dataesr/scientific-paragraphs-categorization huggingface dataset:
Therefore, the initial conditions depend on the years because TG15d can occur between the 1st of July and the 31st of August, and the SSP scenarios. Hence we show how the extremes simulated with the SWG depend on the reference period of analogs  (1951-2000 vs. 2001-2050). The probability distribution of all TG15d values slightly changes with SSP scenarios (similar medians and non significant Kolmogorov-Smirnov tests on the horizontal lines in Figure  2 ). The record 2003 value is exceeded in the three "intense" SSP scenarios, although not in SSP1-2. 6, with this IPSL model simulation. The highest values for TG15d can occur with any scenario, when considering the CMIP6 ensemble (not shown). This results with SWG simulations from the IPSL model data (boxplots in Figure  2a-d  We investigate the atmospheric circulation patterns during the 15-day heatwaves, for the IPSL model.
Data and bias correction We use the simulations of 14 CMIP6 models (out of 31 models)  [4]  (see Table  1  in the SI) and four shared socio-economic pathways (SSP) scenarios  [21]  (SSP1-2. 6, 2-4. 5, 3-7. 0 and 5-8. 5). The criterion to retain these models is their availability on an ESGF server for the four SSP scenarios on daily increments. A data quality check is also performed on the available files. The historical simulations cover 1850-2014. The scenario (SSP) simulations cover 2015-2100. We extract the model gridpoints that cover continental France. For simplicity, we take one simulation for each model (some models provide ensembles) and visually check that this choice samples the overall spread of all simulations. The multivariate bias correction method R 2 D 2  [16]  is used to correct the bias of the marginals and the dependency structure of the temperature and precipitation, with respect to the SAFRAN reanalysis  [22]  (≈ 8km of horizontal resolution).
Code availability: SWG code is available on github: https://github. com/ pascalyiou/UNCLE-with-Analog-SWG. The bias correction code is available on github: https://github. com/yrobink/SBCK. Data availability: ERA5 reanalysis temperature data is available from the Climate Explorer tool https://climexp. knmi. nl/start. cgi. CMIP6 data without bias corrections (temperature, SLP) is available from the Earth System Grid Federation (ESGF) node https://esgf-node. ipsl. upmc. fr/projects/cmip6-ipsl/. Bias corrected data (temperature, SLP), SLP analogs and SWG simulations are available upon request to the corresponding author (PY). Authors contributions: PY designed the experiments. YR computed the bias CMIP6 correction and GEV estimates. All authors contributed to the writing of the manuscript.
Par conséquent, de plus en plus d'auteurs se focalisent aujourd'hui davantage sur l'étude des « réarrangements de la biodiversité » plutôt que sur la « perte de biodiversité »  (Magurran et al. , 2019). L'étude d'un taxon ou d'un trait fonctionnel unique peut également biaiser l'interprétation que l'on peut apporter à la dynamique temporelle de la biodiversité, chacun répondant différemment aux conditions du milieu et pouvant donc évoluer de façon distincte. Les publications récentes préconisent donc l'étude simultanée de différents maillons biologiques, si possible appartenant à différents niveaux trophiques de l'écosystème, et présentant des temps de génération et des capacités de dispersion différents. L'étendue temporelle de la base de données à analyser, influence également l'évaluation de la dynamique de la biodiversité : une échelle temporelle intermédiaire (décennale ou multidécennale) semble adaptée ; les modifications qui interviennent au sein des communautés sont alors majoritairement en lien avec les modifications du milieu, sans que les processus évolutifs de spéciation viennent interférer.
Première étape, construire et analyser une base de données originale Pour chaque variable environnementale et chaque métrique, à l'échelle du site, des modèles ont été ajustés en fonction du temps et des paramètres de tendance ont été calculés pour mesurer l'importance et la significativité de l'éventuel changement temporel survenu. Afin de compléter les analyses par une étude plus précise des changements intervenus au niveau de la composition des communautés, nous avons cherché à mettre en évidence quels taxons et quels traits avaient été favorisés au cours de la période ou au contraire défavorisés. Nous avons ajusté les modèles linéaires correspondant aux abondances cumulées de chaque taxon ou trait en fonction du temps et calculé la pente de tendance pour mettre en évidence un éventuel changement temporel.
Decomposing SST Trend Pattern Into a PDO Signal and a Residual We next decompose the observed SST trend pattern (as a function of latitude and longitude) into the PDO signal, a spatially uniform warming and a non-PDO residual (Figure  3 ). These three signals have all comparable magnitudes. Importantly, the eastern-central Pacific equatorial cooling and enhanced warming of the West Pacific and Indian oceans persist in the residual SST pattern (Figure  3d ). In addition, it shows a clear interhemispheric asymmetry with a greater warming in the Northern Hemisphere and cooling in the Southern Hemisphere. Therefore, we refer to the residual as the NH-IWP. Its structure is mostly similar across different datasets (Supplementary Figures  6 7 8 in Supporting Information S1). Its origin will be discussed next.
Data Availability Statement All CMIP6 data is available on https://esgf-node. llnl. gov/search/cmip6/. All observed data is available as stated in Supplementary Table  1  in Supporting Information S1. All code used for data analysis and figures is available online: https://github. com/ubbu36/Colder-eastern-equatorial-Pacific-and-stronger-Walker-circulation-in-the-early-21st-century-GRL/.
Conflict of Interest The authors declare no conflicts of interest relevant to this study. HEEDE AND FEDOROV 10. 1029/2022GL101020 of 12 A. V. F. is supported by Grants from NASA (80NSSC21K0558) and NOAA (NA20OAR4310377). Additional funding is provided by the ARCHANGE project (ANR-18-MPGA-0001, France). We also acknowledge a generous gift to Yale University from T. Sandoz. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. We further acknowledge freely available observational data sets provided by NOAA PSL, NASA PO. DAAC and the Met Office Hadley Centre.
Homogeneous objects therefore belong to the same category or 'class' of land-cover. The processing of satellite images by supervised or unsupervised classifications (both included in a 'pixel classification') using software (such as Arcgis, QGIS, ENVI) is used to produce land-cover maps (fig  4 ). 'Unsupervised' means classifications based solely on pixel values, with no prior human interpretation. They give a first (radiometric) overview of the land-cover classes (fig  4a ), with a thematic interpretation of the resulting spectral classes being made afterwards. 'Supervised' classification refers to the use of sampled and observed areas in the field for running classification algorithms (fig  4b ). Supervised classification has to be verified by field studies and then adjusted by applying an iterative process that alternates between data analysis and fieldwork.
Google Earth images are also used in supervised classification to complete field data and to identify classes because of their very high resolution that often leaves room for an interpretation of the data (fig  3c ). 'Field checks' were carried out through several observations and surveys conducted among farmers in Sunsari district in October 2013, March 2015 and November 2016. During these periods, cropping and harvesting rapidly followed one another; agricultural land-use therefore varied, enabling the landscape to be studied in all its diversity. The season in which satellite images are captured is important because at the end of the dry season (March to May) it can be difficult, for example, to distinguish almost bare and uncultivated land (especially next to houses) from harvested fields.
Generally speaking, it is difficult to precisely identify isolated or ungrouped settlements (those outside previously settled villages) prior to 2005 because the resolutions of the two main providers, SPOT and Landsat, used to be decametric. Due to the difficulties the students and myself encountered in ). We especially see the densification phenomenon and then the sprawl of houses from the road but also from the town of Jhumka Bazaar. 14 To conclude, the software used, QGIS-extension SCP and Arcgis, made it possible to obtain land-cover maps on a district scale with Landsat (30m) or SPOT (20 to 2. 5m) images and thus to carry out the first identifications. However, this work needs to be followed up by more detailed analyses using specialised remote sensing software (ENVI, eCognition) on judiciously chosen and very localised sectors and on a fine scale, if one wishes to obtain a precise analysis of the housing sprawl phenomenon.
This radiation consists of waves of the electromagnetic spectrum. The spectral bands or channels of the spectrum are categorised according to their wavelength. The channels of the visible range of the spectrum correspond to the short waves visible to the naked eye (colours of the rainbow). The channels of the infrared range, made up of longer waves, are not visible to the naked eye. 2. The project 'Terre Eau/Of lands and waters' -Projet-ANR-12-AGRO-0002 (see introduction to the section). 3. I would like to thank the ISIS (Incentives for the Scientific Use of Spot Images) programme for providing several SPOT 4 and 5 images. Two images were also purchased from Airbus DS Geo SA. 4. These images were provided free of charge by the EQUIPEX GEOSUD project, which was recently supplanted by the DINAMIS system (https://dinamis.
Ensuite, un tournant informationnel, lié notamment au développement des technologies numériques d'information et de communication et l'avènement d'une véritable « ère de l'information »  (Castells, 1996). Les activités scientifiques, économiques et professionnelles agricoles sont de plus en plus dirigées vers un usage intensif de données qui participe à l'émergence de nouvelles formes de contrôle et de régulation des pratiques de production en lien avec les enjeux alimentaires, sanitaires et environnementaux contemporains. À l'instar de la biologie moléculaire, où la numérisation des séquences d'ADN ou de protéines dans les grandes bases de données est devenue incontournable  (Brown, 2003 ; Strasser, 2012) , les sciences et les ingénieries de la sélection animale passent par l'agrégation et la circulation de données hétéroclites  (Hickey, 2013).
En ce début de XXI e siècle, la « révolution » génomique amorce une accélération sans précédent du « progrès génétique » des bovins laitiers. Le capital génétique des animaux reste largement dépendant d'une certaine matérialité organique. Les gamètes, spermatozoïdes et ovules continuent de constituer les vecteurs de l'amélioration génétique. Mais, en réduisant considérablement l'intervalle de génération et en rendant possible une sélection intensive sur la voie femelle, l'innovation génomique permet aux marchands de « progrès génétique » et à leurs clients de s'affranchir encore un peu plus de ce qui s'apparente pour eux à de l'inertie biologique des organismes reproducteurs, bridés par des cycles de vie. Avec le génotypage des vaches et des taureaux, l'idée que le matériel biologique est essentiellement le support des informations génétiques s'impose et se matérialise sous forme d'immenses bases de données contenant les séquences génétiques codant pour les performances productives recherchées.
Analyse des données Les données stockées par le chariot sont récupérées à l'issue de chaque journée de mesures. Elles sont alors traitées au moyen d'un ensemble d'outils numériques développés en Python dans le plugin t4gpd (https://pypi. org/project/t4gpd/) qui reprend et étend des fonctionnalités standards de Pandas, GeoPandas et Matplotlib. Il s'agit principalement de réaliser des jointures temporelles entre les différents ensembles de données pour extraire les mesures pertinentes et les replacer spatialement le long du parcours réalisé. À l'issue de ces traitements, nous obtenons un tableau associant l'ensemble des mesures relevées par le chariot et les points des parcours selon une chronologie temporelle précise. Sur cette base, différents indicateurs de ressenti thermique sont calculés comme indiqué plus haut.
À terme, l'expérience accumulée permettra de constituer une base de connaissances et de développer un référentiel sur les dispositifs de rafraîchissement les plus pertinents selon les situations rencontrées dans l'espace urbain et selon les techniques mises en oeuvre. Faute de référentiel, il est difficile de juger pleinement de l'efficacité de « points frais » comme Coasis pour le confort des citadins et encore moins de leur potentiels effets sanitaires au regard des faibles temps d'arrêt constatés au sein du dispositif. Un tel référentiel aiderait considérablement les collectivités qui doivent actuellement, et dans l'urgence, aménager leurs espaces urbains face aux enjeux d'habilité de la ville durant les périodes caniculaires. Remerciements : La méthodologie présentée dans cet article a été développée dans le cadre du projet COOLSCAPES soutenu par l'Agence Nationale de la Recherche (subvention ANR-18-CE22-0003).
Yet, there is still a need for morphological identification of species to enable the verification of the new sensor modalities. Ongoing and new challenges need to be addressed, for example those associated with taxonomic resolution from image analysis methods; or where the rate of collecting data exceeds that of processing it, a situation arising from collection of huge amounts of fineresolution data. Furthermore, there is a large variety of data formats including for example, images, acoustics, taxonomy, remote sensing etc … collected at different spatial and temporal scales. There is therefore a need to: (1) improve on how these emerging technologies, collecting multi-modal data, work together; (2) develop new methods embedding technological advances in data collection and data analytics, for a fully integrated understanding of pelagic processes; and (3) utilise open access databases that can handle diverse data sets.
A key element of an ever-increasing amount of data is the development of automated and efficient data processing techniques for seamless data flow. Ship time remains an expensive commodity and it is important to be able to capitalise on information collected at sea in real-time. Analysing continuous streams of high-frequency data calls for development and deployment of novel computer vision and machine learning systems  (Panaïotis et al. ; Le et al. ) , while cloud platform and high-performance computing are needed for processing the huge datasets collected. Together they can open new horizons for testing core hypotheses on plankton communities in aquatic ecosystems. Seamless data pipeline and emerging data analytics based on AI further offer the opportunity to move towards real time monitoring of plankton ecosystems  (Kraft et al.
Funding FL recieved funding from the  European Union 's  Horizon 2020 research and innovation programme "Atlantic Ecosystems Assessment ,  Forecasting and Sustainability" (AtlantECO)  under grant agreement No  862923  and the  JERICO-S3  project under grant agreement No  871153. EF was funded through the  UK Natural Environment Research Council 's  National Capability Longterm Single Centre Science Programme, Climate Linked Atlantic Sector Science , grant number  NE/R015953/1 , a contribution to Theme 1. 3 -Biological Dynamics.
For example, the Taiwan Moth Information Center has used Facebook to collect more than 362,000 moth records since 2011, and citizen science data are an important contribution to the first national report of birds (i. e. State of Taiwan's Birds Partnership. , 2020), revealing widespread shifts in distribution of birds. Redmap Australia, the Range Extension Database and Mapping project www. redmap. org. au, is an Australia-wide citizen science project where fishers, divers, boaters and marine naturalists are invited to submit photos of species they opportunistically observe outside of their expected distributions, via the project website or its smartphone application  (Pecl et al. , 2019). Each sighting submitted is verified by one of a network of over 80 scientists, and the observer is then sent a personalised email confirming the species identification and the nature of the sighting (e.
g. birds from the High Andean plateau wetlands; Orchids from tropical dry forests). Offers an online platform (Colombia Naturalist) to document findings Initiative Summary Geographic focus Colombia Redmap Australia http://www. redmap. org. au/ Redmap (Range Extension Database & Mapping project) invites Australia Pecl et al. , 2019 Australian fishers, divers and boaters to spot, log and map marine species that are potentially shifting distribution around the Australian coast. Each submitted photograph is verified by an expert for that species and a personalised email is sent back to the observer What's That Fish New Zealand https:// A Facebook-based project where the community is invited to submit New Zealand www. faceb ook. com/Whats ThatF ishNZ/ photographs of species they suspect are unusual for a given Middleton et al.
Recovery of published nuclear introns We downloaded from GenBank all homologous nuclear intron data published to date for the M. nattereri species complex, including those from  Salicini et al. (2011) , later corrected in  Salicini et al. (2018) , and from  Çoraman et al. (2019). To avoid problems associated with missing data, we restricted the data to individuals with a minimum of four loci in common with our study. This resulted in data from 19 M. crypticus, 15 M. escalerai, 5 M. hoveli, 35 M. nattereri, 6 M. schaubi, 5 M. tschuliensis, and 4 M. zenatius. Using BLAST, we also extracted these introns from the full genomes of Myotis myotis  (Jebb et al. , 2020)  and M. brandtii  (Seim et al. , 2013). Further information about these data and specimens are detailed in Supplementary Table  S1.
Microsatellite analysis The 62 samples included in the study originated from southern France (n=17; M. crypticus), and Corsica (n=45; M. sp. C). As the samples of M. crypticus were geographically dispersed across southern France, we considered all individuals as a single population. For M. sp. C, two locations were represented by over 10 individuals (Ghisoni [n=27] and Zonza [n=12], see Fig. 1 ) while three others (Asco, Albertacce, Evisa; max 16 km apart) had few individuals only and hence were grouped as a single population named AAE (n=6). Deviations from Hardy-Weinberg and linkage equilibrium were tested using the genepop R package v. 1. 2. 2  (Rousset, 2008). Observed heterozygosity and within population gene diversity were calculated in the hierfstat R package v0. 5. 11  (Goudet, 2005).
Fst and significance were tested in the genepop package. Comparisons were made between M. crypticus and M. sp. C, and between the three populations of M. sp. C. Tests were carried out in R v. 4. 2. 1 patched (R Development Core Team, 2022). Population structure was studied using Principal Component Analysis (PCA;  Jombart, 2008)  implemented in the adegenet R package v. 2. 1. 10 (Jombart, 2008). Given the very clear results of this analysis (see Results), we used a discriminant analysis of principal components (DAPC) to assess the extent to which the genetic data from the microsatellites could be used to assign individuals to their population of origin (Corsican versus continental populations). We therefore constructed a DAPC by discriminating between two groups (Corsican versus continental).
Morphological data To characterise the morphological attributes of the Corsican Myotis, we based our comparisons on a range of specimens from continental Europe which were previously used in a revision of the M. nattereri species complex  (Juste et al. , 2018). All these comparative specimens are deposited in the collections of the Muséum d'histoire naturelle de Genève, Switzerland (MHNG), the Hungarian Natural History Museum of Budapest, Hungary (HNHM) and the Estación Biológica de Doñana Seville, Spain (EBD) and represent all four species currently known from this region. Details about their origins can be found in  Juste et al. (2018). In addition, we obtained a single specimen from Corsica that was found dead in Albertacce, Haute-Corse. This specimen is deposited in the collection of the Muséum National d'Histoire Naturelle in Paris (MNHN) under voucher number MNHN-ZM-2023-12.
Distribution Based on previous studies conducted in the field in Corsica  (Courtois et al. , 2011; Groupe Chiroptères Corse, 2019) , we calculated the extent of occurrence and area of occupancy of M. sp. C with the 'EOO. computing' and 'AOO. computing' functions, respectively, via the ConR package v. 1. 3. 0  (Dauby et al. , 2017)  in R.
ACKNOWLEDGMENTS We thank  Yann Le Bris ,  Jean-Yves Courtois ,  Delphine Rist  and  Kate Derrick  for their help with this work,  EDF hydraulique de Corse  for facilitating access to specific locations and,  Benjamin Allegrini ,  Eleni Papadatou ,  Emmanuel Cosson ,  Fabien Sané , the  Groupe Chiroptères Corse ,  Jean-Paul Urcun ,  Laurent Arthur , the  LPO Aquitaine ,  Olivier Vinet ,  Pascal Gaultier ,  Raphael Colombo ,  Roberto Toffoli ,  Sophie Bareille ,  Thomas Bernard , and  Yannick Beucher  for providing samples. Gerald Kerth  provided access to laboratory facilities, and the  Office de l'Environnement de la Corse  provided funding for this study.
L'analyse multiniveau permet notamment de mesurer l'ampleur réelle des variables de contextes, en calculant une variance basée sur le nombre de contextes et non sur le nombre d'individus  (Bringé & Golaz, 2017). Cette méthode, entreprise sur le logiciel SPSS, a donc été choisie considérant qu'elle est la plus adaptée pour saisir l'hétérogénéité des relations entre les individus et leur environnement  (Bressoux, 2007). PISA étant une enquête internationale, nous avons fait le choix d'effectuer un premier modèle vide permettant d'établir la part de variance du score de développement durable en fonction des pays. Le modèle vide, c'est-à-dire un modèle dépourvu de toute variable explicative, est la première étape à réaliser lors d'une analyse multiniveau. Ce premier modèle nous a permis de constater que la variance du score global de développement durable des élèves était expliquée par le pays d'appartenance à hauteur de 4 %.
Acknowledgments This work is a contribution to  H2020 Arctic Passion project , Grant  101003472. We gratefully thank  Camila Artana  and  Marylou Athanase  for their help as well as  Jérôme Sirven  for early discussions. We deeply thank the two anonymous reviewers whose advice helped us improve the manuscript. Louise Abot acknowledges funding from the  H2020 Arctic Passion  project, ( 101003472 ) and  Léa Poli  from a  Sorbonne Université Ph. D. scholarship.
The local authorities also have an urgent need for information to deal with issues linked to coastal erosion, a major problem on the north coast, an area in which two major port projects are underway. With the retreat of the coastline particularly marked on the Langue de Barbarie and the relocation of Guet Ndar populations to the interior (which is not always successful, especially when fishing communities are very resistant to these measures), risk management for vulnerable coastal communities will require planning that takes greater account of the need for observation data on coastal dynamics 10. In this context, updating development and management plans on the basis of documented information is imperative in order to reassess the human and financial Kayar MPA: mapping fishing grounds 32 The fishing areas of Senegal's artisanal fleets have expanded considerably over the last few decades.