Corn (Zea mays L.) is an important crop that contributes to global food security, but understanding how farm management practices and soil health affect corn grain nutrient analysis and therefore human health is lacking. Leveraging Rodale Institute's Farming Systems Trial—a long-term field experiment established in 1981 in Kutztown, PA, USA—this study was conducted to assess the impact of different agricultural management systems on corn grain nutrient profiles in a long-term trial that has resulted in differences in soil health indicators between treatments as a result of long-term management. The main plot factor was two tillage practices (intensive and reduced) and the subplot factor was four cropping systems (non-diversified conventional [nCNV], diversified conventional [dCNV], legume-based organic [ORG-LEG], and manure-based organic [ORG-MNR]). Generally, the levels of amino acids, vitamins, and protein in corn grain were greatest in the ORG-MNR system, followed by the ORG-LEG and dCNV systems, and finally the nCNV system. It is important to consider that the observed difference between the organic and conventionally grown grain could be due to variations in corn hybrids that were used in those systems. However, nutrient composition of corn differed within cropping systems but between management practices (diversified crop rotation and cover cropping) which also contributed to differences in soil health indicators (soil compaction, soil protein, and organic C levels) that may also influence grain nutrient concentrations. With the exception of methionine, nutrient concentration in corn grain was not affected by different tillage regimes. These findings provide novel information on corn grain nutritional quality of organic and conventional cropping systems after long-term management and give insights into how system-specific components affect nutrient composition of corn grain.

The global population and status of Snowy Owls Bubo scandiacus are particularly challenging to assess because individuals are irruptive and nomadic, and the breeding range is restricted to the remote circumpolar Arctic tundra. The International Union for Conservation of Nature (IUCN) uplisted the Snowy Owl to “Vulnerable” in 2017 because the suggested population estimates appeared considerably lower than historical estimates, and it recommended actions to clarify the population size, structure, and trends. Here we present a broad review and status assessment, an effort led by the International Snowy Owl Working Group (ISOWG) and researchers from around the world, to estimate population trends and the current global status of the Snowy Owl. We use long-term breeding data, genetic studies, satellite-GPS tracking, and survival estimates to assess current population trends at several monitoring sites in the Arctic and we review the ecology and threats throughout the Snowy Owl range. An assessment of the available data suggests that current estimates of a worldwide population of 14,000–28,000 breeding adults are plausible. Our assessment of population trends at five long-term monitoring sites suggests that breeding populations of Snowy Owls in the Arctic have decreased by more than 30% over the past three generations and the species should continue to be categorised as Vulnerable under the IUCN Red List Criterion A2. We offer research recommendations to improve our understanding of Snowy Owl biology and future population assessments in a changing world.

We present the Pilot Survey Phase 2 data release for the Wide-field ASKAP L-band Legacy All-sky Blind surveY (WALLABY), carried-out using the Australian SKA Pathfinder (ASKAP). We present 1760 H i detections (with a default spatial resolution of 30′′) from three pilot fields including the NGC 5044 and NGC 4808 groups as well as the Vela field, covering a total of $\sim 180$ deg$^2$ of the sky and spanning a redshift up to $z \simeq 0.09$. This release also includes kinematic models for over 126 spatially resolved galaxies. The observed median rms noise in the image cubes is 1.7 mJy per 30′′ beam and 18.5 kHz channel. This corresponds to a 5$\sigma$ H i column density sensitivity of $\sim 9.1\times10^{19}(1 + z)^4$ cm$^{-2}$ per 30′′ beam and $\sim 20$ km s$^{-1}$ channel and a 5$\sigma$ H i mass sensitivity of $\sim 5.5\times10^8 (D/100$ Mpc)$^{2}$ M$_{\odot}$ for point sources. Furthermore, we also present for the first time 12′′ high-resolution images (“cut-outs”) and catalogues for a sub-sample of 80 sources from the Pilot Survey Phase 2 fields. While we are able to recover sources with lower signal-to-noise ratio compared to sources in the Public Data Release 1, we do note that some data quality issues still persist, notably, flux discrepancies that are linked to the impact of side lobes associated with the dirty beams due to inadequate deconvolution. However, in spite of these limitations, the WALLABY Pilot Survey Phase 2 has already produced roughly a third of the number of HIPASS sources, making this the largest spatially resolved H i sample from a single survey to date.

To investigate the symptoms of SARS-CoV-2 infection, their dynamics and their discriminatory power for the disease using longitudinally, prospectively collected information reported at the time of their occurrence. We have analysed data from a large phase 3 clinical UK COVID-19 vaccine trial. The alpha variant was the predominant strain. Participants were assessed for SARS-CoV-2 infection via nasal/throat PCR at recruitment, vaccination appointments, and when symptomatic. Statistical techniques were implemented to infer estimates representative of the UK population, accounting for multiple symptomatic episodes associated with one individual. An optimal diagnostic model for SARS-CoV-2 infection was derived. The 4-month prevalence of SARS-CoV-2 was 2.1%; increasing to 19.4% (16.0%–22.7%) in participants reporting loss of appetite and 31.9% (27.1%–36.8%) in those with anosmia/ageusia. The model identified anosmia and/or ageusia, fever, congestion, and cough to be significantly associated with SARS-CoV-2 infection. Symptoms’ dynamics were vastly different in the two groups; after a slow start peaking later and lasting longer in PCR+ participants, whilst exhibiting a consistent decline in PCR- participants, with, on average, fewer than 3 days of symptoms reported. Anosmia/ageusia peaked late in confirmed SARS-CoV-2 infection (day 12), indicating a low discrimination power for early disease diagnosis.

Drawing on early work on ethical leadership, we argue that when leaders engage in leader moral hypocrisy (i.e., ethical promotion without ethical demonstration), followers can experience psychological reactance—a negative response to a perceived restriction of freedom—which can have negative downstream consequences. In a survey of employee–manager dyads (study 1), we demonstrate that leader moral hypocrisy is positively associated with follower psychological reactance, which increases follower deviance. In two subsequent laboratory experiments, we find similar patterns of results (study 2) and explore potential alternative mechanisms (study 3). We demonstrate in a final experiment with working adults that the relationship between leader moral hypocrisy and psychological reactance is partly explained by increased perceptions of a leader’s use of power (study 4). We discuss the implications of our findings and advocate for further understanding of the risks associated with psychological reactance in response to leaders and other workplace situations.

The U.S. Department of Agriculture–Agricultural Research Service (USDA-ARS) has been a leader in weed science research covering topics ranging from the development and use of integrated weed management (IWM) tactics to basic mechanistic studies, including biotic resistance of desirable plant communities and herbicide resistance. ARS weed scientists have worked in agricultural and natural ecosystems, including agronomic and horticultural crops, pastures, forests, wild lands, aquatic habitats, wetlands, and riparian areas. Through strong partnerships with academia, state agencies, private industry, and numerous federal programs, ARS weed scientists have made contributions to discoveries in the newest fields of robotics and genetics, as well as the traditional and fundamental subjects of weed–crop competition and physiology and integration of weed control tactics and practices. Weed science at ARS is often overshadowed by other research topics; thus, few are aware of the long history of ARS weed science and its important contributions. This review is the result of a symposium held at the Weed Science Society of America’s 62nd Annual Meeting in 2022 that included 10 separate presentations in a virtual Weed Science Webinar Series. The overarching themes of management tactics (IWM, biological control, and automation), basic mechanisms (competition, invasive plant genetics, and herbicide resistance), and ecosystem impacts (invasive plant spread, climate change, conservation, and restoration) represent core ARS weed science research that is dynamic and efficacious and has been a significant component of the agency’s national and international efforts. This review highlights current studies and future directions that exemplify the science and collaborative relationships both within and outside ARS. Given the constraints of weeds and invasive plants on all aspects of food, feed, and fiber systems, there is an acknowledged need to face new challenges, including agriculture and natural resources sustainability, economic resilience and reliability, and societal health and well-being.

Changes in plasma Cortisol concentrations in response to a stimulus have been used to indicate aversiveness. Hormone concentrations at any time point depend on the interaction between an animal's previous experience and its present physiological state. In order to assess how an animal's perception of, and thus its response to, a stimulus change as it gains experience of the stimulus, eight Welsh Mountain ewes were subject to 2h road transport daily on three occasions and then once again 4 days later. Differences in Cortisol concentrations in plasma samples taken every 15min were assessed using a general linear model and Tukey's test.

A precise knowledge of landfast sea-ice (fast-ice) thickness is relevant to many different disciplines. Sea Ice Monitoring Stations (SIMS) are used to measure time series of fast-ice thickness at a location. SIMS measure ice and ocean temperature via thermistor strings with many different methods for extracting sea-ice thickness from temperature existing. This study investigates: if thickness results from temperature recorded by SIMS of different designs, and analysed with different methods are comparable; which methods are recommended for their robustness, precision and accuracy and how they compare to independent thickness measurements; how otherwise unuseable data can be salvaged through specific SIMS designs. We present an analysis of fast-ice thickness calculated from SIMS deployed in McMurdo Sound, Antarctica and in the Chukchi Sea near Utqiaġvik, Alaska, over two decades. We find that median thicknesses derived by different methods agree within 1 ± 1.5 cm for McMurdo Sound and 2 ± 3 cm for Utqiaġvik. Thus, it is possible to confidently compare data collected from different stations and analysed with different methods. The vertical gradient of sea-ice temperature gives the best results for fast-ice thickness during the growth season and including standard resistors in a thermistor string can reduce potential data loss due to noise.

We present the Widefield ASKAP L-band Legacy All-sky Blind surveY (WALLABY) Pilot Phase I Hi kinematic models. This first data release consists of Hi observations of three fields in the direction of the Hydra and Norma clusters, and the NGC 4636 galaxy group. In this paper, we describe how we generate and publicly release flat-disk tilted-ring kinematic models for 109/592 unique Hi detections in these fields. The modelling method adopted here—which we call the WALLABY Kinematic Analysis Proto-Pipeline (WKAPP) and for which the corresponding scripts are also publicly available—consists of combining results from the homogeneous application of the FAT and 3DBarolo algorithms to the subset of 209 detections with sufficient resolution and $S/N$ in order to generate optimised model parameters and uncertainties. The 109 models presented here tend to be gas rich detections resolved by at least 3–4 synthesised beams across their major axes, but there is no obvious environmental bias in the modelling. The data release described here is the first step towards the derivation of similar products for thousands of spatially resolved WALLABY detections via a dedicated kinematic pipeline. Such a large publicly available and homogeneously analysed dataset will be a powerful legacy product that that will enable a wide range of scientific studies.

We present WALLABY pilot data release 1, the first public release of H i pilot survey data from the Wide-field ASKAP L-band Legacy All-sky Blind Survey (WALLABY) on the Australian Square Kilometre Array Pathfinder. Phase 1 of the WALLABY pilot survey targeted three $60\,\mathrm{deg}^{2}$ regions on the sky in the direction of the Hydra and Norma galaxy clusters and the NGC 4636 galaxy group, covering the redshift range of $z \lesssim 0.08$. The source catalogue, images and spectra of nearly 600 extragalactic H i detections and kinematic models for 109 spatially resolved galaxies are available. As the pilot survey targeted regions containing nearby group and cluster environments, the median redshift of the sample of $z \approx 0.014$ is relatively low compared to the full WALLABY survey. The median galaxy H i mass is $2.3 \times 10^{9}\,{\rm M}_{{\odot}}$. The target noise level of $1.6\,\mathrm{mJy}$ per 30′′ beam and $18.5\,\mathrm{kHz}$ channel translates into a $5 \sigma$ H i mass sensitivity for point sources of about $5.2 \times 10^{8} \, (D_{\rm L} / \mathrm{100\,Mpc})^{2} \, {\rm M}_{{\odot}}$ across 50 spectral channels (${\approx} 200\,\mathrm{km \, s}^{-1}$) and a $5 \sigma$ H i column density sensitivity of about $8.6 \times 10^{19} \, (1 + z)^{4}\,\mathrm{cm}^{-2}$ across 5 channels (${\approx} 20\,\mathrm{km \, s}^{-1}$) for emission filling the 30′′ beam. As expected for a pilot survey, several technical issues and artefacts are still affecting the data quality. Most notably, there are systematic flux errors of up to several 10% caused by uncertainties about the exact size and shape of each of the primary beams as well as the presence of sidelobes due to the finite deconvolution threshold. In addition, artefacts such as residual continuum emission and bandpass ripples have affected some of the data. The pilot survey has been highly successful in uncovering such technical problems, most of which are expected to be addressed and rectified before the start of the full WALLABY survey.