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The root zone is a vital part of the Earth system and a key element in hydrology, ecology, agronomy, and land surface processes. However, its definition varies across disciplines, creating barriers to interdisciplinary understanding. Moreover, characterizing the root zone is challenging due to a lack of consensus on definitions, estimation methods, and their merits and limitations. This opinion paper provides a holistic definition of the root zone from a hydrology perspective, including its moisture storage, deficit, and storage capacity. We demonstrate that the root zone plays a critical role in the biosphere, pedosphere, rhizosphere, lithosphere, atmosphere, and cryosphere of the Earth system. We underscore the limitations of the traditional reductionist approach in modelling this complex and dynamic zone and advocate for a shift towards a holistic, ecosystem-centred approach. We argue that a holistic approach offers a more systematic, simple, dynamic, scalable, and observable way to describe and predict the role of the root zone in Earth system science.

With regard to the pronounced pressure pulsation and cyclic thrust oscillation observed in the tail flow field of an underwater vehicle operating under over-expanded conditions, and drawing inspiration from flow control techniques involving porous media structures like submarine coral reefs and breakwaters, this paper presents an innovative proposition to incorporate a porous media layer on the tail wall of the nozzle in order to regulate the structure of the tail gaseous jets. To optimize the flow control of underwater vehicles, the utilization of porous media layers with varying degrees of porosity is employed to establish a model for underwater supersonic gaseous jets. This model scrutinizes the intricate structure of the tail gaseous jets, as well as the consequential wall pressure and thrust engendered by the nozzle. The findings eloquently demonstrate that the porous media model, boasting a porosity of 0.34, exerts a diminished influence on the morphological characteristics of the tail gaseous jets, while concurrently yielding a superior flow control effect on the pulsation of tail wall pressure and attenuating the differential thrust generated by the underwater vehicle. Consequently, this innovative approach effectively mitigates overall thrust oscillation, thereby enhancing the stability of the underwater vehicle throughout its submerged operations.

Abstract The T2K experiment presents new measurements of neutrino oscillation parameters using $$19.7(16.3)\times 10^{20}$$ 19.7 ( 16.3 ) × 10 20 protons on target (POT) in (anti-)neutrino mode at the far detector (FD). Compared to the previous analysis, an additional $$4.7\times 10^{20}$$ 4.7 × 10 20 POT neutrino data was collected at the FD. Significant improvements were made to the analysis methodology, with the near-detector analysis introducing new selections and using more than double the data. Additionally, this is the first T2K oscillation analysis to use NA61/SHINE data on a replica of the T2K target to tune the neutrino flux model, and the neutrino interaction model was improved to include new nuclear effects and calculations. Frequentist and Bayesian analyses are presented, including results on $$\sin ^2\theta _{13}$$ sin 2 θ 13 and the impact of priors on the $$\delta _{\textrm{CP}}$$ δ CP measurement. Both analyses prefer the normal mass ordering and upper octant of $$\sin ^2\theta _{23}$$ sin 2 θ 23 with a nearly maximally CP-violating phase. Assuming the normal ordering and using the constraint on $$\sin ^2\theta _{13}$$ sin 2 θ 13 from reactors, $$\sin ^2\theta _{23}=0.561^{+0.021}_{-0.032}$$ sin 2 θ 23 = 0 . 561 - 0.032 + 0.021 using Feldman–Cousins corrected intervals, and $$\varDelta {}m^2_{32}=2.494_{-0.058}^{+0.041}\times 10^{-3}~\text {eV}^2$$ Δ m 32 2 = 2 . 494 - 0.058 + 0.041 × 10 - 3 eV 2 using constant $$\varDelta \chi ^{2}$$ Δ χ 2 intervals. The CP-violating phase is constrained to $$\delta _{\textrm{CP}}=-1.97_{-0.70}^{+0.97}$$ δ CP = - 1 . 97 - 0.70 + 0.97 using Feldman–Cousins corrected intervals, and $$\delta _{\textrm{CP}}=0,\pi $$ δ CP = 0 , π is excluded at more than 90% confidence level. A Jarlskog invariant of zero is excluded at more than $$2\sigma $$ 2 σ credible level using a flat prior in $$\delta _{\textrm{CP}},$$ δ CP , and just below $$2\sigma $$ 2 σ using a flat prior in $$\sin \delta _{\textrm{CP}}.$$ sin δ CP . When the external constraint on $$\sin ^2\theta _{13}$$ sin 2 θ 13 is removed, $$\sin ^2\theta _{13}=28.0^{+2.8}_{-6.5}\times 10^{-3},$$ sin 2 θ 13 = 28 . 0 - 6.5 + 2.8 × 10 - 3 , in agreement with measurements from reactor experiments. These results are consistent with previous T2K analyses.

The first source catalog of the Large High Altitude Air Shower Observatory (LHAASO) reported the detection of a very high energy gamma-ray source, 1LHAASO J1219+2915. This Letter presents a further detailed study of the spectral and temporal behavior of this pointlike source. The best-fit position of the TeV source (R.A. = 185.°05 ± 0.°04, decl. = 29.°25 ± 0.°03) is compatible with NGC 4278 within ∼0.°03. Variation analysis shows an indication of variability on a timescale of a few months in the TeV band, which is consistent with low-frequency observations. Based on these observations, we report the detection of TeV γ -ray emissions from this low-luminosity active galactic nucleus. The observation by LHAASO's Water Cherenkov Detector Array during the active period has a significance level of 8.8 σ with a best-fit photon spectral index Γ = 2.56 ± 0.14 and a flux f _1–10 TeV = (7.0 ± 1.1 _sta ± 0.35 _syst ) × 10 ^−13 photons cm ^−2 s ^−1 , or approximately 5% of the Crab Nebula. The discovery of VHE gamma-ray emission from NGC 4278 indicates that compact, weak radio jets can efficiently accelerate particles and emit TeV photons.

Functional trait databases are emerging as a crucial tool for a wide range of ecological studies, including next-generation vegetation modelling across the world. However, few large-scale studies have been reported on plant traits in the Tibetan Plateau (TP), the cradle of East Asian flora and fauna with specific alpine ecosystems, and no report on plant trait databases could be found. In this work, an extensive dataset of 11 leaf functional traits (TiP-Leaf), mainly for herbs and shrubs and a few trees on the TP, was compiled through field surveys. The TiP-Leaf dataset, which was compiled from 336 sites distributed mainly on the plateau surface and the northern margin of the TP across alpine and temperate vegetation regions and sampled from 2018 to 2021, contained 1692 morphological trait measurements of leaf thickness, leaf fresh weight, leaf dry weight, leaf dry-matter content, leaf water content, leaf area, specific leaf area and leaf mass per area and 1645 chemical element trait measurements of leaf carbon, nitrogen and phosphorus contents. Thus, 468 species that belong to 184 genera and 51 families were obtained and measured. In addition to leaf trait measurements, the geographic coordinates, bioclimate variables, disturbance intensities and vegetation types of each site were also recorded. The dataset could provide solid data support to effectively quantify the modern ecological features of alpine ecosystems, thereby further evaluating the response of alpine ecosystems to climate change and human disturbances and improving the next-generation vegetation model. The dataset, which is available from the National Tibetan Plateau Data Center (TPDC; Jin et al., 2022a; https://doi.org/10.11888/Terre.tpdc.272516), can make a great contribution to the regional and global plant trait databases.

We present the first catalog of very-high-energy and ultra-high-energy gamma-ray sources detected by the Large High Altitude Air Shower Observatory. The catalog was compiled using 508 days of data collected by the Water Cherenkov Detector Array from 2021 March to 2022 September and 933 days of data recorded by the Kilometer Squared Array from 2020 January to 2022 September. This catalog represents the main result from the most sensitive large coverage gamma-ray survey of the sky above 1 TeV, covering decl. from −20° to 80°. In total, the catalog contains 90 sources with an extended size smaller than 2° and a significance of detection at >5 σ . Based on our source association criteria, 32 new TeV sources are proposed in this study. Among the 90 sources, 43 sources are detected with ultra-high energy ( E > 100 TeV) emission at >4 σ significance level. We provide the position, extension, and spectral characteristics of all the sources in this catalog.

Preceding a core-collapse supernova (CCSN), various processes produce an increasing amount of neutrinos of all flavors characterized by mounting energies from the interior of massive stars. Among them, the electron antineutrinos are potentially detectable by terrestrial neutrino experiments such as KamLAND and Super-Kamiokande (SK) via inverse beta decay interactions. Once these pre-supernova (pre-SN) neutrinos are observed, an early warning of the upcoming CCSN can be provided. In light of this, KamLAND and SK, both located in the Kamioka mine in Japan, have been monitoring pre-SN neutrinos since 2015 and 2021, respectively. Recently, we performed a joint study between KamLAND and SK on pre-SN neutrino detection. A pre-SN alert system combining the KamLAND detector and the SK detector was developed and put into operation, which can provide a supernova alert to the astrophysics community. Fully leveraging the complementary properties of these two detectors, the combined alert is expected to resolve a pre-SN neutrino signal from a 15 M _⊙ star within 510 pc of the Earth at a significance level corresponding to a false alarm rate of no more than 1 per century. For a Betelgeuse-like model with optimistic parameters, it can provide early warnings up to 12 hr in advance.

The DIII-D tokamak has elucidated crucial physics and developed projectable solutions for ITER and fusion power plants in the key areas of core performance, boundary heat and particle transport, and integrated scenario operation, with closing the core-edge integration knowledge gap being the overarching mission. New experimental validation of high-fidelity, multi-channel, non-linear gyrokinetic turbulent transport models for ITER provides strong confidence it will achieve Q ⩾ 10 operation. Experiments identify options for easing H-mode access in hydrogen, and give new insight into the isotopic dependence of transport and confinement. Analysis of 2,1 islands in unoptimized low-torque IBS demonstration discharges suggests their onset time occurs randomly in the constant β phase, most often triggered by non-linear 3-wave coupling, thus identifying an NTM seeding mechanism to avoid. Pure deuterium SPI for disruption mitigation is shown to provide favorable slow cooling, but poor core assimilation, suggesting paths for improved SPI on ITER. At the boundary, measured neutral density and ionization source fluxes are strongly poloidally asymmetric, implying a 2D treatment is needed to model pedestal fuelling. Detailed measurements of pedestal and SOL quantities and impurity charge state radiation in detached divertors has validated edge fluid modelling and new self-consistent ‘pedestal-to-divertor’ integrated modeling that can be used to optimize reactors. New feedback adaptive ELM control minimizes confinement reduction, and RMP ELM suppression with sustained high core performance was obtained for the first time with the outer strike point in a W-coated, compact and unpumped small-angle slot divertor. Advances have been made in integrated operational scenarios for ITER and power plants. Wide pedestal intrinsically ELM-free QH-modes are produced with more reactor-relevant conditions, Low torque IBS with W-equivalent radiators can exhibit predator-prey oscillations in T _e and radiation which need control. High- β _P scenarios with q _min > 2, q _95 –7.9, β _N > 4, β _T –3.3% and H _98y2 > 1.5 are sustained with high density ( $\bar n$ = 7E19 m ^−3 , f _G –1) for 6 τ _E , improving confidence in steady-state tokamak reactors. Diverted NT plasmas achieve high core performance with a non-ELMing edge, offering a possible highly attractive core-edge integration solution for reactors.

A series of dedicated experiments from the DIII-D tokamak provide spatially and temporally resolved measurements of electron density and temperature, and multiscale and multichannel fluctuations over a wide range of conditions. Measurements of long wavelength density fluctuations in the type-I ELMing H-mode pedestals routinely reveal a coexistence of multiple instabilities that exhibit dramatic different dynamic behaviors as q _95 and temperature gradients are varied, apparently responsible for limiting pedestal temperature profiles. Two distinct frequency bands of density fluctuations are modulated by an ELM cycle with frequency above 200 kHz propagating in the electron diamagnetic direction in the lab frame (electron mode) and below 200 kHz propagating in the ion diamagnetic direction (ion mode). The electron mode amplitude peaks near the electron temperature gradient region and increases with q _95 which seems to be correlated with the increased χ _e at higher q _95 , similar to the characteristics expected for the micro-tearing mode (MTM). At higher q _95 , during the inter-ELM period, the ion mode decays at the later phase of the ELM cycle. Consistently, the poloidal correlation length of the ion mode is also found to reduce, which suggests the possible E × B flow shear suppression of the ion mode at the later phase of the ELM cycle as the E _r well recovers. In contrast, the electron mode grows during the ELM cycle and reaches saturation at around 50%–60% of the ELM period. Linear gyrokinetic simulations find the MTMs to be the most unstable mode in the pedestal electron temperature gradient region. The higher q _95 and lower magnetic shear destabilize the MTMs. These observations provide key insights into the underlying physics of multifield properties and a rich dataset of experimental ‘fingerprints’ that enable new tests of theoretical pedestal models and lead to the development of a predictive model for pedestal formation on the ITER and future burning plasma experiments.

Among multimessenger observations of the next Galactic core-collapse supernova, Super-Kamiokande (SK) plays a critical role in detecting the emitted supernova neutrinos, determining the direction to the supernova (SN), and notifying the astronomical community of these observations in advance of the optical signal. In 2022, SK has increased the gadolinium dissolved in its water target (SK-Gd) and has achieved a Gd concentration of 0.033%, resulting in enhanced neutron detection capability, which in turn enables more accurate determination of the supernova direction. Accordingly, SK-Gd’s real-time supernova monitoring system has been upgraded. SK_SN Notice, a warning system that works together with this monitoring system, was released on 2021 December 13, and is available through GCN Notices. When the monitoring system detects an SN-like burst of events, SK_SN Notice will automatically distribute an alarm with the reconstructed direction to the supernova candidate within a few minutes. In this paper, we present a systematic study of SK-Gd’s response to a simulated Galactic SN. Assuming a supernova situated at 10 kpc, neutrino fluxes from six supernova models are used to characterize SK-Gd’s pointing accuracy using the same tools as the online monitoring system. The pointing accuracy is found to vary from 3° to 7° depending on the models. However, if the supernova is closer than 10 kpc, SK_SN Notice can issue an alarm with three-degree accuracy, which will benefit follow-up observations by optical telescopes with large fields of view.

The regionalization of hydrological model parameters is key to hydrological predictions in ungauged basins. The commonly used multiple linear regression (MLR) method may not be applicable in complex and nonlinear relationships between model parameters and watershed properties. Moreover, most regionalization methods assume lumped parameters for each catchment without considering within-catchment heterogeneity. Here we incorporated the Penman–Monteith–Leuning (PML) equation into the Distributed Time Variant Gain Model (DTVGM) to improve the mechanistic representation of the evapotranspiration (ET) process. We calibrated six key model parameters, grid by grid across China, using a multivariable calibration strategy which incorporates spatiotemporal runoff and ET datasets (0.25∘; monthly) as reference. In addition, we used the gradient boosting machine (GBM), a machine learning technique, to portray the dependence of model parameters on soil and terrain attributes in four distinct climatic zones across China. We show that the modified DTVGM could reasonably estimate the runoff and ET over China using the calibrated parameters but performed better in humid rather than arid regions for the validation period. The regionalized parameters by the GBM method exhibited better spatial coherence relative to the calibrated grid-by-grid parameters. In addition, GBM outperformed the stepwise MLR method in both parameter regionalization and gridded runoff simulations at a national scale, though the improvement pertaining to watershed streamflow validation is not significant due to most of the watersheds being located in humid regions. We also revealed that the slope, saturated soil moisture content, and elevation are the most important explanatory variables to inform model parameters based on the GBM approach. The machine-learning-based regionalization approach provides an effective alternative to deriving hydrological model parameters from watershed properties, particularly in ungauged regions.

We report the first search result for the flux of astrophysical electron antineutrinos for energies ${ \mathcal O }(10)\,\mathrm{MeV}$ in the gadolinium-loaded Super-Kamiokande (SK) detector. In 2020 June, gadolinium was introduced to the ultrapure water of the SK detector in order to detect neutrons more efficiently. In this new experimental phase, SK-Gd, we can search for electron antineutrinos via inverse beta decay with efficient background rejection thanks to the high efficiency of the neutron tagging technique. In this paper, we report the result for the initial stage of SK-Gd, during 2020 August 26, and 2022 June 1 with a 22.5 × 552 kton · day exposure at 0.01% Gd mass concentration. No significant excess over the expected background in the observed events is found for the neutrino energies below 31.3 MeV. Thus, the flux upper limits are placed at the 90% confidence level. The limits and sensitivities are already comparable with the previous SK result with pure water (22.5 × 2970 kton · day) owing to the enhanced neutron tagging. Operation with Gd increased to 0.03% started in 2022 June.

Abstract The focal plane camera is the core component of the Wide Field-of-view Cherenkov/fluorescence Telescope Array (WFCTA) of the Large High-Altitude Air Shower Observatory (LHAASO). Because of the capability of working under moonlight without aging, silicon photomultipliers (SiPM) have been proven to be not only an alternative but also an improvement to conventional photomultiplier tubes (PMT) in this application. Eighteen SiPM-based cameras with square light funnels have been built for WFCTA. The telescopes have collected more than 100 million cosmic ray events and preliminary results indicate that these cameras are capable of working under moonlight. The characteristics of the light funnels and SiPMs pose challenges (e.g. dynamic range, dark count rate, assembly techniques). In this paper, we present the design features, manufacturing techniques and performances of these cameras. Finally, the test facilities, the test methods and results of SiPMs in the cameras are reported here.

Deep basins create uniquely favorable conditions for causing air pollution, and the Sichuan Basin (SCB) in Southwest China is such a basin featuring frequent heavy pollution. A wintertime heavy haze pollution event in the SCB was studied with conventional and intensive observation data and the WRF-Chem model to explore the 3D distribution of PM2.5 to understand the impact of regional pollutant emissions, basin circulations associated with plateaus, and downwind transport to the adjacent areas. It was found that the vertical structure of PM2.5 over the SCB was characterized by a remarkable hollow sandwiched by high PM2.5 layers at heights of 1.5–3 km and a highly polluted near-surface layer. The southwesterlies over the Tibetan Plateau (TP) and Yunnan-Guizhou Plateau (YGP) resulted in a lee vortex over the SCB, which helped form and maintain heavy PM2.5 pollution. The basin PM2.5 was lifted into the free troposphere and transported outside of the SCB. At the bottom of the SCB, high PM2.5 concentrations were mostly located in the northwestern and southern regions. Due to the blocking effect of the plateau terrain on the northeasterly winds, PM2.5 gradually increased from northeast to southwest in the basin. In the lower free troposphere, the high PM2.5 centers were distributed over the northwestern and southwestern SCB areas, as well as the central SCB region. For this event, the regional emissions from the SCB contributed 75.4 %–94.6 % to the surface PM2.5 concentrations in the SCB. The SCB emissions were the major source of PM2.5 over the eastern regions of the TP and the northern regions of the YGP, with contribution rates of 72.7 % and 70.5 %, respectively, during the dissipation stage of heavy air pollution over the SCB, which was regarded as the major pollutant source affecting atmospheric environment changes in Southwest China.

Multiple lines of evidence have demonstrated the persistence of global land carbon (C) sink during the past several decades. However, both annual net ecosystem productivity (NEP) and its inter-annual variation (IAVNEP) keep varying over space. Thus, identifying local indicators for the spatially varying NEP and IAVNEP is critical for locating the major and sustainable C sinks on land. Here, based on daily NEP observations from FLUXNET sites and large-scale estimates from an atmospheric-inversion product, we found a robust logarithmic correlation between annual NEP and seasonal carbon uptake–release ratio (i.e. U ∕ R). The cross-site variation in mean annual NEP could be logarithmically indicated by U ∕ R, while the spatial distribution of IAVNEP was associated with the slope (i.e. β) of the logarithmic correlation between annual NEP and U ∕ R. Among biomes, for example, forests and croplands had the largest U ∕ R ratio (1.06 ± 0.83) and β (473 ± 112 g C m−2 yr−1), indicating the highest NEP and IAVNEP in forests and croplands, respectively. We further showed that these two simple indicators could directly infer the spatial variations in NEP and IAVNEP in global gridded NEP products. Overall, this study provides two simple local indicators for the intricate spatial variations in the strength and stability of land C sinks. These indicators could be helpful for locating the persistent terrestrial C sinks and provide valuable constraints for improving the simulation of land–atmospheric C exchanges.

Remote sensing is a potentially very useful source of information for spatial monitoring of natural or cultivated vegetation. The latest advances, in particular the arrival of new image acquisition programs, are changing the temporal approach to monitoring vegetation. The latest European satellites launched, delivering an image every 5 days for each point on the globe, allow the end of a growing season to be monitored. The main objective of this work is to identify and map the vegetation in the Pays de Brest area by using a multi sensors stacking of Sentinel-1 and Sentinel-2 satellites data via Random Forest, Rotation forests (RoF) and Canonical Correlation Forests (CCFs). RoF and CCF create diverse base learners using data transformation and subset features. Twenty four radar images and optical dataa representing different dates in 2017 were processed in time series stacks. The results of RoF and CCF were compared with the ones of RF.

Many studies have shown that downstream flood regimes have been significantly altered by upstream reservoir operation. Reservoir effects on the downstream flow regime are normally performed by comparing the pre-dam and post-dam frequencies of certain streamflow indicators, such as floods and droughts. In this study, a rainfall–reservoir composite index (RRCI) is developed to precisely quantify reservoir impacts on downstream flood frequency under a framework of a covariate-based nonstationary flood frequency analysis using the Bayesian inference method. The RRCI is derived from a combination of both a reservoir index (RI) for measuring the effects of reservoir storage capacity and a rainfall index. More precisely, the OR joint (the type of possible joint events based on the OR operator) exceedance probability (OR-JEP) of certain scheduling-related variables selected out of five variables that describe the multiday antecedent rainfall input (MARI) is used to measure the effects of antecedent rainfall on reservoir operation. Then, the RI-dependent or RRCI-dependent distribution parameters and five distributions, the gamma, Weibull, lognormal, Gumbel, and generalized extreme value, are used to analyze the annual maximum daily flow (AMDF) of the Ankang, Huangjiagang, and Huangzhuang gauging stations of the Han River, China. A phenomenon is observed in which although most of the floods that peak downstream of reservoirs have been reduced in magnitude by upstream reservoirs, some relatively large flood events have still occurred, such as at the Huangzhuang station in 1983. The results of nonstationary flood frequency analysis show that, in comparison to the RI, the RRCI that combines both the RI and the OR-JEP resulted in a much better explanation for such phenomena of flood occurrences downstream of reservoirs. A Bayesian inference of the 100-year return level of the AMDF shows that the optimal RRCI-dependent distribution, compared to the RI-dependent one, results in relatively smaller estimated values. However, exceptions exist due to some low OR-JEP values. In addition, it provides a smaller uncertainty range. This study highlights the necessity of including antecedent rainfall effects, in addition to the effects of reservoir storage capacity, on reservoir operation to assess the reservoir effects on downstream flood frequency. This analysis can provide a more comprehensive approach for downstream flood risk management under the impacts of reservoirs.

Understanding the projection performance of hydrological models under contrasting climatic conditions supports robust decision making, which highlights the need to adopt time-varying parameters in hydrological modeling to reduce performance degradation. Many existing studies model the time-varying parameters as functions of physically based covariates; however, a major challenge remains in finding effective information to control the large uncertainties that are linked to the additional parameters within the functions. This paper formulated the time-varying parameters for a lumped hydrological model as explicit functions of temporal covariates and used a hierarchical Bayesian (HB) framework to incorporate the spatial coherence of adjacent catchments to improve the robustness of the projection performance. Four modeling scenarios with different spatial coherence schemes and one scenario with a stationary scheme for model parameters were used to explore the transferability of hydrological models under contrasting climatic conditions. Three spatially adjacent catchments in southeast Australia were selected as case studies to examine the validity of the proposed method. Results showed that (1) the time-varying function improved the model performance but also amplified the projection uncertainty compared with the stationary setting of model parameters, (2) the proposed HB method successfully reduced the projection uncertainty and improved the robustness of model performance, and (3) model parameters calibrated over dry years were not suitable for predicting runoff over wet years because of a large degradation in projection performance. This study improves our understanding of the spatial coherence of time-varying parameters, which will help improve the projection performance under differing climatic conditions.

Predicting future changes in ecosystem services is not only highly desirable but is also becoming feasible as several forces (e.g., available big data, developed data assimilation (DA) techniques, and advanced cyber-infrastructure) are converging to transform ecological research into quantitative forecasting. To realize ecological forecasting, we have developed an Ecological Platform for Assimilating Data (EcoPAD, v1.0) into models. EcoPAD (v1.0) is a web-based software system that automates data transfer and processing from sensor networks to ecological forecasting through data management, model simulation, data assimilation, forecasting, and visualization. It facilitates interactive data–model integration from which the model is recursively improved through updated data while data are systematically refined under the guidance of model. EcoPAD (v1.0) relies on data from observations, process-oriented models, DA techniques, and the web-based workflow. We applied EcoPAD (v1.0) to the Spruce and Peatland Responses Under Climatic and Environmental change (SPRUCE) experiment in northern Minnesota. The EcoPAD-SPRUCE realizes fully automated data transfer, feeds meteorological data to drive model simulations, assimilates both manually measured and automated sensor data into the Terrestrial ECOsystem (TECO) model, and recursively forecasts the responses of various biophysical and biogeochemical processes to five temperature and two CO2 treatments in near-real time (weekly). Forecasting with EcoPAD-SPRUCE has revealed that mismatches in forecasting carbon pool dynamics are more related to model (e.g., model structure, parameter, and initial value) than forcing variables, opposite to forecasting flux variables. EcoPAD-SPRUCE quantified acclimations of methane production in response to warming treatments through shifted posterior distributions of the CH4:CO2 ratio and the temperature sensitivity (Q10) of methane production towards lower values. Different case studies indicated that realistic forecasting of carbon dynamics relies on appropriate model structure, correct parameterization, and accurate external forcing. Moreover, EcoPAD-SPRUCE stimulated active feedbacks between experimenters and modelers to identify model components to be improved and additional measurements to be taken. It has become an interactive model–experiment (ModEx) system and opens a novel avenue for interactive dialogue between modelers and experimenters. Altogether, EcoPAD (v1.0) acts to integrate multiple sources of information and knowledge to best inform ecological forecasting.

The rapid advancement of global navigation satellite system (GNSS) occultation technology in recent years has made it one of the most advanced space-based remote sensing technologies of the 21st century. GNSS radio occultation has many advantages, including all-weather operation, global coverage, high vertical resolution, high precision, long-term stability, and self-calibration. Data products from GNSS occultation sounding can greatly enhance ionospheric observations and contribute to space weather monitoring, forecasting, modeling, and research. In this study, GNSS occultation sounder (GNOS) results from a radio occultation sounding payload aboard the Fengyun 3 C (FY3-C) satellite were compared with ground-based ionosonde observations. Correlation coefficients for peak electron density (NmF2) derived from GNOS Global Position System (GPS) and Beidou navigation system (BDS) products with ionosonde data were higher than 0.9, and standard deviations were less than 20 %. Global ionospheric effects of the strong magnetic storm event in March 2015 were analyzed using GNOS results supported by ionosonde observations. The magnetic storm caused a significant disturbance in NmF2 level. Suppressed daytime and nighttime NmF2 levels indicated mainly negative storm conditions. In two longitude section zones of geomagnetic inclination between 40 and 80∘, the results of average NmF2 observed by GNOS and ground-based ionosondes showed the same basic trends during the geomagnetic storm and confirmed the negative effect of this storm event on the ionosphere. The analysis demonstrates the reliability of the GNSS radio occultation sounding instrument GNOS aboard the FY3-C satellite and confirms the utility of ionosphere products from GNOS for statistical and event-specific ionospheric physical analyses. Future FY3 series satellites and increasing numbers of Beidou navigation satellites will provide increasing GNOS occultation data on the ionosphere, which will contribute to ionosphere research and forecasting applications.

One known bias in current Earth system models (ESMs) is the underestimation of global mean soil carbon (C) transit time (τsoil), which quantifies the age of the C atoms at the time they leave the soil. However, it remains unclear where such underestimations are located globally. Here, we constructed a global database of measured τsoil across 187 sites to evaluate results from 12 ESMs. The observations showed that the estimated τsoil was dramatically shorter from the soil incubation studies in the laboratory environment (median = 4 years; interquartile range = 1 to 25 years) than that derived from field in situ measurements (31; 5 to 84 years) with shifts in stable isotopic C (13C) or the stock-over-flux approach. In comparison with the field observations, the multi-model ensemble simulated a shorter median (19 years) and a smaller spatial variation (6 to 29 years) of τsoil across the same site locations. We then found a significant and negative linear correlation between the in situ measured τsoil and mean annual air temperature. The underestimations of modeled τsoil are mainly located in cold and dry biomes, especially tundra and desert. Furthermore, we showed that one ESM (i.e., CESM) has improved its τsoil estimate by incorporation of the soil vertical profile. These findings indicate that the spatial variation of τsoil is a useful benchmark for ESMs, and we recommend more observations and modeling efforts on soil C dynamics in regions limited by temperature and moisture.

The interaction between terrestrial carbon (C) and nitrogen (N) cycles has been incorporated into more and more land surface models. However, the scheme of C–N coupling differs greatly among models, and how these diverse representations of C–N interactions will affect C-cycle modeling remains unclear. In this study, we explored how the simulated ecosystem C storage capacity in the terrestrial ecosystem (TECO) model varied with three different commonly used schemes of C–N coupling. The three schemes (SM1, SM2, and SM3) have been used in three different coupled C–N models (i.e., TECO-CN, CLM 4.5, and O-CN, respectively). They differ mainly in the stoichiometry of C and N in vegetation and soils, plant N uptake strategies, downregulation of photosynthesis, and the pathways of N import. We incorporated the three C–N coupling schemes into the C-only version of the TECO model and evaluated their impacts on the C cycle with a traceability framework. Our results showed that all three of the C–N schemes caused significant reductions in steady-state C storage capacity compared with the C-only version with magnitudes of −23 %, −30 %, and −54 % for SM1, SM2, and SM3, respectively. This reduced C storage capacity was mainly derived from the combined effects of decreases in net primary productivity (NPP; −29 %, −15 %, and −45 %) and changes in mean C residence time (MRT; 9 %, −17 %, and −17 %) for SM1, SM2, and SM3, respectively. The differences in NPP are mainly attributed to the different assumptions on plant N uptake, plant tissue C  :  N ratio, downregulation of photosynthesis, and biological N fixation. In comparison, the alternative representations of the plant vs. microbe competition strategy and the plant N uptake, combined with the flexible C  :  N ratio in vegetation and soils, led to a notable spread in MRT. These results highlight the fact that the diverse assumptions on N processes represented by different C–N coupled models could cause additional uncertainty for land surface models. Understanding their difference can help us improve the capability of models to predict future biogeochemical cycles of terrestrial ecosystems.

The Global Navigation Satellite System (GNSS) Occultation Sounder (GNOS) is one of the new-generation payloads on board the Chinese FengYun 3 (FY-3) series of operational meteorological satellites for sounding the Earth's neutral atmosphere and ionosphere. FY-3C GNOS, on board the FY-3 series C satellite launched in September 2013, was designed to acquire setting and rising radio occultation (RO) data by using GNSS signals from both the Chinese BeiDou Navigation Satellite System (BDS) and the US Global Positioning System (GPS). So far, the GNOS measurements and atmospheric and ionospheric data products have been validated and evaluated and then been used for atmosphere- and ionosphere-related scientific applications.This paper reviews the FY-3C GNOS instrument, RO data processing, data quality evaluation, and preliminary research applications according to the state-of-the-art status of the FY-3C GNOS mission and related publications. The reviewed data validation and application results demonstrate that the FY-3C GNOS mission can provide accurate and precise atmospheric and ionospheric GNSS (i.e., GPS and BDS) RO profiles for numerical weather prediction (NWP), global climate monitoring (GCM), and space weather research (SWR). The performance of the FY-3C GNOS product quality evaluation and scientific applications establishes confidence that the GNOS data from the series of FY-3 satellites will provide important contributions to NWP, GCM, and SWR scientific communities.

Skeletonema costatum is a common bloom-forming diatom and encounters eutrophication and severe carbon dioxide (CO2) limitation during red tides. However, little is known regarding the role of phosphorus (P) in modulating inorganic carbon acquisition in S. costatum, particularly under CO2 limitation conditions. We cultured S. costatum under five phosphate levels (0.05, 0.25, 1, 4, 10 µmol L−1) and then treated it with two CO2 conditions (2.8 and 12.6 µmol L−1) for 2 h. The lower CO2 reduced net photosynthetic rate at lower phosphate levels (−1) but did not affect it at higher phosphate levels (4 and 10 µmol L−1). In contrast, the lower CO2 induced a higher dark respiration rate at lower phosphate levels (0.05 and 0.25 µmol L−1) and did not affect it at higher phosphate levels (> 1 µmol L−1). The lower CO2 did not change relative electron transport rate (rETR) at lower phosphate levels (0.05 and 0.25 µmol L−1) and increased it at higher phosphate levels (> 1 µmol L−1). Photosynthetic CO2 affinity (1/K0.5) increased with phosphate levels. The lower CO2 did not affect photosynthetic CO2 affinity at 0.05 µmol L−1 phosphate but enhanced it at the other phosphate levels. Activity of extracellular carbonic anhydrase was dramatically induced by the lower CO2 in phosphate-replete conditions (> 0.25 µmol L−1) and the same pattern also occurred for redox activity of the plasma membrane. Direct bicarbonate (HCO3−) use was induced when phosphate concentration was more than 1 µmol L−1. These findings indicate P enrichment could enhance inorganic carbon acquisition and thus maintain the photosynthesis rate in S. costatum grown under CO2-limiting conditions via increasing activity of extracellular carbonic anhydrase and facilitating direct HCO3− use. This study sheds light on how bloom-forming algae cope with carbon limitation during the development of red tides.

The Global Navigation Satellite System (GNSS) Occultation Sounder (GNOS) is one of the new-generation payloads onboard the Chinese FengYun 3 (FY-3) series of operational meteorological satellites for sounding the Earth's neutral atmosphere and ionosphere. The GNOS was designed for acquiring setting and rising radio occultation (RO) data by using GNSS signals from both the Chinese BeiDou System (BDS) and the US Global Positioning System (GPS). An ultra-stable oscillator with 1 s stability (Allan deviation) at the level of 10−12 was installed on the FY-3C GNOS, and thus both zero-difference and single-difference excess phase processing methods should be feasible for FY-3C GNOS observations. In this study we focus on evaluating zero-difference processing of BDS RO data vs. single-difference processing, in order to investigate the zero-difference feasibility for this new instrument, which after its launch in September 2013 started to use BDS signals from five geostationary orbit (GEO) satellites, five inclined geosynchronous orbit (IGSO) satellites and four medium Earth orbit (MEO) satellites. We used a 3-month set of GNOS BDS RO data (October to December 2013) for the evaluation and compared atmospheric bending angle and refractivity profiles, derived from single- and zero-difference excess phase data, against co-located profiles from European Centre for Medium-Range Weather Forecasts (ECMWF) analyses. We also compared against co-located refractivity profiles from radiosondes. The statistical evaluation against these reference data shows that the results from single- and zero-difference processing are reasonably consistent in both bias and standard deviation, clearly demonstrating the feasibility of zero differencing for GNOS BDS RO observations. The average bias (and standard deviation) of the bending angle and refractivity profiles were found to be about 0.05 to 0.2 % (and 0.7 to 1.6 %) over the upper troposphere and lower stratosphere. Zero differencing was found to perform slightly better, as may be expected from its lower vulnerability to noise. The validation results indicate that GNOS can provide, on top of GPS RO profiles, accurate and precise BDS RO profiles both from single- and zero-difference processing. The GNOS observations by the series of FY-3 satellites are thus expected to provide important contributions to numerical weather prediction and global climate change analysis.

Under the Grain for Green Project in China, vegetation recovery construction has been widely implemented on the Loess Plateau for the purpose of soil and water conservation. Now it is becoming controversial whether the recovery construction involving vegetation, particularly forest, is reducing the streamflow in the rivers of the Yellow River basin. In this study, we chose the Wei River, the largest branch of the Yellow River, with revegetated construction area as the study area. To do that, we apply the widely used Soil and Water Assessment Tool (SWAT) model for the upper and middle reaches of the Wei River basin. The SWAT model was forced with daily observed meteorological forcings (1960–2009) calibrated against daily streamflow for 1960–1969, validated for the period of 1970–1979, and used for analysis for 1980–2009. To investigate the impact of LUCC (land use and land cover change) on the streamflow, we firstly use two observed land use maps from 1980 and 2005 that are based on national land survey statistics merged with satellite observations. We found that the mean streamflow generated by using the 2005 land use map decreased in comparison with that using the 1980 one, with the same meteorological forcings. Of particular interest here is that the streamflow decreased on agricultural land but increased in forest areas. More specifically, the surface runoff, soil flow, and baseflow all decreased on agricultural land, while the soil flow and baseflow of forest areas increased. To investigate that, we then designed five scenarios: (S1) the present land use (1980) and (S2) 10 %, (S3) 20 %, (S4) 40 %, and (S5) 100 % of agricultural land that was converted into mixed forest. We found that the streamflow consistently increased with agricultural land converted into forest by about 7.4 mm per 10 %. Our modeling results suggest that forest recovery construction has a positive impact on both soil flow and baseflow by compensating for reduced surface runoff, which leads to a slight increase in the streamflow in the Wei River with the mixed landscapes on the Loess Plateau that include earth–rock mountain area.

Terrestrial ecosystems have absorbed roughly 30 % of anthropogenic CO2 emissions over the past decades, but it is unclear whether this carbon (C) sink will endure into the future. Despite extensive modeling and experimental and observational studies, what fundamentally determines transient dynamics of terrestrial C storage under global change is still not very clear. Here we develop a new framework for understanding transient dynamics of terrestrial C storage through mathematical analysis and numerical experiments. Our analysis indicates that the ultimate force driving ecosystem C storage change is the C storage capacity, which is jointly determined by ecosystem C input (e.g., net primary production, NPP) and residence time. Since both C input and residence time vary with time, the C storage capacity is time-dependent and acts as a moving attractor that actual C storage chases. The rate of change in C storage is proportional to the C storage potential, which is the difference between the current storage and the storage capacity. The C storage capacity represents instantaneous responses of the land C cycle to external forcing, whereas the C storage potential represents the internal capability of the land C cycle to influence the C change trajectory in the next time step. The influence happens through redistribution of net C pool changes in a network of pools with different residence times. Moreover, this and our other studies have demonstrated that one matrix equation can replicate simulations of most land C cycle models (i.e., physical emulators). As a result, simulation outputs of those models can be placed into a three-dimensional (3-D) parameter space to measure their differences. The latter can be decomposed into traceable components to track the origins of model uncertainty. In addition, the physical emulators make data assimilation computationally feasible so that both C flux- and pool-related datasets can be used to better constrain model predictions of land C sequestration. Overall, this new mathematical framework offers new approaches to understanding, evaluating, diagnosing, and improving land C cycle models.

Attributing changes in evapotranspiration (ET) and gross primary productivity (GPP) is crucial for impact and adaptation assessment of the agro-ecosystems to climate change. Simulations with the VIP model revealed that annual ET and GPP slightly increased from 1981 to 2013 over the North China Plain. The tendencies of both ET and GPP were upward in the spring season, while they were weak and downward in the summer season. A complete factor analysis illustrated that the relative contributions of climatic change, CO2 fertilization, and management to the ET (GPP) trend were 56 (−32) %, −28 (25) %, and 68 (108) %, respectively. The decline of global radiation resulted from deteriorated aerosol and air pollution was the principal cause of GPP decline in summer, while air warming intensified the water cycle and advanced the plant productivity in the spring season. Generally, agronomic improvements were the principal drivers of crop productivity enhancement.

Representations of the terrestrial carbon cycle in land models are becoming increasingly complex. It is crucial to develop approaches for critical assessment of the complex model properties in order to understand key factors contributing to models' performance. In this study, we applied a traceability analysis which decomposes carbon cycle models into traceable components, for two global land models (CABLE and CLM-CASA′) to diagnose the causes of their differences in simulating ecosystem carbon storage capacity. Driven with similar forcing data, CLM-CASA′ predicted ∼ 31 % larger carbon storage capacity than CABLE. Since ecosystem carbon storage capacity is a product of net primary productivity (NPP) and ecosystem residence time (τE), the predicted difference in the storage capacity between the two models results from differences in either NPP or τE or both. Our analysis showed that CLM-CASA′ simulated 37 % higher NPP than CABLE. On the other hand, τE, which was a function of the baseline carbon residence time (τ′E) and environmental effect on carbon residence time, was on average 11 years longer in CABLE than CLM-CASA′. This difference in τE was mainly caused by longer τ′E of woody biomass (23 vs. 14 years in CLM-CASA′), and higher proportion of NPP allocated to woody biomass (23 vs. 16 %). Differences in environmental effects on carbon residence times had smaller influences on differences in ecosystem carbon storage capacities compared to differences in NPP and τ′E. Overall, the traceability analysis showed that the major causes of different carbon storage estimations were found to be parameters setting related to carbon input and baseline carbon residence times between two models.

Integrated water system modeling is a feasible approach to understanding severe water crises in the world and promoting the implementation of integrated river basin management. In this study, a classic hydrological model (the time variant gain model: TVGM) was extended to an integrated water system model by coupling multiple water-related processes in hydrology, biogeochemistry, water quality, and ecology, and considering the interference of human activities. A parameter analysis tool, which included sensitivity analysis, autocalibration and model performance evaluation, was developed to improve modeling efficiency. To demonstrate the model performances, the Shaying River catchment, which is the largest highly regulated and heavily polluted tributary of the Huai River basin in China, was selected as the case study area. The model performances were evaluated on the key water-related components including runoff, water quality, diffuse pollution load (or nonpoint sources) and crop yield. Results showed that our proposed model simulated most components reasonably well. The simulated daily runoff at most regulated and less-regulated stations matched well with the observations. The average correlation coefficient and Nash–Sutcliffe efficiency were 0.85 and 0.70, respectively. Both the simulated low and high flows at most stations were improved when the dam regulation was considered. The daily ammonium–nitrogen (NH4–N) concentration was also well captured with the average correlation coefficient of 0.67. Furthermore, the diffuse source load of NH4–N and the corn yield were reasonably simulated at the administrative region scale. This integrated water system model is expected to improve the simulation performances with extension to more model functionalities, and to provide a scientific basis for the implementation in integrated river basin managements.

Ancient architecture is an important cultural symbol of a nation, which has high historical, artistic and technology of cultural value. A building not only carries the creator of effort, but also the past with the future of the historical traditions and humanistic significance. It is not purely construction of artistic expression, even more the witness of the production and development of social groups. Therefore, it is not only the common cultural heritage of mankind, as more equally important to protect these ancient buildings for the promotion of spiritual civilization and local economic development. In recent years, China and other developing countries, which in the pursuit of rapid economic development, are also facing the problems of development and preservation, Especially influenced by the inherent "reform and innovation" traditional concepts, many ancient villages and buildings with rich cultural connotation are in a great danger. Xiang'an is one of the six administrative regions of Xiamen, The Tungyuan village and numerous surrounding villages which in Xiang'an retain a large number of ancient buildings of Ming and Qing Dynasties, but it has not been given due attention, many ancient buildings are facing the crisis of disappearing. Changs ancient residential is one of typical Minnan architectural which located in Tungyuan village. its main feature is as follows: Cheng is before the rear is Cuo, Facing south, Three bays with double Hucuo , Red brick and White stone wall, Architectural form of Hard mountain type roof and Double cocked dovetail ridge. In this paper, on the basis of the fieldwork, In addition to the overall building community environment and monomer building surveying and mapping, photograph, record, and through the collection, interviews and analysis of relevant historical materials, etc. Grasping the historical background of Changs ancient residential building community, exploring the formation and characteristics of the overall layout of the community, analyzing the cultural connotation of the basic shape of each individual building and architectural decorative arts, and making recommendations for saving Changs ancient residential maintenance.

In mountainous areas of southwestern China, especially Guizhou province, continuous, broadly distributed karst landscapes with harsh and fragile habitats often lead to land degradation. Research indicates that vegetation located in karst terrains has low aboveground biomass and land degradation that reduces vegetation biomass, but belowground biomass measurements are rarely reported. Using the soil pit method, we investigated the root biomass of karst vegetation in five land cover types: grassland, grass–scrub tussock, thorn–scrub shrubland, scrub–tree forest, and mixed evergreen and deciduous forest in Maolan, southern Guizhou province, growing in two different soil-rich and rock-dominated habitats. The results show that roots in karst vegetation, especially the coarse roots, and roots in rocky habitats are mostly distributed in the topsoil layers (89 % on the surface up to 20 cm depth). The total root biomass in all habitats of all vegetation degradation periods is 18.77 Mg ha−1, in which roots in rocky habitat have higher biomass than in earthy habitat, and coarse root biomass is larger than medium and fine root biomass. The root biomass of mixed evergreen and deciduous forest in karst habitat (35.83 Mg ha−1) is not greater than that of most typical, non-karst evergreen broad-leaved forests in subtropical regions of China, but the ratio of root to aboveground biomass in karst forest (0.37) is significantly greater than the mean ratio (0.26 ± 0.07) of subtropical evergreen forests. Vegetation restoration in degraded karst terrain will significantly increase the belowground carbon stock, forming a potential regional carbon sink.

A long-term (33 years) experiments were conducted to investigate the effect of chemical fertilization on rice yield, yield trends, soil properties, agronomic efficiency of applied nutrients and nutrient balance for the double rice cropping systems in subtropical China. The treatments were different combinations of N, P and K fertilizers (N, NP, NK and NPK), double dose of recommended NPK (2NPK) and no fertilizer control (control). Compared with no fertilizer control, all fertilization treatments had no significant effects on soil pH and SOC contents (P > 0.05), but generally increased nutrients content when corresponding elements were applied. The impact of fertilizers on grain yields was 2NPK > NPK > NP > NK > N, and application of P fertilizer not only increased the rice yield, but improved yield stability. The trend of agronomic use efficiency of applied P was significantly positive (P < 0.05) only for the first rice crop, suggesting that P fertilizer played a less important role in the second rice season than in the first rice season. The study indicated that the current local fertilizer recommendations should be optimized for the consideration of differences in indigenous nutrient supplies in different rice seasons.

Magnetic skyrmions might be used for building next-generation nanomagnetic and spintronic devices, as they have several perspective properties, such as topologically protected stability, nanoscale size, and ultra-low depinning current density. Here we study the influence of the edge effect on the current-induced generation of a magnetic skyrmion in a finite-length thin-film ferromagnetic nanotrack with interface-induced Dzyaloshinskii-Moriya interaction. It shows that a stable skyrmion or a bunch of skyrmions can be successfully generated as long as the distance between the current injection region and the nanotrack terminal is larger than a certain threshold. We investigate the failed skyrmion generation caused by the edge effect, which will lead to an error writing event. We also present the phase diagrams of the skyrmion generation obtained for different material and geometric parameters. Our results could be useful for designing skyrmion-based information storage devices.

This paper evaluates the performance of a statistical post-processor for imperfect hydrologic model forecasts. Assuming that the meteorological forecasts are well-calibrated, we employ a "General Linear Model (GLM)" to post-process simulations produced by a hydrologic model. For a particular forecast date, the observations and simulations from an "analysis window" and hydrologic model forecasts for a "forecast window", the GLM Post-Processor (GLMPP) is used to produce an ensemble of predictions of the streamflow observations that will occur during the "forecast window". The objectives of the GLMPP are to: (1) preserve any skill in the original hydrologic ensemble forecast; (2) correct systematic model biases; (3) retain the equal-likelihood assumption for the ensemble; (4) preserve temporal scale dependency relationships in streamflow hydrographs and the uncertainty in the predictions; and, (5) produce reliable ensemble predictions. Observed and simulated daily streamflow data from the Second Workshop on Model Parameter Estimation Experiment (MOPEX) are used to test how well these objectives are met when the GLMPP is applied to ensemble hydrologic forecasts driven by well calibrated meteorological forecasts. A 39-year hydrologic dataset from the French Broad basin is split into calibration and verification periods. The results show that the GLMPP built using data from the calibration period removes the mean bias when applied to hydrologic model simulations from both the calibration and verification periods. Probability distributions of the post-processed model simulations are shown to be closer to the climatological probability distributions of observed streamflow than the distributions of the unadjusted simulated flows. A number of experiments with different GLMPP configurations were also conducted to examine the effects of different configurations for forecast and analysis window lengths on the robustness of the results.

The magnitude of daily minimum temperature increase is greater than that of daily maximum temperature increase under climate warming. This study was conducted to examine whether changes in soil respiration under diurnal warming are equal to the summed changes under day and night warming in a temperate steppe in northern China. A full factorial design with day and night warming was used in this study, including control, day (06:00 a.m.–06:00 p.m., local time) warming, night (06:00 p.m.–06:00 a.m.) warming, and diurnal warming. Day warming showed no effect on soil respiration, whereas night warming significantly increased soil respiration by 7.1% over the 3 growing seasons in 2006–2008. The insignificant effect of day warming on soil respiration could be attributable to the offset of the direct positive effects of increased temperature by the indirect negative effects via aggravating water limitation and suppressing ecosystem C assimilation. The positive effects of night warming on soil respiration were largely due to the stimulation of ecosystem C uptake and substrate supply via overcompensation of plant photosynthesis. Changes in both soil respiration (+20.7 g C m−2 y−1) and GEP (−2.8 g C m−2 y−1) under diurnal warming are smaller than their summed changes (+40.0 and +24.6 g C m−2 y−1, respectively) under day and night warming. Our findings that the effects of diurnal warming on soil respiration and gross ecosystem productivity are not equal to the summed effects of day and night warming are critical for model simulation and projection of climate-carbon feedback.

Purpose. Angiosarcoma is a rare tumor with endothelial cell differentiation that may arise in any anatomic location.The purpose of this report was to identify prognostic factors on outcome in a group of prospectively followed patients with confirmed angiosarcoma.