dataesr/scientific-paragraphs-categorization huggingface dataset:
Phylogenetic reconstructions were performed, for both single-gene data sets and the combined data set, using maximum likelihood (ML) and Bayesian Inference (BI) approaches. ML analyses were performed using the software Treefinder  (Jobb et al. 2004 ) and robustness of the nodes was assessed using nonparametric bootstrapping (1000 replicates)  (Felsenstein 1985). BI analyses were performed using MrBayes (Ronquist and Huelsenbeck 2003) as implemented on the Bioportal cluster (University of Oslo, Bioportal: http://www. bioportal. uio. no). Eight Markov chains and two parallel analyses were run over 50M generations, sampled every 5000th step, and associated with a heating temperature of 0. 01. To assess if the two independent runs converged, likelihood curves and standard deviation of split frequencies were analyzed using Tracer v1.
Molecular assignation of species to genera The taxon sampling used for the phylogenetic analysis covers the lineage diversity but not for all lineages the species diversity. Thus, to compare the species diversity among redefined genera we use a DNA barcoding-like approach (i. e. , based on COI data), to assign species to genera. We first gathered from World Register of Marine Species (WORMS; http://www. marinespecies. org) a provisional list of valid names for each genus, and gathered, when available, the associated COI data from Gen-Bank. Second, we gathered the COI data for the species identified in the literature using molecular data, but that have not yet been attributed to species names. This set of species was identified by  Miyazaki et al. (2004) ,  Iwasaki et al. (2006) ,  Fujita et al.
(2009) , and  Kyuno et al. (2009)  using the COI and ND4 gene fragments. These taxa were labeled according to  Kyuno et al. (2009)  and were, first, tentatively attributed to either named species or ESUs of our data set. In the literature, the mean intraspecific genetic distance estimated using the Kimura 2-parameters (K2P) distance was about ~1% in  Won et al. (2003)  and  Miyazaki et al. (2004) , and of 1. 8% in  Lorion et al. (2010). We thus used a conservative threshold of 2% K2P genetic distance to attribute a sequence to defined species or ESU. Second, an extended COI data set was constituted to perform a phylogenetic analysis. This data set included a reference data set (i. e. , one sequence per named species or ESUs of our data set that are all attributed to a genus name based on the seven-genes phylogeny), and all COI data gathered from GenBank.
This extended COI data set was analyzed using BI and ML approaches (see Table  2 ) to determine among the reference data set the closest relatives of each of the additional species or ESUs gathered from the literature. The attribution to a genus name was based on the sister relationship with a speciesor a clade of speciesof the reference data set. For one species name (B. elongatus), no COI data were available, although data for another gene fragment (ITS2) were available in Gen-Bank. In this case, the attribution to genus followed the result of the phylogenetic analysis provided by the authors (see Table  2 ). Last, for named species for which no genetic data were available, species were tentatively placed in genera considering the available morphological data.
Character evolution Ancestral character state reconstruction of habitat use and depth was conducted using the ML method implemented in Mesquite 2. 75  (Maddison and Maddison 2011). Taxa were assigned to four different habitats (hydrothermal vent, cold seep, organic falls, nonchemosynthetic environment). The character "habitat" was coded as "0″ for nonchemosynthetic environment, "1" for hydrothermal vent, "2" for cold seep, and "3" for organic remain. The character  "depth" was coded according to  Craddock et al. (1995)  and  Jones et al. (2006)  in taking the shallowest recorded depth lesser ("0") and greater than 1000 m ("1"). Ancestral states were reconstructed for all Bayesian trees retained from the analysis of the combined data set and their mean likelihood was then plotted on the maximum clade credibility tree.
2010 ), but contrary to these studies the pairs of populations geographically very distant but genetically weakly distant have been considered as unique ESUs. The attribution based on the distance threshold was confirmed for most of the added species by the phylogenetic analysis of the extended COI data set (Fig. 2 ). The only three exceptions are Chamorro B. sp. , Kikaijima B. sp. , and Sissano B. sp. 1 for which the sister taxa could not be determined using the COI data set. These three taxa are, however, robustly placed in the "childressi" group by  Miyazaki et al. (2010) , using a combined phylogenetic analysis with two mitochondrial (COI and ND4 genes), a lineage that branched in Gigantidas in our multigenic phylogeny. Last, B. elongatus was maintained in Bathymodiolus because it falls close to B.
Acknowledgments New material was collected on board of R/V Alis during the BioPapua 2010 cruise (Principal investigators:  S. Samadi  and  L. Corbari ). Sincere thanks to  B. Buge  and  J. Brisset  for curation of specimens and the staff of the " Service de Syst ematique Mol eculaire " ( UMS2700 CNRS-MNHN ). It is part of the agreement no. 2005/67  between the Genoscope and the  Museum National d'Histoire Naturelle  on the project " Macrophylogeny of life " directed by  G. Lecointre. We thank  Philippe Bouchet  and  Patrice David  for constructive comments, and  St ephane Hourdez  and  Eric Pante  for discussions and English improvement of this manuscript. This work was supporetd in part by the grant  TF-DeepEvo ANR-12-ISV7-0005 , and by the " Action Transversale du MNHN : Taxonomie moleculaire : DNA Barcode et gestion durable des collections ".
Funding Information This study was supported by a grant of the  Fondation pour la Recherche sur la Biodiversit e (FRB   AAP-IN-2009-009 ), the  "Consortium National de Recherche en G enomique", and the "Service de Syst ematique Mol  eculaire" of the  Mus eum National d'Histoire Naturelle  ( CNRS UMS 2700 ), part of the agreement n°2005/67 between the Genoscope and the  Mus eum National d'Histoire Naturelle  on the project " Macrophylogeny of life" directed by Guillaume Lecointre and by the network "Biblioth eque du Vivant " funded by the  CNRS , the  Mus eum National d'Histoire Naturelle , the  INRA  and the  CEA (Genoscope). "This work is part of the projects @  SPEED-ID "Accurate SPEciEs Delimitation and IDentification of eukaryotic biodiversity using DNA  markers" proposed by  F-BoL , the  French Barcode of life initiative.
Climate models are sensitive to even small changes in the cirrus coverage and the numerical representation of cirrus in GCMs were not accurately constrained by available satellite data  (Zhang et al. , 2005)  before the recent use of space-borne lidar measurements  (Chepfer et al. , 2008). Furthermore, in situ observations constitute a demanding and expensive operation and cannot provide a representative database to derive consistent cirrus climatology. In summary, in GCM cloud prognostic schemes, there are still open questions regarding cirrus. These issues are related to both a lack of reliable observations and to the shortcomings of the forecast models to simulate ice clouds  (Immler et al. , 2008). Lidar technique can detect cirrus with high spatial and temporal resolution, providing accurate information on their vertical distribution that can be used to develop highly resolved cirrus databases.
3, respectively). A lidar climatology of midlatitude cirrus in Utah has been derived by  Sassen and Campbell (2001). In this work, detected cirrus were related to three different weather patterns: zonal jet stream flow, strong amplitude ridge, and cases of split-jet flow. However, the link between these patterns and the processes of cirrus formation is difficult to deduce. Recent research projects performed through the lidar at Observatoire de Haute-Provence (OHP) have aimed to use lidar database to characterize midlatitude cirrus. In particular, statistical description of cirrus clouds at midlatitude was derived  (Goldfarb et al. , 2001)  and three distinct cirrus classes with different optical properties were identified  (Keckhut et al. , 2006). This type of classification could be useful both for the validation of height-resolved cirrus fields as reproduced by models and for the investigation of the key processes controlling cirrus formation and evolution.
In fact, any parameterization of cirrus clouds should take into account the generating mechanism of cirrus to well characterize cirrus optical properties  (Whiteman et al. , 2004)  and their radiative impact. The French analyses suggested that cirrus morphologies can be linked to the mechanisms of their formation. The present study conducted with the lidar system located at Rome Tor Vergata (RTV) fits within this context. In fact, our aim has been to utilize the lidar database acquired independently for other purposes (i. e. , Raman water vapor measurements in troposphere and Rayleigh/Raman temperature measurements in upper atmosphere) to derive information on cirrus clouds. In fact, although the multichannel configuration of the Rayleigh-Mie-Raman (RMR) lidar is well suited to characterize cirrus clouds, before this work this system was never applied to this type of study.
Lidar ratio analysis The optical properties of each cirrus class have been studied through the combined use of elastic and Raman nitrogen lidar channels. In particular, to have an homogenous data set, the values of the effective LR (LR eff , the ratio between the extinction and the integrated value of SR inside the cirrus) have been estimated only for cirrus cases with τ Rm / τ Rm ≤ 30 %, where τ Rm , the error associated to τ Rm , is calculated applying the propagation error formula to Eq. (  7 ) (considering the signal random errors). Only 107 cirrus cases (65 % of the total 167) have been considered. The number of cirrus cases analyzed, the values of the mean for τ LR , τ Rm , LR eff , the root mean square (RMS) of the errors associated to LR eff values ( LR eff ), together with the relative position of SR mass center compared to the mean geometric height, are listed for each class in Table  4.
Cirrus class and meteorological parameters Since the LR eff analysis is limited by the random noise lidar error and by the uncertainty of multiple scattering effects, a preliminary analysis of some meteorological parameters have been performed to characterize cirrus classes. One of the main applications of the RMR lidar is to provide atmospheric WV measurements in the whole troposphere  (Congeduti et al. , 1999) ; recently, a semi-automatic parametric calibration procedure  (Dionisi et al. , 2010)  allowed calibrating the entire data set  (2003) (2004) (2005) (2006) (2007) (2008) (2009) (2010) (2011). Thus, deriving the WV mixing ratio from the Raman signals acquired together with the cirrus elastic channel and the temperatures from Pratica di Mare radiosonde, it has been possible to estimate the mean relative humidity over ice (RHi) for class I.
The lower value of LR eff for class I could be associated to the  formation of a large amount of small crystals due to the injection of WV by the aircraft engines. For the other classes a reliable estimation of RHi has not been possible due to the weakness of the WV Raman signal at higher altitudes, which causes a relative uncertainty of more than 60 %, and the wet bias effect (approximately between 10-20 ppm) affecting the measurements above 10 km. Radiosonde data from Pratica di Mare WMO station (no. 16245) have been used to verify if there are some evident relationships between the identified cirrus classes and meteorological parameters other than temperature. In Fig. 7  the mean profiles of RH, of the zonal (U ) and of the meridional (V ) components of the wind are depicted (panels a, b and c) for each class (black, blue, red, and green curves for classes I, IIa, IIb and III, respectively) in functions of the relative height regarding the cirrus lower boundary (DZ = zz bot , where z bot is the cirrus bottom).
Summary and conclusions The data set of RTV lidar, a multichannel instrument (optimized for water vapor measurements), has been, for the first time, employed to characterize cirrus clouds. In particular, using the elastic and the Raman nitrogen channels of the system, cirrus characteristics such as effective height, geometrical and optical thickness and mean back-scattering ratio have been derived. The mid-height temperature inside the cloud, estimated through the radiosonde data of Pratica di Mare, 25 km southwest from RTV site, was added to integrate the data set. Defining the cirrus occurrence as the ratio of the number of cirrus detections and the total number of measurements, cirrus clouds were detected in 47 % of the operational days, a value similar to the one (45 %) measured by  Gobbi et al.
(2004)  above the same site. However, this percentage lowers to 30 % if the ratio of cirrus detection time for the total measurement time is taken into account. It is noteworthy that these statistics are derived for nighttime measurements acquired in the absence of precipitation and of lower tropospheric clouds. The characterization of the detected cirrus was performed through a clustering multivariate analysis approach previously adopted for the OHP lidar. This statistical method was applied to the Italian site for the considered period, the RTV cirrus data set for the period February 2007-April 2010 (93 lidar sessions, approximately 500 h of lidar acquisitions), which resulted in the identification of four cirrus classes above two thin cirrus clusters in the mid-and upper troposphere (class I and III, respectively) and two thick cirrus clusters in the upper troposphere (class IIa and IIb).
In particular, the retrieved well-defined humid layer surrounding high, thin tropopause cirrus (class III) confirms that the formation of this class is connected to the large-scale transport processes of moist tropical upper tropospheric air masses  (Keckhut et al. , 2005 and Montoux et al. , 2010). At the latitudes of the RTV site, thick cirrus (classes IIa and IIb) could be associated with midlatitude cirrus preceding weather disturbances, as indicated by the work of  Sassen and Comstock (2001) , but no significant indications on this were found in the present study. Dedicated studies are needed to further investigate the attribution and origin of cirrus classes I, IIa and IIb. The comparison of the RTV cirrus results with other lidar cirrus data sets through the classification scheme of  Sassen and Cho (1992)  are in good agreement with other midlatitude lidar measurements regarding optical depth.
Acknowledgements. The research leading to these results has received funding from the  European Union Seventh Framework Programme  (FP7/2007-2013) and  University of Versailles and Saint Quentin en Yvelines (UVSQ)  under grant agreement RBUCE-UP no. 246556. Radiosonde data are routinely supplied by the  Italian Meteorological Service of the Military Aeronautics. Edited by:  S. Buehler  The publication of this article is financed by  CNRS-INSU.
To understand food webs functioning in intertidal soft-sediments, it is critical to assess the macrobenthic prey fraction accessible to waders. Here we describe a simple core sampler device allowing to directly relating the vertical distribution of macrozoobenthos to waders bill length. Bill length measurements were used as a proxy of probing depth to estimate the amount of food supply accessible. Several metal plates can be inserted in the core sampler at different heights according to the bill length data of the studied species. These data are provided in a literature survey. For each species, the bill length variability is then explicitly taken into account in the estimation of food accessibility. The core is transparent to check for the quality of the sample. It could also be used to estimate a Benthic Habitat Quality index (BHQ) based on characteristics of the vertical structure of the sediment.
The mean probing depth of the Sanderling is 25 mm and the range for the Ringed Plover is 10 to 25 mm, two supplementary grooves were hence placed at these depths. The probing range of Dunlin (subspecies alpina and schinzii) is 25 -50 mm. Finally, the last groove placed at 200 mm embraced the high variability of Curlew probing depth (100 -200 mm), the latter varying between males and females. Our data set was obtained from four stations sampled at two intertidal sites in the Canche estuary (one north and the other south of the estuary) from April to August 2001 (see  [26]  for details on the study area and sampling dates). Two replicate samples were collected at each station. The first site (Northern Site: NS) was characterized by medium to fine sands while the second one (Southern Site: SS) was characterized by muddy fine sand.
These geographical favourable conditions and the instrumental characteristics of OHP and RTV lidars (similar in terms of emitted wavelengths and capabilities) suggested testing the Matchlidar cirrus strategy, analysing the existing dataset of these two systems. Thus, in this work, subsamples of the two lidar have been processed with a common algorithm procedure and coupled with a trajectory analysis. The main idea was to assess the technique feasibility through the study of a Match test. Therefore, a case of upper tropospheric thin cirrus measured over the two sites has been selected and analysed through the Match strategy and the main critical issues of this approach have been characterized. The paper is organized as follows: in Sect. 2, the main instrumental characteristics of the both lidar systems are briefly described together with the cirrus retrieval algorithms, while Sect.
3 addresses the Match-lidar methodology itself. The results of this approach are provided in Sect. 4, where the developed procedure is applied to both lidar datasets. A test case of an upper tropospheric cirrus observed by the two systems during the night between 13 and 14 March 2008 is studied. The associated uncertainties and the case consistency are discussed. Finally, in Sect. 5, the results, the limitations and the improvements required to quantitatively adopt this technique are discussed as a preparation for the setup of specific campaigns performed on alert.
High-resolution radiosounding data (Vaisala RS92) are available from the Italian Meteorological Service in Pratica di Mare (25 km south-west of Tor Vergata). These are utilized for the calibration of the water vapour Raman profiles, and to add complementary parameters (e. g. density, temperature, etc. ) to the lidar results. Technical characteristics of the two instruments are provided in Table  1. In cases of Match events (see Sect. 3), the same data analysis procedure is applied to the raw lidar data of the two instruments in order to detect the presence of a cirrus and provide its vertical shape. In particular, this procedure consists in deriving the backscattering ratio (BSR, the ratio between the sum of the Mie and Rayleigh backscattering coefficients and the Rayleigh backscattering coefficient) vertical profiles from the ratio between the return signal at 532 nm and nitrogen Raman signal  (Ferrare et al.
e. representativeness of individual lidar sessions to describe cirrus mean variations), are two critical points because of the high temporal and spatial variability of cirrus clouds. The contribution of the latter source can be reduced by the quasi-stationary integration approach described previously, which somehow gives an average quantity of the location of the cloud that smooth the local variability due to inhomogeneities of temperature and water vapour fields  (Keckhut et al. , 2013). A suitable maximum match radius (R max ), instead, must be applied to limit the error contribution of the former source. However, the value of R max strictly depends on the horizontal extension and variability of the cirrus; for the case considered in this work, R max is fixed to 150 km. If air masses fulfil these conditions and the presence of cirrus is revealed in both lidar datasets, the significant changes of cirrus mean optical characteristics can then be attributed to real changes of the cirrus vertical structures.
French-Italian experimental setup The French and the Italian lidar sites are located along one of the typical directions of the front progression in the Mediterranean area. This statement has been confirmed by studying the origin of the air masses arriving daily above the RTV site at 00:00 UTC. In fact, using the GDAS (Global Data Assimilation System) dataset for five years  (2006) (2007) (2008) (2009) (2010) , the 24-h backward trajectories for three different heights (8, 10 and 12 km, respectively) have been calculated through the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT,  Draxler and Rolph, 2003)  model, in order to determine the frequency of occurrence of the air masses that passed over a 0. 7 • × 0. 7 • grid centred at OHP before arriving at RTV. This analysis has highlighted that the OHP-RTV direction (N-SE) is one of the more frequent directions for the upper tropospheric air mass displacement in the northwest Mediterranean region, and more than 10 % of the air masses, which arrive at RTV at 00:00 UTC, have previously passed over OHP (OHP/RTV air mass coincidence).
During the OHP lidar session there is no presence of cirrus between 19:20 and 21:38 UTC, while cirrus is constantly present over the RTV site with a case of two-layer cirrus for the first two hours. The cirrus clouds sensed through the OHP lidar have similar characteristics of those identified through RMR system. In particular, both cirrus clouds exhibit similar values of optical depth, mean altitude, thickness and intensity of the mean backscattering ratio. These values highlight the presence, over both sites, of a subvisible cirrus (SVC), which has an optical depth always below 0. 03 (except for period 2 of the OHP), a thickness varying from 500 m and 1. 3 km, an altitude between 10. 8 and 11. 4 km and a top height that is around the local tropopause (11. 24 and 11. 10 km for OHP and RTV), which was calculated using radiosonde temperature data and the definition of thermal tropopause.
To overcome this difficulty (i. e. to verify the processes to which cirrus crystals are subjected during the transport from one site to the other), several improvements can be proposed. The first one consists in increasing the observation sampling in using, for example, other lidar stations, reduced distances between stations and/or additional observations using space measurements, as can be provided by CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization), the space-borne lidar installed on CALIPSO (Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observation). Another possible tool to track cirrus advection could be the use of satellite data from passive space-borne instruments. In our case, the small optical thickness of the cirrus limited the use of passive sensors (we do not have any geostationary images) while coincident CALIOP lidar-tracks were not available.
Conclusions In this work, an observation strategy to study the evolution of cirrus optical properties has been evaluated. This methodology, which couples lidar measurements through the Match approach, foresees characterization of mean significant changes in optical properties of cirrus quasi-stationary periods from the analysis of the lidar parameter variations observed between successive measurements located along the direction of the air mass advection. To assess its feasibility, the technique has been tested using the existing subsamples of datasets  (2007) (2008)  of OHP and RTV lidars, which are located along one of the typical directions of the front progression in the Mediterranean area, and exhibiting similar instrumental characteristics in terms of emitted wavelengths, data resolution and performances.