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Rangelands support nearly one-third of Earth's population and provide a multitude of ecosystem services. Land managers and society face increasing pressures to sustainably intensify rangeland food systems; therefore, the time is ripe for thoughtful approaches to simultaneously produce more food, provide economic opportunities for livestock-dependent communities, and enhance environmental benefits from rangeland ecosystems. Payments for ecosystem services (PES) programs have been put forth as potential mechanisms to maintain the quality and quantity of ecosystem services while enhancing economic viability of livestock operations. Free markets have long been proposed as solutions for mitigating trade-offs from ecosystem services that are not co-produced with livestock production; such markets have failed to emerge at the scale required to address global threats to sustainability. We highlight fundamental obstacles on demand and supply sides that challenge the concept of a market as a panacea; we do so through an interdisciplinary lens of fundamental economic underpinnings overlaid with a social survey of cattle producers' perspectives. Relevant to the demand side, we discuss the most significant impediments to development and function of non-bundled ecosystem service markets; on the supply side, we provide unique perspectives, using novel interview data from California rangeland cattle producers. Producer interviews highlighted substantial financial challenges threatening the economic sustainability of their operations. Among interviewed producers, 85% identified government regulations as the central threat to their livelihoods. Producers identified opportunities for enhancing enterprise sustainability via improved value and marketing of livestock goods co-produced with ecosystem services, participation in conservation easements, and improved connections with society. Only 11% of producers identified PES programs as future opportunities. When asked about willingness to participate in PES markets, 13% of interviewees indicated they would not, 45% were neutral, and 42% indicated they would consider participating. Interviewees stated trust in the market broker is key and they would be less willing to participate if there was government involvement. Ecosystem service markets—whether voluntary or non-voluntary—are likely not sustainable solutions to the complex social-economic-ecological dilemma ranchers and society face. Sustainability on working rangelands will require partnerships to co-develop strategies to build more equitable food systems and sustain these ecosystems.

The “5G” is a new generation of wireless telecommunications technology that promises to revolutionize how the world communicates. Everything from autonomous vehicles, robots conducting delicate surgery, virtual and augmented reality devices, drones, the “Internet of Things” (IoT), and generally all mobile communications will be enabled by a new tranche of bandwidth between 6-Ghz and 300-Ghz, some of it licensed, but much of it not. But 5G is different. For the first time, the physical infrastructure will be separated from the logical or “virtual” infrastructure. Software Defined Networks (SDN) will be set up and torn down, grown and lessened according to demand.Complex network management will be done by Machine Learning (ML) and Artificial Intelligence (AI). But for all of this to work properly, major carriers will need to accept international standards and open up their interfaces to outsiders, even to competitors. This is where the regulatory and legal fight will take place. Unless sufficient attention is paid now to these emerging issues, users dependent on advanced telecommunications in both North American and the European Union will be prevented from enjoying the full range of benefits promised by 5G, and as a consequence innovation will lag behind other regions of the world.

The “5G” new generation of wireless telecommunications technology promises to revolutionize how the world communicates. It he makes obsolete many traditional methodologies employed in tele-geography studies, but at the same time we can expect to find new vectors of both theoretical and applied research.

In this paper, we present the GRISLI (Grenoble ice sheet and land ice) model in its newest revision (version 2.0). Whilst GRISLI is applicable to any given ice sheet, we focus here on the Antarctic ice sheet because it highlights the importance of grounding line dynamics. Important improvements have been implemented in the model since its original version (Ritz et al., 2001). Notably, GRISLI now includes a basal hydrology model and an explicit flux computation at the grounding line based on the analytical formulations of Schoof (2007) or Tsai et al. (2015). We perform a full calibration of the model based on an ensemble of 300 simulations sampling mechanical parameter space using a Latin hypercube method. Performance of individual members is assessed relative to the deviation from present-day observed Antarctic ice thickness. To assess the ability of the model to simulate grounding line migration, we also present glacial–interglacial ice sheet changes throughout the last 400 kyr using the best ensemble members taking advantage of the capacity of the model to perform multi-millennial long-term integrations. To achieve this goal, we construct a simple climatic perturbation of present-day climate forcing fields based on two climate proxies: atmospheric and oceanic. The model is able to reproduce expected grounding line advances during glacial periods and subsequent retreats during terminations with reasonable glacial–interglacial ice volume changes.

Abstract Background Buffered intravenous fluid preparations contain substrates to maintain acid-base status. The objective of this systematic review was to compare the effects of buffered and non-buffered fluids administered during the perioperative period on clinical and biochemical outcomes. Methods We searched MEDLINE, EMBASE, CINAHL and the Cochrane Library until May 2017 and included all randomised controlled trials that evaluated buffered versus non-buffered fluids, whether crystalloid or colloid, administered to surgical patients. We assessed the selected studies for risk of bias and graded the level of evidence in accordance with Cochrane recommendations. Results We identified 19 publications of 18 randomised controlled trials, totalling 1096 participants. Mean difference (MD) in postoperative pH was 0.05 units lower immediately following surgery in the non-buffered group (12 studies of 720 participants; 95% confidence interval (CI) 0.04 to 0.07; I 2 = 61%). This difference did not persist on postoperative day 1. Serum chloride concentration was higher in the non-buffered group at the end of surgery (10 trials of 530 participants; MD 6.77 mmol/L, 95% CI 3.38 to 10.17). This effect persisted until postoperative day 1 (5 trials of 258 participants; MD 8.48 mmol/L, 95% CI 1.08 to 15.88). Quality of this evidence was moderate. We identified variable protocols for fluid administration and total volumes of fluid administered to patients intraoperatively. Outcome data was variably reported at disparate time points and with heterogeneous patient groups. Consequently, the effect size and overall confidence interval was reduced, despite the relatively low inherent risk of bias. There was insufficient evidence on the effect of fluid composition on mortality and organ dysfunction. Confidence intervals of this outcome were wide and the quality of evidence was low (3 trials of 276 participants for mortality; odds ratio (OR) 1.85, 95% CI 0.37 to 9.33; I 2 = 0%). Conclusions Small effect sizes for biochemical outcomes and lack of correlated clinical follow-up data mean that robust conclusions on major morbidity and mortality associated with buffered versus non-buffered perioperative fluid choices are still lacking. Buffered fluid may have biochemical benefits, including a significant reduction in postoperative hyperchloraemia and metabolic acidosis.

Abstract Background Energy homeostasis is regulated by the hypothalamus but fails when animals are fed a high-fat diet (HFD), and leptin insensitivity and obesity develops. To elucidate the possible mechanisms underlying these effects, a microarray-based transcriptomics approach was used to identify novel genes regulated by HFD and leptin in the mouse hypothalamus. Results Mouse global array data identified serpinA3N as a novel gene highly upregulated by both a HFD and leptin challenge. In situ hybridisation showed serpinA3N expression upregulation by HFD and leptin in all major hypothalamic nuclei in agreement with transcriptomic gene expression data. Immunohistochemistry and studies in the hypothalamic clonal neuronal cell line, mHypoE-N42 (N42), confirmed that alpha 1-antichymotrypsin (α1AC), the protein encoded by serpinA3, is localised to neurons and revealed that it is secreted into the media. SerpinA3N expression in N42 neurons is upregulated by palmitic acid and by leptin, together with IL-6 and TNFα, and all three genes are downregulated by the anti-inflammatory monounsaturated fat, oleic acid. Additionally, palmitate upregulation of serpinA3 in N42 neurons is blocked by the NFκB inhibitor, BAY11, and the upregulation of serpinA3N expression in the hypothalamus by HFD is blunted in IL-1 receptor 1 knockout (IL-1R1 −/− ) mice. Conclusions These data demonstrate that serpinA3 expression is implicated in nutritionally mediated hypothalamic inflammation.

Abstract Background Historically, the human womb has been thought to be sterile in healthy pregnancies, but this idea has been challenged by recent studies using DNA sequence-based methods, which have suggested that the womb is colonized with bacteria. For example, analysis of DNA from placenta samples yielded small proportions of microbial sequences which were proposed to represent normal bacterial colonization. However, an analysis by our group showed no distinction between background negative controls and placenta samples. Also supporting the idea that the womb is sterile is the observation that germ-free mammals can be generated by sterile delivery of neonates into a sterile isolator, after which neonates remain germ-free, which would seem to provide strong data in support of sterility of the womb. Results To probe this further and to investigate possible placental colonization associated with spontaneous preterm birth, we carried out another study comparing microbiota in placenta samples from 20 term and 20 spontaneous preterm deliveries. Both 16S rRNA marker gene sequencing and shotgun metagenomic sequencing were used to characterize placenta and control samples. We first quantified absolute amounts of bacterial 16S rRNA gene sequences using 16S rRNA gene quantitative PCR (qPCR). As in our previous study, levels were found to be low in the placenta samples and indistinguishable from negative controls. Analysis by DNA sequencing did not yield a placenta microbiome distinct from negative controls, either using marker gene sequencing as in our previous work, or with shotgun metagenomic sequencing. Several types of artifacts, including erroneous read classifications and barcode misattribution, needed to be identified and removed from the data to clarify this point. Conclusions Our findings do not support the existence of a consistent placental microbiome, in either placenta from term deliveries or spontaneous preterm births.

Understanding how SARS-CoV-2 spreads globally and within infected individuals is critical to the development of mitigation strategies. We found that most lineages in Philadelphia had resembled sequences from New York, suggesting infection primarily but not exclusively from this location.

Coronaviruses (CoVs) have caused several global outbreaks with relatively high mortality rates, including Middle East Respiratory Syndrome coronavirus (MERS)-CoV, which emerged in 2012, and Severe Acute Respiratory Syndrome (SARS)-CoV-1, which appeared in 2002. The recent emergence of SARS-CoV-2 highlights the need for immediate and greater understanding of the immune evasion mechanisms used by CoVs. Interferon (IFN)-α is the body’s natural antiviral agent, but its Janus kinase/signal transducer and activators of transcription (JAK/STAT) signalling pathway is often antagonized by viruses, thereby preventing the upregulation of essential IFN stimulated genes (ISGs). Therapeutic IFN-α has disappointingly weak clinical responses in MERS-CoV and SARS-CoV-1 infected patients, indicating that these CoVs inhibit the IFN-α JAK/STAT pathway. Here we show that in lung alveolar A549 epithelial cells expression of MERS-CoV-nsp2 and SARS-CoV-1-nsp14, but not MERS-CoV-nsp5, increased basal levels of total and phosphorylated STAT1 & STAT2 protein, but reduced IFN-α-mediated phosphorylation of STAT1-3 and induction of MxA. While MERS-CoV-nsp2 and SARS-CoV-1-nsp14 similarly increased basal levels of STAT1 and STAT2 in bronchial BEAS-2B epithelial cells, unlike in A549 cells, they did not enhance basal pSTAT1 nor pSTAT2. However, both viral proteins reduced IFN-α-mediated induction of pSTAT1-3 and ISGs (MxA, ISG15 and PKR) in BEAS-2B cells. Furthermore, even though IFN-α-mediated induction of pSTAT1-3 was not affected by MERS-CoV-nsp5 expression in BEAS-2B cells, downstream ISG induction was reduced, revealing that MERS-CoV-nsp5 may use an alternative mechanism to reduce antiviral ISG induction in this cell line. Indeed, we subsequently discovered that all three viral proteins inhibited STAT1 nuclear translocation in BEAS-2B cells, unveiling another layer of inhibition by which these viral proteins suppress responses to Type 1 IFNs. While these observations highlight cell line-specific differences in the immune evasion effects of MERS-CoV and SARS-CoV-1 proteins, they also demonstrate the broad spectrum of immune evasion strategies these deadly coronaviruses use to stunt antiviral responses to Type IFN.

Rangelands support many important ecosystem services and are highly sensitive to climate change. Understanding temporal dynamics in rangeland gross primary production (GPP) and how it may change under projected future climate, including more frequent and severe droughts, is critical for ranching communities to cope with future changes. Herein, we examined how climate regulates the interannual variability of GPP in California’s diverse annual rangeland, based on the contemporary records of satellite derived GPP at 500 m resolution since 2001. We built Gradient Boosted Regression Tree models for 23 ecoregion subsections, relating annual GPP with 30 climatic variables, to disentangle the partial dependence of GPP on each climate variable. The machine learning results showed that GPP was most sensitive to growing season (GS) precipitation, with a reduction in GPP up to 200 g cm ^−2 yr ^−1 when GS precipitation decreased from 400 to 100 mm yr ^−1 in one of the driest subsections. We also found that years with more evenly distributed GS precipitation had higher GPP. Warmer winter minimum air temperature enhanced GPP in approximately two-thirds of the subsections. In contrast, average GS air temperatures showed a negative relationship with annual GPP. When the pre-trained models were forced by downscaled future climate projections, changes in the predicted rangeland productivity by mid- and end of century were more remarkable at the ecoregion subsection scale than at the state level. Our machine learning-based analysis highlights key regional differences in GPP vulnerability to climate and provides insights on the intertwining and potentially counteracting effects of seasonal temperature and precipitation regimes. This work demonstrates the potential of using remote sensing to enhance field-based rangeland monitoring and, combined with machine learning, to inform adaptive management and conservation within the context of weather extremes and climate change.

[This corrects the article DOI: 10.1371/journal.pone.0209236.].

The oxygen-18 to oxygen-16 ratio recorded in fossil planktonic foraminifer shells has been used for over 50 years in many geoscience applications. However, different planktonic foraminifer species generally yield distinct signals, as a consequence of their specific living habitats in the water column and along the year. This complexity is usually not taken into account in model–data integration studies. To overcome this shortcoming, we developed the Foraminifers As Modeled Entities (FAME) module. The module predicts the presence or absence of commonly used planktonic foraminifers and their oxygen-18 values. It is only forced by hydrographic data and uses a very limited number of parameters, almost all derived from culture experiments. FAME performance is evaluated using the Multiproxy Approach for the Reconstruction of the Glacial Ocean surface (MARGO) Late Holocene planktonic foraminifer calcite oxygen-18 and abundance datasets. The application of FAME to a simple cooling scenario demonstrates its utility to predict changes in planktonic foraminifer oxygen-18 to oxygen-16 ratio in response to changing climatic conditions.

Atmospheric CO2 levels during interglacials prior to the Mid-Brunhes Event (MBE, ∼ 430 ka BP) were around 40 ppm lower than after the MBE. The reasons for this difference remain unclear. A recent hypothesis proposed that changes in oceanic circulation, in response to different external forcings before and after the MBE, might have increased the ocean carbon storage in pre-MBE interglacials, thus lowering atmospheric CO2. Nevertheless, no quantitative estimate of this hypothesis has been produced up to now. Here we use an intermediate complexity model including the carbon cycle to evaluate the response of the carbon reservoirs in the atmosphere, ocean and land in response to the changes of orbital forcings, ice sheet configurations and atmospheric CO2 concentrations over the last nine interglacials. We show that the ocean takes up more carbon during pre-MBE interglacials in agreement with data, but the impact on atmospheric CO2 is limited to a few parts per million. Terrestrial biosphere is simulated to be less developed in pre-MBE interglacials, which reduces the storage of carbon on land and increases atmospheric CO2. Accounting for different simulated ice sheet extents modifies the vegetation cover and temperature, and thus the carbon reservoir distribution. Overall, atmospheric CO2 levels are lower during these pre-MBE simulated interglacials including all these effects, but the magnitude is still far too small. These results suggest a possible misrepresentation of some key processes in the model, such as the magnitude of ocean circulation changes, or the lack of crucial mechanisms or internal feedbacks, such as those related to permafrost, to fully account for the lower atmospheric CO2 concentrations during pre-MBE interglacials.

This paper is the first of a series of four GMD papers on the PMIP4-CMIP6 experiments. Part 2 (Otto-Bliesner et al., 2017) gives details about the two PMIP4-CMIP6 interglacial experiments, Part 3 (Jungclaus et al., 2017) about the last millennium experiment, and Part 4 (Kageyama et al., 2017) about the Last Glacial Maximum experiment. The mid-Pliocene Warm Period experiment is part of the Pliocene Model Intercomparison Project (PlioMIP) – Phase 2, detailed in Haywood et al. (2016).The goal of the Paleoclimate Modelling Intercomparison Project (PMIP) is to understand the response of the climate system to different climate forcings for documented climatic states very different from the present and historical climates. Through comparison with observations of the environmental impact of these climate changes, or with climate reconstructions based on physical, chemical, or biological records, PMIP also addresses the issue of how well state-of-the-art numerical models simulate climate change. Climate models are usually developed using the present and historical climates as references, but climate projections show that future climates will lie well outside these conditions. Palaeoclimates very different from these reference states therefore provide stringent tests for state-of-the-art models and a way to assess whether their sensitivity to forcings is compatible with palaeoclimatic evidence. Simulations of five different periods have been designed to address the objectives of the sixth phase of the Coupled Model Intercomparison Project (CMIP6): the millennium prior to the industrial epoch (CMIP6 name: past1000); the mid-Holocene, 6000 years ago (midHolocene); the Last Glacial Maximum, 21 000 years ago (lgm); the Last Interglacial, 127 000 years ago (lig127k); and the mid-Pliocene Warm Period, 3.2 million years ago (midPliocene-eoi400). These climatic periods are well documented by palaeoclimatic and palaeoenvironmental records, with climate and environmental changes relevant for the study and projection of future climate changes. This paper describes the motivation for the choice of these periods and the design of the numerical experiments and database requests, with a focus on their novel features compared to the experiments performed in previous phases of PMIP and CMIP. It also outlines the analysis plan that takes advantage of the comparisons of the results across periods and across CMIP6 in collaboration with other MIPs.

This paper presents the inclusion of an online dynamical downscaling of temperature and precipitation within the model of intermediate complexity iLOVECLIM v1.1. We describe the following methodology to generate temperature and precipitation fields on a 40 km × 40 km Cartesian grid of the Northern Hemisphere from the T21 native atmospheric model grid. Our scheme is not grid specific and conserves energy and moisture in the same way as the original climate model. We show that we are able to generate a high-resolution field which presents a spatial variability in better agreement with the observations compared to the standard model. Although the large-scale model biases are not corrected, for selected model parameters, the downscaling can induce a better overall performance compared to the standard version on both the high-resolution grid and on the native grid. Foreseen applications of this new model feature include the improvement of ice sheet model coupling and high-resolution land surface models.

Wildfires are increasing in frequency and severity across the Western United States. However, there is limited information available on the impacts these fires are having on the livelihood of livestock producers and their animals. This work presents the results of a survey evaluating the direct and indirect impacts of the 2020 wildfire season on beef cattle, dairy cattle, sheep, and goat, producers in California, Oregon, and Nevada. Seventy completed surveys were collected between May and July 2021. While dairy producers reported no direct impacts from the fires, beef, sheep, and goat producers were impacted by evacuations and pasture lost to fires. Only beef producers reported losses due to burns and burn-associated deaths or euthanasia. Dairy, beef, sheep, and goat producers observed reduced conception, poor weight gain, and drops in milk production. All but dairy producers also observed pneumonia. Lower birthweights, increased abortion rates, and unexplained deaths were reported in beef cattle, sheep, and goats. This work documents the wide-ranging impacts of wildfires on livestock producers and highlights the need for additional work defining the health impacts of fire and smoke exposure in livestock, as well as the policy changes needed to support producers experiencing direct and indirect losses.

Oesophageal adenocarcinoma (OAC) is an exemplar model of obesity-associated cancer. Previous work in our group has demonstrated that overweight/obese OAC patients have better responses to neoadjuvant therapy, but the underlying mechanisms are unknown. Unravelling the immune–metabolic signatures of adipose tissue may provide insight for this observation. We hypothesised that different metabolic pathways predominate in visceral (VAT) and subcutaneous adipose tissue (SAT) and inflammatory secretions will differ between the fat depots. Real-time ex vivo metabolic profiles of VAT and SAT from 12 OAC patients were analysed. These samples were screened for the secretion of 54 inflammatory mediators, and data were correlated with patient body composition. Oxidative phosphorylation (OXPHOS) was significantly higher in VAT when compared to SAT. OXPHOS was significantly higher in the SAT of patients receiving neoadjuvant treatment. VEGF-A, VEGF-C, P1GF, Flt-1, bFGF, IL-15, IL-16, IL-17A, CRP, SAA, ICAM-1, VCAM-1, IL-2, IL-13, IFN-γ, and MIP-1β secretions were significantly higher from VAT than SAT. Higher levels of bFGF, Eotaxin-3, and TNF-α were secreted from the VAT of obese patients, while higher levels of IL-23 and TARC were secreted from the SAT of obese patients. The angiogenic factors, bFGF and VEGF-C, correlated with visceral fat area. Levels of OXPHOS are higher in VAT than SAT. Angiogenic, vascular injury and inflammatory cytokines are elevated in VAT versus SAT, indicating that VAT may promote inflammation, linked to regulating treatment response.

Abstract Nutrigenetic research examines the effects of inter-individual differences in genotype on responses to nutrients and other food components, in the context of health and of nutrient requirements. A practical application of nutrigenetics is the use of personal genetic information to guide recommendations for dietary choices that are more efficacious at the individual or genetic subgroup level relative to generic dietary advice. Nutrigenetics is unregulated, with no defined standards, beyond some commercially adopted codes of practice. Only a few official nutrition-related professional bodies have embraced the subject, and, consequently, there is a lack of educational resources or guidance for implementation of the outcomes of nutrigenetic research. To avoid misuse and to protect the public, personalised nutrigenetic advice and information should be based on clear evidence of validity grounded in a careful and defensible interpretation of outcomes from nutrigenetic research studies. Evidence requirements are clearly stated and assessed within the context of state-of-the-art ‘evidence-based nutrition’. We have developed and present here a draft framework that can be used to assess the strength of the evidence for scientific validity of nutrigenetic knowledge and whether ‘actionable’. In addition, we propose that this framework be used as the basis for developing transparent and scientifically sound advice to the public based on nutrigenetic tests. We feel that although this area is still in its infancy, minimal guidelines are required. Though these guidelines are based on semi-quantitative data, they should stimulate debate on their utility. This framework will be revised biennially, as knowledge on the subject increases.

The Last Glacial Maximum (LGM, 21 000 years ago) is one of the suite of paleoclimate simulations included in the current phase of the Coupled Model Intercomparison Project (CMIP6). It is an interval when insolation was similar to the present, but global ice volume was at a maximum, eustatic sea level was at or close to a minimum, greenhouse gas concentrations were lower, atmospheric aerosol loadings were higher than today, and vegetation and land-surface characteristics were different from today. The LGM has been a focus for the Paleoclimate Modelling Intercomparison Project (PMIP) since its inception, and thus many of the problems that might be associated with simulating such a radically different climate are well documented. The LGM state provides an ideal case study for evaluating climate model performance because the changes in forcing and temperature between the LGM and pre-industrial are of the same order of magnitude as those projected for the end of the 21st century. Thus, the CMIP6 LGM experiment could provide additional information that can be used to constrain estimates of climate sensitivity. The design of the Tier 1 LGM experiment (lgm) includes an assessment of uncertainties in boundary conditions, in particular through the use of different reconstructions of the ice sheets and of the change in dust forcing. Additional (Tier 2) sensitivity experiments have been designed to quantify feedbacks associated with land-surface changes and aerosol loadings, and to isolate the role of individual forcings. Model analysis and evaluation will capitalize on the relative abundance of paleoenvironmental observations and quantitative climate reconstructions already available for the LGM.

Abstract Metabolic markers associated with the Metabolic Syndrome (MetS) may be affected by interactions between the APOE genotype and plasma fatty acids (FA). In this study, we explored FA-gene interactions between the missense APOE polymorphisms and FA status on metabolic markers in MetS. Plasma FA, blood pressure, insulin sensitivity and lipid concentrations were determined at baseline and following a 12-week randomized, controlled, parallel, dietary FA intervention in 442 adults with MetS (LIPGENE study). FA-APOE gene interactions at baseline and following change in plasma FA were assessed using adjusted general linear models. At baseline E4 carriers had higher plasma concentrations of total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C) and apolipoprotein B (apo B) compared with E2 carriers; and higher TC, LDL-C and apo B compared with E3/E3. Whilst elevated plasma n-3 polyunsaturated FA (PUFA) was associated with a beneficially lower concentration of apo CIII in E2 carriers, a high proportion of plasma C16:0 was associated with insulin resistance in E4 carriers. Following FA intervention, a reduction in plasma long-chain n-3 PUFA was associated with a reduction in apo CII concentration in E2 carriers. Our novel data suggest that individuals with MetS may benefit from personalized dietary interventions based on APOE genotype.

Among men, depression is often unrecognised and untreated. Men employed in male-dominated industries and occupations may be particularly vulnerable. However, efforts to develop tailored workplace interventions are hampered by lack of prevalence data. A systematic review of studies reporting prevalence rates for depression in male dominated workforce groups was undertaken. Studies were included if they were published between 1990 - June 2012 in English, examined adult workers in male-dominated industries or occupations (> 70% male workforce), and used clinically relevant indicators of depression. Twenty studies met these criteria. Prevalence of depression ranged from 0.0% to 28.0%. Five studies reported significantly lower prevalence rates for mental disorders among male-dominated workforce groups than comparison populations, while six reported significantly higher rates. Eight studies additionally found significantly higher levels of depression in male-dominated groups than comparable national data. Overall, the majority of studies found higher levels of depression among workers in male-dominated workforce groups. There is a need to address the mental health of workers in male-dominated groups. The workplace provides an important but often overlooked setting to develop tailored strategies for vulnerable groups.

The spread and persistence of weedy plants in rangelands highlight the need for refinement of existing management techniques and development of novel strategies to address invasions. Strip-seeding – the strategic seeding of a portion of an invaded area to reduce costs and enhance success – is an underutilized management approach that holds promise for reducing weed dominance in grassland habitats. A strip-seeding experiment was established in 2011 in a California grassland where portions (between 0-100%) of invaded plots were seeded with native grasses. In 2016, we assessed the height, above-ground biomass and flower production of two late-season invasive plants: field bindweed and prickly lettuce. We found significant reductions in plant height and flower production (for both target invasives), and biomass (for field bindweed) in many of the seeded strips compared to the unseeded strips. Smaller seed applications demonstrated similar or better utility for weed control compared to greater seed applications, suggesting that this approach can be effective while reducing labor and materials cost of typical restoration management approaches. We did not find evidence that seeded strips provided invasion resistance to unseeded strips. This is possibly due to the lag in native species dispersal and establishment into contiguous unseeded strips, and suggests that strip-seeding might not provide invasion resistance to unseeded strips on timescales that are relevant to managers. However, this work does suggest that strip-seeding native species that overlap in phenology with target invasives can reduce late-season weed dominance on rangelands.

Finding genetic variants that cause functional disruption or regulatory change among the many implicated GWAs variants remains a key challenge to translating the findings from GWAs to therapeutic treatments. Defining the causal mechanisms behind the variants require functional screening experiments that can be complex and costly. Prioritizing variants for functional characterization using techniques that capture important functional and regulatory elements can assist this. The genetic architecture of complex traits such as cardiovascular disease and type II diabetes comprise an enormously large number of variants of small effect contributing to heritability and spread throughout the genome. This makes it difficult to distinguish which variants or core genes are most relevant for prioritization and how they contribute to the regulatory networks that become dysregulated leading to disease. Despite these challenges, recent GWAs for CAD prioritized genes associated with lipid metabolism, coagulation and adhesion along with novel signals related to innate immunity, adipose tissue and, vascular function as important core drivers of risk. We focus on three examples of novel signals associated with CAD which affect risk through missense or UTR mutations indicating their potential for therapeutic modification. These variants play roles in adipose tissue function vascular function and innate immunity which form the cornerstones of immuno-metabolism. In addition we have explored the putative, but potentially important interactions between the environment, specifically food and nutrition, with respect to key processes.

Rangelands are a key global resource, providing a broad range of ecological services and economic benefits. California’s predominantly annual rangelands cover ∼12% of the state’s land area, and the forage production is highly heterogeneous, making balancing economic (grazing), conservation (habitat) and environmental (erosion/water quality) objectives a big challenge. Herein, we examined how climate and environmental factors regulate annual grassland forage production spatially across the state and among four ecoregions using machine learning models. We estimated annual forage production at 30 m resolution over a 14 year period (2004–2017) using satellite images and data fusion techniques. Our satellite-based estimation agreed well with independent field measurements, with a R ^2 of 0.83 and RMSE of 682 kg ha ^−1 . Forage production (14 year average) showed large spatial variability (2940 ± 934 kg ha ^-1 yr ^-1 ; CV = 35%) across the study area. The gradient boosted regression tree with 11 feature variables explained 67% of the variability in forage production across the state. Precipitation amount, especially in November (germination) and April (rapid growth), was found as the dominant driver for spatial variation in forage production, especially in drier ecoregions and during drier years. Seasonal distribution of precipitation and minimum air temperature showed a relatively stronger control on forage production in wetter regions and during wet years. Additionally, solar energy became more important in wetter ecoregions. Drought reduced forage production from the long-term mean, i.e. a 33% ± 19% decrease in production (2397 ± 926 kg ha ^-1 yr ^-1 ; CV = 38%) resulting from a 29% ± 5% decrease in precipitation. The machine learning based spatial analysis using ‘big data’ provided insights on impacts of climate and environmental factors on forage production variation at various scales. This study demonstrates a cost-effective approach for rapid mapping and assessment of annual forage production with the potential for near real-time application.

Past climate is an important benchmark to assess the ability of climate models to simulate key processes and feedbacks. Numerous proxy records exist for stable isotopes of water and/or carbon, which are also implemented inside the components of a growing number of Earth system model. Model–data comparisons can help to constrain the uncertainties associated with transfer functions. This motivates the need of producing a comprehensive compilation of different proxy sources. We have put together a global database of proxy records of oxygen (δ18O), hydrogen (δD) and carbon (δ13C) stable isotopes from different archives: ocean and lake sediments, corals, ice cores, speleothems and tree-ring cellulose. Source records were obtained from the georeferenced open access PANGAEA and NOAA libraries, complemented by additional data obtained from a literature survey. About 3000 source records were screened for chronological information and temporal resolution of proxy records. Altogether, this database consists of hundreds of dated δ18O, δ13C and δD records in a standardized simple text format, complemented with a metadata Excel catalog. A quality control flag was implemented to describe age markers and inform on chronological uncertainty. This compilation effort highlights the need to homogenize and structure the format of datasets and chronological information as well as enhance the distribution of published datasets that are currently highly fragmented and scattered. We also provide an online portal based on the records included in this database with an intuitive and interactive platform (http://climateproxiesfinder.ipsl.fr/), allowing one to easily select, visualize and download subsets of the homogeneously formatted records that constitute this database, following a choice of search criteria, and to upload new datasets. In the last part, we illustrate the type of application allowed by our database by comparing several key periods highly investigated by the paleoclimate community. For coherency with the Paleoclimate Modelling Intercomparison Project (PMIP), we focus on records spanning the past 200 years, the mid-Holocene (MH, 5.5–6.5 ka; calendar kiloyears before 1950), the Last Glacial Maximum (LGM, 19–23 ka), and those spanning the last interglacial period (LIG, 115–130 ka). Basic statistics have been applied to characterize anomalies between these different periods. Most changes from the MH to present day and from LIG to MH appear statistically insignificant. Significant global differences are reported from LGM to MH with regional discrepancies in signals from different archives and complex patterns.

The last deglaciation, which marked the transition between the last glacial and present interglacial periods, was punctuated by a series of rapid (centennial and decadal) climate changes. Numerical climate models are useful for investigating mechanisms that underpin the climate change events, especially now that some of the complex models can be run for multiple millennia. We have set up a Paleoclimate Modelling Intercomparison Project (PMIP) working group to coordinate efforts to run transient simulations of the last deglaciation, and to facilitate the dissemination of expertise between modellers and those engaged with reconstructing the climate of the last 21 000 years. Here, we present the design of a coordinated Core experiment over the period 21–9 thousand years before present (ka) with time-varying orbital forcing, greenhouse gases, ice sheets and other geographical changes. A choice of two ice sheet reconstructions is given, and we make recommendations for prescribing ice meltwater (or not) in the Core experiment. Additional focussed simulations will also be coordinated on an ad hoc basis by the working group, for example to investigate more thoroughly the effect of ice meltwater on climate system evolution, and to examine the uncertainty in other forcings. Some of these focussed simulations will target shorter durations around specific events in order to understand them in more detail and allow for the more computationally expensive models to take part.

The purpose of this paper is to create a dialogue between disparate academic disciplines around the topics of decision making, human communication networks, and information exchange. The emergence of modern telecommunications, including social media, gaming platforms, and instant messaging has enabled the emergence of massive online global communities numbering into the tens and hundreds of millions of persons regardless of culture and language capable of exchanging ideas, images, and impressions in real time. The unprecedented scope and scale of these networks challenges contemporary theories in management and decision making, political organization and governance of institutions, sociology, and communications. Our argument is that these theories are outdated and must be rethought. We propose a simple model, "asygnosis", in which decisions and strategies are the product of the continuous (non-discrete) flows of information, ideas and impressions (“memes”) along ever-changing communication pathways between individuals and/or machines. These networks reflect the undirected emergence, exchange and demise of knowledge that forms around a specific idea or activity. They challenge traditional assumptions about rationality, causality, and the use of organizational structures as control mechanisms which form the basis of most social, economic and political theories. After developing the concept in detail of asyngnosis and asyngnotic networks, we apply it to current issues including unpredictable events that takes place without direct control such as the rise of spontaneous terrorism, and other social and political phenomenon such as the Arab Spring and Occupy Wall Street. Finally, the paper suggests areas of future research in a number of disciplines that might help develop the concept further, test assumptions, and lead to new insights into this emerging phenomenon.