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Through the analysis of benthic foraminifera in the soft bottom sediments of the Laizhou Bay – Yellow River Delta system, this study characterized the foraminiferal biotopes and explored the possibility of obtaining an index of ecological quality comparable with other estuarine and coastal environments of the world. Five foraminiferal biotopes have been identified and their distribution patterns highlight the ecological stress from the marine-fluvial water mixing and pollution. The foraminiferal species were analyzed as a function of organic carbon gradients, and the main species were assigned to four ecological groups based on their sensitivity/tolerance towards an increasing stress gradient. Finally, the relative proportions of the species assigned to the four different ecological groups were used for the definition of a marine biotic index based on foraminifera, i.e. the Foram-AMBI, and thus the assessment of the ecological quality status of marine soft-bottom habitats.

Here we present a rapid and versatile method for capturing and concentrating SARS-CoV-2 from contrived transport medium and saliva samples using affinity-capture magnetic hydrogel particles. We demonstrate that the method concentrates virus from 1 mL samples prior to RNA extraction, substantially improving detection of virus using real-time RT-PCR across a range of viral titers (100–1,000,000 viral copies/mL) and enabling detection of virus using the 2019 nCoV CDC EUA Kit down to 100 viral copies/mL. This method is compatible with commercially available nucleic acid extraction kits (i.e., from Qiagen) and a simple heat and detergent method that extracts viral RNA directly off the particle, allowing a sample processing time of 10 min. We furthermore tested our method in transport medium diagnostic remnant samples that previously had been tested for SARS-CoV-2, showing that our method not only correctly identified all positive samples but also substantially improved detection of the virus in low viral load samples. The average improvement in cycle threshold value across all viral titers tested was 3.1. Finally, we illustrate that our method could potentially be used to enable pooled testing, as we observed considerable improvement in the detection of SARS-CoV-2 RNA from sample volumes of up to 10 mL. Published version

International audience; Wildfire activity is expected to increase across the Mediterranean Basin because of climate change. However, the effects of future climate change on the combinations of atmospheric conditions that promote wildfire activity remain largely unknown. Using a fire-weather based classification of wildfires, we show that future climate scenarios point to an increase in the frequency of two heat-induced fire-weather types that have been related to the largest wildfires in recent years. Heat-induced fire-weather types are characterized by compound dry and warm conditions occurring during summer heatwaves, either under moderate (heatwave type) or intense (hot drought type) drought. The frequency of heat-induced fire-weather is projected to increase by 14% by the end of the century (2071-2100) under the RCP4.5 scenario, and by 30% under the RCP8.5, suggesting that the frequency and extent of large wildfires will increase throughout the Mediterranean Basin. Wildfire is a complex phenomenon that occurs when three conditions are met: available fuel, an ignition source (due to lightning or human activities) and weather conditions conducive to fires (fire weather) 1. Climate and weather are important drivers of wildfire activity across a range of timescales 2-5 , and, consequently, current and potential future climate-induced changes in wildfire activity might threaten ecosystems and human well-being 6. In most Euro-Mediterranean countries, wildfire activity has been declining owing to management and suppression measures undertaken since the 1980s 7. However, some recent extreme wildfire events, including those that occurred in 2016 in France 8 , 2017 in Spain and Portugal 9 and 2018 in Greece 10 have highlighted the limits of wildfire suppression capabilities under exceptional fire-weather conditions. Furthermore, studies show that wildfire activity is expected to increase across the Mediterranean Basin due to climate change 11,12. However, how the combinations of climate and weather conditions that promote the largest wildfires will respond to climate change remain largely unknown. Climate and weather are both drivers of wildfire activity. Soil moisture deficit over days to months increases fuel aridity and flammability 6,13 while a number of synoptic weather conditions associated to different combinations of short-term and instantaneous meteorological fields (precipitation, temperature, relative humidity and wind speed) influence wildfire behaviour 5,14. Most of the largest wildfires occur when these conditions are met 8. For instance, the combination of extreme drought with extreme wind or heatwaves have both been identified as crucial factors in the occurrence of crown wildfires in Mediterranean forests and shrublands 15-17. In this study, we focus on the frequency of current and future weather and climate conditions associated with wildfires in four countries (France, Portugal, Greece, Tunisia) of the Mediterranean basin covering most of its diverse biogeographic and climatic conditions (Supplementary Figs. S1-S3). Building on the insights gained open

[Departement_IRSTEA]Territoires [TR1_IRSTEA]SEDYVIN [ADD1_IRSTEA]Adaptation des territoires au changement global; International audience; In the French Mediterranean, large fires have significant socio-economic and environmental impacts. The previous works dealing with fires in the French Mediterranean were based on gridded fire data commencing from the mid-1970s (e.g., Ruffault et al., 2016; Fréjaville and Curt, 2017; Ganteaume and Guerra, 2018; Lahaye et al., 2018). Working with longer time-series of georeferenced fires (extending back to 1958) would allow examining both spatial and temporal distributions of large fires (>100 ha) across the French Mediterranean. The objectives of this work were (i) to identify the locations associated with large fire recurrence and to quantify the spatial extent of the region with reburns, (ii) to establish the mean fire extent and the fire return level as well as the LF causes along a longitudinal transect spanning the study area (identifying possible roles of climate conditions and fuel continuity in shaping this longitudinal gradient), and (iii), building on previous research, to re-estimate trends in large fires across the region taking advantage of a fire record spanning almost six decades. A long-term geo-referenced fire time series (1958-2017) was used to analyse both spatial and temporal distributions of large fires (LF; ≥100 ha). Large fire causes were analysed according to the regional fire database Promethée that has recorded fires since 1973. The region was impacted in some locations up to 6 times by recurrent LF (Fig. 1) and 21% of the total area burned by LF occurred on a surface that previously burned in the past, with potential impact on forest resilience. We found contrasting patterns between the East and the West of the study area, the former experiencing fewer LF but of a larger extent compared to the latter, with an average time of occurrence between LF exceeding 4,000 ha 50 years in the West. This longitudinal gradient in LF return level contrasts with what we would expect from mean fire weather conditions strongly decreasing eastwards during the fire season but is consistent with larger fuel cover in the East, highlighting the strong role of fuel continuity in fire spread (Fig. 2). Figure 1: Fire recurrence on the 1961-2017 and 1958-2016 period in the western and eastern areas, respectively. Figure 2: Top) Longitudinal cross-section of mean LF extent computed over 30-km sliding windows. The 95% confidence intervals were estimated using a bootstrapping approach. Bottom) Same as top panel but for mean June-September FWI (in red) and the percent of biomass (in green). Additionally, our analysis confirms the sharp decrease in both LF frequency and burned area in the early 1990s, due to the efficiency of fire suppression and prevention reinforced at that time, thereby weakening the functional climate-fire relationship across the region. Regarding the causes of LF, the proportion of unknown cause was high throughout the region, varying from 74% to 77% from the West to the East. It is worth noting that the knowledge of smaller fires

International audience; Large wildfires across parts of France can cause devastating damage which puts lives, infrastructure, and the natural ecosystem at risk. In the climate change context, it is essential to better understand how these large wildfires relate to weather and climate and how they might change in a warmer world. Such projections rely on the development of a robust modelling framework linking large wildfires to present-day atmospheric variability. Drawing from a MODIS product and a gridded meteorological dataset, we derived a suite of biophysical and fire danger indices and developed generalized linear models simulating the probability of large wildfires ( > 100 ha) at 8 km spatial and daily temporal resolutions across the entire country over the last two decades. The models were able to reproduce large-wildfire activity across a range of spatial and temporal scales. Different sensitivities to weather and climate were detected across different environmental regions. Long-term drought was found to be a significant predictor of large wildfires in flammability-limited systems such as the Alpine and south-western regions. In the Mediterranean, large wildfires were found to be associated with both short-term fire weather conditions and longer-term soil moisture deficits, collectively facilitating the occurrence of large wildfires. Simulated probabilities on days with large wildfires were on average 2-3 times higher than normal with respect to the mean seasonal cycle, highlighting the key role of atmospheric variability in wildfire spread. The model has wide applications, including improving our understanding of the drivers of large wildfires over the historical period and providing a basis on which to estimate future changes to large wildfires from climate scenarios.

National audience; Historical in situ sub-daily rainfall observations are essential for the understanding of short-duration rainfall extremes but records are typically not readily accessible and data are often subject to errors and inhomogeneities. Furthermore, these events are poorly quantified in projections of future climate change making adaptation to the risk of flash flooding problematic. Consequently, knowledge of the processes contributing to intense, short-duration rainfall is less complete compared with those on daily timescales. The INTENSE project is addressing this global challenge by undertaking a data collection initiative that is coupled with advances in high-resolution climate modelling to better understand key processes and likely future change. The project has so far acquired data from over 23 000 rain gauges for its global sub-daily rainfall dataset (GSDR) and has provided evidence of an intensification of hourly extremes over the US. Studies of these observations, combined with model simulations, will continue to advance our understanding of the role of local-scale thermodynamics and large-scale atmospheric circulation in the generation of these events and how these might change in the future.

Made available in DSpace on 2018-12-11T17:16:50Z (GMT). No. of bitstreams: 0 Previous issue date: 2017-12-01 Natural Resources Conservation Service The objective of this study was to determine the effect of stockpiled forage type and protein supplementation on VFA production, serum metabolites, and BW in yearling beef heifers. Over 2 yr, spring-born, Angus crossbred yearling beef heifers (n = 42; 305 ± 2.9 kg initial BW) were randomly assigned to 1 of 3 forage pasture types: 1) endophyteinfected tall fescue [TF; Schedonorus arundinaceus (Schreb.) Dumort], 2) a big bluestem (Andropogon gerardii Vitman) and indiangrass (Sorghastrum nutans L.) combination (BI), or 3) switchgrass (SG; Panicum virgatum L.). Each pasture was then randomly assigned to receive either 1 of 2 isonitrogenous CP treatments: 1) 0.68 kg·heifer−1·d−1 of dried distiller’s grains with solubles (DDGS; 28% CP and 88% TDN) or 2) 0.22 kg·heifer−1·d−1 of blood meal and fish meal (BF; 72.5% CP and 69.5% TDN), resulting in a 3 × 2 factorial arrangement of treatments. Treatments were initiated in January and terminated in April in both years of the study. Body weights and blood samples were collected approximately every 28 d from initiation of grazing until the end of the trial. Heifer BW change from January to February and overall BW change were greater (P < 0.01) for TF heifers. However, BW change from March to April was not different (P = 0.84) among forage types. Supplement type did not influence (P ≥ 0.13) BW or BW change from January to February and from January to April; however, heifers fed DDGS had greater (P = 0.03) BW gain from March to April. Heifer BW change from February to March exhibited (P < 0.05) a forage type × supplement interaction, with BF-fed heifers gaining more BW on BI pastures than DDGSfed heifers. Serum glucose concentrations, ruminal acetate, and the acetate:propionate ratio were greater (P ≤ 0.04) for SG heifers. However, circulating serum NEFA and urea N (SUN) concentrations were not different (P ≥ 0.85) among forage types. Serum glucose and NEFA concentrations were not influenced (P ≥ 0.61) by supplement type. Circulating SUN concentrations were greater (P < 0.01) in BF-supplemented heifers. Ruminal acetate tended to be greater (P = 0.09) and butyrate concentrations were greater (P < 0.01) for BF-supplemented heifers. The acetate:propionate ratio was not influenced (P = 0.15) by supplement type. These results suggest that a compensatory gain period prior to breeding would be needed for these native warm-season species to be a viable opportunity for growing and developing replacement heifers in the southeastern United States. Department of Animal Science University of Tennessee Departamento de Produção Animal Instituto de Zootecnia UFRRJ – Univ Federal Rural do Rio de Janeiro Department of Plant Sciences University of Tennessee Departamento de Ciências Exatas Faculdade de Ciências Agrárias e Veterinárias UNESP – Univ Estadual Paulista Departamento de Zootecnia Faculdade de Ciências Agrárias e Veterinárias UNESP – Universidade Estadual Paulista West Central Research and Extension Center University of Nebraska Departamento de Ciências Exatas Faculdade de Ciências Agrárias e Veterinárias UNESP – Univ Estadual Paulista Departamento de Zootecnia Faculdade de Ciências Agrárias e Veterinárias UNESP – Universidade Estadual Paulista Natural Resources Conservation Service: 69-3A75-14-257

[Departement_IRSTEA]Territoires [ADD1_IRSTEA]Adaptation des territoires au changement global; International audience; Extreme precipitation events are widely thought to intensify in a warmer atmosphere through the Clausius-Clapeyron equation. The temperature-extreme precipitation scaling was proposed to analyse the temperature dependency of short-duration extreme precipitation and since then, the concept has been widely used in climatology. Bao et al. (2017) suggest that the apparent scaling reflects not only how surface air properties affect extreme precipitation, but also reflects how synoptic conditions and localized cooling due to the storm itself affect the scaling - implying two-way causality. We address here critical issues of this paper and provide evidence that dew point temperature drives extreme precipitation, with the direction of causality reversed only for the storm's peak intensity. This physical inference may serve as a basis to better quantify scaling rates and to help establish the relationship between extreme precipitation and environmental conditions in the current climate, and thereby provide insights into future changes to precipitation extremes due to climate change.