dataesr/scientific-paragraphs-categorization huggingface dataset:
g. , algae, anemones, echinoderms, gorgonians, mangrove roots, soft corals, sponges). Finally, trait values for adult life stage were extracted from specific literature for the Indo-Pacific (see  Mouillot et al. , 2013) , the Atlantic  (Halpern & Floeter, 2008 ) and from FishBase. We related the variance purely explained by the historical variable in the SDMs and the corresponding life-history traits using a linear model. We compared the Akaike information criterion (AIC) resulting from the model including different combinations of traits  (Burnham & Anderson, 2002)  using the "MuMIn" package  (Bartoń, 2015). From all subset models, the Akaike weight (w) provides the probability that a specific model is the best among the others  (Kissling, Field, & Böhning-Gaese, 2008; Pellissier et al. , 2014).
GBD 2015 extended the methods and datasets used in GBD 2013 to estimate the burden of disease attributable to ambient air pollution for 1990-2015. 4, 5 Estimates of exposure to ambient air pollution were updated with additional air pollution measurements and improved estimation methods,  3, 6  relative risk estimates were updated using more recent epidemiological studies and refined statistical estimation techniques,  3  and new methods were developed and applied to identify key drivers of global trends in the burden of disease attributable to ambient air pollution. The GBD 2015 estimates update the entire time series beginning in 1990, so the changes in methodology affect the estimates for each year in the 1990-2015 interval and supersede estimates previously released.
(2013). A brief description of this DIAL system follows. It uses a frequency-tripled Nd : YAG laser, which provides a beam at 355 nm of wavelength, with a repetition rate of 30 Hz and a XeCl excimer laser that emits radiation at 308 nm at 40 Hz. The optical receiver is a telescope composed of four parabolic mirrors with which the backscattered signal is collected by four optical fibers located at the focal points. The current configuration of the DIAL system mainly detects signals in the UV regions of the spectrum  (308, 332, 355, and 387 nm). The lidar dataset used in this study consists of daily records of backscattering signals obtained from the Maïdo facility between 1 November 2014 and 30 November 2016 (106 profiles). It should be noted that no measurements were recorded at Reunion Island from January to April 2016 because of technical problems.
, 2012)  based on data from the European Centre for Medium-Range Weather Forecasts (ECMWF). The altitude of reference is determined for each profile. On average, the reference altitude is located between 30 and 40 km. Another parameter that we need to retrieve the optical properties is the ratio of backscatter and the extinction coefficient for aerosol, also called lidar ratio. For background stratospheric aerosol, the value found in the literature is near 60  (Trickl et al. , 2013; Ridley et al. , 2014; Sakai et al. , 2016; Khaykin et al. , 2017). This value is commonly used for volcanically quiescent conditions and periods of moderate eruptions  (Sakai et al. , 2016). The lidar ratio depends on the particle size distribution and the type of aerosol  (Jäger and Deshler, 2002; Young and Vaughan, 2009).
CALIOP The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) was used to study the transport of the Calbuco plume. CALIPSO was launched into a sun-synchronous polar orbit in 2006  (Winkler et al. , 2009)  with a repeat cycle of 16 days. CALIPSO is composed of an infrared imager radiometer (IIR), a wide field visible camera, and the CALIOP lidar. CALIOP is a two-wavelength polarization-sensitive lidar (532 and 1064 nm) that measures total attenuated backscatter vertical profiles with altitude-varying vertical (30-300 m) and horizontal (300-5000 m) resolution  (Winker et al. , 2009). The data used in this study are the total and perpendicular backscatter coefficient at 532 nm, available from the CALIOP level 1B v4.
OMPS The Ozone Mapper and Profiler Suite (OMPS) limb profiler (LP) is also used in the present study to analyze the optical properties of the volcanic plume over the Reunion Island site. OMPS was launched in October 2011 onboard the Suomi National Polar Partnership (NPP) spacecraft. The data used in this study are the daily extinction profiles at 675 nm. A detailed description of the aerosol extinction retrieval algorithm is given by  Jaross et al. (2012)  and  Rault and Loughman (2013). The aerosol extinction profiles are retrieved from the scattering solar radiation. The aerosol extinction rates are retrieved using spectral channels with weak gaseous absorption. The Rodgers maximum likelihood technique is used to retrieve the aerosol extinction profiles independently for each wavelength s  (Taha et al.
DyBAL code The Dynamical BArrier Location (DyBAL) code is original software developed at the Laboratoire de l'Atmosphere et des Cyclones (LACy, France) to detect barriers to mixing in the subtropical stratosphere  (Portafaix et al. , 2003). The dynamical barriers are detected from the equivalent length of the tracer contour and the gradient of isentropic Ertel potential vorticity (PV) in equivalent latitude coordinates as defined by  Nakamura (1996). These two diagnostic tools are used by DyBAL to identify weak mixing and transport barriers. The position of the dynamical barrier is characterized by a local maximum of the PV gradient and a local minimum of the equivalent length  (Nakamura, 1996). The DyBAL code is applied to the PV map obtained from the MIMOSA model runs. The ability of DyBAL to detect the position and the deformation of the dynamical barriers has been highlighted in previous studies  (Bencherif et al.
Summary and conclusion The long-range transport of the volcanic aerosol produced following the Calbuco eruption has been examined. The analysis focuses on the dynamical context that led to the spread of the aerosol plume over the Indian Ocean between April 2015 and November 2016. The transport of the volcanic aerosols to the Indian Ocean was investigated by combining satellite (CALIOP, IASI, OMPS) and ground-based experiments (optical particle counter (LOAC) and lidar) in addition to numerical tools (the DyBAL code and the high-resolution MI-MOSA model). The amount of SO 2 injected into the atmosphere during the Calbuco eruption has been quantified using IASI observations. SO 2 mass emitted by the Calbuco eruption was about 2 times lower than for the moderate Northern Hemisphere eruption of Sarychev in June 2009, but had a similar SO 2 efolding time  (Jégou et al.
, 2013; Kravitz et al. , 2011). It is found from CALIOP observations that the Calbuco aerosol layer was observable in the lower stratosphere between 18 and 21 km and spread exclusively in the Southern Hemisphere. OMPS observations reveal that the Calbuco plume reached the Indian Ocean 2 weeks after the eruption. It is shown from ground-based observations deployed at Reunion Island that SAOD increased by a factor of ∼ 2 by the beginning of May 2015 and decreased afterward, returning to preeruption values by November 2016. The aerosol e-folding time is estimated to be ∼ 90 days, close to the ∼ 80 days reported for the Sarychev eruption  (Jégou et al. , 2013). Though the various datasets agree in terms of aerosol signal intensity, we report significant differences for the plume height and its variability, possibly as a result of the different observation geometries, resolutions, and spatial scales inherent in each instrument.
Acknowledgements. This work is supported by the  Labex Étude des géofluides et des VOLatils-Terre ,  Atmosphère et Interfaces -Ressources et Environnement (VOLTAIRE ;  ANR-10-LABX-100-01 ). This study is integrated and supported by the  LEFE  project  SATORI (Stratospheric Aerosols in the Tropics Observed from Reunion Island ). The authors thank the  LPC2E  and  UMS balloon launching team  for their technical collaboration. We would especially like to thank the staff of the team working on the lidar systems at the Maïdo observatory. Lieven Clarisse  is a research associate with the Belgian FNRS-F. R. S. The authors also thank the CALIOP team and  Jean-Paul Vernier  for processing and providing data. OMPS observations were obtained from the  OMPS  website (https://ozoneaq. gsfc. nasa. gov/).
Statistical Analysis All the analyses were performed using the R software (version 3. 0. 3, R Development Core Team, Vienna, Austria) and related packages, notably "mulcomp" and "Rcmdr". Multivariate analyses-Factorial Correspondence Analysis (FCA) and Principal Components Analysis (PCA)-were used to investigate the spatiotemporal distribution of the fruit flies (data from "Vinegar-Wine" and from Condition 1 of the "Frozen Fruits" method being treated separately) or the parasitoid species (Condition 1 of the "Frozen Fruits" method). Generalized Linear Models (GLM) were used to test the effect of the different experimental (e. g. , Different experimental conditions of the "Frozen Fruit" method) and environmental factors such as Space ("Type of Habitat" and "Location") and Time ("Sampling Date") on various aspects of D.
Influence of the Trapping Method on the Fruit Flies Sampling Taken as a whole, the drosophilid species retrieved were (alphabetical order): Information on the diversity and abundance of fruit flies was obtained using three complementary approaches (see Materials and Methods): from (i) adult flies (hereafter "wild adults") found in the traps of the Condition 1 (fruits alone) of the FF method; (ii) flies having emerged from the same traps after their return to the laboratory (hereafter "lab offspring"); and (iii) flies found in the VW traps. Data from these three methods could only be compared for three locations (BAR, CIP, TIG), from February 2015 (Session 3) to October 2015 (Session 7). Overall, the total number of collected individuals largely varied according to the sampling method. Indeed, 2097 individuals were collected with the VW method compared to 453 "wild adults" and 5079 "lab offspring" with the FF sampling.
The projection of each drosophilid species is explicitly indicated by a black point. Most individuals were collected in mid-April (43% of collected individuals) and at the end of October (28%) while few individuals (3%) were observed in August. The temporal dynamics were characterized by dominance of D. subobscura in fruit fly communities early in the year (50% in February, n = 202) and of D. suzukii later (61% between April and October 2015, n = 1895). In addition to this global pattern, the FCA was used to highlight spatiotemporal interactions. From a statistical point of view, the first four eigenvalues represented 88% of the total inertia. Sampling data and projections of each Drosophila species were, therefore, plotted along the corresponding axis (Figure  1 ). Overall, the 1st, 2nd, and 4th axes were useful a posteriori for discrimination between Drosophila species, while the 3rd axis clearly evidenced the specificity of the TIG location (natural habitat in Meso-Mediterranean) compared to the other two.
Acknowledgments: We thank  C. Rebuf  for help in rearing Drosophila species as well as  M. Boijout ,  J. -C. Malausa , and the extension service CREAT for access to their lands. Climatic data were made available through a partnership initiated by  Michela Ion Scotta  and  Nadine Sellier  with  Meteo France. We thank also the anonymous reviewers for helpful suggestions and remarks. This work was supported by the  European Union 's  Seventh Framework Program  for research, technological development and demonstration, under grant agreement N • 613678 (DROPSA), the  CASDAR "Drosophila suzukii" project, the "Investments for the Future" LABEX SIGNALIFE: program  reference  ANR-11-LABX-0028  and the  INRA Plant Health Department.
5  (Peakall and Smouse 2006)  to reveal genetic variation within and between the forest and dune ecotype. Unbiased expected heterozygosity (UH E ) was calculated for each population using GENALEX 6. 5. In order to generate a useful sequence matrix for phylogenetic analyses, the nucleotide identity data from individual homozygous SNP loci (variable among individuals) were sorted and concatenated following  Emerson et al. (2010)  and  Reitzel et al. (2013). Phylogenetic relationships were inferred through statistical methods following the maximum-likelihood criterion as implemented in PHYML ver. 3. 0  (Guindon et al. 2010) , assuming the general time-reversible model (GTR) of nucleotide substitution  (Tavare 1986). Topological robustness was assessed through 1000 nonparametric bootstrap replicates.
Acknowledgements -We would like to thank  Karolien Coenen  for help with the field work and for performing the experimental pollinations and subsequent seed counting,  Sabrina Neyrinck  and  An Van Breusegem  for the lab assistance. We also thank  Marc Leten  for permission to carry out this research and for help with locating study populations. Funding -Funding was provide by  Onderzoeksraad, KU Leuven.
LC-HRMS analysis and TPs identification A LC-QTOF-MS instrument from Agilent (Wilmington, DE, USA) was used for the identification and determination of benzodiazepines and TPs. The LC was a 1200 Series liquid chromatographic system consisting of a membrane degasser, a binary high-pressure gradient pump, a thermostated LC column compartment and an autosampler. First, the peak-picking from raw data was performed with an algorithm taking account the isotopic ion cluster for the identification of these entities, called Find molecular feature function, included in Mass Hunter Qualitative software. The data were exported as CEF (compound exchange file) to the Mass Profile Professional software (Agilent Technologies) for the retention time and m/z value alignment, filtering and normalization. Then, the statistically significant differences were evaluated by ANOVA (p: 0.
Then, half-lives were calculated as t 1/2 = ln 0. 5/k' for each experiment ranging between 1. 9 and 146 h for oxazapam, 1. 8 and 87 h for nordazepam and 2. 5-637 h for diazepam (Table  S1 ). These magnitudes were used as experimental response, which was statistically analyzed (Statgraphics Centurion XVI software, Statpoint Technologies, Warrenton, VA, USA) in order to evaluate the significance of the main effects associated to each factor and their two-factor interactions. Alternatively, second order rate constants (k) could be also calculated as the product of k' and the initial chlorine concentration (Table  S1 ). As it can be observed, oxazepam reaction was faster (1. 8-43 M -1 s -1 ) in comparison with nordazepam (0. 13- 1. 16 M -1 s -1 ) and diazepam (0. 02-2. 0 M -1 s -1 ). Table  2  shows the standardized values for main factor effects and their two-factor interactions.
QSAR estimation of ecotoxicological implications A preliminary evaluation of the toxicity of the TPs was carried out with TEST and ECOSAR software as described in the section 2. 4. The results obtained are compiled in Table  5. The observed differences for predicted accurate toxicity in fish using both software have already been reported in the bibliography  (Barron et al. , 2012; Melnikov et al. , 2016). Besides the differences in the parameters and algorithm used, Fathead Minnow is the only fish considered when TEST software is applied; while several genera and families are considered in ECOSAR. For oxazepam, in all cases, its only TP, OXA-TP, showed a lower predicted toxicity (higher acute and chronic concentration values) than the precursor drug itself. In the case of Nordiazepam and according to ECOSAR data, NOR-TPI and NOR-TPII would present higher acute toxicity using fish and daphnid as end points (lower LC 50 ) and higher chronical toxicity for daphnid endpoint (lower chronic toxicity concentration); and, the estimated toxicity for NOR-TPIII were higher than nordazepam in all cases (lower acute and chronic concentration values).
Conclusions Diazepam, nordazepam and oxazepam significantly react with free chlorine. In excess of chlorine, the transformations kinetics followed first-order pseudo-kinetics with t 1/2 affected positively by pH and negatively by chlorine dosage, without being influenced by bromide. The TPs detected were mainly generated by pyrimidine or benzophenone formation. Moreover, in real samples these TPs can also be formed, when the organic load of the samples is not too high. Finally, their toxicity was evaluated using the EPA TEST and ECOSAR software showing that some TPs could be more toxic than the pharmaceuticals parent chemicals and all, except three, would show a positive result in the mutagenicity test. However, differences between acute toxicity values predicted with the two software tools for fish were observed, pointing to a need for a real toxicity estimation.
Acknowledgement This study has been supported by Xunta de Galicia (EM2014-004 and GRC2013-020) and FEDER/ERDF. I. C. acknowledges her postdoctoral formation grant to Xunta de Galicia government. Tables 469  b The solubility was not enough to measure the predicted effect. c OXA-TP and NOR-TPIV are be the same compound. Fig. 2. QTOF product ion scan spectra of oxazepam TP (OXA-TP). The spectrum of oxazepam is presented in the Supplementary Information (Fig. S5 ).
In ECOSAR, toxicity values can be estimated using different linear regression models, for each chemical class, between log LC 50 (50% lethal concentration) from a database and log P calculated by EPISUITE KOWWIN software. When a structure could not be related to predefined chemical class, the estimations were given by neutral organics QSAR equations which represent the minimum of the toxicity and, therefore, the toxicity might be less accurate. Thus, 48-hour Daphnia magna LC 50 , 96-hour fish LC 50 and 96-hour green algae half maximal effective concentration (EC 50 ) were estimated as well as the chronic values defined as geometric mean of no observed effect concentration and the lowest observed effect concentration ("https://www. epa. gov/tsca-screening-tools/ecological-structure-activity-relationships-ecosar-predictive-model (accesible 04/07/2015)," n.
Recognition of these challenges has led to the creation of policies, conventions, and various other legislative frameworks aimed at preventing future introductions and mitigating or reversing the impacts of existing marine invasions. One of these is the European Union Marine Strategy Framework Directive (MSFD, Directive 2008/56/EC  [12] ), which aims to adopt integrated ecosystem-based management approaches to achieve or maintain "Good Environmental Status" (GES) for marine waters, habitats and associated resources, including the goal that "non-indigenous species introduced by human activities are at levels that do not adversely alter the ecosystem" (MSFD, Descriptor 2). Among the various objectives of the MSFD is the promotion of regionally standardized monitoring approaches capable of delivering temporal datasets reflecting long-term trends in marine ecosystem status, incorporating indicators related to the abundance, distribution, and impacts of NIS.
Rapid technological advances, including dramatic increases in cost-effectiveness  [18] [19] [20] , continue to render such tools increasingly attractive to a wide range of potential end-users. Nevertheless, it is clear that existing molecular genetic tools could be made more responsive and relevant to management needs  [21]. In particular, progress must be made toward standardized approaches in order to accomplish the harmonization of global and regional long-term datasets. This need is made explicit in recent EU decision 2017/848  [22] , which outlines the importance of "specifications and standardised methods for monitoring and assessment," including the definition of threshold values. For NIS, recommended criteria and methodological standards for GES assessment require Member States to establish a) regional and subregional inventories of NIS, b) the number of new introductions over a 6year assessment basis, and the definition of a threshold value; c) abundance and spatial distribution of NIS and particularly of invasive species, and their adverse effects on native species groups and habitat types.
e. a specific molecular reference). DNA sequence data is therefore often only as good as the reference database used to interpret it, and those databases in turn are only as good as the taxonomic expertise behind deposited reference sequences and associated meta-data  [23, 24]. Unfortunately, such expertise has been in decline for decades  [25, 26]. This loss raises the specter of crippling bottlenecks to advancement of our understanding of marine biological invasions and marine biodiversity. Already a proliferation of molecular studies indicates the likelihood of previously unrecognized cryptic diversity, resulting in numerous systematic hypotheses that in many instances remain untested through integrated taxonomic study  [20, 27]. The failure to resolve these issues can lead to confusion regarding both invasion history and the degree to which marine biota have been shaped by species introductions  [28, 29].
In this respect, substantial resource investment in networks of marine stations (such as the European Marine Biological Resource Centre, EMBRC) might help to build focal points of observatory NIS networks, serving as repositories for vouchered specimens, DNA/tissue samples, and taxonomic expertise, all while leveraging existing collections and their potential value for untangling invasion histories  [38]. One of the greatest challenges for metabarcoding studies is the lack of reference sequences for determination of species identities based on barcode data. While the growth of dedicated bar-coding databases maintaining stringent quality control standards (e. g. the Barcode of Life Database, http://www. boldsystems. org/) has proceeded rapidly, such repositories still barely scratch the surface of estimated extant eukaryotic diversity, particularly in marine systems  [39] , and are heavily biased toward taxa and regions that have been well sampled and receive generous support for molecular data collection  [23, 40, 41].
With a few exceptions (e. g  [42]. ), there have thus far been a limited number of initiatives aimed directly at building up molecular reference data dedicated to NIS. Although the usefulness of barcoding studies to develop marine NIS inventories is already well documented  [43] , building up a dedicated, regularly updated, accurate reference database is a cornerstone to sustain efficient NIS molecular (meta)barcoding approach, and promoting such an initiative at the European level would clearly support MSFD objectives. Fortunately, evidence suggests that focused dedication of human and financial resources can result in rapid accumulation of expertly curated taxonomic information relevant to broad scale metabarcoding efforts  [44].
Reference database To assign a species name to a specimen barcode, it is necessary to compare that barcode to an existing sequence that has been attached to a species name by a competent expert. Reference databases provide public access to such sequences. Ideally, sequences in reference databases have been subjected to rigorous quality control for sequence quality and taxonomic accuracy Site occupancy-detection modelling (SODM) Models that estimate the population distribution of a monitored species across sites using observed patterns of detection of that species Targeted surveillance Surveillance directed at detecting the presence of a specific target taxon. Typically takes advantage of species-specific molecular genetic probes (frequently through PCR or qPCR) to recognize the presence of the target in the sample.