvement of carbon stock prediction in future studies

Terrestrial biosphere models need better representation of vegetation phenology: results from the North American Carbon Program Site Synthesis

Phenology, by controlling the seasonal activity of vegetation on the land surface, plays a fundamental role in regulating photosynthesis and other ecosystem processes, as well as competitive interactions and feedbacks to the climate system. We conducted an analysis to evaluate the representation of phenology, and the associated seasonality of ecosystem-scale CO2 exchange, in 14 models participating in the North American Carbon Program Site Synthesis. Model predictions were evaluated using long-term measurements (emphasizing the period 2000-2006) from 10 forested sites within the AmeriFlux and Fluxnet-Canada networks. In deciduous forests, almost all models consistently predicted that the growing season started earlier, and ended later, than was actually observed; biases of 2 weeks or more were typical. For these sites, most models were also unable to explain more than a small fraction of the observed interannual variability in phenological transition dates. Finally, for deciduous forests, misrepresentation of the seasonal cycle resulted in over-prediction of gross ecosystem photosynthesis by +160 ± 145 g C m-2 y-1 during the spring transition period, and +75 ± 130 g C m-2 y-1 during the autumn transition period (13% and 8% annual productivity, respectively) compensating for the tendency of most models to under-predict the magnitude of peak summertime photosynthetic rates. Models did a better job of predicting the seasonality of CO2 exchange for evergreen forests. These results highlight the need for improved understanding of the environmental controls on vegetation phenology, and incorporation of this knowledge into better phenological models. Existing models are unlikely to predict future responses of phenology to climate change accurately, and therefore will misrepresent the seasonality and interannual variability of key biosphere-atmosphere feedbacks and interactions in coupled global climate models.Engineering and Applied SciencesOrganismic and Evolutionary Biolog

The GEOTRACES Intermediate Data Product 2014

The GEOTRACES Intermediate Data Product 2014 (IDP2014) is the first publicly available data product of the international GEOTRACES programme, and contains data measured and quality controlled before the end of 2013. It consists of two parts: (1) a compilation of digital data for more than 200 trace elements and isotopes (TEIs) as well as classical hydrographic parameters, and (2) the eGEOTRACES Electronic Atlas providing a strongly inter-linked on-line atlas including more than 300 section plots and 90 animated 3D scenes. The IDP2014 covers the Atlantic, Arctic, and Indian oceans, exhibiting highest data density in the Atlantic. The TEI data in the IDP2014 are quality controlled by careful assessment of intercalibration results and multi-laboratory data comparisons at cross-over stations. The digital data are provided in several formats, including ASCII spreadsheet, Excel spreadsheet, netCDF, and Ocean Data View collection. In addition to the actual data values the IDP2014 also contains data quality flags and 1-? data error values where available. Quality flags and error values are useful for data filtering. Metadata about data originators, analytical methods and original publications related to the data are linked to the data in an easily accessible way. The eGEOTRACES Electronic Atlas is the visual representation of the IDP2014 data providing section plots and a new kind of animated 3D scenes. The basin-wide 3D scenes allow for viewing of data from many cruises at the same time, thereby providing quick overviews of large-scale tracer distributions. In addition, the 3D scenes provide geographical and bathymetric context that is crucial for the interpretation and assessment of observed tracer plumes, as well as for making inferences about controlling processes

Regioselective copper-catalyzed aminoborylation of styrenes with bis(pinacolato)diboron and diazo compounds

A Cu(I)-catalyzed aminoborylation reaction of styrenes is reported. In this transformation, diazo compounds are used as the electrophilic amination agent. The in situ generated benzylcopper species is trapped by the electrophilic nitrogen terminus of the diazo substrate to afford borylated hydrazones in a regioselective manner

An Efficient Confidentiality and Integrity Preserving Aggregation Protocol in Wireless Sensor Networks

Wireless sensor networks (WSNs) are composed of sensor nodes with limited energy which is difficult to replenish. In-network data aggregation is the main solution to minimize energy consumption and maximize network lifetime by reducing communication overhead. However, performing data aggregation while preserving data confidentiality and integrity is challenging, because adversaries can eavesdrop and modify the aggregation results easily by compromised aggregation nodes. In this paper, we propose an efficient confidentiality and integrity preserving aggregation protocol (ECIPAP) based on homomorphic encryption and result-checking mechanism. We also implement ECIPAP on SimpleWSN nodes running TinyOS. Security and performance analysis show that our protocol is quite efficient while persevering both aggregation confidentiality and integrity

Strain Transfer Characteristic of a Fiber Bragg Grating Sensor Bonded to the Surface of Carbon Fiber Reinforced Polymer Laminates

Structural health monitoring is of great importance for the application of composites in aircrafts. Fiber Bragg grating (FBG) sensors are very suitable for structure strain measurement. However, the strain measured by FBG sensors is different from the original strain in host materials. The relationship between them is defined as strain transfer. As composites are anisotropic, the traditional strain transfer model, which regards the elasticity modulus of host materials as a constant, is inadaptable. In this paper, a new strain transfer model is proposed for FBG sensors bonded to the surface of carbon fiber reinforced polymer (CFRP) laminates. Based on the measurement structure, the model is established and the transfer function is derived. The characteristics influencing the strain transfer are analyzed. The stacking directions, stacking numbers, and stacking sequences of CFRP laminates have a distinct effect on the transfer efficiency, which is different from the isotropy host materials. The accuracy of the proposed model was verified by experiments on a nondestructive tensile system, and the maximum model error is less than 0.5%. Moreover, the model was applied to the strain measurement of CFRP wing skin, which indicates that measurement errors decrease by 11.6% to 19.8% after the compensation according to the model