Chinese students in a UK business school: hearing the student voice in reflective teaching and learning practice.

This paper presents the outcomes of a study carried out in 2001-2002 with nine postgraduate students from China, enrolled on taught master's programmes in a UK university business school. The aims of the research were to explore the development of the students' orientations to learning during their year of study in the UK, and to explore how the researcher's interactions with the study group contributed to her professional reflections and influenced her academic practice. The main conclusions of the project were that participants' underlying approaches to learning did not change substantially over the year, owing to the culturally implicit nature of UK academic conventions and that they experienced high levels of emotional isolation and loneliness, which affected their academic confidence

The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.Peer reviewe

Residential proximity to industrial combustion facilities and risk of non-Hodgkin lymphoma: a case–control study

Abstract Background Residence near municipal solid waste incinerators, a major historical source of dioxin emissions, has been associated with increased risk of non-Hodgkin lymphoma (NHL) in European studies. The aim of our study was to evaluate residence near industrial combustion facilities and estimates of dioxin emissions in relation to NHL risk in the United States. Methods We conducted a population-based case–control study of NHL (1998–2000) in four National Cancer Institute-Surveillance Epidemiology and End Results centers (Detroit, Iowa, Los Angeles, Seattle). Residential histories 15 years before diagnosis (similar date for controls) were linked to an Environmental Protection Agency database of dioxin-emitting facilities for 969 cases and 749 controls. We evaluated proximity (3 and 5 km) to 10 facility types that accounted for \u3e85% of U.S. emissions and a distance-weighted average emission index (AEI [ng toxic equivalency quotient (TEQ)/year]). Results Proximity to any dioxin-emitting facility was not associated with NHL risk (3 km OR = 1.0, 95% CI 0.8-1.3). Risk was elevated for residence near cement kilns (5 km OR = 1.7, 95% CI 0.8-3.3; 3 km OR = 3.8, 95% CI 1.1-14.0) and reduced for residence near municipal solid waste incinerators (5 km OR = 0.5, 95% CI 0.3-0.9; 3 km OR = 0.3, 95% CI 0.1-1.4). The AEI was not associated with risk of NHL overall. Risk for marginal zone lymphoma was increased for the highest versus lowest quartile (5 km OR = 2.6, 95% CI 1.0-6.8; 3 km OR = 3.0, 95% CI 1.1-8.3). Conclusions Overall, we found no association with residential exposure to dioxins and NHL risk. However, findings for high emissions and marginal zone lymphoma and for specific facility types and all NHL provide some evidence of an association and deserve future study

Residential proximity to industrial combustion facilities and risk of non-Hodgkin lymphoma: a case–control study

Abstract Background Residence near municipal solid waste incinerators, a major historical source of dioxin emissions, has been associated with increased risk of non-Hodgkin lymphoma (NHL) in European studies. The aim of our study was to evaluate residence near industrial combustion facilities and estimates of dioxin emissions in relation to NHL risk in the United States. Methods We conducted a population-based case–control study of NHL (1998–2000) in four National Cancer Institute-Surveillance Epidemiology and End Results centers (Detroit, Iowa, Los Angeles, Seattle). Residential histories 15 years before diagnosis (similar date for controls) were linked to an Environmental Protection Agency database of dioxin-emitting facilities for 969 cases and 749 controls. We evaluated proximity (3 and 5 km) to 10 facility types that accounted for \u3e85% of U.S. emissions and a distance-weighted average emission index (AEI [ng toxic equivalency quotient (TEQ)/year]). Results Proximity to any dioxin-emitting facility was not associated with NHL risk (3 km OR = 1.0, 95% CI 0.8-1.3). Risk was elevated for residence near cement kilns (5 km OR = 1.7, 95% CI 0.8-3.3; 3 km OR = 3.8, 95% CI 1.1-14.0) and reduced for residence near municipal solid waste incinerators (5 km OR = 0.5, 95% CI 0.3-0.9; 3 km OR = 0.3, 95% CI 0.1-1.4). The AEI was not associated with risk of NHL overall. Risk for marginal zone lymphoma was increased for the highest versus lowest quartile (5 km OR = 2.6, 95% CI 1.0-6.8; 3 km OR = 3.0, 95% CI 1.1-8.3). Conclusions Overall, we found no association with residential exposure to dioxins and NHL risk. However, findings for high emissions and marginal zone lymphoma and for specific facility types and all NHL provide some evidence of an association and deserve future study

Evaluation of the remote-sensing-based DIFFUSE model for estimating photosynthesis of vegetation

Vegetation captures carbon from the atmosphere through photosynthesis, the rate of which varies across space, through time and is determined by both physical and biological factors. Methods for estimating photosynthesis (A) vary in their complexity and in which driving processes they capture. Whilst the effect of diffuse shortwave irradiance on A is well understood, few models have explicitly incorporated the diffuse effect into estimates of A. Here we present the DIFFUSE model, a simple, generic, diffuse-light-based method for estimating A at the monthly time scale. This model is based on the assumption that, at the monthly time scale, the majority of variability in A can be explained by the variability in total and diffuse irradiance and in the fraction of shortwave irradiance absorbed by foliage (f). Comparison of model estimates to eddy flux tower-derived monthly A showed that the majority (83%) of variability in observed A could be explained by the DIFFUSE model. The diffuse fraction contributed 5 to 10% of the model's accuracy across many of Australia's coastal regions, but contributed up to 50% in the monsoonal north. Various aspects of the DIFFUSE model were tested including its performance relative to an example of the more commonly used "stress-scalar" type of photosynthesis model. In all tests, the DIFFUSE model performed at least as well as more complex alternative models, and often outperformed them. The strengths of DIFFUSE are its physical basis, its simplicity and transparency, and its minimalist data requirements - all of which are expected to make it useful to a wide variety of contexts and applications

The SMAP Level 4 Carbon Product for Monitoring Ecosystem Land-Atmosphere CO₂ Exchange

The National Aeronautics and Space Administration\u27s Soil Moisture Active Passive (SMAP) mission Level 4 Carbon (L4C) product provides model estimates of the Net Ecosystem CO₂ exchange (NEE) incorporating SMAP soil moisture information. The L4C product includes NEE, computed as total ecosystem respiration less gross photosynthesis, at a daily time step posted to a 9-km global grid by plant functional type. Component carbon fluxes, surface soil organic carbon stocks, underlying environmental constraints, and detailed uncertainty metrics are also included. The L4C model is driven by the SMAP Level 4 Soil Moisture data assimilation product, with additional inputs from the Goddard Earth Observing System, Version 5 weather analysis, and Moderate Resolution Imaging Spectroradiometer satellite vegetation data. The L4C data record extends from March 31, 2015 to present with ongoing production and 8-12 day latency. Comparisons against concurrent global CO₂ eddy flux tower measurements, satellite solar-induced canopy florescence, and other independent observation benchmarks show favorable L4C performance and accuracy, capturing the dynamic biosphere response to recent weather anomalies. Model experiments and L4C spatiotemporal variability were analyzed to understand the independent value of soil moisture and SMAP observations relative to other sources of input information. This analysis highlights the potential for microwave observations to inform models where soil moisture strongly controls land CO₂ flux variability; however, skill improvement relative to flux towers is not yet discernable within the relatively short validation period. These results indicate that SMAP provides a unique and promising capability for monitoring the linked global terrestrial water and carbon cycles

Carbon, water and energy fluxes in agricultural systems of Australia and New Zealand

A comprehensive understanding of the effects of agricultural management on climate–crop interactions has yet to emerge. Using a novel wavelet–statistics conjunction approach, we analysed the synchronisation amongst fluxes (net ecosystem exchange NEE, evapotranspiration and sensible heat flux) and seven environmental factors (e.g., air temperature, soil water content) on 19 farm sites across Australia and New Zealand. Irrigation and fertilisation practices improved positive coupling between net ecosystem productivity (NEP = −NEE) and evapotranspiration, as hypothesised. Highly intense management tended to protect against heat stress, especially for irrigated crops in dry climates. By contrast, stress avoidance in the vegetation of tropical and hot desert climates was identified by reverse coupling between NEP and sensible heat flux (i.e., increases in NEP were synchronised with decreases in sensible heat flux). Some environmental factors were found to be under management control, whereas others were fixed as constraints at a given location. Irrigated crops in dry climates (e.g., maize, almonds) showed high predictability of fluxes given only knowledge of fluctuations in climate (R2 > 0.78), and fluxes were nearly as predictable across strongly energy- or water-limited environments (0.60 2 2 2 2 < 0.36). By incorporating a temporal component to regression, wavelet–statistics conjunction provides an important step forward for understanding direct ecosystem responses to environmental change, for modelling that understanding, and for quantifying nonstationary, nonlinear processes such as precipitation pulses, which have previously defied quantitative analysis.</p