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595 results for “expectation”
French wine dataset to mapping the expected harvest value by county
<p>This database is built from open data as described in the paper entitled ‘French wine: Combination of multiple open data sources to mapping the expected harvest value’ (2024).</p> <table> <tbody> <tr> <td> <p>CODE_CULTU</p> </td> <td> <p><strong>Crop code of the graphic land registry database </strong></p> </td> </tr> <tr> <td> <p>CodeCdC</p> </td> <td> <p><strong>Crop code in Multi Perils Crop Insurance specification </strong></p> </td> </tr> <tr> <td> <p>Harvest Value B</p> </td> <td> <p><strong>Harvest value (€/ha organic wine)</strong></p> </td> </tr> <tr> <td> <p>Harvest Value C</p> </td> <td> <p><strong>Harvest value (€/ha no-organic wine)</strong></p> </td> </tr> <tr> <td> <p>IDA</p> </td> <td> <p><strong>ID of geographical areas of INAO</strong></p> </td> </tr> <tr> <td> <p>Insee_Com</p> </td> <td> <p><strong>County code (INSEE)</strong></p> </td> </tr> <tr> <td> <p>Label_CdC</p> </td> <td> <p><strong>Crop label in Multi Perils Crop Insurance specification </strong></p> </td> </tr> <tr> <td> <p>Label_Dpt</p> </td> <td> <p><strong>Department</strong></p> </td> </tr> <tr> <td> <p>Label_Insee_com</p> </td> <td> <p><strong>County</strong></p> </td> </tr> <tr> <td> <p>Label_RA</p> </td> <td> <p><strong>Agricultural Region (AGRESTE)</strong></p> </td> </tr> <tr> <td> <p>Label_appellation</p> </td> <td> <p><strong>Appellation (INAO)</strong></p> </td> </tr> <tr> <td> <p>Label_code3</p> </td> <td> <p><strong>Crop (FADN)</strong></p> </td> </tr> <tr> <td> <p>Label_cvi</p> </td> <td> <p><strong>Wine name (vineyard register of customs services) </strong></p> </td> </tr> <tr> <td> <p>Label_idGeo</p> </td> <td> <p><strong>Geographical ID of Quality Sign (INAO)</strong></p> </td> </tr> <tr> <td> <p>PxBaremAOP</p> </td> <td> <p><strong>Price listed in Multi Perils Crop Insurance specification (€/hl no-organic) </strong></p> </td> </tr> <tr> <td> <p>PxBaremAOPBio</p> </td> <td> <p><strong>Price listed in Multi Perils Crop Insurance specification (€/hl organic) </strong></p> </td> </tr> <tr> <td> <p>RdtMOAOP</p> </td> <td> <p><strong>Harvest wine yield (hl/ha)</strong></p> </td> </tr> <tr> <td> <p>SurfaceModel</p> </td> <td> <p><strong>Surface of wine as fitted by model</strong></p> </td> </tr> <tr> <td> <p>code3</p> </td> <td> <p><strong>Crop code (FADN)</strong></p> </td> </tr> <tr> <td> <p>code_dept</p> </td> <td> <p><strong>Department code</strong></p> </td> </tr> <tr> <td> <p>code_regag</p> </td> <td> <p><strong>Code of Agricultural Region (AGRESTE)</strong></p> </td> </tr> <tr> <td> <p>cvi</p> </td> <td> <p><strong>Wine code (vineyard register of customs services)</strong></p> </td> </tr> <tr> <td> <p>id_appellation</p> </td> <td> <p><strong>Appellation code (INAO)</strong></p> </td> </tr> <tr> <td> <p>id_denomination_geo</p> </td> <td> <p><strong>Geographical ID of Quality Sign (INAO)</strong></p> </td> </tr> </tbody> </table> <p> </p> <p>Find here the relative research paper :</p> <p><a href="https://univ-lemans.hal.science/hal-04627672">https://univ-lemans.hal.science/hal-04627672</a></p> <p>Please find below the list of the sites where used data could be found (lasted view the June 26, 2024).</p> <p><a href="https://agreste.agriculture.gouv.fr/agreste-web/methodon/Z.1/!searchurl/listeTypeMethodon/">https://agreste.agriculture.gouv.fr/agreste-web/methodon/Z.1/!searchurl/listeTypeMethodon/</a></p> <p><a href="https://www.casd.eu/source/reseau-dinformation-comptable-agricole/?tab=16">https://www.casd.eu/source/reseau-dinformation-comptable-agricole/?tab=16</a></p> <p><a href="https://www.douane.gouv.fr/la-douane/opendata?f%5B0%5D=categorie_opendata_facet%3A467">https://www.douane.gouv.fr/la-douane/opendata?f%5B0%5D=categorie_opendata_facet%3A467</a></p> <p><a href="http://www.inao.gouv.fr">www.inao.gouv.fr</a></p> <p><a href="https://www.data.gouv.fr/fr/datasets/?q=inao">https://www.data.gouv.fr/fr/datasets/?q=inao</a></p> <p><a href="https://maisons-champagne.com/fr/appellation/aire-geographique/">https://maisons-champagne.com/fr/appellation/aire-geographique/</a></p> <p><a href="https://info.agriculture.gouv.fr/boagri/document_administratif-4b9ef75e-29a7-449d-9e40-7e5253bfd642/telechargement">https://info.agriculture.gouv.fr/boagri/document_administratif-4b9ef75e-29a7-449d-9e40-7e5253bfd642/telechargement</a></p> <p><a href="https://agreste.agriculture.gouv.fr/agreste-web/download/publication/publie/Dos2203/2Pages%20de%20Dossier2022-3_CCAN_ChapitreII.pdf">https://agreste.agriculture.gouv.fr/agreste-web/download/publication/publie/Dos2203/2Pages%20de%20Dossier2022-3_CCAN_ChapitreII.pdf</a></p>
Figure 5 in How long do dolphins live? Survival rates and life expectancies for bottlenose dolphins in zoological facilities ťs. wild populations
Figure 5. Kaplan-Meier survival curves depicting the proportion of bottlenose dolphins in zoological care surviving to each age (calculated in days, then transformed to years) during four time periods.
Figure 2 in How long do dolphins live? Survival rates and life expectancies for bottlenose dolphins in zoological facilities ťs. wild populations
Figure 2. ASR (95% confidence intervals) of bottlenose dolphin calves <1 yr old in zoological care across historical time periods.
Figure 4 in How long do dolphins live? Survival rates and life expectancies for bottlenose dolphins in zoological facilities ťs. wild populations
Figure 4. The population age structure for bottlenose dolphins in zoological care on the last day of each time period.
Figure 3 in How long do dolphins live? Survival rates and life expectancies for bottlenose dolphins in zoological facilities ťs. wild populations
Figure 3. Survivorship to each age as calculated for age-at-death data for modern-day dolphins in zoological care and two wild populations.
Figure 1 in How long do dolphins live? Survival rates and life expectancies for bottlenose dolphins in zoological facilities ťs. wild populations
Figure 1. ASR (95% confidence intervals) of bottlenose dolphins>1 yr old in zoological care across historical time periods.
Fig. 3 in Avian Assemblages in Forest Fragments do not Sum to the Expected Regional Community in the Brazilian Atlantic Forest.
Fig. 3. The number of local Atlantic Forest species by forest fragment size (log10 scales), showing that the number increases with fragment size (F = 13.4, r2 = 0.625, p = 0.0065).
Fig. 2 in Avian Assemblages in Forest Fragments do not Sum to the Expected Regional Community in the Brazilian Atlantic Forest.
Fig. 2. Numbers of species and similarities (PCoA) among the 10 Atlantic Forest fragments in southern Bahia, Brazil. A) Species accumulation curves, illustrating that with over 5000 sightings, the predicted total number of species had not been reached in any fragment, or in all fragments combined. Also, the similarity of the curves and their lack of a relationship with fragment size suggests that all fragments are similar with respect to accumulation of species. Note that both axes are log10 scaled. B) Principal Coordinate Analysis, using Bray similarities, illustrating that similarity among fragments was always low. Larger symbols indicate fragment centroids, and each smaller point indicates a sample list of species (see text). No particular pattern is evident, and all fragments are variable and do not form groups based on fragment size.
Fig. 4 in Avian Assemblages in Forest Fragments do not Sum to the Expected Regional Community in the Brazilian Atlantic Forest.
Fig. 4. Functional diversity analysis comparing different-sized fragments and functional evenness, dispersion, and divergence. A–C: Black squares and lines indicate the Atlantic Forest expected regional assemblage, circles and lines indicate the observed assemblages, with blue indicated only the Atlantic Forest species, and the open circle indicates all observed species (all based on presence-absence). D–F: estimated from presence-absence data of the expected local assemblage that were absent from the fragment. Regression results are presented in table 3.
Data set for the PLOS ONE paper Expecto transitio: Exploring non-experts' techno-economic expectations of the energy future
<p>Raw data file (SPSS and .cv versions) consisting of all data used for the Plos One publication.</p> <p> </p>
data for the PCI publication "New insights into the population genetics of partially clonal organisms: when seagrass data meet theoretical expectations"
<p><strong>Data analyzed int he article "New insights into the population genetics of partially clonal organisms: when seagrass data meet theoretical expectations", doi </strong> <a href="https://arxiv.org/abs/1902.10240v5">https://arxiv.org/abs/1902.10240v5</a> <strong> doi of the PCI recommandation: </strong>https://doi.org/10.24072/pci.evolbiol.100083</p>
Fig. 5 in The Alvarez impact theory of mass extinction; limits to its applicability and the "great expectations syndrome"
Fig. 5. Evolving timing of the multi−ring Woodleigh impact structure, manifested in purported causal connection with the P–T and F–F mass extinctions, as a reflection of variously dated processes. Age constraints still range from post−Middle Devonian to pre−Early Jurassic, but the connection with the D–C global event seems to be most likely (Glikson et al. 2005).
Fig. 4 in The Alvarez impact theory of mass extinction; limits to its applicability and the "great expectations syndrome"
Fig. 4. Evolving timing of the Siljan Ring (53 km diameter; see Fig. 2), depending on different timescales and improved radiometric dates.
Fig. 3 in The Alvarez impact theory of mass extinction; limits to its applicability and the "great expectations syndrome"
Fig. 3. Extraterrestrial elemental proxy Ir, and supplementary Ni, against other geochemical markers in the F–F boundary beds at Kowala, Holy Cross Mountains (after Racki et al. 2002: fig. 8; used with permission from Elsevier); Ir values from an unpublished report (dated 2004) by Yuichi Hatsukawa and Mohammad Mahmudy Gharaie; Ni contents from Racka (1999: table 2); for other data see references in Racki et al. (2011).
Fig. 2 in The Alvarez impact theory of mass extinction; limits to its applicability and the "great expectations syndrome"
Fig. 2. Crater temporal distribution, with possible record at the F–F boundary (A), plotted against Devonian biodiversity losses in terms of substages (B), data from Bambach 2006: fig. 1 (used with permission from the Annual Review of Earth and Planetary Sciences, Volume 34 © 2006 by Annual Reviews, http://www.annualreviews.org.), re−arranged according to the timescale of Kaufman (2006; see the updated tiiming in Becker et al. 2012; Fig. 4); the reconstructed middle Frasnian Alamo crater is also shown to reveal low biodiversity loss in that time (arrowed), as well as the controversial Woodleigh impact structure (see Fig. 5) and the biostratigraphically dated Flynn Creek submarine crater (Schieber and Over 2005). Vertical lines correspond to possible temporal ranges. Abbreviations: Carb., Carboniferous; Givet., Givetian; Lochk., Lochkovian; Prag., Pragian; Silur, Silurian.
Fig. 1 in The Alvarez impact theory of mass extinction; limits to its applicability and the "great expectations syndrome"
Fig. 1. Scheme of the three successive levels in the testing process, encompassing application of the Alvarez impact theory of mass extinction, and possible errors resulting from the "great expectations syndrome" (sensu Tsujita 2001).
Fig. 6 in The Alvarez impact theory of mass extinction; limits to its applicability and the "great expectations syndrome"
Fig. 6. The Late Triassic cratering record plotted against extinction events (based on Lucas and Tanner 2008: fig. 8; crater dates modified after Schmieder and Buchner 2008 and Martin Schmieder personal communication, 2011) and two alternative time scales. Note that the 100 km−sized and precisely dated Manicouagan crater (214.56±0.05 Ma; see ottawa−rasc.ca/wiki/index.php?title=Odale−Articles− Manicouagan) is within the age range of the end−Carnian extinction only in the ICS 2009 geochronologic scheme (see also Lucas et al. 2012). Carbon isotope events compiled from Tanner (2010) and Ruhl and Kürschner (2011: fig.1). Vertical lines correspond to possible temporal ranges. J., Jurassic.
FIGURE 10 in Three decades of Chondrichthyan research in Brazil assessed from conferences' abstracts: patterns, gaps, and expectations
FIGURE 10 | Funnel representing the total number of abstracts with Chondrichthyes, the proportion of studies with Evolution within those, the proportion of Systematics, and the final proportion of women acting as last authors (WLA) in Chondrichthyan Systematics. The "leaking pipeline" is demonstrated by the reasons women might be leaving academia in the right side of the image. ECO, Ecology; EVO, Evolution; PHY, Physiology.
FIGURE 9 in Three decades of Chondrichthyan research in Brazil assessed from conferences' abstracts: patterns, gaps, and expectations
FIGURE 9 | Proportion of abstracts with each Chondrichthyan order and proportion of studies by research area: ECO, Ecology; EVO, Evolution; PHY, Physiology. The percentage might be higher than 100% since some abstracts were counted twice as they dealt with more than one order.
FIGURE 6 in Three decades of Chondrichthyan research in Brazil assessed from conferences' abstracts: patterns, gaps, and expectations
FIGURE 6 | Proportion of each research area and most studied Chondrichthyan orders by Brazilian region. Green, Northern (N); brown, Northeastern (NE); red, Midwestern (M); orange, Southeastern (SE); blue, Southern (S). Upper graph at the right of each region representing research areas: ECO, Ecology; EVO, Evolution; PHY, Physiology. Lower graph at the right of each region representing Chondrichthyan orders: CAR, Carcharhiniformes; MYL, Myliobatiformes; RAJ, Rajiformes; Other*, other orders.
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