dataesr/scientific-paragraphs-categorization huggingface dataset:
Differential expression of Spitsbergen vs. Roscoff sporophytes at control conditions (8_30) To investigate differences between the responses of Arctic versus temperate sporophytes suggested by the PCA (Fig. 1 ), we first looked at differences in gene expression between samples of Spitsbergen and Roscoff under control conditions (8_30): 958 differentially expressed genes (DEGs) (120 annotated with the UniProt Swiss-Prot database) were down-regulated in Roscoff in comparison to Spitsbergen material while 1766 (162 annotated) were up-regulated (Additional file 2). We identified DEGs involved in nucleic acid metabolism, transport, cell wall synthesis and reorganization, general stress response, signaling and amino acid metabolism. In addition, nine genes involved in lipid metabolism were up-regulated in Roscoff control samples in contrast to only 2 genes in the Spitsbergen specimens (Additional file 2).
Manual classification of DEGs To identify the most important mechanisms involved in temperature and salinity acclimation and to investigate differences driven by geographical variation, we manually classified and examined all the annotated DEGs using the UniProt Swiss-Prot database as a starting point. The most obvious distinction was that in sporophytes from Roscoff more DEGs were regulated in several categories than the Spitsbergen isolates in response to the applied treatments. Genes involved in transcription and/or translation were down-regulated at low salinity and decreased from R_0_20 (29 DEGs) to R_8_20  (19)  to R_15_20 (2) but they were not differentially expressed in the temperature x control salinity treatments. In comparison, algae from Spitsbergen showed similar response at S_8_20 but less DEGs were regulated at S_0_20 (Fig.
Discussion Out of the 6114 DEGs in our study (unique DEGs versus control in specimens from both locations), only 756 (12. 4%) could be functionally annotated using the UniProt Swiss-Prot database. Therefore, almost 90% of the genes regulated in S. latissima under a combination of temperature and salinity stress remain unknown. These results highlight the potential and need to discover new metabolic pathways required by the species to tackle environmental changes and further support brown algae as a relevant piece in understanding evolutionary history  [25]. The number of DEGs in our study is comparable to the numbers reported in other studies, i. e. in Desmarestia anceps in response to light, temperature and CO 2 [between 337 and 3255 DEGs in the comparison to the control  [26] ;].
Pigment quantification and statistical analysis Pigment analysis was performed according to the method described in Bollen et al. [82]. Then we calculated the percentage of initial values (before salinity acclimation) of violaxanthin and zeaxanthin concentrations. All data were tested for normality using the Shapiro-Wilk normality test and for homogeneity of variances using the Levene's test. Similarity of pigment contents were tested using a twoway ANOVA with the fixed factors temperature and salinity. Significant differences and interaction of means were compared with the post hoc Tukey test (HSD). When data failed to comply with normality and homogeneity of variances assumptions, we performed a non-parametric test (Mann-Whitney U or Kruskal-Wallis test). All statistical analyses were carried out using SPSS software version 24 (IBM, Armonk, USA).
RNA-sequencing and data processing Data obtained, quality control and trimming Total RNA extraction was conducted using the method described in Heinrich et al. [83]. RNA quality was analysed by the NanoDrop ND-1000 UV-Vis Spectrophotometer and Agilent 2100 Bioanalyzer (Agilent Technologies, Germany). cDNA libraries were prepared with an Illumina TruSeq RNA Library Prep Kit according to the manufacturer protocol and sequenced in triplicates. The libraries were sequenced on an Illumina Hiseq 2500 and 75 bp paired reads were clipped using default values of the Illumina software. Raw reads were quality controlled by FastQC v. 0. 11. 5  [84]  and quality filtered using Trimmomatic v. 0. 36  [85]. Quality filtering was performed using the following parameters: leading 3, trailing 3, sliding window 4:15, minlen 30.
Assembly Reads from all treatments were assembled de novo all together and separately for sporophytes from Spitsbergen and Roscoff. The assemblies were performed with Trinity v 2. 4. 0 including the reads normalization step corresponding to the Trinity implementation of the diginorm method. The assembler was run with default parameters  [86]. The quality of the transcriptome assemblies was evaluated by using BUSCO v2. 0  [87]  with eukaryote dataset (OrthoDB v9. 1]. To check for potential contamination, bacterial and oomycete sequences obtained from Genbank were compared to the transcriptome assembly by sequence similarity search (blastn).
Functional annotation and enrichment Functional annotation was performed using the Trinotate functional annotation pipeline  [90]  with the Uni-Ref90 database as additional reference to the default database Uniprot Swiss-Prot database (all databases up to date in October 2017). To investigate the function of significantly up-and down-regulated genes, Gene Ontology (GO) enrichments were conducted using GOseq  [91]. Enriched GO terms were summarized with CateGOrizer using the EGAD2GO classification file  [92]. For exploring constitutively expressed transcripts within the control, normalized read counts, given as transcripts per kilobase million (TPM), were analysed, following the approach of Iñiguez et al. [26]. Venn diagrams were produced through a webtool  [93].
Funding This work was supported by the  German Research Foundation  for funding within the  ERA-Net Cofund BiodivERsA 3 program MARFOR  ( ANR-16-EBI3-0005-01 ). Further funding was provided by the  MARES Joint Doctoral Programme on Marine Ecosystem Health & Conservation funded through Erasmus Mundus  (grant number  MARES_14_09 ) and by the  Alfred-Wegener-Institute Helmholtz-Centre for Polar and Marine Research (Bremerhaven, Germany ). The scientific board of the MARES doctoral programme provided feedback concerning experimental design of this experiment. In addition, the study addressed central aspects of the  MAROR project focusing on "Functional Variability and Dynamics of Responses of Marine Forests to Global Change ".
Acknowledgements. This project was supported by the  French ANR agency  under contract no. ANR-11-LabX-0005-01   CaPPA (Chemical and Physical Properties of the Atmosphere) , the  Région Hauts-de-France , the  Ministère de l'Enseignement Supérieur et de la Recherche  ( CPER Climibio ) and the  European Fund for Regional Economic Development. Alexander T. Archibald  and  Scott Archer-Nicholls  thank  NERC-NCAS  and the  Walters Kundert Trust  under whose auspices this work was enabled. Valerio Ferracci  thanks the  European Research Council  for funding through the  Atmospheric Chemistry-Climate Interactions (ACCI)  project, project number  267760. UM-UKCA runs in this work used the  ARCHER UK National Supercomputing Service. The authors thank  Paul Wennberg  for very helpful discussions. Edited by: Frank Keutsch Reviewed by: two anonymous referees.
For plagioclase and pyroxene analyses a spot size of 4 μm and a 100 nA beam current was used. Rims of crystals were analyzed, where we can discern a difference rim growth from Back scatter electron (BSE) images (e. g. , supporting information Figure  S2 ). For glasses, a 10-μm defocused spot was used with a beam current of 10 nA, with counting times of 50-200 s per analysis. During glass measurements, Na peaks were counted first to avoid significant migration during the run. In the 2007 eruptive products, most melt inclusions were crystallized or considerably affected by post entrapment crystallization, so to generate a more representative preeruptive composition (prior to microlite crystallization), 50-μm spots of were used over areas of groundmass mixed glass and microlites, the average and standard deviation was calculated from 23 data points.
Geochemistry, Geophysics, Geosystems To estimate the proportion of different mineral phases present in the natural and experimental products, energy dispersive spectrometer (EDS) mapping was conducted on an Oxford instruments detector on the SEM at the University of Mainz. Al, Ti, and Mg maps were made for plagioclase and glass and Ca and Na maps for pyroxene. At least three maps of 1,024 × 1,024 pixel areas (at 70 frames each) were taken for each sample, using a similar method to  Muir et al. (2012). Image J was then used to threshold and calculate the relative proportions of glass, plagioclase, pyroxene and oxides (supporting information Table  S1 ). Backscattered electron images of thin sections at varying magnifications were taken with the SEM to measure bubble number densities via the FOAMS program following the method of  Shea et al.
In contrast, the eruptions with a more rapid onset of seismicity prior to the eruption (or decoupled from the deformation signature) may be triggered internally, not requiring fresh inputs of magmas but resulting from a magma crystallizing as it cools (second boiling). This leads to volatile saturation and high overpressures, likely leading to faster   (1993 ), Sheveluch (1999 ) and Sarychev Peak (2009)  were not included due to insufficient monitoring data collected. The symbols indicate the onset of unrest, and the colored lines denote unrest that was recorded >1 month prior to the eruption. The color indicates the type of unrest signal, in accordance with the symbol colors. The symbol "*" indicates eruptions with patchy monitoring data sets, and thus, there is uncertainty over run-up times.
Figure14. Run-up time for explosive eruptions VEI 4 and greater since 1992. The eruptions ofLascar (1993),Sheveluch (1999) and Sarychev Peak (2009)  were not included due to insufficient monitoring data collected. The symbols indicate the onset of unrest, and the colored lines denote unrest that was recorded >1 month prior to the eruption. The color indicates the type of unrest signal, in accordance with the symbol colors. The symbol "*" indicates eruptions with patchy monitoring data sets, and thus, there is uncertainty over run-up times. Data compiled for this figure is from Global volcanism reports (ed. Venzke, 2018), distal seismic data from White and McCausland, (2016) , and the following sources: Cordon Caulle, (Jay et al. , 2014) ;Wolf (de Novellis et al. , 2017; Xu et al. , 2016) ; Calbuco (Delgado et al.
Acknowledgments COSMO-SkyMed imagery were obtained through a  UK Satellite Applications Catapult COSMO-SkyMed Radar Science and Innovation Research (CORSAIR)  project. The TanDEM-X WorldDEM used for topographic corrections was provided through a  TanDEM-X Science Proposal  ( DEM_GEOL1333 ). Some of the EMPA analyses costs were covered by a  NERC-COMET small grant  to S. K. E. , M. C. , and S. F. L. W. S. K. E. is supported by a  Leverhulme Early Career Fellowship  and by the  European Space Agency's Living Planet  fellowship programme. M. C. acknowledges an  Alexander Von Humboldt fellowship  and a  NERC Independent Research fellowship ,  NE/N014286/1. We thank  Rémi Colbalchini ,  Jean-Philippe Métaxian ,  Thibault Arnal , and  Alexis Le Pichon  who constructed the Figure 10 and shared their insights into seismoacoustic data from  Pelabuhan Ratu  and  Merapi volcano.
7 ). Twenty-five concordant analyses yield a Concordia age of 555. 4 ± 2. 9 Ma (MSWD(C + E) = 1. 2) (Table  2 ). Five zircon crystals revealed 1. 3-2. 2 Ga Meso and Paleoproterozoic inherited ages. The occurrence of such old zircons inherited in the magma chamber or scavenged from the basement during the volcanic eruption is frequently recorded  46. The remaining three analysed zircons were not considered in the calculations owing to a small common Pb contribution. We interpret this age of 555. 4 ± 2. 9 Ma as dating the crystallization of the volcanic zircons. Zircons from bentonite B1 bed was analysed by CA-ID-TIMS method. All data are interpreted in terms of weighted mean 206 Pb/ 238 U dates by defining the youngest coherent population which yields statistically acceptable MSWD (Table  3 ).
Methods Mineralogical compositions of the bulk bentonite samples and their clay fraction (<2 µm) have been compared to that of under-and overlying deposits using X-ray diffraction. Bulk analyses were carried out on the material previously crushed and sieved at 50 μm and mounted in randomly ordered powder mode in order to characterize (hkl) reflections. The <2 μm fractions have been separated by sedimentation after dispersion and centrifugation at 20 °C -1000 rpm during 120 s using a JOUAN GR 422 centrifuge. After drying, 15 mg of clay were dispersed in 1. 5 mL of osmosed water. The solution was deposited on a glass slide to study position of (00 l) reflections in   different states: air-dried and ethylene-glycol solvatation  56, 57. The obtained diffraction profiles were compared to ones calculated with NEWMOD software for illite-smectite mixed layer minerals.
The major, trace and rare earth elements (REE) were analyzed by spectrometry of inductively coupled plasma emission (ICP) at the department of Rocks and Minerals analysis (SARM) in the Petrographic and Geochemical Research Center (CRPG) of Nancy, France. Bentonites B1 and B4 were subjected to radioisotopic dating using single zircon grains that were separated after dispersion of 200 g of bentonite in sodium solution (1 N NaCl). U-Th-Pb isotope data from bentonite B4 were measured by laser ablation inductively coupled mass spectrometry (LA-ICP-MS) at the Laboratoire Magmas & Volcans of Clermont-Ferrand, France. Zircons were ablated using a Resonetics Resolution M-50 laser system operating at a wavelength of 193 nm coupled to a Thermo Element XR ICP-MS. Helium carrier gas was supplemented with N 2 prior to mixing with Ar for sensitivity enhancement  58, 59.
The laser was operated with a spot diameter of 20 µm, a repetition rate of 3 Hz, and a fluence of 2. 5 J/cm 2. Instrumental operating conditions and data acquisition parameters are basically similar to that reported in Hurai et al. 44  and Moyen et al. 59. Reduction of raw data was carried out using the GLITTER ® software package of Macquarie Research Ltd 60. Isotope ratios were corrected for laser-induced and instrumental mass fractionation via sample-standard bracketing using the GJ-1 zircon ( 206 Pb/ 238 U age of 601 Ma 61 ). Data were not corrected for common Pb. 207 Pb/ 206 Pb vs. The 238 U/ 206 Pb diagram was generated using the Isoplot/Ex v. 2. 49 software of Ludwig  62. Error ellipses for each point are shown at the 2σ level and incorporate both internal and external uncertainties.
Data points were pooled to calculate a date and associated 2σ error. The 91500 zircon reference material -1065 Ma 62 -was analyzed along with the samples to independently monitor the external precision and accuracy of the measurements. The Concordia age for 132 analyses of 91500 conducted over the course of the study was 1063. 9 ± 2. 4 Ma (2σ including decay constant errors). All data are reported in Table  1. Zircons from bentonite B1 were analyzed by high precision U-Pb Chemical Abrasion Isotope Dilution Thermal Ionisation Mass-Spectrometry (CA-ID-TIMS) at University of Geneva, Switzerland. After initial dissolution of the clay minerals, the remaining sample was subjected to methylene iodide heavy liquid separation. The retrieved zircons were predominantly long prismatic, with clear pyramids and sharp prisms.
Acknowledgements We are very grateful to  La Région Nouvelle Aquitaine , the  Centre National de la Recherche Scientifique "CNRS" , the  French Embassy at Kiev  and the  University of Poitiers. We thank the  University of Schevchenko  and to the  National Mining University of Ukraine. Permits were provided by the  University of Schevchenko. For scientific discussion, we thank  U. Schaltergger ,  L. Shumlyansky ,  A. Bekker  and  R. Macchiarelli. For assistance, we acknowledge  C. Laforest ,  A. Chuprina ,  A. Martyshyn ,  O. Bankole ,  C. Compagnon  and  N. Youbi.
Acknowledgements. This work is a contribution of the  Collaborative Research Centre 754 "Climate-Biogeochemistry interactions in the Tropical Ocean " (https://www. sfb754. de/,last access: 21 May 2019), which is supported by the  Deutsche Forschungsgemeinschaft (DFG). Financial support. The article processing charges for this openaccess publication were covered by a  Research Centre of the Helmholtz Association. Review statement. This paper was edited by  Xinming Wang  and reviewed by  Patrick Rafter  and one anonymous referee.
Data availability. All data are available at https://doi. pangaea. de/ 10. 1594/PANGAEA. 901858 (Doering et al. , 2019). Supplement. The supplement related to this article is available online at: https://doi. org/10. 5194/bg-16-2163-2019-supplement. Author contributions. KD conducted the sampling of the sediment cores at Bordeaux University. KD prepared the samples and performed the isotope measurements. KD wrote the manuscript with contributions from all co-authors.
Nocturnal low-level stratus clouds (LLCs) are frequently observed in the atmospheric boundary layer (ABL) over southern West Africa (SWA) during the summer monsoon season. Considering the effect these clouds have on the surface energy and radiation budgets as well as on the diurnal cycle of the ABL, they are undoubtedly important for the regional climate. However, an adequate representation of LLCs in the state-of-the-art weather and climate models is still a challenge, which is largely due to the lack of highquality observations in this region and gaps in understanding of underlying processes. In several recent studies, a unique and comprehensive data set collected in summer 2016 during the DACCIWA (Dynamics-aerosol-chemistry-cloud interactions in West Africa) ground-based field campaign was used for the first observational analyses of the parameters and physical processes relevant for the LLC formation over SWA.
, 2013; Babić et al. , 2019). Based on the analysis of data gathered during the DACCIWA field campaign,  Lohou et al. (2019)  developed a conceptual model of LLC formation, maintenance and dissolution over SWA. However, stratus clouds do not necessarily form every night during the monsoon season (e. g. ,  Kalthoff et al. , 2018) , even though some of the key features, such as southwesterly monsoon flow and an embedded NLLJ, are present. So far, only a few studies have investigated differences in the conditions between nights with and without stratus clouds in West Africa. Schrage et al. (2007)  investigated local and synoptic conditions for 11 cloudy and 12 clear nights using radiosonde measurements from Parakou (Benin; 9 • 21 N, 2 • 37 E; 324 m a. s. l. ) and operational model output from the European Centre for Medium-Range Weather Forecasts (ECMWF).
3 g kg -1 less than for clear nights between 18:00 and 06:00 UTC. They also found a stronger monsoon circulation during cloudy nights. The analysis of atmospheric conditions and processes during stratus and stratus-free nights has important practical implications with respect to the regional climate, especially considering the challenges that state-of-the-art numerical weather prediction and climate models encounter in representing extensive and persistent LLCs over SWA  (Knippertz et al. , 2011; Hannak et al. , 2017). In this work, we present an observation-based analysis of differences in conditions and processes during stratus and stratus-free nights based on a high-quality, comprehensive data set collected during the DACCIWA campaign. Therefore, our results not only provide the observational verification of previous modeling studies but also complement the previous observational studies reported farther north of Savè (e.
g. ,  Schrage et al. , 2007; Schrage and Fink, 2012) , thus enabling a comprehensive overview for the SWA. The research questions we address in this study are as follows: (i) what are the main differences in the ABL conditions between nights with and without stratus clouds? (ii) How do the observed differences influence the main processes relevant for the development of LLCs? (iii) What are the main factors leading to these differences? The paper is organized as follows: in Sect. 2 a brief description of the study site and data and methods used is given. In Sect. 3 the spatial distribution of LLCs in the DACCIWA region is presented, while in Sect. 4 we compare ABL conditions during stratus and stratus-free nights. Two case studies representing stratus and stratus-free nights are presented in Sect.
ERA5 reanalysis data and calculation of backward trajectories The large-scale conditions during stratus and stratus-free nights affecting the SWA are investigated based on the ERA5 reanalysis data (Copernicus Climate Change Service, 2017) from the ECMWF with a 30 km horizontal grid, 137 vertical levels and hourly temporal resolution. For each stratus and stratus-free night, backward trajectories are calculated using the Lagrangian analysis tool (LAGRANTO;  Sprenger and Wernli, 2015)  for the Savè region (represented by five ERA5 grid points surrounding Savè; i. e. , at 8 • N, 2 • E; 8 • N, 2. 5 • E; 8 • N, 3 • E; 7. 5 • N, 2. 5 • E; and 8. 5 • N, 2. 5 • E) , which defines a 60 km×60 km box. We used hourly 3-D wind fields from the ERA5 reanalysis data set. The trajectories start at 03:00 UTC, since for most stratus nights, LLCs are present at this time (Fig.
Spatial distribution of LLCs For the selected stratus and stratus-free nights at the Savè supersite, maps of the low-level cloud cover at 06:00 UTC at 53 stations across SWA are shown in Fig. 3. Although these reports do not discriminate between stratus and other lowlevel cloud types, it is most likely that the reported coverage corresponds to stratus clouds. The information on the lowlevel cloud cover is retrieved from the Karlsruhe African Surface Station Database (KASS-D), which contains long-term, in situ observations for the whole African continent from various sources. Due to long-standing collaborations with African national weather services and African researchers, KASS-D contains many observations not available in standard, GTS-fed (global telecommunication system-fed) station databases, and it is an especially valuable source of the precipitation observations  (Fink et al.
Summary and conclusions This study investigates differences in the boundary-layer conditions between stratus and stratus-free nights over SWA during the 2016 summer monsoon season. We have used observational data collected during the DACCIWA campaign as well as the newest ERA5 reanalysis data set. Conditions during 6 stratus-free nights are compared with 20 nights with LLCs using in situ and remote-sensing measurements at the Savè supersite and radiosonde measurements from coastal stations (Abidjan, Accra and Cotonou) and inland stations in Lamto and Parakou. The analysis is complemented by the investigation of the large-scale conditions during the selected nights, for which we use ERA5 reanalysis, as well as by backward-trajectory calculation using LAGRANTO. We find that LLCs typically form during undisturbed monsoon flow, while stratus-free nights occurred in the premonsoon period as well as after the monsoon onset.
These results highlight that in order to adequately simulate the LLCs over SWA it is crucial to reproduce and capture the main features, i. e. , the onset time and strength of the maritime inflow and NLLJ, turbulent mixing, cold-air advection and the background moisture level. Considering that the involved processes range from synoptic and mesoscale to the boundary-layer microscale, it is necessary to apply numerical models with horizontal grid spacing able to resolve the involved scales of motions and to use appropriate parameterization schemes. Finally, the comprehensive, high-quality DACCIWA data set can serve as an observational benchmark for investigating which of the relevant processes are realistically reproduced in the numerical models as well as to contribute to their improvement.