dataesr/scientific-paragraphs-categorization huggingface dataset:
It is worth noting that Andean ice cores spanning the last glacial-interglacial transition show a similar deglacial isotopic shift  (Vimeux, 2009b). The water stable isotopic composition in those ice cores is likely reflecting precipitation changes at the regional scale, and such a similar deglacial structure is explained by simultaneous cold conditions in the high latitudes and wetter conditions in the Andes  (Vimeux et al. , 2005; Chiang and Koutavas, 2004). Different patterns emerge from speleothem records covering the LGM and MH, as only half of the datasets are marked by a more depleted glacial δ 18 O level. Depending on the location, speleothem calcite δ 18 O may reflect paleotemperature and/or past changes in the atmospheric water cycle (including precipitation and circulation). Additional sitespecific factors (cave microclimate, mixing and evaporation of source waters through the soil and the epikarst, kinetic fractionation during carbonate precipitation) may also influence the signal  (Lachniet, 2009).
Regional effects may also be at play in the western Middle East, where speleothem records can be directly influenced by changes in the Mediterranean or the Black Sea, which had diverging oceanographic evolutions between the LGM and the MH, with the opening of the Bosphorus Strait. Individual records must therefore be understood in their own regional environmental context, a feature also evidenced by different amplitudes of change arising from different source archives. Thus, Figs. 8-10 might be considered as an inventory of the available datasets, rather than a cartography of the amplitude of climatically relevant signals, expected to be representative of the amplitude of annual mean precipitation or sea water isotopic composition changes.
Conclusions, recommendations and perspectives Our compilation of hundreds of records from different sources highlights the needs for a standardized protocol of data storage. The output files provided by the different depositories have different archiving formats. Several ongoing projects rely on massive and automated extraction of Clim. Past, 12, 1693 Past, 12, -1719 Past, 12, , 2016  www. clim-past. net/12/1693/2016/ datasets provided by authors. This effort would be made easier if the data and publication information (core site specifications, references, article title and abstract) were stored in individual CSV (comma-separated value) text files, rather than within files specifically designed for spreadsheet software (e. g. , Microsoft Excel/Apache OpenOffice), sometimes containing several spreadsheets, that may not be readable by automated data extraction programs.
We also think that building a fixed disposition for datasets constitutes a preliminary step and that it is essential for the existing and future data depositories to find an agreement for an harmonized disposition, structure, and labeling for metadata and age modeling data storage. Some projects are following a promising philosophy of homogenously structured metadata (e. g. , LiPD; McKay and Emile-Geay, 2016). We highly encourage these constructive initiatives, as it is becoming urgent for the paleoclimate research community to definitively adopt a universal file format and metadata disposition and to define the type of contents to be included, before starting to compile data, as this will otherwise lead to a high risk of incompatibility or of conflicting information from different sources or projects.
Adopting this universal format will, however, necessitate a clear agreement between data producers, users, and compilers, as it requests at the end a unique structure compatible with all types of archive and proxies, which may lead to some complications due to the variable number of parameters to be included for each proxy and archive. If a universal standard format is definitively adopted, the conversion of our metadata spreadsheet into a hierarchical structured may be relatively easy and fast. Divergences in data units also constitute a major obstacle for automated extraction, intercomparison of records, and model-data comparisons. An illustrative example is the use of various time units (years CE, years or before 2000 CE, years before 1950 CE, kiloyears BP, and million years BP). The establishment of standard time units for paleoclimatology such as the use of "ka" (calendar kiloyears before 1950) would avoid errors and homogenization of future datasets.
Several discrepancies also exist with respect to the geographical coordinates of core sites. Although the most common format found in the literature is DMS (degrees, minutes, seconds; e. g. , 25 • 22 34 N, 38 • 16 43 W), it is not supported by most mapping programs. Here, we converted all the geographical coordinates into decimal degrees. We again highly encourage the adoption of a standard notation, with the systematic presence of the decimal degree version of the coordinates; we observe that an increasing number of authors now provide both DMS and decimal formats. Gathering information about the age models was a particularly critical step of the construction of this database, in particular for the inclusion of lacustrine and deep-sea cores as well as speleothems. We highly encourage authors to systematically provide both depth and age scales as well as a comprehensive description of the methodology used to establish the age scale, when available.
Several publications have also suggested changes in reservoir ages between glacial and interglacial periods (e. g. ,  Waelbroeck et al. , 2001; Bondevik et al. , 2006; Sikes and Guilderson, 2013). In this context, the age model of many old records may be outdated, and even considered to be wrong. Unfortunately, the lack of information concerning the construction of these initial age models makes the construction of an updated age model virtually impossible. In this study, we did not aim to evaluate the accuracy of published reservoir ages, which remain sometimes vigorously debated. We encourage authors of publications to systematically justify their choice of a reservoir age, to describe the associated uncertainties, together with the detailed age model information. Our database may in the future allow the implementation of statistical age models built on the existing age markers.
Reporting the exact number of source records for tree rings and ice cores is also important with respect to the signal to noise issue; this is not always a standard practice. Our software tool was designed to make the update of the database user-friendly and easy in order to allow future extension. Indeed, major synthesis efforts as the MARGO project  (Waelbroeck et al. , 2009)  are time-limited (MARGO only includes records published prior to 2005). Options for an automatic update include regular browsing of new published data, but we highly encourage authors to upload their new data in our database using the user-friendly interface on the online platform. This constitutes a fast and easy way to disseminate new data and increase their visibility, and a unique opportunity for the scientific community to access and exploit newly published datasets.
This allows "data producers" to easily compare their records with other existing records in a given area or at the global scale, and climate modelers to access easily the data, and to the source references and their authors. In the future, and if manpower resources are available, the database and web interface could be easily opened to other proxies (paleotemperature proxies and nitrogen isotopes for seawater, CO 2 and CH 4 from ice cores, tree-ring width and boreholes, pollen, circulation tracers such as 14 C and Pa/Th, etc. ) of past and future datasets. We also hope that our database, associated with current and upcoming projects focusing on time-series age control (INTIMATE PROJECT, COST Action ES0907) and chronological data managing  (Mulitza and Paul, 2013) , will in the future facilitate the use of paleoclimate datasets for data comparison and integration into models with an homogenous and robust chronological frame.
Data availability All the data compiled in our database and used in this manuscript are available on the IPSL "Climate Proxies Finder" online depository at the following address: http: //climateproxiesfinder. ipsl. fr/. The source code of the online platform is also available in the "Help" section of our website: http://climateproxiesfinder. ipsl. fr/help. html. Clim. Past, 12, 1693 Past, 12, -1719 Past, 12, , 2016  www. clim-past. net/12/1693/2016/.
, 2007;  Löwemark et al. , 2008; Fallet et al. , 2012). Solving these issues might require a precise investigation of bioturbation tracks in the upper layers of sediment cores and drastic improvement in the coring and analysis techniques, as suggested by the final conclusions of Keigwin and Guilderson (2009) : "Until we can directly radiocarbon date individual foraminifera, the role of bioturbation will always be a problem in core top calibration studies. " These sedimentary issues are often accompanied by insufficient resolution and quality of the sediment core-tops dating procedure. In fact, present-day conditions are represented by only one data point in about half of the datasets, generally dated via linear extrapolation of deeper tie points. About 95 marine δ 18 O and.
tion techniques (d3. js [https://d3js. org/],dc. js[https://dc-js. github. io/dc. js/],Leaflet[http://leafletjs. com/], and Bokeh [http://bokeh. pydata. org]). Figure1ashows the layout of the Climate Proxies Finder, which consists of a world map (top row) and four charts representing, respectively, the proxy depth, age (oldest, most recent), archive type (ice, lake,.
d. Quality flag 4 (below average): the age scale of Core• N, 177. 08 • E) is particularly well described byKohfeld and Chase (2011). However, only three AMS 14 C dates and one δ 18 O data point for oxygen isotope stratigraphy are available between 10 and 22 ka, while the δ 13 C and δ 18 O records span a consider- ably wider time interval(10-86 ka). The starting point of Termination I is not well defined in δ 18 O, making the datum at 22 ka relatively imprecise. Although the authors did not focus on the last deglaciation, we incorporated this record in the database, because only very few www. clim-past. net/12/1693/2016/ Clim. Past, 12, 1693-1719, 2016 records have been recovered in this part of the North Pacific. e. Quality flag 5 (poor): δ 18 O record from Core M44/3_KL83 (32. 60 • N, 34.
tion techniques (d3. js [https://d3js. org/],dc. js[https://dc-js. github. io/dc. js/],Leaflet[http://leafletjs. com/], and Bokeh [http://bokeh. pydata. org]). Figure1ashows the layout of the Climate Proxies Finder, which consists of a world map (top row) and four charts representing, respectively, the proxy depth, age (oldest, most recent), archive type (ice, lake, Clim. Past, 12, 1693Past, 12,  -1719Past, 12,  , 2016www. clim-past. net/12/1693/2016/.
■ MATERIALS AND METHODS This study was conducted in Central Butana rangelands whose areas are about 3600 km² (Figure  1 ). The current ecological situation of these rangelands was evaluated in 2006 by field surveys covering 25 sites in the region. The above-ground biomass and floristic composition were determined for each site. Remote sensing data derived from Spot image for the same period (Spot View Ortho Basic, date 5/10/2006, columns 7252, rows 6802, projection UTM zone 36 N, datum WGS 84) was integrated to the ground field surveys to create the spatial distribution of biomass production (kg ha -1 ) by mean of vegetation indices, particularly the perpendicular vegetation index (PVI)  (Gintzburger et al. , 2005). A rainfall map of the region was established from the regression correlation between the meteorological data of six stations around the area for the period 1980-2004 and the digital elevation model.
Remerciements Le projet Passy a été financé par l'ADEME via le programme national LEFE du  CNRS/INSU. La campagne Passy-2015 a été financée par l'ADEME via le projet et par METEO- FRANCE. Nous remercions les Villes de Passy et de Sallanches pour leur soutien. La campagne Passy-2015 a été pilotée par le CNRM, tandis que le LEGI est porteur du projet Passy. Les données sont gérées par le SEDOO à l'observatoire  Midi-Pyrénées  (http://passy. sedoo. fr). Nous remercions les agents  METEO-FRANCE du centre de Chamonix-Mont-Blanc et du service PAM de l'École Nationale de la Météorologie , pour leur soutien lors de la période sur alerte pour les phases d'observation intensive. Nous remercions  Sébastien Blein  (LEGI),  Hélène Guyard  (IGE),  Frédéric Murguet  (CNRM),  Isabel Peinke  (LEGI),  Jean-Emmanuel Sicart  (IGE),  Delphine Six  (IGE) et  David Suquia  (CNRM), pour leur soutien ou participation à la campagne.
The opposite approach assumes that simulated outcomes provide quantitative scenarios. Various modeling techniques can be used for these two main approaches aiming to explore the future. In any case, it is recognized that the SAS approach allows to explore a wider diversity of futures, with contrasted / breaking trends scenarios. Such forecasts have been shown to be important for creative scenario-based land use planning  (Xiang and Clarke, 2003). LUCC models exhibit more or less ability to simulate a wide diversity of futures due to their design and architecture, especially those that are path-dependent  (Brown et al. 2005). Whatever the approach adopted, the question of model's validation is crucial when combined with scenarios. While the model's calibration allows to validate the simulated outcomes under a path-dependent approach, the question remains for the SAS approach: how can we validate such a model although the calibration may constrain its ability to explore a wider range of futures? The objective of this paper is twofold: (1) to present an urban growth simulation model, derived from the SLEUTH modeling framework, specifically dedicated to simulating contrasting / breaking trends scenarios accordingly to the "storyline and simulation" approach; (2) to propose a validation framework aiming at demonstrating the ability of the model to simulate such kind of scenarios according to  Houet (2015).
We assume it goes beyond conventional validation procedures by focusing on assessing the model's ability to simulate observed changes as well as contrasted -and potentially unrealistic -futures. The first part of the paper (section 2) exposes the reason why the SLEUTH* model has been developed. It proposes a review of modeling techniques usually combined with scenarios and claims for the need for "non path-dependent models" when the SAS approach is adopted. Then, it presents the SLEUTH experience and challenges. The second part (section 3) lists the materials and methods: it describes the study area, input data and the SLEUTH* model. Section 4 focuses on the validation experiments and results to validate the model's ability to simulate contrasting / breaking trends scenarios. Section 5 illustrates an application of SLEUTH* to explore futures based on three contrasting scenarios.
Secondly, a non path-dependent approach assumes that LUCC models are used to spatially explicitly render a set of pre-defined contrasted scenarios. They are inherently used within the SAS approach. Path-dependent models can be used within the SAS approach as well. In this case, the parameterization of the future land demand does not depend on input maps used to calibrate the future amount of changes. Some studies illustrate this approach (e. g. Price et al, 2014; Verburg et al, 2008)  as the land demand is defined by narratives and/or economic model outcomes. However, this kind of models use suitability maps to allocate future changes that are defined by comparing past changes (occurred during the period covered by these two input maps for instance) with spatially explicit drivers (such as the elevation, the slope, or the distance from a land cover) using statistical method.
Hence, considering that these kinds of scenarios are deliberately imaginative, some of these models may have computational limitations for simulating various types of scenarios as they were simply not initially developed for that purpose. Moreover, the urban system under study will not remain stationary over time. New driving forces may affect the quantity, types, location and/or the patterns of LUCC. Some of the previously cited models may be used in such an approach since the land demand and/ or the suitability maps are from scenarios or models' outcomes. Nevertheless, the theoretical distinction between SAS vs. path-dependent approaches remains unclear when path-dependent models are used within a SAS approach. Their calibration is made using historical land use and land cover maps to define LUCC transition rules and inherently assume the system to be stationary.
Finally, some existing LUCC models have inherent constraints that prevent them from simulating future contrasted scenarios that assume or create a 'break' with the past or current trend  (Mas et al. , 2014). Path-dependent and SAS approaches illustrate two ways in which scenarios can be produced and implemented  (Marchadier et al. , 2012). In the first case, scenarios are inherited from a numerical -quantitative -modeling approach with prescribed rules for producing simulated cities. In the second case, scenarios are based on a narrative -qualitative -approach producing imagined cities. Approaches combining both narrative and model approaches for building scenarios are not so common whereas they are fundamental to land-use planning  (Xiang and Clarke, 2003). Moreover, the use of models adds value to qualitative prospective studies  (Kok et al.
How SLEUTH works has been summarized by  Clarke (2008)  and is presented in the following box (box 1). Putting aside its international recognition, we selected SLEUTH for four reasons: • the open-source code allows it to be modified for a non path-dependent approach (http:// www. ncgia. ucsb. edu/projects/gig/); • the availability of experiences and feedbacks that have explored the model and its use  (Clarke et al, 2007; Clarke, 2008; Chaudhuri and Clarke, 2013 ); • its reliability with regard to environmental and participatory issues, due to its relative simplicity and pattern-based characteristics  (Suarez-Rubio et al. , 2012) ; • its capabilities to simulate various urban growth patterns and emergent phenomena  (Silva and Clarke 2005). Box 1: Summary of the SLEUTH's functioning. SLEUTH is a model for the computational simulation of urban growth and the land use changes that are caused by urbanization.
The calibration phase is critical and delicate as it strongly depends on the historical maps used and their resolution. Calibration has constituted one of the main issues of previous works. It has been considerably improved using efficient algorithms and methods  (Goldstein 2004a)  that challenged the computation time initially required and the refinement of model parameters that replicate the best historical changes (Dietzle and  Clarke 2004 ). Moreover, it has been shown that refining spatial resolution increases model sensitivity to local conditions  (Silva and Clarke 2002). SLEUTH is a robust model largely explored through sensitivity tests  (Candau 2002; Dietzle and Clarke 2004; Goldstein et al 2005). Unresolved issues and problems have been highlighted by  Clarke (2008). Details on algorithms and parameters used are presented in the tutorial provided with the SLEUTH* software.
However, the aim was to assess model performance using similar parameters values that can be derived from various simple -GIS, expert-based or scenario-based -approaches as shown with the other two experiments. The second point, which is closely related to the first one, concerns the various ways that SLEUTH* can be used. The SAS approach requires it to be simple and flexible when used within a participatory framework, as well as sophisticated when tightly coupled with other models. Hence, even if some parameters are empirically calibrated, the resulting simulations still provide valuable urban maps. Indeed, the experience of the ACCLIMAT project shows that results for the simulation of a past evolution were sufficient to improve the confidence that stakeholders have in SLEUTH*'s ability to simulate (future) urban changes  (Masson et al.
Contexte Parmi les outils donnant lieu à des analyses de visibilité du paysage, on observe une nette opposition entre (1) les SIG grand public -commerciaux ou libres -qui offrent une prise en main souvent simple mais présentent des fonctionnalités restreintes, et (2) les programmes « prototype » aux paramétrages plus avancés, développés au sein de laboratoires de recherche, mais qui restent cependant confidentiels et très peu diffusés à un large public. Dans le cas des logiciels grand public, Idrisi a très tôt été utilisé pour la réalisation d'analyses de visibilité, initialement pour la réalisation de bassins de visibilité (viewsheds)  (Fisher, 1992) , ou plus récemment pour l'étude d'impacts visuels d'aménagements  (Falconer, Hunter, Telfer, & Ross, 2013). Cependant, la majorité des travaux ayant recours aux analyses de visibilité utilisent les fonctionnalités d'ArcGIS, que ce soit pour déterminer l'impact visuel d'aménagements  (Mouflis, Gitas, Iliadou, & Mitri, 2008) , la prégnance visuelle d'éléments bâtis  (Rød & van der Meer, 2009) , ou pour évaluer la qualité esthétique du paysage visible  (Palmer, 2004; Schirpke, Tasser, & Tappeiner, 2013).
Certains travaux en archéologie utilisent également ArcGIS dans l'objectif de constituer des modèles d'intervisibilité, par le cumul de viewsheds  (Sevenant & Antrop, 2007)  ou par la réalisation de graphes de visibilité (De  Montis & Caschili, 2012). D'autres SIG commerciaux (par exemple MapInfo Vertical Mapper, Geoconcept 3D, ENVI ou ERDAS) produisent également des analyses de visibilité, en n'offrant cependant que certaines fonctionnalités basiques. De manière analogue, parmi les logiciels SIG libres, OpenJump, Saga GIS, Geoserver, Open Layers ou TNTmips offrent également certaines fonctionnalités restreintes. C'est aussi le cas de certaines fonctions associées à Qgis et Grass, comme le module r. los 2 , le programme r. cva 3 , ou plus récemment le module viewshed analysis 4. L'ensemble de ces outils SIG sont cependant limités au calcul de viewsheds.
PixScape -un outil logiciel intégré pour l'analyse du paysage visible Cybergeo : European Journal of Geography , GeOpenMod -Modèles et logiciels 7 PixScape est un outil logiciel développé au Laboratoire ThéMA à Besançon, conçu pour la modélisation du paysage visible à partir de données spatiales numériques et pour le calcul d'un grand nombre d'indicateurs paysagers. Il s'appuie en partie sur les précédents développement de Daniel Joly, utilisés dans le cadre de plusieurs travaux de recherche  (Brossard, Joly, & Tourneux, 2008; Cavailhès et al. , 2009; Joly, Brossard, & Cavailhès, 2009)  mais peu diffusés au reste de la communauté scientifique. La version 1. 0 est disponible en téléchargement sur https://sourcesup. renater. fr/pixscape/fr. html. Un manuel d'utilisation, un jeu de données test ainsi que le code source sont disponibles en ligne.
8 Par rapport aux outils existants, le logiciel PixScape 1. 0 a été conçu comme un outil intégré, qui regroupe les fonctionnalités disponibles dans les outils SIG standards afin de faciliter l'ensemble de la chaîne de traitement des analyses de visibilité, depuis l'importation des données spatiales numériques jusqu'au calcul de métriques paysagères. De plus, il intègre un ensemble de paramètres de calculs de visibilité spécifiques et propose des métriques originales. Ce logiciel offre également l'avantage d'être diffusé en open source. Il s'adresse à un public habitué à l'utilisation des outils SIG, étudiants ou chercheurs, mais également collectivités locales et bureaux d'étude concernés par l'évaluation des paysages. 9 D'un point de vue informatique, PixScape 1. 0 est développé en Java version 1.