dataesr/scientific-paragraphs-categorization huggingface dataset:
(quotation 132J 1-244) and have been converted into electronic images by M et eo-France. From French National Library (Biblioth eque Nationale de France -BNF -). The French National Library (BNF) is intended to be the repository of all that is published in France. Gallica, the digital library maintained by BNF, is an access portal that holds collections from different public partners (e. g. institutions, learned societies, research centres, libraries). This digital library makes these French records freely available. Numerous imaged scientific annals and reports of academies and learned societies, newspapers in French extending back to 1700 are accessible via Gallica and are also very interesting sources to recover French ex-colonies data http://gallica. bnf. fr/.
Directorate of climatology (Direction de la Climatologie) All the directorates for Climatology of the successive French meteorological services (Bureau Central M et eorologique, Office National de la M et eorologie, M et eorologie Nationale and now M et eo-France) collected climate data gathered from volunteer observers, professional stations and other institutions. The Archives of Directorate for Climatology in Toulouse hold surface and upper-air data for the French mainland, overseas and French ex-colonies in hard copy and microfilms. The archives have been inventoried and are briefly summarised as follows: French mainland records in paper form: Monthly climate reports, Tableau Climatologique Mensuel (TCM) from synoptic stations and semaphore stations since 1920 and monthly climate reports from all climatological stations since 1961.
French mainland records in microfilms: Daily Climate Report, Compte Rendu Quotidien (CRQ) with daily and sub-daily data from synoptic stations since 1955. The usage of these types of reports began in May 1923 in mainland France for all synoptic stations, but they were also used at synoptic stations of the French colonies from the end of World War II. These Daily Climate Reports, however, remained in the former colonies. North African former colonies records in microfilms: The collection concerns 74 synoptic stations: TCM for Tunisia and Morocco from 1923 to 1962, TCM and CRQ for Algeria from 1924 to 1966, but with a big gap between 1937 and 1944.
Both aspects are the focus of this sub-section. As early as the first computer was purchased by the Algerian NMS in the 1970s and climate data management systems and other hardware and software were available thanks to the international cooperation fostered by the WMO Voluntary Cooperation Programme, the Climatological Branch started both the digitalisation and quality control of its recent weather observations and an early DARE program aimed at locating, organising and preserving the national historical assets and to image and digitise some of these assets for some of the essential climate variables (i. e. surface temperature and precipitation) measured anywhere at any time and date in the Algerian territory. The recovery effort first emphasised the digitisation and quality control of the observations for 50 synoptic stations for the period 1953-1991, which include all climatic variables and weather phenomena at sub-daily (eight observations per day) and daily scales.
The digitised data were recorded and kept on magnetic tapes from the mid-1970s to early-1990s. These required later transfer of the data onto currently operable systems. From the mid-to late-1980s, the availability of new climate data management systems, such as the French DataStar (digitisation of precipitation and temperature) and the WMO/CLICOM (for digitising synoptic data before 1953 and after 1991) systems enabled the digitisation of the main and climatological stations for the six Algerian meteorological regions, which were then sent to the central climatological branch for quality control in delayed mode. A problem with the digitised data related to the non-interoperability of the media where the data were kept (NORKS DATA) turned out to be a very time-consuming and intensive task.
The effort was and is being concentrated on the digitisation and quality controlling of a dense network of precipitation stations (about 790 rain gauge sites; ~25 of them going back in time to the mid 19th century, ~220 starting in the late 19th century, ~350 beginning around the early 20th century and the remaining from the 1960s and later). Figure  2  provides details (i. e. location and approximate length of the records) of the precipitation network that has been digitised and is being quality controlled by the Climatological Branch at the Algerian NMS. At present, the DARE program has also scanned a large number of documents (272K daily reports with four images per day) containing climate daily data for 17 stations for the period 1949-2002, although it is still pending the scanning of the TCM source and other manuscripts with the oldest data sources for Algiers station with records going back to 1856.
Among other recent organisational, dissemination, cooperation and raising awareness activities  (Brunet, 2012) , the MEDARE Community has set up a metadata portal (http://app. omm. urv. cat/urv/), which is being populated by the MEDARE Community with metadata for the longest and key climate records selected on a national basis. Up to 656 past and current observing sites from which key climate variables (e. g. surface temperature, precipitation, air pressure) are documented and available. Table  5  gives details of the total number of observing sites for which metadata exists in the MEDARE meta database and also provides the number of stations at the ECA&D (http://eca. knmi. nl/) project for comparison purposes with an emphasis on the southern Mediterranean and Middle East. The MEDARE meta database gives information on station identifiers (i.
php). At present, the network of participants is being gradually extended to countries in the Middle East and North Africa, which is expected to result in a dramatically increased climate data availability and accessibility at the finest time scales for this region in conjunction with the EURO4M project and WMO/MEDARE Initiative efforts. Several other initiatives attempting to directly or indirectly increase data availability or their accessibility are worth to mention. (Xoplaki et al. , 2012) , four sites where air pressure, temperature and rainfall were measured since the late 18th and mid-19th centuries are being recovered, imaged, digitised and quality controlled. Finally, a number of projects aimed at the establishment of data repositories or the implementation of high-performance computing (HPC) systems in the Eastern Mediterranean region have been recently set up.
The EU-funded DARECLIMED project aims to identify, rescue, collect and disseminate regional data sets of interest for the climate, water and energy sectors over the eastern Mediterranean region through establishing a network of partners that have access to, own or have collected relevant data and implement a regional infrastructure for climate research (http://www. cyi. ac. cy/index. php/dareclimed-welcome. html). Another project, aimed at the implementation of a HPC ecosystem interlinking and coordinating regional computing, storage and visualisation resources to implement an integrated e-infrastructure, is the LinkSCEEM-2 project (http://www. linksceem. eu/ls2/project/about-us. html). It is expected that both projects improve data accessibility over the Eastern Mediterranean, a region where the need for long climate data is crucial.
Concluding remarks Despite the wealthy heritage of historical climate records that have been taken across the GMR since the inception of instrumental data, current availability and accessibility to long-term and high-quality climate series are still largely inadequate. This shortcoming is impeding scientific progress on climate variability and change, along with its impacts in the Mediterranean socio-ecosystems, and it is obstructing the definition of the best strategies to adapt the countries to current and future climate change effects. The study highlights the rich and still largely underexploited heritage of historical climate data over the GMR by means of assessing and describing the climate assets gathered and kept in various online repositories and physical archives around the world.
Particularly, a revision is provided of the relevant Mediterranean data sources gathered and maintained by the NCDC/CDMP online repository. This is the largest repository of worldwide climatological data sources, which has recently seen a dramatic cut in funding in the 2012 financial exercise that could put in peril this valuable US-program. Also, the BADC repository and its potential for long climate DARE and reconstruction has been presented. Special emphasis has been placed on the French online and physical holdings containing not only French-mainland data, but also overseas former colonial data over the GMR with the focus put on southern and Middle East Mediterranean countries. Several initiatives and projects intending to increase climate data availability and accessibility over the GMR have been analysed.
The WMO/MEDARE Initiative along with the EU-funded EURO4M project have been the focus, since both ongoing activities in the DARE field are making valuable forward steps for ensuring that the rich heritage of Mediterranean climate records is not lost forever. Other EU-and national-funded projects have been also assessed. Some of the examples used in the article suggest that good coordination among data producers/holders (i. e. NMSs) and scholars (i. e. research centres, universities) in the DARE arena brings improved results when considering enhancing and accessing to crucial historical climate data that remain in unusable formats. The analyses have shown the need and potential for continuing to promote and carry out DARE activities over this climate change hot spot and have given the necessary details pointing to the relevant climate data sources and holders.
Thanks to the EU-funded Climate Change and Impact Research: the Mediterranean Environment (CIRCE) integrated project, a handful of southern Mediterranean climate series [i. e. for seven (six) Tunisian (Moroccan) locations have been added covering most of the 20th century for a few of the longest records]. Recently and under the framework of a local DARE project funded by the University of Giessen in Germany and supported by the ACRE Initiative to increase availability and accessibility of long historical observations series from Mediterranean and Middle East.
Acknowledgements Manola Brunet ,  Phil Jones  and  Dimitrios Efthymiadis  thank the  EU-funded  project  EURO4M  ( FP7-SPACE-2009-1 Project No. 242093 ). Manola Brunet also thanks  WMO/CCl  and  WMO/WCDMP  for their support. Sylvie Jourdain  thanks the  ANR -funded  CHEDAR  project and to the foundation  BNP Paribas (Climate Initiative Program , Project to the climate archives).
S E I S M I C N E T W O R K S A N D DATA C O L L E C T I O N Since 2005, the seismic activity in the Campania-Lucania region is monitored by ISNet (Irpinia Seismic Network), a permanent seismic network operated by the research consortium AMRA (Analysis and Monitoring of Environmental Risk), consisting of 26 stations covering an area of 100 km × 70 km, with average interstation distance from 10 to 30 km. ISNet is equipped with collocated tri-axial strong-motion accelerometers and three-components short-period or broad-band seismometers, allowing for high dynamic range  (Weber et al. 2007). The data set collected by ISNet is extended and integrated by the inclusion of the closest stations of the Italian Seismic Network, managed by INGV (Istituto Nazionale di Geofisica e Vulcanologia), allowing for better quality in the determination of the hypocentral parameters.
The data set used in this study consists of 17 202 traces recorded by 42 ISNet and INGV stations from 1312 small-magnitude earthquakes, with local magnitude ranging between 0. 1 and 3. 2 (Fig. 2b ), occurred from 2005 August to 2011 April. To obtain a high-quality data set, we manually picked the first P-and S-wave arrival times of earthquakes recorded by at least four stations. A weighting factor was assigned to the readings of the first P-and S-wave arrival times according to the estimated uncertainties (decreasing weight- ing factors were associated to uncertainties <0. 05 s, 0. 05-0. 10 s, 0. 10-0. 20 s, 0. 20-0. 50 s and >0. 50 s). A first evaluation of picking consistency has been performed by analysing the 'modified Wadati diagram'  (Chatelain 1978) , which also provides an estimate of the average V p /V s ratio.
DATA A N D R E S O U RC E S Data can be obtained from the ISNet Bulletin at http://seismnet. na. infn. it (Elia et al. 2009; last accessed November 2011)  and from the INGV data management centre http://iside. rm. ingv. it/iside/ standard/index. jsp (last accessed December 2011). Most of the figures were made using Generic Mapping Tools software  (Wessel & Smith 1998 ; http://gmt. soest. hawaii. edu/ last accessed March 2013).
A C K N O W L E D G E M E N T S The research has been partially funded by REAKT [European Community's Seventh Framework Programme (FP7-ENV-2011) under grant agreement n. 282862] and GEISER [European Community's Seventh Framework Programme (FP7-ENERGY-2009-1) under grant agreement n. 241321] projects. We thank the editor, Prof. Xiaofei Chen, and two anonymous reviewers for their constructive considerations. Moreover, we acknowledge Dr. Mauro Caccavale (KNMI), Dr. Tony Alfredo Stabile (IMAA-CNR) and all the members of the seismological laboratory of the Department of Physics (University of Naples Federico II) for useful discussions and comments.
A C K N O W L E D G M E N T S We are extremely grateful to the reviewers who provided very constructive comments which helped to significantly improve the manuscript. We acknowledge S. L. Karner and M. Nakatani for providing their experimental results used in our result analysis. We also acknowledge J. Sulem and M. Nakatani for very fruitful discussions. The project was supported by ANR Grants CATTEL-MODALSIS and RISKNAT-SUPNAF and by INSU (3F program #07CV00).
In PlankTOM5 food preferences are expressed more strongly with the result that microzooplankton and mesozooplankton become specialized grazers of one prey, which ultimately enhances the spatial separation that result from grazing of mesozooplankton on microzooplankton. By comparing PISCES and PlankTOM5, it appears that the choice of parameters for zooplankton has an influence on the impact of zooplankton on the resulting ecosystem, by shaping the food web and modifying the strength of the interactions between prey and predator. This highlights the necessity for well chosen parameters and equations. For a proper choice of parameters and formulations, there is a need for more observations and experiments on zooplankton grazing dynamics and food preferences. Also, data on zooplankton distribution are very dependent on the species or the size class (e.
g. copepods have much better data coverage than microzooplankton;  Buitenhuis et al. , 2006 Buitenhuis et al. , , 2010)). The comparison of model output with observations is difficult at present, due to the patchy nature of observations, with the added consideration that PFTs often represent more than one species or taxonomic group of plankton  (Buitenhuis et al. , 2012). The latter limitations underline the need for more data on zooplankton biomass, distribution, composition, size structure and rates, in order to compare observational data with outputs of models that do not use a generic zooplankton type. We have shown how predator-prey interactions shape the foodweb structure and its dynamics. This is particularly true for the models with two or more zPFT: PISCES, PlankTOM5 and NEMURO. For example, PISCES has a balanced interaction between prey and predators.
Spaceborne reflectance measurements from the POLDER instrument are used to study the specific directional signature close to the backscatter direction. The data analysis makes it possible to derive the extinction-tobackscatter ratio (EBR), which is related to the inverse of the scattering phase function for an angle of 180 • and is needed for a quantitative interpretation of lidar observations (active measurements). In addition, the multidirectional measurements are used to quantify the scattering phase function variations close to backscatter, which also provide some indication of the aerosol particle size and shape. The spatial distributions of both parameters show consistent patterns that are consistent with the aerosol type distributions. Pollution aerosols have an EBR close to 70, desert dust values are on the order of 50 and EBR of marine aerosols is close to 25.
Data and method The POLDER instrument is composed of a wide field-ofview lens, a filter wheel and a detector. The filter wheel permits radiance measurements in eight spectral bands from 440 (blue) to 1020 nm (near IR). The detector is a twodimensional CCD array with 242 × 274 independent sensitive areas. One snapshot provides an image of a portion of the Earth of size roughly 1900 × 1400 km 2 , similar to what a camera with a wide field-of-view lens would provide, with a spatial resolution on the order of 6 km. The pixels in the image are viewed with various zenith angles and azimuths. The zenith angle at the surface varies between 0 • at the image center to 50 • crosstrack and 60 • forward and aft. One snapshot is acquired, for each spectral band, every 20 s. There is a large overlap of the areas observed by successive snapshots.
These correspond to measurements acquired before and after the backscatter observations. has shown that R mod is a close approximation to R mes so that the correction to P mod remains small. The operational processing of POLDER data includes the derivation of P aer as described above. This is done for all pixels for which there is a successful aerosol retrieval, although this parameter is not included in the operational product that is widely distributed. We have had access to the restricted product, and have extracted all pixels that include one observation in the backscatter direction. In the following, we analyze the values of P aer (γ ) close to backscattering (γ ≈180 • ). One parameter of interest is the value of the phase function for γ = 180 •. This value is of particular interest to relate to lidar observations.
The uncertainty on the dust EBR results from the refractive index variability  (Schuster et al. , 2012)  and the non-spherical nature of the particles  (Veselovskii et al. , 2012). CALIPSO measurements are also affected by multiple scattering  (Wandinger et al. , 2010) , which is not the case for ground-based or airborne measurements, because of the respective size of the instrument field of view. Therefore, over areas with well-defined aerosol types, the POLDER retrievals of the lidar ratio are similar to the expected values. This analysis cannot be seen as a quantitative evaluation of the POLDER product, but it nevertheless generates some confidence in the results. Figure  5  shows the derivative of the phase function V (see Eq. 4) for the same data points as in Fig. 4. This figure shows very clear spatial and temporal patterns, some of which are not apparent on the EBR retrievals.
Multiple aerosol layers are certainly present in our database, but the presence of clear patterns in the global distribution indicates they are not significant. Although the POLDER instrument does provide measurements in the antisolar (backscatter) direction, these observations are relatively rare. Let us recall that the POLDER measurement principle is that of a very wide field of view that acquires one shot for each spectral band every ≈ 20 s. For each such acquisition, there is one point on Earth that is observed in the backscatter direction. As a consequence, the backscatter sampling per day is 14. 5 (the number of orbits) roughly north-south sets of observations, distant by 25 • of longitude. Each observation set (i. e. , each orbit) contains measurements distant by ≈ 140 km (the distance traveled by the satellite during the 20 s).
Sampling Samples of Mnemiopsis leidyi were collected either by surface dipping, scuba diving or with different plankton nets; sampling locations and years are displayed in Table  1. Animals were dried individually on filter paper and DNA was extracted and analysed as described previously  (Reusch et al. 2010). For the Northern time series, M. leidyi from the 3 locations (Helgoland, Kiel Bight and Bornholm Basin) were analysed for 2008 and 2010 from data collected in this study. We used published data for the same locations for the 2009 analyses  (Reusch et al. 2010) , thus continuous sampling over 3 years was obtained. From the Mediterranean Sea, 3 different sites (Mar-seille, Barcelona, and Haifa) were sampled: these were analysed together with published data from native and invaded habitats  (Reusch et al.
Genetic analysis We analyzed polymorphism at 7 microsatellite loci  (Reusch et al. 2010 ) using multiplex PCR with fluorescently labelled primers and subsequent electrophoretic separation on an ABI3130xl genetic analyzer. Raw electropherograms were binned and their alleles called using the software GENEMAPPER (Applied Biosystems). All allele calls were verified by eye and samples with missing data for more than one locus were excluded from further analysis.
Data analysis For the time series data from the northern invasion wave (Table  1 , Dataset A) all 7 loci were used. For the Mediterranean samples (Dataset B), one locus (L211) was excluded because it shows poor performance in the southern clade, as described previously  (Reusch et al. 2010). The fixation index between subpopulations and total population (pairwise F ST ; significance level p < 0. 05) was calculated for both datasets with the software Genetix  (Belkhir et al. 1996). To compensate for multiple testing, the false discovery rate (FDR) approach  (Benjamini & Hochberg 1995)  was applied and adjusted q-values were calculated from the p-value distributions. The q-value is defined as the FDR-adjusted analogue of the p-value, i. e. the value of an individual hypothesis test is the minimum FDR at which a test is called significant.
The significant q-value for the 36 comparisons of the time series (Dataset A) was 0. 026 while for the 136 pairwise comparisons of the population genetic overview (Data set B) the FDR-adjusted q-value was 0. 007. Before calculating the mean number of alleles, rarefaction was applied to compensate for differences in sample size between sites and/or years  (Leberg 2002). For this calculation of allelic richness, data were imported into the software HP-Rare  (Kalinowski 2005). The time series data were subjected to rarefaction according to the smallest sample size of 13 individuals and the mean number of alleles over 7 loci was calculated. Dataset B, including the Mediterranean samples, was subjected to rarefaction to a size of 15 samples and allelic richness calculated over 6 loci. The mean diversity measures of allelic rich-ness were tested for significant differences between groups.
For both datasets (A and B) the mean number of alleles were normally distributed (Shapiro Wilk Test; p > 0. 05) and the data met the assumptions of ANOVA. For the northern time series we grouped all 3 years from one location and tested over all 7 loci. We performed a repeated-measures ANOVA, testing site against number of alleles (NA) for each locus; this was followed by a pairwise t-test. For the southern invasion, event sites were grouped according to expected introduction sequence: native (Gulf of Mexico), primary invasion (Black Sea) and putative secondary invasions (Caspian Sea and Mediterranean Sea), and we performed a 1-way ANOVA and a pairwise t-test. All statistical analysis were per formed in the R software package (www. r-project. org). All maps were created with Ocean Data View  (Schlitzer 2002).