Design for ground beetle abundance and diversity sampling within the National Ecological Observatory Network

The National Ecological Observatory Network (NEON) will monitor ground beetle populations across a network of broadly distributed sites because beetles are prevalent in food webs, are sensitive to abiotic factors, and have an established role as indicator species of habitat and climatic shifts. We describe the design of ground beetle population sampling in the context of NEON's long-term, continentalscale monitoring program, emphasizing the sampling design, priorities, and collection methods. Freely available NEON ground beetle data and associated field and laboratory samples will increase scientific understanding of how biological communities are responding to land-use and climate change.Peer reviewe

Cube law, condition factor and weight-length relationships: history, meta-analysis and recommendations

This study presents a historical review, a meta-analysis, and recommendations for users about weight–length relationships, condition factors and relative weight equations. The historical review traces the developments of the respective concepts. The meta-analysis explores 3929 weight–length relationships of the type W = aLb for 1773 species of fishes. It shows that 82% of the variance in a plot of log a over b can be explained by allometric versus isometric growth patterns and by different body shapes of the respective species. Across species median b = 3.03 is significantly larger than 3.0, thus indicating a tendency towards slightly positive-allometric growth (increase in relative body thickness or plumpness) in most fishes. The expected range of 2.5 < b < 3.5 is confirmed. Mean estimates of b outside this range are often based on only one or two weight–length relationships per species. However, true cases of strong allometric growth do exist and three examples are given. Within species, a plot of log a vs b can be used to detect outliers in weight–length relationships. An equation to calculate mean condition factors from weight–length relationships is given as Kmean = 100aLb−3. Relative weight Wrm = 100W/(amLbm) can be used for comparing the condition of individuals across populations, where am is the geometric mean of a and bm is the mean of b across all available weight–length relationships for a given species. Twelve recommendations for proper use and presentation of weight–length relationships, condition factors and relative weight are given

ICON 2019: International Scientific Tendinopathy Symposium Consensus: Clinical Terminology

© Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ.Background Persistent tendon pain that impairs function has inconsistent medical terms that can influence choice of treatment.1 When a person is told they have tendinopathy by clinician A or tendinitis by clinician B, they might feel confused or be alarmed at receiving what they might perceive as two different diagnoses. This may lead to loss of confidence in their health professional and likely adds to uncertainty if they were to search for information about their condition. Clear and uniform terminology also assists inter-professional communication. Inconsistency in terminology for painful tendon disorders is a problem at numerous anatomical sites. Historically, the term ‘tendinitis’ was first used to describe tendon pain, thickening and impaired function (online supplementary figure S1). The term ‘tendinosis’ has also been used in a small number of publications, some of which were very influential.2 3 Subsequently, ‘tendinopathy’ emerged as the most common term for persistent tendon pain.4 5 To our knowledge, experts (clinicians and researchers) or patients have never engaged in a formal process to discuss the terminology we use. We believe that health professionals have not yet agreed on the appropriate terminology for painful tendon conditions.Peer reviewedFinal Accepted Versio

Maternal deaths in Pakistan : intersection of gender, class and social exclusion.

Background: A key aim of countries with high maternal mortality rates is to increase availability of competent maternal health care during pregnancy and childbirth. Yet, despite significant investment, countries with the highest burdens have not reduced their rates to the expected levels. We argue, taking Pakistan as a case study, that improving physical availability of services is necessary but not sufficient for reducing maternal mortality because gender inequities interact with caste and poverty to socially exclude certain groups of women from health services that are otherwise physically available. Methods: Using a critical ethnographic approach, two case studies of women who died during childbirth were pieced together from information gathered during the first six months of fieldwork in a village in Northern Punjab, Pakistan. Findings: Shida did not receive the necessary medical care because her heavily indebted family could not afford it. Zainab, a victim of domestic violence, did not receive any medical care because her martial family could not afford it, nor did they think she deserved it. Both women belonged to lower caste households, which are materially poor households and socially constructed as inferior. Conclusions: The stories of Shida and Zainab illustrate how a rigidly structured caste hierarchy, the gendered devaluing of females, and the reinforced lack of control that many impoverished women experience conspire to keep women from lifesaving health services that are physically available and should be at their disposal

Ensembles of global climate model variants designed for the quantification and constraint of uncertainty in aerosols and their radiative forcing

Tropospheric aerosol radiative forcing has persisted for many years as one of the major causes of uncertainty in global climate model simulations. To sample the range of plausible aerosol and atmospheric states and perform robust statistical analyses of the radiative forcing, it is important to account for the combined effects of many sources of model uncertainty, which is rarely done due to the high computational cost. This paper describes the designs of two ensembles of the HadGEM-UKCA global climate model and provides the first analyses of the uncertainties in aerosol radiative forcing and their causes. The first ensemble was designed to comprehensively sample uncertainty in the aerosol state, while the other samples additional uncertainties in the physical model related to clouds, humidity and radiation, thereby allowing an analysis of uncertainty in the aerosol effective radiative forcing. Each ensemble consists of around 200 simulations of the pre-industrial and present-day atmospheres. The uncertainty in aerosol radiative forcing in our ensembles is comparable to the range of estimates from multi-model intercomparison projects. The mean aerosol effective radiative forcing is –1.45 W m–2 (credible interval –2.07 to –0.81 W m–2), which encompasses but is more negative than the –1.17 W m–2 in the 2013 Atmospheric Chemistry and Climate Model Intercomparison Project and –0.90 W m–2 in the IPCC 5th Assessment Report. The ensembles can be used to reduce aerosol radiative forcing uncertainty by challenging them with multiple measurements as well as to isolate potential causes of multi-model differences

Impact of assimilating NOAA VIIRS aerosol optical depth (AOD) observations on global AOD analysis from the Copernicus Atmosphere Monitoring Service (CAMS)

Global monitoring of aerosols is required to analyse the impacts of aerosols on air quality and to understand their role in modulating the climate variability. The Copernicus Atmosphere Monitoring Service (CAMS) provides near-real-time forecasts and reanalyses of aerosols using the ECMWF Integrated Forecasting System (IFS), constrained by the assimilation of MODIS and Polar Multi-Sensor Aerosol Optical Properties (PMAp) aerosol optical depth (AOD). Given the potential end of lifetime of MODIS AOD, implementing new AOD observations in the CAMS operational suite is a priority to ensure the continuity of the CAMS forecast performances. The objective of this work is to test the assimilation of the NOAA VIIRS AOD product from S-NPP and NOAA20 satellites in the IFS model. Simulation experiments assimilating VIIRS on top or in place of MODIS were carried out from June 2021 to November 2021 to evaluate the impacts on the AOD analysis. For maritime aerosol background, the assimilation of VIIRS and the use of VIIRS from NOAA20 as an anchor reduce the analysis AOD values compared to MODIS-based experiments, in which the analysis values were too high due to the positive bias of MODIS/Terra over ocean. Over land, the assimilation of VIIRS induces a large increase in the analysis over biomass burning regions where VIIRS shows larger AOD than MODIS due to differences in the aerosol models and cloud filtering between MODIS and VIIRS retrieval algorithms. For dust source regions, the analysis is reduced when VIIRS is assimilated on top of or in place of MODIS, particularly over the Sahara, the Arabian Peninsula and a few places in Asia in the July–August period. The assimilation of VIIRS leads to an overall reduction of the bias in AOD analysis evaluated against AERONET measurements, with the largest bias reduction over Europe and desert and maritime sites.</p

GRAZ, Hauptplatz

Hauptplatz mit Erzherzog-Johann-Brunnendenkma

To what extent is climate change adaptation a novel challenge for agricultural modellers?

Modelling is key to adapting agriculture to climate change (CC), facilitating evaluation of the impacts and efficacy of adaptation measures, and the design of optimal strategies. Although there are many challenges to modelling agricultural CC adaptation, it is unclear whether these are novel or, whether adaptation merely adds new motivations to old challenges. Here, qualitative analysis of modellers’ views revealed three categories of challenge: Content, Use, and Capacity. Triangulation of findings with reviews of agricultural modelling and Climate Change Risk Assessment was then used to highlight challenges specific to modelling adaptation. These were refined through literature review, focussing attention on how the progressive nature of CC affects the role and impact of modelling. Specific challenges identified were: Scope of adaptations modelled, Information on future adaptation, Collaboration to tackle novel challenges, Optimisation under progressive change with thresholds, and Responsibility given the sensitivity of future outcomes to initial choices under progressive change