Fingerprint of rice paddies in spatial-temporal dynamics of atmospheric methane concentration in monsoon Asia.

Agriculture (e.g., rice paddies) has been considered one of the main emission sources responsible for the sudden rise of atmospheric methane concentration (XCH4) since 2007, but remains debated. Here we use satellite-based rice paddy and XCH4 data to investigate the spatial-temporal relationships between rice paddy area, rice plant growth, and XCH4 in monsoon Asia, which accounts for ~87% of the global rice area. We find strong spatial consistencies between rice paddy area and XCH4 and seasonal consistencies between rice plant growth and XCH4. Our results also show a decreasing trend in rice paddy area in monsoon Asia since 2007, which suggests that the change in rice paddy area could not be one of the major drivers for the renewed XCH4 growth, thus other sources and sinks should be further investigated. Our findings highlight the importance of satellite-based paddy rice datasets in understanding the spatial-temporal dynamics of XCH4 in monsoon Asia

Estimating leaf area index and aboveground biomass of grazing pastures using Sentinel-1, Sentinel-2 and Landsat images

Grassland degradation has accelerated in recent decades in response to increased climate variability and human activity. Rangeland and grassland conditions directly affect forage quality, livestock production, and regional grassland resources. In this study, we examined the potential of integrating synthetic aperture radar (SAR, Sentinel-1) and optical remote sensing (Landsat-8 and Sentinel-2) data to monitor the conditions of a native pasture and an introduced pasture in Oklahoma, USA. Leaf area index (LAI) and aboveground biomass (AGB) were used as indicators of pasture conditions under varying climate and human activities. We estimated the seasonal dynamics of LAI and AGB using Sentinel-1 (S1), Landsat-8 (LC8), and Sentinel-2 (S2) data, both individually and integrally, applying three widely used algorithms: Multiple Linear Regression (MLR), Support Vector Machine (SVM), and Random Forest (RF). Results indicated that integration of LC8 and S2 data provided sufficient data to capture the seasonal dynamics of grasslands at a 10–30-m spatial resolution and improved assessments of critical phenology stages in both pluvial and dry years. The satellite-based LAI and AGB models developed from ground measurements in 2015 reasonably predicted the seasonal dynamics and spatial heterogeneity of LAI and AGB in 2016. By comparison, the integration of S1, LC8, and S2 has the potential to improve the estimation of LAI and AGB more than 30% relative to the performance of S1 at low vegetation cover (LAI \u3c 2m2/m2, AGB \u3c 500 g/m2) and optical data of LC8 and S2 at high vegetation cover (LAI \u3e 2m2/m2, AGB \u3e 500 g/m2). These results demonstrate the potential of combining S1, LC8, and S2 monitoring grazing tallgrass prairie to provide timely and accurate data for grassland management

Focus on form: A critical review

‘Focus on form’ (FonF) is a central construct in task-based language teaching. The term was first introduced by Michael Long to refer to an approach where learners’ attention is attracted to linguistic forms as they engage in the performance of tasks. It contrasts with a structure-based approach – ‘focus on forms’ (FonFs) – where specific linguistic forms are taught directly and explicitly. However, there is perhaps no construct in second language acquisition (SLA) that has proved so malleable and shifted in meaning so much. This review article begins by considering how Long’s original definition of it has stretched over time and then offers an updated definition of the construct based on the view that the term is best used to refer to specific kinds of ‘activities’ or ‘procedures’ rather than to an ‘approach’. A classification of different types of focus-on-form activities/procedures is then presented. There follows a discussion of focus on form from a psycholinguistic and discoursal perspective along with a review of research relevant to these perspectives. The article addresses a number of criticisms that have been levelled against focus on form, with special consideration paid to how focus on form can be utilized in instructional contexts where more traditional (i.e. FonFs) approaches have been the norm

Ecological engineering projects increased vegetation cover, production, and biomass in semiarid and subhumid Northern China

Multiple ecological engineering projects have been implemented in semiarid and subhumid Northern China since 1978 with the purpose to combat desertification, control dust storms, and improve vegetation cover. Although a plethora of local studies exist, the effectiveness of these projects has not been studied in a systematic and comprehensive way. Here, we used multiple satellite-based time-series data as well as breakpoint analysis to assess shifts in leaf area index (a proxy for green vegetation cover), gross primary production, and aboveground biomass in Northern China. We documented increased vegetation growth in northwest and southeastern parts of the region, despite drought anomalies as documented by the standardized precipitation-evapotranspiration index during 1982–2016. Significant breakpoints in leaf area index were observed for over 72.5% of the southeastern and northwestern regions, and 70.6% of these breakpoints were detected after 1999, which correspond well to the areas with the highest ecological engineering efforts. Areas with negative trends were mainly located in the Inner Mongolian Plateau, Hulun Biur, Horqin Sand Land, and urban areas. The Loess Plateau had the largest increase in vegetation growth, followed by the north parts of Northern China where biomass increased more in the provinces of Shanxi, Liaoning, Shannxi, Hebei, and Beijing than Xinjiang, Inner Mongolia, Tianjin, and Qinghai. Our results show that multiple ecological engineering projects in the region have increased vegetation cover, production, and aboveground biomass that have led to improved environmental conditions in the study area

Low temperature Rosseland opacities with varied abundances of carbon and nitrogen

We attempt to produce low temperature opacity data incorporating the effects of varied abundances of the elements carbon and nitrogen. For our temperature range of interest, molecules represent the dominant opacity source. Our dataset covers a wide metallicity range and is meant to provide important input data for stellar evolution models and other applications. We conduct chemical equilibrium calculations to evaluate the partial pressures of neutral atoms, ions, and molecules. Based on a large dataset containing atomic line and continuum data and, most importantly, a plethora of molecular lines, we calculate Rosseland mean opacity coefficients not only for a number of different metallicities, but also for varied abundances of the isotopes ^{12}C and ^{14}N at each metallicity. The molecular data comprise the main opacity sources for either an oxygen-rich or carbon-rich chemistry. We tabulate the opacity coefficients as a function of temperature and, basically, density. Due to the special role of the CO molecule, within a certain chemistry regime an alteration to the carbon abundance causes considerable changes in the Rosseland opacity. The transition from a scaled solar (i. e. oxygen-rich) mixture to a carbon-rich regime results in opacities that can, at low temperatures, differ by orders of magnitude from to the initial situation. The reason is that the mean opacity in either case is due to different molecular absorbers. Variations in the abundance of nitrogen have less pronounced effects but, nevertheless, cannot be neglected. [abridged]Comment: 14 pages, 11 figures, 3 tables, accepted for publication in A&A, language revised. The data described in the article are available at the CDS or on request from the autho

Pest population dynamics are related to a continental overwintering gradient

Overwintering success is an important determinant of arthropod populations that must be considered as climate change continues to influence the spatiotemporal population dynamics of agricultural pests. Using a long-term monitoring database and biologically relevant overwintering zones, we modeled the annual and seasonal population dynamics of a common pest, Helicoverpa zea (Boddie), based on three overwintering suitability zones throughout North America using four decades of soil temperatures: the southern range (able to persist through winter), transitional zone (uncertain overwintering survivorship), and northern limits (unable to survive winter). Our model indicates H. zea population dynamics are hierarchically structured with continental-level effects that are partitioned into three geographic zones. Seasonal populations were initially detected in the southern range, where they experienced multiple large population peaks. All three zones experienced a final peak between late July (southern range) and mid-August to mid-September (transitional zone and northern limits). The southern range expanded by 3% since 1981 and is projected to increase by twofold by 2099 but the areas of other zones are expected to decrease in the future. These changes suggest larger populations may persist at higher latitudes in the future due to reduced low-temperature lethal events during winter. Because H. zea is a highly migratory pest, predicting when populations accumulate in one region can inform synchronous or lagged population development in other regions. We show the value of combining long-term datasets, remotely sensed data, and laboratory findings to inform forecasting of insect pests

General anaesthetic and airway management practice for obstetric surgery in England: a prospective, multi-centre observational study

There are no current descriptions of general anaesthesia characteristics for obstetric surgery, despite recent changes to patient baseline characteristics and airway management guidelines. This analysis of data from the direct reporting of awareness in maternity patients' (DREAMY) study of accidental awareness during obstetric anaesthesia aimed to describe practice for obstetric general anaesthesia in England and compare with earlier surveys and best-practice recommendations. Consenting patients who received general anaesthesia for obstetric surgery in 72 hospitals from May 2017 to August 2018 were included. Baseline characteristics, airway management, anaesthetic techniques and major complications were collected. Descriptive analysis, binary logistic regression modelling and comparisons with earlier data were conducted. Data were collected from 3117 procedures, including 2554 (81.9%) caesarean deliveries. Thiopental was the induction drug in 1649 (52.9%) patients, compared with propofol in 1419 (45.5%). Suxamethonium was the neuromuscular blocking drug for tracheal intubation in 2631 (86.1%), compared with rocuronium in 367 (11.8%). Difficult tracheal intubation was reported in 1 in 19 (95%CI 1 in 16-22) and failed intubation in 1 in 312 (95%CI 1 in 169-667). Obese patients were over-represented compared with national baselines and associated with difficult, but not failed intubation. There was more evidence of change in practice for induction drugs (increased use of propofol) than neuromuscular blocking drugs (suxamethonium remains the most popular). There was evidence of improvement in practice, with increased monitoring and reversal of neuromuscular blockade (although this remains suboptimal). Despite a high risk of difficult intubation in this population, videolaryngoscopy was rarely used (1.9%)