The state of the Martian climate

60°N was +2.0°C, relative to the 1981–2010 average value (Fig. 5.1). This marks a new high for the record. The average annual surface air temperature (SAT) anomaly for 2016 for land stations north of starting in 1900, and is a significant increase over the previous highest value of +1.2°C, which was observed in 2007, 2011, and 2015. Average global annual temperatures also showed record values in 2015 and 2016. Currently, the Arctic is warming at more than twice the rate of lower latitudes

Hidden treasures of herbaria - even small collections contain a wealth of diversity: the powdery mildews of the North Carolina State Larry F. Grand Mycological Herbarium

The occurrence of cryptic species is well documented in fungi but the extent of their diversity is not fully understood. This study assessed the fungal diversity within a part of the Larry F. Grand Mycological Herbarium (NCSLG), a small, well-maintained collection at North Carolina State University, with a focus on the powdery mildew fungi (Erysiphaceae). Erysiphaceae were selected due to their economic impact as plant pathogens and availability of extensive DNA sequence data for multiple barcode loci. Our research objectives included determining the number of phylogenetic species compared with those identified morphologically, and to identify undescribed species. We generated sequence data for 220 of the 299 powdery mildew specimens (73% success rate) in the herbarium, which represented 60 species in 10 genera, collected from 134 host plant species. Our analyses revealed that ~83% (183/220) of the sequenced specimens had identifications that were incorrect and/or outdated based on current genus/species concepts. Additionally, four new species are described: Erysiphe amphicarpaeicola, E. ulmi-alatae, E. quercus-virginianae, and Takamatsuella grandii. A specimen deposited at NCSLG is designated as an epitype for Phyllactinia liriodendri, and a species of Phyllactinia identified on Carpinus caroliniana, as well as multiple species infecting Quercus spp., likely represent additional undescribed species that require more data. This research highlights the critical role of herbarium collections in uncovering fungal biodiversity, and underscores the importance of preserving these valuable resources, particularly with the growing trend to discard herbaria due to financial and space constraints

Psychiatric and medical comorbidities of eating disorders : findings from a rapid review of the literature

Background: Eating disorders (EDs) are potentially severe, complex, and life-threatening illnesses. The mortality rate of EDs is signifcantly elevated compared to other psychiatric conditions, primarily due to medical complications and suicide. The current rapid review aimed to summarise the literature and identify gaps in knowledge relating to any psychiatric and medical comorbidities of eating disorders. Methods: This paper forms part of a rapid review) series scoping the evidence base for the feld of EDs, conducted to inform the Australian National Eating Disorders Research and Translation Strategy 2021–2031, funded and released by the Australian Government. ScienceDirect, PubMed and Ovid/Medline were searched for English-language studies focused on the psychiatric and medical comorbidities of EDs, published between 2009 and 2021. High-level evidence such as meta-analyses, large population studies and Randomised Control Trials were prioritised. Results: A total of 202 studies were included in this review, with 58% pertaining to psychiatric comorbidities and 42% to medical comorbidities. For EDs in general, the most prevalent psychiatric comorbidities were anxiety (up to 62%), mood (up to 54%) and substance use and post-traumatic stress disorders (similar comorbidity rates up to 27%). The review also noted associations between specifc EDs and non-suicidal self-injury, personality disorders, and neurodevelopmental disorders. EDs were complicated by medical comorbidities across the neuroendocrine, skeletal, nutritional, gastrointestinal, dental, and reproductive systems. Medical comorbidities can precede, occur alongside or emerge as a complication of the ED. Conclusions: This review provides a thorough overview of the comorbid psychiatric and medical conditions cooccurring with EDs. High psychiatric and medical comorbidity rates were observed in people with EDs, with comorbidities contributing to increased ED symptom severity, maintenance of some ED behaviours, and poorer functioning as well as treatment outcomes. Early identifcation and management of psychiatric and medical comorbidities in people with an ED may improve response to treatment and overall outcomes

Informing the development of Australia's national eating disorders research and translation strategy : a rapid review methodology

Background Eating disorders (EDs) are highly complex mental illnesses associated with significant medical complications. There are currently knowledge gaps in research relating to the epidemiology, aetiology, treatment, burden, and outcomes of eating disorders. To clearly identify and begin addressing the major deficits in the scientific, medical, and clinical understanding of these mental illnesses, the Australian Government Department of Health in 2019 funded the InsideOut Institute (IOI) to develop the Australian Eating Disorder Research and Translation Strategy, the primary aim of which was to identify priorities and targets for building research capacity and outputs. A series of rapid reviews (RR) were conducted to map the current state of knowledge, identify evidence gaps, and inform development of the national research strategy. Published peer-reviewed literature on DSM-5 listed EDs, across eight knowledge domains was reviewed: (1) population, prevalence, disease burden, Quality of Life in Western developed countries; (2) risk factors; (3) co-occurring conditions and medical complications; (4) screening and diagnosis; (5) prevention and early intervention; (6) psychotherapies and relapse prevention; (7) models of care; (8) pharmacotherapies, alternative and adjunctive therapies; and (9) outcomes (including mortality). While RRs are systematic in nature, they are distinct from systematic reviews in their aim to gather evidence in a timely manner to support decision-making on urgent or high-priority health concerns at the national level. Results Three medical science databases were searched as the primary source of literature for the RRs: Science Direct, PubMed and OVID (Medline). The search was completed on 31st May 2021 (spanning January 2009-May 2021). At writing, a total of 1,320 articles met eligibility criteria and were included in the final review. Conclusions For each RR, the evidence has been organised to review the knowledge area and identify gaps for further research and investment. The series of RRs (published separately within the current series) are designed to support the development of research and translation practice in the field of EDs. They highlight areas for investment and investigation, and provide researchers, service planners and providers, and research funders rapid access to quality current evidence, which has been synthesised and organised to assist decision-making

Same data, different analysts: Variation in effect sizes due to analytical decisions in ecology and evolutionary biology

Although variation in effect sizes and predicted values among studies of similar phenomena is inevitable, such variation far exceeds what might be produced by sampling error alone. One possible explanation for variation among results is differences among researchers in the decisions they make regarding statistical analyses. A growing array of studies has explored this analytical variability in different fields and has found substantial variability among results despite analysts having the same data and research question. Many of these studies have been in the social sciences, but one small “many analyst” study found similar variability in ecology. We expanded the scope of this prior work by implementing a large-scale empirical exploration of the variation in effect sizes and model predictions generated by the analytical decisions of different researchers in ecology and evolutionary biology. We used two unpublished datasets, one from evolutionary ecology (blue tit, Cyanistes caeruleus, to compare sibling number and nestling growth) and one from conservation ecology (Eucalyptus, to compare grass cover and tree seedling recruitment). The project leaders recruited 174 analyst teams, comprising 246 analysts, to investigate the answers to prespecified research questions. Analyses conducted by these teams yielded 141 usable effects (compatible with our meta-analyses and with all necessary information provided) for the blue tit dataset, and 85 usable effects for the Eucalyptus dataset. We found substantial heterogeneity among results for both datasets, although the patterns of variation differed between them. For the blue tit analyses, the average effect was convincingly negative, with less growth for nestlings living with more siblings, but there was near continuous variation in effect size from large negative effects to effects near zero, and even effects crossing the traditional threshold of statistical significance in the opposite direction. In contrast, the average relationship between grass cover and Eucalyptus seedling number was only slightly negative and not convincingly different from zero, and most effects ranged from weakly negative to weakly positive, with about a third of effects crossing the traditional threshold of significance in one direction or the other. However, there were also several striking outliers in the Eucalyptus dataset, with effects far from zero. For both datasets, we found substantial variation in the variable selection and random effects structures among analyses, as well as in the ratings of the analytical methods by peer reviewers, but we found no strong relationship between any of these and deviation from the meta-analytic mean. In other words, analyses with results that were far from the mean were no more or less likely to have dissimilar variable sets, use random effects in their models, or receive poor peer reviews than those analyses that found results that were close to the mean. The existence of substantial variability among analysis outcomes raises important questions about how ecologists and evolutionary biologists should interpret published results, and how they should conduct analyses in the future

Demonstration of sub-3 ps temporal resolution with a superconducting nanowire single-photon detector

Improvements in temporal resolution of single-photon detectors enable increased data rates and transmission distances for both classical and quantum optical communication systems, higher spatial resolution in laser ranging, and observation of shorter-lived fluorophores in biomedical imaging. In recent years, superconducting nanowire single-photon detectors (SNSPDs) have emerged as the most efficient time-resolving single-photon-counting detectors available in the near-infrared, but understanding of the fundamental limits of timing resolution in these devices has been limited due to a lack of investigations into the timescales involved in the detection process. We introduce an experimental technique to probe the detection latency in SNSPDs and show that the key to achieving low timing jitter is the use of materials with low latency. By using a specialized niobium nitride SNSPD we demonstrate that the system temporal resolution can be as good as 2.6 ± 0.2 ps for visible wavelengths and 4.3 ± 0.2 ps at 1,550 nm

Demonstration of sub-3 ps temporal resolution with a superconducting nanowire single-photon detector

Improvements in temporal resolution of single-photon detectors enable increased data rates and transmission distances for both classical and quantum optical communication systems, higher spatial resolution in laser ranging, and observation of shorter-lived fluorophores in biomedical imaging. In recent years, superconducting nanowire single-photon detectors (SNSPDs) have emerged as the most efficient time-resolving single-photon-counting detectors available in the near-infrared, but understanding of the fundamental limits of timing resolution in these devices has been limited due to a lack of investigations into the timescales involved in the detection process. We introduce an experimental technique to probe the detection latency in SNSPDs and show that the key to achieving low timing jitter is the use of materials with low latency. By using a specialized niobium nitride SNSPD we demonstrate that the system temporal resolution can be as good as 2.6 ± 0.2 ps for visible wavelengths and 4.3 ± 0.2 ps at 1,550 nm

Same data, different analysts: variation in effect sizes due to analytical decisions in ecology and evolutionary biology

Although variation in effect sizes and predicted values among studies of similar phenomena is inevitable, such variation far exceeds what might be produced by sampling error alone. One possible explanation for variation among results is differences among researchers in the decisions they make regarding statistical analyses. A growing array of studies has explored this analytical variability in different fields and has found substantial variability among results despite analysts having the same data and research question. Many of these studies have been in the social sciences, but one small "many analyst" study found similar variability in ecology. We expanded the scope of this prior work by implementing a large-scale empirical exploration of the variation in effect sizes and model predictions generated by the analytical decisions of different researchers in ecology and evolutionary biology. We used two unpublished datasets, one from evolutionary ecology (blue tit, Cyanistes caeruleus, to compare sibling number and nestling growth) and one from conservation ecology (Eucalyptus, to compare grass cover and tree seedling recruitment). The project leaders recruited 174 analyst teams, comprising 246 analysts, to investigate the answers to prespecified research questions. Analyses conducted by these teams yielded 141 usable effects (compatible with our meta-analyses and with all necessary information provided) for the blue tit dataset, and 85 usable effects for the Eucalyptus dataset. We found substantial heterogeneity among results for both datasets, although the patterns of variation differed between them. For the blue tit analyses, the average effect was convincingly negative, with less growth for nestlings living with more siblings, but there was near continuous variation in effect size from large negative effects to effects near zero, and even effects crossing the traditional threshold of statistical significance in the opposite direction. In contrast, the average relationship between grass cover and Eucalyptus seedling number was only slightly negative and not convincingly different from zero, and most effects ranged from weakly negative to weakly positive, with about a third of effects crossing the traditional threshold of significance in one direction or the other. However, there were also several striking outliers in the Eucalyptus dataset, with effects far from zero. For both datasets, we found substantial variation in the variable selection and random effects structures among analyses, as well as in the ratings of the analytical methods by peer reviewers, but we found no strong relationship between any of these and deviation from the meta-analytic mean. In other words, analyses with results that were far from the mean were no more or less likely to have dissimilar variable sets, use random effects in their models, or receive poor peer reviews than those analyses that found results that were close to the mean. The existence of substantial variability among analysis outcomes raises important questions about how ecologists and evolutionary biologists should interpret published results, and how they should conduct analyses in the future

Sea Ice Climate Normals for Seasonal Ice Monitoring of Arctic and Sub-Regions

The climate normal, that is, the latest three full-decade average, of Arctic sea ice parameters is useful for baselining the sea ice state. A baseline ice state on both regional and local scales is important for monitoring how the current regional and local states depart from their normal to understand the vulnerability of marine and sea ice-based ecosystems to the changing climate conditions. Combined with up-to-date observations and reliable projections, normals are essential to business strategic planning, climate adaptation and risk mitigation. In this paper, monthly and annual climate normals of sea ice parameters (concentration, area, and extent) of the whole Arctic Ocean and 15 regional divisions are derived for the period of 1981–2010 using monthly satellite sea ice concentration estimates from a climate data record (CDR) produced by NOAA and the National Snow and Ice Data Center (NSIDC). Basic descriptions and characteristics of the normals are provided. Empirical Orthogonal Function (EOF) analysis has been utilized to describe spatial modes of sea ice concentration variability and how the corresponding principal components change over time. To provide users with basic information on data product accuracy and uncertainty, the climate normal values of Arctic sea ice extents (SIE) are compared with that of other products, including a product from NSIDC and two products from the Copernicus Climate Change Service (C3S). The SIE differences between different products are in the range of 2.3–4.5% of the CDR SIE mean. Additionally, data uncertainty estimates are represented by using the range (the difference between the maximum and minimum), standard deviation, 10th and 90th percentiles, and the first, second, and third quartile distribution of all monthly values, a distinct feature of these sea ice normal products.</jats:p