dataesr/scientific-paragraphs-categorization huggingface dataset:
includes the Triangular Irregular Network (TIN), Digital elevation Map (DEM), land use, river geometry file and peak streamflow data are the input files for HEC-RAS model to generate the water surface level along the river (Olajuyigbe and Rotowa 2012). A constant monthly baseflow approach was used to consider baseflow at all simulation period for each month from long-term datasets. The initial value before calibration was taken as the average of minimum flow. Boundary conditions are an important part of hydraulic modeling because they enable programs like HEC-RAS to start performing calculations. Boundary conditions are needed at each boundary node in unsteady flow simulations to identify the inflows and outflows at the model boundary. An observed mean daily discharge or a stage hydrograph defines the upstream boundary condition of the lower Shabelle river model whereas the hydrograph, frictional slope and normal depth are considered for downstream boundary conditions.
J Figure6shows the correlation between the simulated and observed peak flow datasets. The results indicate close agreement between the observed and simulated peak flow during calibration and validation with coefficient of correlation greater than 0. 77. In all the result obtained the model of this study provides enough result which fit the criteria of all parameters of peak flow generated in the catchment from particular rainfall measures. This indicate that sufficient for analysis of rainfall runoff modelling of Shabelle river basin using HEC-RAS for flood inundation mapping.
05) was used to define the best-fit distribution ranking. The highest p-value is 0. 9615. The optimum distribution parameters of the flood frequency study were provided by the Easy-Fit tool, and the ranks of the parameters rely on how different distributions are accepted. Test indicators J o u r n a l P r e -p r o o f used for the flood frequency analysis to computed datasets. It was observed that according, to Kolmogorov Smirnov, Anderson Darling, and Chi-square tests, General Extreme Value (GEV).
Comparison of geometrical and crystallographical anisotropy In Fig. 6 (a) and Fig. 7  we see the typical evolution of the geometrical anisotropy in snow, firn, and ice and its survival up to high densities. Initially, snow exhibits a horizontal orientation of ice matrix  (Leinss et al. , 2016). As the volume fraction increases from snow to firn, we observe the transition of the orientation to the vertical direction. This change is a result of temperature gradient metamorphism, which can be easily confirmed from the temperature gradient metamorphism experiments (TS-TGM2 and TS-TGM17), and also from the Arc-EGRIP dataset. The existence of geometric anisotropy in polar snow are well known  (Fujita et al. , 2014; Moser et al. , 2020)  and can be quantitatively related to temperature gradient metamorphism  (Montagnat et al.
Vegetarianism is growing dramatically among adolescents and young adults. Professionals specialized in eating disorders (ED) may routinely face patients adhering to these popular vegetarian practices. This qualitative study aimed to investigate healthcare professionals' subjective experience of vegetarianism in ED patients. Interviews of practitioners specialized in ED, recruited from the French federation of anorexia and bulimia (FFAB), were conducted using a semi-structured guide. We reached data saturation. Thematic analysis was used to identify and analyze patterns of meaning in the dataset. Eighteen professionals (dieticians, physician-nutritionists, and a psychiatrist) with private or institutional practices were interviewed. Three meta-themes emerged from our thematic analysis: (1) heterogeneous perceptions of vegetarianism among healthcare professionals, (2) diverse nutritional care practices, (3) factors influencing professionals' nutritional strategies and approaches.
Procedure We designed a semi-structured interview guide using the authors' multidisciplinary clinical experience and research expertise in the field of EDs in adolescents, nutritional care, and qualitative methodology. Questions were assessed by clinical experts, checked for consistency by healthcare professionals, and revised accordingly. The topic guide explored the following: (i) professionals' perceptions of vegetarianism; (ii) interactions perceived between vegetarianism and EDs; (iii) care options offered to vegetarian patients with EDs. The interview guide was used flexibly; it included open questions relating to vegetarianism in adolescents with EDs and the types of care offered, followed by prompts to gather richer data about each clinician's experience. One researcher/ dietitian (A.
T. ) conducted all interviews between January and April 2021. These took place remotely (videoconferences n = 11; telephone n = 7) due to restrictions linked to the COVID-19 pandemic. Interviews were audio recorded and lasted 25 min to 1 h. Data collection by purposive sampling continued until reaching theoretical sufficiency, with the data collection process no longer offering any new or relevant insights (M. Q. Patton, 2015; M. Q. Patton & Patton, 2002). AT produced verbatim transcripts of all interviews, removed all identifying information, and assigned numbers for anonymization. Ethics waivers were granted by the institutional review committee (AP-HP Centre Research Ethics Committee) (IRB registration: 00011928). All participants provided informed verbal consent. This research followed the COREQ checklist for qualitative data reporting  (Harper & Thompson, 2012; Tong et al.
Analysis We used thematic analysis to identify and analyze patterns of meaning in the dataset, highlighting the most salient clusters of content. This method is best suited for exploring a group's conceptualization of a specific phenomenon  (Braun & Clarke, 2006; Harper & Thompson, 2012). The researchers examined their own sources of bias and prior assumptions, including knowledge and experience gained from working in adolescent medicine departments (AL, AT, CB, EC, and MRM) and conducting qualitative research among adolescents with EDs (AL, CB, EC, and MRM). Constant comparative techniques, based on Braun and Clarke's six-stage thematic analysis method, were used to analyze the data  (Braun & Clarke, 2006). In stage 1, the first author (AT) became familiar with the data by conducting and transcribing the interviews, and then reading and re-reading the transcripts.
, 2021). Moreover, adolescents or young adults vegetarians may experience a higher risk for binge eating or further unhealthful weight-control behaviors (Robinson-O  'Brien et al. , 2009). The effectiveness and safety of a vegetarian-only refeeding protocol should also be assessed, both regarding the nutritional outcome but also the patient's overall long-term mental health evolution. Our stance is neither to question the legitimacy of vegetarianism, nor to make claims in favor of or against it, but to rely on evidence-based data providing guidance on whether and how this practice is compatible with refeeding care in a situation of undernutrition and conducive to a favorable outcome. Treating ED patients who claim to be vegetarians nonetheless remains a sensitive issue, involving medical but also philosophical and cultural choices.
However, a systematic model for the WPV of budburst is still lacking. Here we developed a model that simulates the WPV of budburst in temperate deciduous trees. We calibrated and validated the model over an extensive budburst dataset acquired from five tree populations at the individual tree scale over 23 years  (representing 48,442 observations). Specially, we aim to 1) develop the WPV model and validate its ability for predicting the progress of budburst in tree populations, 2) use the model to in a retrospective simulation exercise testing whether the duration of budburst period in the population changed with climate warming in the recent decades.
Study sites We used budburst data collected from two forests located near Paris (France): Barbeau (48. 476° N, 2. 780° E, 95 m asl) and Orsay (48. 705° N, 2. 167° E, 105 m asl). At these sites, the progress of budburst was observed at the individual scale in populations of three major temperate deciduous tree species, namely, hornbeam (Carpinus betulus L. ), oak (Quercus petraea (Matt. ) Liebl) and chestnut (Castanea sativa Mill. ). Hornbeam is an early leafing tree species, chestnut is a late species while oak is intermediate. Hornbeam and oak are present in both forests, while chestnut is present in Orsay only (Table  1 ). For each species, we focused on healthy and dominant trees, except for hornbeam (an understory species). We collected budburst observations from 2000 to 2022, which yielded a dataset comprising 5 populations and 103 population-years.
Phenology dataset A team of eight local observers (including most of the authors of this paper) conducted the observations of developing buds in the tree crowns throughout spring. The observers used binoculars and occasionally received training in order to reduce observer bias  (Liu et al. , 2021). The interval between phenological observations was of 4 days on average (from 2 to 7 days). A tree was considered to have burst its buds when at least 50% of the buds in the upper third of the crown presented leaves that extended beyond the tip of the scales, which corresponded to stage BBCH 9  (Meier, 1997). At each observation date, we calculated the percentage of trees that had reached budburst in the tree population, dividing the number of trees at BBCH 9 by the total number of trees observed on that date and multiplying the result by 100.
" We chose these quantiles instead of more extreme quantiles of distribution (e. g. , 5% and 95%), because they are well represented in our dataset (Fig. 1 ), thus implying higher model accuracy. For sake of model evaluation, we calculated the DurBB in observed phenology data. Specifically, we selected years which had records before BP20 and after BP80. Then the date of BP20 or BP80 were calculated by using the nearest two data (one is below BP20 or BP80, another is above BP20 or BP80) through interpolation (e. g. , 15 % budburst percent is on DoY 80 and 25 % budburst percent is on DoY 84. We can obtain the date of BP20 by interpolation, that is DoY 82).
Statistical analyses For each population, we quantified by linear regression the sensitivity of budburst date (BP20 and BP80) and the DurBB to time (days year -1 ) and to Jan-May temperature (days o C -1 ). Analysis of Variance (ANOVA) was used to analysis whether the significance of the regression slopes (=0. 05). All simulations and statistical analyses were carried out with R statistical software v. 4. 0. 3 (R Development Core Team, 2020). Orsay were very close, with average differences of 2 and 1 days (Table  S1 ). The duration of budburst in the population (DurBB) (i. e. , time interval, in days, during which the proportion of trees having reached budburst increases from 20% to 80%) differs for each species depending on the site and year, with a mean of 8 days over the whole dataset and ranging from 3 days for hornbeam at Orsay in 2018 and 2021 to 21 days for oak at Orsay in 2012 (Fig.
Model performance For all the populations considered here, the WPV model predicted with good accuracy the progress of budburst in tree populations during spring as well as the interannual variability of budburst (Fig. 2 , Fig. 3 ; see Fig. S4  for a comparison of observed and simulated time series). The model predicted the percentage of budburst in tree populations with an error (RMSEBP) of 16% ± 0. 2% for the calibration dataset and 20% ± 2. 1% for the validation dataset. This corresponded to prediction errors for the date of budburst (RMSEDOY) of 3. 9 ± 0. 6 days for the calibration dataset and 5. 6 ± 0. 3 days for the validation dataset. This compared well to the time resolution of the phenological observations (3-7 days). The mean bias was within 1 day (Fig. 3 ).
Study area and catchments Figure  1  shows the location of the 55 catchments considered in this study. They cover a region in the Northern French Alps delimited by the contours of French administrative entities (so-called "Département" of Drôme, Isère, Savoie, Haute-Savoie, and Hautes-Alpes). These catchments have been selected according to their size (area between 10 km 2 and 300 km 2 ) and the availability and quality of streamflow measurements (at least 10 years in the period 1997-2017). Streamflow data have been obtained from the French national database Banque Hydro (http://hydro. eaufrance. fr/, last date of access: 10 October 2022). By construction, most of these catchments are small (75% are smaller than 150 km 2 ) and typical of mountainous catchments, with 25% and 75% quantiles for the median elevations equal to 580 m and 1450 m, respectively, 1380 m and 2330 m for the maximum elevations, and 9% and 25% for the mean slopes (see Table  S1  in the Supplement for the complete list of characteristics).
As such, they are widely used and can be considered as a reference dataset for the analysis of land surface variables, e. g. streamflow  (Alfieri et al. , 2020; Xu et al. , 2022; Probst and Mauser, 2022). The ERA5-Land dataset provides many atmospheric and surface variables, including hourly precipitation amounts and temperature at a 9 km resolution. Unlike the other reanalysis considered in this study, ERA5-Land mostly assimilates satellite data and does not consider gauged measurements. It also has the coarsest spatial resolution.
At later forecast times (years 6-9) the surface temperature anomalies largely decrease in magnitude (Figure  7e -h), consistent with the recovery time-scale after the eruptions (Figure  3 ). The response on these time-scales is partly related to the magnitude of the eruption. For the eruption of Agung we find that negative surface temperature anomalies persist over the tropics and the Southern Hemisphere (Figure  7e ). For the eruption of El Chichón, which is the weakest of the three, there are barely any significant anomalies remaining (Figure  7f ). Finally, for the eruption of Pinatubo, we find some regions with significant anomalies which are particularly strong over the Arctic (Figure  7g ). To determine the importance of volcanic forcing at the regional scale, we evaluate the predicted surface temperature anomalies in the three DCPP-A and DCPP-C hindcast sets against the HadCRUT5 observational dataset.
https://doi. org/10. 5194/esd-2023-36 Preprint. Discussion started: 15 November 2023 c Author(s) 2023. CC BY 4. 0 License. climatology for the period 1970-2005 using the DCPP-A decadal hindcasts initialised in 1960 to 2015. Forecast drift is assumed to be equal in the DCPP-A and DCPP-C hindcast sets. The observational datasets used for verification are HadCRUT5 (Morice et al. , 2021) for near-surface temperature and HadSST. 4. 0. 1. 0 (Kennedy et al. , 2019) for sea surface temperature. To determine whether the predicted anomalies in the DCPP-A or the DCPP-C hindcast are closer to the observations we use the root mean square error (RMSE).
12  They can also be related to damages caused by a stress such as lipid peroxidation  13  or hypoxia. 14  The whole metabolome is mainly examined using a non-targeted Liquid Chromatography-High Resolution Mass Spectrometry (LC-HRMS)  15  and is often called the metabolomic fingerprint. 16  In this approach, both unannotated and annotated metabolites are considered; the annotation consisting of assigning a tentative metabolite candidate on the basis of the mass of the ion, its retention time and its spectral fragmentation using a specific database. Metabolite responses are then often processed using multivariate statistical approach to distinguish between control and contaminant exposed group. 17  Less frequently used, dose-response curves can also be drawn using the metabolite response, from which benchmark doses (BMD) -which correspond to the doses of the tested contaminants at which the response of the organisms differs from the control groupcan be retrieved.
Meta-metabolomics response In total, 2,117 metabolites were observed (Table  S4 ) among all samples and 159 of them were annotated. Different families of molecules were attemptedly identified, including several lipids or lipid precursors (Lyso-diacylglyceryltrimethylhomoserine (LDGTS), sterol, phosphatidylethanolamine (PE), lysophosphatidylcholine (LPC), sphingosines) (Figures  S3  and S5 ). The biofilm meta-metabolomic response was examined by comparing the samples at each exposure Co concentration and each exposure time, first for the whole 2,117 metabolites and second using the 159-annotated metabolite datasets.
2019). Species occurrences were extracted from the "ATLANTIS initiative in the Azores" GBIF dataset (GBIF. org). It comprises a total of 1,338,102 georeferenced records at a 500 x 500 m cell resolution  (Borges et al. , 2018) , including native and non-native species. Taxonomic and temporal data cleaning procedure is detailed in  Leo et al. (2021) , resulting in 135,014 suitable records of native vascular plants. We considered three types of habitats representing the dominant, less disturbed onesin most Azorean islands: native forests, characterized by a dense tree and shrub cover of small stature and currently restricted to high elevations in the islands (detailed description of the current types of native forest can be seen at  Elias et al. 2016) ; naturalized vegetation patches mostly composed by native plants and located outside the native forest; and seminatural pastures, which are mid-and high-elevation pastures that maintain some native plants and are subject to short-term cattle grazing activity and low inputs of fertilizers (fig.
, 2021; Quinn et al. , 2021; Karstensen et al. , 2020; Speich, 2021). A wide range of innovative and standard observing platforms were deployed, including Saildrones, ocean gliders, wave gliders, surface buoys, profiling floats, and 4 research vessels (RVs). The paper is organized as follows. The data sources are presented in section 2. The different methods used to analyze the upper ocean, the air-sea interface and the vertical profiles of the atmosphere are described in section 3, and a discussion of the main results is given in section 4. A conclusion follows in section 5. (Clayson et al. , 2014)  and the shading shows the seafloor depth from the ETOPO2 product  (Ducet et al. , 2000). Detailed information on all datasets in this figure can be found in the section 2.
Satellite and Reanalysis Data We rely on daily satellite maps of SST, SSS and Absolute Dynamic Topography (ADT) to provide a broad overview of the environmental conditions in which the in-situ measurements take place. The salinity maps are from the SMAP-SSS Level 3, 8-day running mean gridded product  (Meissner et al. , 2019). This product provides daily fields with a spatial resolution of 0. 25 Daily results are obtained using a multi-scale variational approach that combines all available observations. The satellite-based LHF is taken from the SeaFlux dataset  (Clayson et al. , 2014). The SeaFlux version used in this paper is called SeaFluxV3 and uses a nonlinear neural network technique to estimate near-surface air properties from microwave radiances  (Roberts et al. , 2010). To compute surface turbulent fluxes from near-surface variables, SeaFlux uses a neural network version of the COARE3.
0 algorithm  (Fairall et al. , 2003). This dataset has a spatial resolution of nearly 25 km and a temporal resolution of 1 hour. Only daily averages of LHF are considered for the period 2008-2018. To better understand the surface ocean circulation around the in-situ measurements, we use the daily ADT maps at 0. 25 • resolution from the AVISO product  (Ducet et al. , 2000). It combines data from all available satellites for the period 1993 to present. With this ADT field, the TOEddies algorithm developed by  Laxenaire et al. (2018)  identifies eddies and their trajectories using the closed contours of the ADT as well as the maximum geostrophic velocity associated with the eddy. We also evaluate the seafloor depth map in the NWTA using the ETOPO2 dataset  (Smith & Sandwell, 1997)  at a 2-minute latitude/longitude spatial resolution.
To investigate the behavior of the marine atmospheric boundary layer height  (MABLH)  in regions where atmospheric in-situ data are missing, we use the ERA5 reanalysis  (Hersbach et al. , 2020). Note that ERA5 does not include coupling with an ocean model, but it is forced at the lower boundary by the Hadley Center Sea Ice and Sea Surface Temperature (HadISST) dataset as well as the Climate Change Initiative (ESA-CCI) until 2007  (Merchant et al. , 2014)  and the Operational Sea Surface Temperature and Ice Analysis (OSTIA) in the modern period  (Donlon et al. , 2007). ERA5 has a spatial resolution of 0. 25 • × 0. 25 • and a time resolution of 1 hour. We consider only the MABLH between 2 nd and 5 th and between 16 th and 19 th of February 2020, which we collocate with the corresponding in-situ observations as described in section 1 of the Appendix.
•. The product is optimized for the Northwest Tropical Atlantic in Febru- ary 2020 and is designed to provide the best possible representation of Amazon plume variability. The product, its uncertainties, and the comparison between TSG salinity and satellite SSS are detailed in Reverdin et al. (2021). Daily SST maps are derived from the MUR-JPL dataset. This satellite product pro- vides high-resolution SST values distributed over a global 0. 01 • × 0. 01 • grid. SST val- ues from the version 4 Multiscale Ultrahigh Resolution (MUR) Level 4 analysis (Chin et al. , 2017) are based on nighttime observations from several instruments, including the NASA Advanced Microwave Scanning Radiometer-EOS (AMSR-E), the JAXA Advanced Microwave Scanning Radiometer 2 on GCOM-W1, the Moderate Resolution Imaging Spec- troradiometers (MODIS) on the NASA Aqua and Terra platforms, the US Navy Wind- Sat microwave radiometer, the Advanced Very High Resolution Radiometer (AVHRR) on several NOAA satellites, and in-situ SST observations from the NOAA iQuam project.
Baselines are an integral part of the conceptual framework of the UN's decade on ecosystem restoration (2021-2030) and are an asset of palaeoecological records  (Willis et al. , 2010; Nogué et al. , 2022; Burge et al. , 2023)  as the current status of nature is often assessed with reference to relatively recent baselines (e. g. mostly after 1970 CE;  Purvis et al. , 2019). In this context, the pollen record indicates that tree cover was 60% higher around 1990-2000 CE than in 1940-1950 CE. Though the increase matches with a net gain in tree cover documented based on land-cover datasets (25%) for Europe from 1950 to 2010 CE  (Fuchs et al. , 2013) , it suggests the occurrence of a high spatial variability that could be further explored with a network of pollen records. Likewise, tree cover rose at an average per-decade rate of 10% between 1970-1979 and 2000 CE, suggesting that tree cover in the southern Alps rose about five times faster than the global average (2.
A1 Material The pollen data from Lago Grande di Avigliana with associated metadata and chronology  (Finsinger et al. , 2019)  were obtained from the Neotoma database  (Giesecke et al. , 2014; Williams et al. , 2018)  using the NeotomaExplorer App. The pollen and diatom datasets were treated with custom-coded functions in the R environment (R Core Team, 2020) to adapt their format for the R-Ratepoll v1. 2. 1 package  (Mottl et al. , 2021b).