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6,014 results for “fossil”
CoCO2-MOSAIC 1.0: a global mosaic of regional, gridded, fossil and biofuel CO2 emission inventories
<p>CoCO2-MOSAIC 1.0 is a global mosaic of regional bottom-up inventories of anthropogenic CO2 emissions developed in the framework of the CoCO2 project (<a href="https://coco2-project.eu/">https://coco2-project.eu/</a>). CoCO2-MOSAIC 1.0 provides gridded (0.1˚×0.1˚) monthly emissions fluxes of CO2 fossil fuel (CO2ff, long cycle) and CO2 biofuel (CO2bf, short cycle) for the years 2015 to 2018 disaggregated in seven sectors: energy_s (super-emitting sources above 7.9e-6 kg/m2/s), energy_a (average emitters), manufacturing, settlements, transport, aviation land/take-off (LTO) and other. The regional inventories included are CAMS-GHG-REG 5.1 (Europe), DACCIWA 2.0 (Africa), GEAA-AEI 3.0 (Argentina), INEMA 1.0 (Chile), REAS 3.2.1 (South-East Asia) and VULCAN 3.0 (USA). EDGAR 6.0 and CAMS-GLOB-SHIP 3.1 are used for gap-filling missing sectors and regions. CAMS-GLOB-TEMPO 3.1 is used for temporal disaggregation of inventories providing annual emissions. Aviation emissions from climb, descent, and cruise are not covered by regional inventories and are provided as a separate file. Note that 2015 is the only year when all regional inventories are simultaneously available. </p> <p>Compared to global inventories, CoCO2-MOSAIC 1.0 includes all the regional information available without the limitation of providing spatially consistent emissions. Therefore, CoCO2-MOSAIC 1.0 can be used as a global baseline inventory due to the higher level of detail, higher spatial resolution, and country-specific information included by regional inventories. </p> <p>For further details see Urraca et al. 2023 (ESSD submitted). The paper (i) describes the CoCO2-MOSAIC methodology and (ii) uses the mosaic to inter-compare the most widely used global inventories: CAMS-GLOB-ANT 5.3, EDGAR 6.0/7.0, ODIAC v2020b, and CEDS v2020_04_24.</p>
Figure data and model used in Stranded fossil-fuel assets translate to major losses for investors in advanced economies
<p>The package contains i) the figure code and underlying data to create all figures in the main paper and supplementary information of the journal article and ii) the network and imputation model used to calculate the shock calculation.</p>
Gridded fossil CO2 emissions and related O2 combustion consistent with national inventories
<p><strong>Data Access Notice</strong></p> <p>Please note that, at present, the data for a sample of years are provided in this data record due to Zenodo's 50GB data limit. Data for all years 1959-2023 can be accessed via the following link:</p> <p><a href="http://opendap.uea.ac.uk/opendap/hyrax/greenocean/GridFED/GridFEDv2024.0/contents.html">http://opendap.uea.ac.uk/opendap/hyrax/greenocean/GridFED/GridFEDv2024.0/contents.html</a></p> <p><strong>Product Description</strong></p> <p>See Jones et al. (2021) for a detailed description of this dataset and the core methods used to produce it. Key details are provided below.</p> <p>GCP-GridFED (version 2024.0) is a gridded fossil emissions dataset that is consistent with the national CO<sub>2</sub> emissions reported by the Global Carbon Project (GCP; <a href="https://www.globalcarbonproject.org/">https://www.globalcarbonproject.org/</a>) in the annual editions of its Global Carbon Budget (Friedlingstein et al., 2023).</p> <p>GCP-GridFEDv2024.0 provides monthly fossil CO<sub>2 </sub>emissions for the period 1959-2023 at a spatial resolution of 0.1° × 0.1°. The gridded emissions estimates are provided separately for fossil CO<sub>2</sub> emitted by the oxidation of oil, coal and natural gas, international bunkers, and the calcination of limestone during cement production. The dataset also includes the cement carbonation sink of CO<sub>2</sub>. Note that positive values in GridFED signify a surface-to-atmosphere CO<sub>2 </sub>flux (emissions). Negative values signify an atmosphere-to-surface flux and apply only to the cement carbonation sink.</p> <p>GCP-GridFED also includes gridded uncertainties in CO<sub>2 </sub>emission, incorporating differences in uncertainty across emissions sectors and countries, and gridded estimates of corresponding O<sub>2</sub> uptake based on oxidative ratios for oil, coal and natural gas (see Jones et al., 2021).</p> <p><strong>Core Methodology in Brief</strong></p> <p>GCP-GridFEDv2024.0 was produced by scaling monthly gridded emissions for the year 2010, from the Emissions Database for Global Atmospheric Research (EDGAR v4.3.2; Janssens-Maenhout et al., 2019), to the national annual emissions estimates compiled as part of the 2024 global carbon budget (GCP-NAE) for the years 1959-2023 (Friedlingstein et al., 2024). </p> <p>GCP-GridFEDv2024.0 uses a preliminary release of GCP-NAE covering the years 1959-2023 (timestamp 1st August 2024; an update from Andrew and Peters [2023]). The GCP-NAE estimates for year 2023 are based on data available at the timestamp and the estimates are thus expected to differ somewhat from those that will be presented by Friedlingstein et al. (2024), which will adopt updates to GCP-NAE since the timestamp.</p> <p>For full details of the core methodology, see Jones et al. (2021).</p> <p><strong>Changes to the Seasonality of Emissions in GCP-GridFEDv2022.2 onwards</strong></p> <p>The seasonality of emissions (monthly distribution of annual emissions) for the following countries/sources is now based on the seasonality observed in the Carbon Monitor dataset (Liu et al., 2020; Dou et al., 2022): </p> <ul> <li>Austria, Belgium, Brazil, Bulgaria, China, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, India, Ireland, Italy, Japan, Latvia, Lithuania, Luxembourg, Malta, Netherlands, Poland, Portugal, Romania, Russia, Slovakia, Slovenia, Spain, Sweden, United Kingdom, United States.</li> <li>State or province-level data is used for Brazil, China, Russia, and the United States.</li> <li>This also applies for the Bunker Aviation and Bunker Shipping sectors.</li> </ul> <p>Seasonality is determined in the following ways for those countries/sources:</p> <ul> <li>The seasonality of emissions in 2019-2023 is taken from Carbon Monitor.</li> <li>The seasonality of emissions in all years prior to 2019 is assigned as the average of the seasonality from Carbon Monitor in all years excluding 2020 (due to the impact of COVID-19 on the seasonality of emissions in 2020).</li> </ul> <p>For all countries not listed above and all years 1959-2023, GCP-GridFED adopts the seasonality from EDGAR v4.3.2 (year 2010; Janssens-Maenhout et al., 2019) and applies a small correction based on heating/cooling degree days to account for inter-annual climate variability which effects emissions in some sectors (see Jones et al., 2021).</p> <p><strong>Other New Features of GCP-GridFEDv2024.0</strong></p> <ul> <li>There have been no changes to the functionality of the GridFED code in this update versus the previous update (v2023.1).</li> </ul> <p> </p>
The Global Carbon Project's fossil CO2 emissions dataset
<p>The <a href="https://www.globalcarbonproject.org/">Global Carbon Project</a> (GCP) has been publishing estimates of global and national fossil CO2 emissions since 2001. In the first instance these were simple re-publications of data from another source, but over subsequent years refinements have been made in response to feedback and identification of inaccuracies. In this article (PDF document) we describe the history of this process leading up to the methodology used in the 2025 release of the GCP's fossil CO2 dataset.</p> <p>The fossil CO2 emissions dataset is included in both its standard, absolute form, and per capita, with associated metadata files in JSON format. A file indicating the source(s) of each data point is also provided.</p> <p>This is the initial release of the 2025 dataset.</p>
Hybridization of Fossil- and CO2-Based Routes for Ethylene Production using Renewable Energy
<p>Dataset associated with the publication "Hybridization of Fossil- and CO<sub>2</sub>-Based Routes for Ethylene Production using Renewable Energy" by Iasonas Ioannou, Sebastiano C. D'Angelo, Antonio J. Martín, Javier Pérez-Ramírez, and Gonzalo Guillén-Gosálbez, available at <a href="https://doi.org/10.1002/cssc.202001312">https://doi.org/10.1002/cssc.202001312</a>. The dataset includes the numeric data associated with most of the scenarios described in the main manuscript and in the Supporting Information (SI), as well as the tables presented in the main manuscript and in the SI converted in a machine-readable format.</p> <p>The structure of the dataset is here elucidated sheet by sheet:</p> <ul> <li><strong>MS-Results</strong>: numerical values associated with the economic and environmental results included in both the main manuscript and the SI, for all the considered scenarios. The results include the total price for the assessed scenarios, with and without externalities, with uncertainty ranges, as well as the environmental results for human health, ecosystems, resources, and global warming potential (GWP).</li> <li><strong>MS-Tables</strong>: table reported in the main manuscript associated with the price and breakeven point of four assessed scenarios dependent on different CO<sub>2</sub> source assumptions.</li> <li><strong>SI-Tables-Economics</strong>: tables reported in the SI associated with the economic assessment of all the scenarios.</li> <li><strong>SI-Tables-LCI</strong>: tables reported in the SI associated with the environmental assessment of all the scenarios.</li> <li><strong>SI-Tables-AdditionalResults</strong>: tables reported in the SI associated with additional results presented in the work.</li> </ul>
Supplementary videos for "A second fossil species of the enigmatic rove beetle genus Charhyphus in Eocene Baltic amber, with implications on the morphology of the female genitalia (Coleoptera: Staphylinidae: Phloeocharinae)"
<p><strong>Original figures used in this study:</strong></p> <p>The holotype of <em>Charhyphus serratus </em>sp. nov. and four extant <em>Charhyphus </em>species.</p> <p> </p> <p><strong>Supplementary Videos 1–3:</strong></p> <p><strong>Supplementary Videos 1</strong> <em>Charhyphus serratus </em>sp. nov., 001 DUBC, holotype, habitus, movie of X-ray micro-CT volume renderings.</p> <p><strong>Supplementary Videos 2</strong> <em>Charhyphus serratus </em>sp. nov., 001 DUBC, holotype, habitus, movie of X-ray micro-CT volume renderings using different parameters from Supplementary Videos 1.</p> <p><strong>Supplementary Videos 3</strong> <em>Charhyphus serratus </em>sp. nov., 001 DUBC, holotype, female genitalia, movie of X-ray micro-CT volume renderings.</p>
Data for article: A quantitative framework to infer the effect of traits, diversity and environment on dispersal and extinction rates from fossils
<p>Supplementary information for:</p> <p><strong>A quantitative framework to infer the effect of traits, diversity and environment on dispersal and extinction rates from fossils</strong></p> <p>Torsten Hauffe, Mathias M. Pires, Tiago B. Quental, Thomas Wilke, and Daniele Silvestro</p> <p> </p><ul> <li> Simulations <ul> <li>Scripts <ul> <li>Scenario1_SamplingHeterogeneity.R: Script to simulate biogeographic histories with sampling heterogeneity</li> <li>Scenario3_SealevelInvasion.R: Script to simulate biogeographic histories where sea level facilitates dispersal and invasion induces extinction</li> <li>Scenario3_DiversityDependence.R: Script to simulate diversity-dependent biogeographic histories</li> <li>Scenario4_TraitDependence.R: Script to simulate trait-dependent biogeographic histories</li> <li>Scenario5_CategoricalTraitDependence.R: Script to simulate trait-dependent biogeographic histories</li> </ul> </li> <li>Results <ul> <li>Scenario1_SamplingHeterogenetiy_alpha05.txt: Results of simulations scenario 1 with a sampling heterogeneity of alpha = 0.5</li> <li>Scenario1_SamplingHeterogenetiy_alpha1.txt: Results of simulations scenario 1 with a sampling heterogeneity of alpha = 1</li> <li>Scenario1_SamplingHeterogenetiy_alpha2.txt: Results of simulations scenario 1 with a sampling heterogeneity of alpha = 2</li> <li>Scenario1_SamplingHeterogenetiy_alpha10.txt: Results of simulations scenario 1 with a sampling heterogeneity of alpha = 10</li> <li>Scenario2_Independent_dispersal_and_extinction.txt: Results of simulation scenario 2 with sea-level independent dispersal and no invasion induced extinction</li> <li>Scenario2_Sealevel_dependent_dispersal_and_independent_extinction.txt: Results of simulation scenario 2 with sea-level dependent dispersal and no invasion induced extinction</li> <li>Scenario2_Sealevel_independent_dispersal_and_invasion_induced_extinction.txt: Results of simulation scenario 2 with sea-level independent dispersal and invasion induced extinction</li> <li>Scenario2_Sealevel_dependent_dispersal_and_invasion_induced_extinction.txt: Results of simulation scenario 2 with sea-level dependent dispersal and invasion induced extinction</li> <li>Scenario3_Independent_dispersal_and_extinction.txt: Results of simulations scenario 3 with diversity-independent dispersal and extinction</li> <li>Scenario3_Diversity_dependent_dispersal_and_independent_extinction.txt: Results of simulations scenario 3 with diversity-dependent dispersal and diversity-independent extinction</li> <li>Scenario3_Independent_dispersal_and_Diversity_dependent_extinction.txt: Results of simulations scenario 3 with diversity-dependent dispersal and diversity-independent extinction</li> <li>Scenario3_Diversity_dependent_dispersal_and_extinction.txt: Results of simulations scenario 3 with diversity-dependent dispersal and extinction</li> <li>Scenario4_Independent_dispersal_and_extinction.txt: Results of scenario 4 with trait-independent dispersal and extinction</li> <li>Scenario4_Trait_dependent_dispersal_and_independent_extinction.txt: Results of scenario 4 with trait-dependent dispersal and independent extinction</li> <li>Scenario4_Independent_dispersal_and_trait_dependent_extinction.txt: Results of scenario 4 with independent dispersal and trait-dependent extinction</li> <li>Scenario4_trait_dependent_dispersal_and_extinction.txt: Results of scenario 4 with trait-dependent dispersal and extinction</li> <li>Scenario5_CatTrait_dependent_dispersal_and_independent_extinction.txt: Results of model 2 with categorical traits (e.g family) influence dispersal but no influence of a category-specific continuous traits</li> </ul> </li> </ul> </li> <li>Carnivora <ul> <li>BinnedOccurrence: Folder with 100 replicates of binned occurrences of max. 330 carnivoran genera throughout the Neogene</li> <li>BodyMass: Folder with 100 replicates of body mass for 330 carnivoran genera</li> <li>Sealevel: Folder with sea level through the Neogene</li> <li>Temperature: Folder with the temperature record of the Neogene</li> <li>Families: Folder with families as taxonomic proxy for phylogeny. FamilyGeneraNumeric.txt is the numeric coding used for the Bayesian analyses of carnivoran biogeography</li> </ul> </li> </ul> <p></p>
Sub-fossil crustacean zooplankton relative abundances from 101 lakes across Canada
<p>This data set contains cladoceran sub-fossil relative abundances for 101 lakes across Canada sampled as part of the NSERC Canadian Lake Pulse Network project. Lakes were sampled once, over three summers (2017-2018-2019). Cores were collected using a gravity corer in the deepest point of each lake and were sectioned on site with a vertical extruder. Each lake was sampled for a “top” sediment sample, represented by the first centimeter of the surface of the sediment core, and a “bottom” sediment sample, corresponding to the 1 cm of sediment located between 3 and 4 cm from the base of the core. Cladoceran extraction and preparation followed the protocol from Korhola and Rautio (2001). Cladocerans were identified using DM 2500 Leica compound inverted microscope under 200X-400X magnification with a minimal count size of 100 individuals. Identification at the species, genus, or species complex level followed Szeroczynska and Sarmaja-Korjonen (2007) and Korosi and Smol (2012a; b).</p> <p>Sites are identified with Lake ID number, followed by “T” for top samples and “B” for bottom samples. Lakes IDs with respective locations (longitude and latitude coordinates) and Continental Basin allocations can be found here: <a href="https://doi.org/10.5281/zenodo.4701262">https://doi.org/10.5281/zenodo.4701262</a></p> <p>References</p> <p>Korhola, A., and M. Rautio. 2001. Cladocera and other branchiopod crustaceans, p. 225–234. <em>In</em> J.P. Smol, H.J.B. Birks, and W.M. Last [eds.], Tracking Environmental Change Using Lake Sediments. Springer.</p> <p>Korosi, J. B., and J. P. Smol. 2012a. An illustrated guide to the identification of cladoceran subfossils from lake sediments in northeastern North America: Part 1-the Daphniidae, Leptodoridae, Bosminidae, Polyphemidae, Holopedidae, Sididae, and Macrothricidae. J. Paleolimnol. <strong>48</strong>: 571–586. doi:10.1007/S10933-012-9632-3</p> <p>Korosi, J. B., and J. P. Smol. 2012b. An illustrated guide to the identification of cladoceran subfossils from lake sediments in northeastern North America: Part 2-the Chydoridae. J. Paleolimnol. <strong>48</strong>: 587–622.</p> <p>Szeroczyfiska, K., and K. Sarmaja-Korjonen. 2007. Atlas of Subfossil Cladocera from Central and Northern Europe, Friends of the Lower Vistula Society, Warsaw, Pol.</p>
Diversity of options to eliminate fossil fuels and reach carbon-neutrality across the entire European energy system
<p><strong>Sector-coupled Euro-Calliope model outputs</strong></p> <p>The subdirectories found here cover cost-optimal and cost relaxation (SPORES) carbon-neutrality runs for a sector-coupled, sub-national resolution European energy system model.</p> <p>The underlying model to produce these results, <a href="https://github.com/calliope-project/sector-coupled-euro-calliope">Sector-coupled Euro-Calliope</a>, is an extension of the power-sector only <a href="https://github.com/calliope-project/euro-calliope">Euro-Calliope model</a>. It incorporates all energy consuming sectors and includes a more detailed representation of transmission capacities between 98 model regions in Europe.</p> <p>The model runs here are based on specific Sector-Coupled Euro-Calliope minor releases:</p> <ul> <li><a href="https://github.com/calliope-project/euro-calliope-2.0/commit/74f6a9b2e157b6147e155b556f521c03ef23246a">cost-opt</a></li> <li><a href="https://github.com/calliope-project/euro-calliope-2.0/commit/519a4fb26920114e451b8247b38ed86b93b6af89">slack-*</a></li> </ul> <p>The models were optimised using the <a href="https://github.com/calliope-project/calliope">Calliope open energy system modelling framework</a>, again based on different minor releases:</p> <ul> <li><a href="https://github.com/calliope-project/calliope/commit/1faed85eeddbe41c29d52982a6bfb147ef9001a3">cost-opt</a></li> <li><a href="https://github.com/calliope-project/calliope/commit/19460da2e23e752995a9a02ae6dca49379565d43">slack-*</a></li> </ul> <p><code>slack-*</code> results are for cost relaxation runs, where <code>*</code> refers to the percentage relaxation from the optimal cost of the 2018 energy system. All results use the <a href="https://github.com/sentinel-energy/friendly_data">friendly data</a> format. Data files are structured according to standardised sector-coupled Euro-Calliope output processing provided by the <a href="https://github.com/brynpickering/friendly-calliope">friendly-calliope</a> package + additional processing to produce data relevant to nine high-level metrics (see script <a href="https://github.com/calliope-project/sector-coupled-euro-calliope/blob/main/src/analyse/result_to_friendly.py">here</a>).</p> <p>Both cost optimal and SPORES results related to a projected demand scenario are given in the directories ending in "demand-update".</p> <p>To explore the data, please refer to the <a href="https://sentinel-energy.github.io/friendly_data/">friendly data documentation</a>.</p>
EOL Fossil Fishes Patch: EOL Fossil Fishes Patch
<p>Taxonomy of fossil fishes compiled from multiple sources:</p> <p>Bardack, D. & Richardson, E. S., Jr. 1977. New agnathous fishes from the Pennsylvanian of Illinois. Fieldiana, Geology 33(26):489-510. <a href="http://doi.org/10.5962/bhl.title.5167">http://doi.org/10.5962/bhl.title.5167</a></p> <p>Bardack, D. and Zangerl, R., 1968. First fossil lamprey: a record from the Pennsylvanian of Illinois. Science, 162(3859), pp.1265-1267. <a href="http://doi.org/10.1126/science.162.3859.1265">http://doi.org/10.1126/science.162.3859.1265</a></p> <p>Denison, R.H., 1967. Ordovician vertebrates from western United States. Fieldiana, Geology 16(6):131-192. <a href="http://doi.org/10.5962/bhl.title.5321">http://doi.org/10.5962/bhl.title.5321</a></p> <p>Denison, R.H., 1970. Revised classification of Pteraspididae with description of new forms from Wyoming. Fieldiana, Geology 20(1):1-41. <a href="https://doi.org/10.5962/bhl.title.3330">https://doi.org/10.5962/bhl.title.3330</a></p> <p>Dineley, D.L., 1964. New specimens of Traquairaspis from Canada. Palaeontology 7:210–219. Dineley, D. L. and Loeffler, E. J. 1976. Osctracoderm faunas of the Delorme and associated Siluro-Devonian formations, North West Territories, Canada. Spec. Pap. Paleont. 18:1-214. Dzik, J. and Moskalenko, T.A., 2016. Problematic scale-like fossils from the Ordovician of Siberia with possible affinities to vertebrates. Neues Jahrbuch für Geologie und Paläontologie-Abhandlungen, pp.251-260. <a href="http://doi.org/10.1127/njgpa/2016/0553">http://doi.org/10.1127/njgpa/2016/0553</a> </p> <p>Janvier, P. and Lund, R., 1983. Hardistiella montanensis n. gen. et sp.(Petromyzontida) from the Lower Carboniferous of Montana, with remarks on the affinities of the lampreys. Journal of vertebrate Paleontology, 2(4), pp.407-413. <a href="http://doi.org/10.1080/02724634.1983.10011943">http://doi.org/10.1080/02724634.1983.10011943</a> </p> <p>Märss, T., 2019. Silurian cyathaspidid heterostracans of Northern Eurasia. Estonian Journal of Earth Sciences, 68(3), pp.113-146. <a href="https://doi.org/10.3176/earth.2019.11">https://doi.org/10.3176/earth.2019.11</a> </p> <p>Märss, T. and Karatajūte-Talimaa, V., 2009. Late Silurian-Early Devonian tessellated heterostraean Oniscolepis Pander, 1856 from the East Baltic and North Timan. Estonian Journal of Earth Sciences, 58(1). <a href="http://doi.org/10.3176/EARTH.2009.1.05">http://doi.org/10.3176/EARTH.2009.1.05</a> </p> <p>Paleobiology Database, PBDB, accessed at h<a>ttps://paleobiodb.org</a> </p> <p>Shu, D.G., Luo, H.L., Conway Morris, S., Zhang, X.L., Hu, S.X., Chen, L., Han, J.I.A.N., Zhu, M., Li, Y. and Chen, L.Z., 1999. Lower Cambrian vertebrates from south China. Nature, 402(6757), pp.42-46. <a href="http://doi.org/10.1038/46965">http://doi.org/10.1038/46965</a> </p> <p>Tarlo, L. B. H. 1964. Psammosteiformes (Agnatha). 1 General part. Palaeontologia Polonica 13:1-135. Tarrant, P.R., 1991. The ostracoderm Phialaspis from the Lower Devonian of the Welsh Borderland and South Wales. Palaeontology 34:399–438. Van der Laan, R., 2018. Family-group names of fossil fishes. European Journal of Taxonomy, (466). <a href="http://doi.org/10.5852/ejt.2018.466">http://doi.org/10.5852/ejt.2018.466</a> </p> <p>WoRMS Editorial Board (2020). World Register of Marine Species. Available from <a href="http://www.marinespecies.org">http://www.marinespecies.org</a> at VLIZ. <a href="https://doi.org/10.14284/170">https://doi.org/10.14284/170</a> </p> <p>Zarling, A., 2017. Phenotypic trajectories during the evolution of hybrid lineages: the case of Oophaga histrionica and Oophaga lehmanni. Thesis, Universidad de los Andes, Colombia. <a href="http://doi.org/10.1038/nature0473">http://doi.org/10.1038/nature0473</a></p>
Revised marine fossil record of the Mediterranean before and after the Messinian Salinity Crisis
<p>This is a unified and revised marine fossil record of the Mediterranean covering the Tortonian stage, the pre-evaporitic Messinian and the Zanclean stage and encompassing 23032 occurrences of calcareous nannoplankton, dinoflagellates, foraminifera, corals, ostracods, bryozoans, echinoids, mollusks, fishes, and marine mammals. It consists of four files in .csv format: 1) 'MessinianDB' contains the fossil occurrences; 2) 'coord' has the list of fossiliferous localities with their coordinates and the groups of organisms reported from each one; 3) 'DBrefs' contains the full citations of the references in the database; 4) 'corals' contains the list of coral genera in the database, indicating whether or not they include zooxanthellate (z-corals) or azooxanthellate (az-corals) species, or both. In the latter case, we further indicate if the species found in the database should be considered z- or az-corals, based on the accompanying fauna. </p>
RESEARCH DATA IN PALEOBOTANICAL: DATASET OF THE THIN PETROGRAPHIC SLIDES AT FOSSIL WOODS
<p>Objective: The study aims to disseminate and analyze the collection of fossil wood stored in the collection of thin slides sections of the paleobotany collection of the Department of Paleontology and Stratigraphy of the Institute of Geosciences of a University in southern Brazil. Thin sheets of petrified wood are described, while research data used for research in Geosciences, specifically, seeks to compose a model for the use of this type of sheet in paleobotany, allowing to visualize its representativeness in studies published in 40 years, will be obtained the anatomical characteristics of fossil woods and aiming to define their systematic affinities as a specific typology of research data in Geosciences.<br> Methods: The methodology involves interviewing a paleobotany specialist and using different techniques applied in metric studies to map their scientific production. Thus, a dataset of (20) thin slides sections of petrified fossil wood used in the study Stressing environmental conditions in the “petrified forest” from the Mata Sequence in the Triassic context of the Paraná Basin published by the Journal of South American Earth Sciences, according to (DOI: 10.1016/j.jsames.2023.104415). According to the methodology used, these thin petrified wood sheets have the potential to identify paleoclimatic signatures based on the anatomical characteristics of fossil wood. In addition to this case study, which represents a collection of more than (2.000) thousand blades of fossil wood and about 40 years of research, this paleobotany collection of the Department is reused in methodology classes. It comprises a database of research physicists that provides information about anatomical features, systematic affinities, paleoclimatic conditions, and paleoenvironmental insights.<br> Potential for reuse: Its reuse, registration, storage, identification, and preservation of thin sections as a type of research data used by paleobotany aims to improve the methodology associated with the organization of a physical database of the institution. The research data, and blades of fossil wood, are being digitized, and soon, all will be available under the CC BY 4.0 license in the ZENODO repository, according to the sample described here in this data paper. (DOI Zenodo) and may be reused by optical and electronic scanning microscopy software.</p> <p> </p>
Result data related to "Tröndle et al (2023): Public preferences for phasing-out fossil fuels in the German building and transport sectors"
<p>Parameter estimations from the conjoint experiments performed in "Tröndle et al (2023): Public preferences for phasing-out fossil fuels in the German building and transport sectors". Parameter estimations are given for different:</p> <p>* estimands: average marginal component effects (amce) or marginal means,</p> <p>* variables: choice and rating,</p> <p>* sectors: buildings (heat) and transport sector,</p> <p>* subgroups: by-<subgroupname>.</p> <p>Filenames accordingly are: <estimand>-<variable>-<sector>.csv or <estimand>-<variable>-<sector>-by-<subgroup>.csv</p>
Figures from: A Saharan fossil and the dawn of Neotropical armoured catfishes in Gondwana
<p>This repository contains high-resolution versions of the figures from the manuscript by Paulo M. Brito et al., "A Saharan fossil and the dawn of Neotropical armoured catfishes in Gondwana"</p>
Holocene insect fossil data for Indian Peaks Wilderness and Rocky Mountain National Park, 1985 and 1993.
Insect fossil assemblages were analyzed from the Indian Peaks Wilderness and Rocky Mountain National Park. Assemblages span the last 10,000 years revealing climate change and the response of both insects and vegetation in the montane to upper subalpine zones. The Longs Peak Inn Bog site (LPIB) yielded insect assemblages ranging in age from recent to 3500 yr BP. This insect fossil record suggests climatic cooling at about 1800 yr BP and between 250 and 300 yr BP (AD 1700-1850). The bog may experience colder microclimates than the surrounding forests, yielding insect assemblages reflective of the colder, local microclimate. Also, alpine and upper subalpine insects may have been washed into the catchment basin of the bog from nearby slopes. Assemblages from four additional Front Range sites suggested a climatic optimum between 9000 and 7000 BP. Faunal evidence indicates a tree-limit decline at 4500 BP. Declining forest-tundra insect ratios, combined with the conifer macrofossil record, suggest a climatic deterioration from 4500 to 3100 BP followed by a rapid amelioration, from 3000 to 2000 BP. A gradual decline in the forest-tundra ratios occurred after 2000 BP, reaching 1:1 ratios at or before 1000 BP.
Fig. 1 in The oldest fossil of the family Issidae (Hemiptera, Fulgoromorpha) from the Paleocene of Menat (France)
Fig. 1. Forewing of Cubicostissus palaeocaeni gen. et sp. nov. (NEL3485). Scale bar = 1 mm. Photograph© T. Schubnel.
Figures 1–4. Fossil elateroids. 1 in Descriptions of two new elateroid beetles (Coleoptera: Eucnemidae, Elateridae) from Burmese amber
Figures 1–4. Fossil elateroids. 1) Cenomana clavata holotype, dorsal habitus. 2) Cenomana clavata holotype, ventral habitus. 3) Cretopityobius pankowskiorum holotype, dorsal habitus. 4) Cretopityobius pankowskiorum holotype, ventral habitus. (Scale: 1–4 = 1.0 mm)
FIG. 1 in Two fossil conifer species from the Neogene of Alonissos Island (Iliodroma, Greece)
FIG. 1. — Geological sketch – map of Alonissos Island, by Jacobshagen & Matarangas (2004) (based on the work of Kelepertsis [1975] for the Institute of Geology and Mineral Exploration [I.G.M.E.]), modified. The Neogene formations are included by the red circles.
FIG. 1 in An appraisal of the Middle-Late Miocene fossil decapod crustaceans of the 'Faluns' (Anjou-Touraine, France)
FIG. 1. — Location map of the outcrops area, and extension of the Falun's Sea during the Middle-Late Miocene (shaded area). Map from Gagnaison et al. 2012.?, limits of the "Faluns sea" probable extension.
FIG. 8 in A review of fossil Bursidae and their use for phylogeny calibration
FIG. 8. — Stratigraphic range of the extinct and extant Bursidae. Black arrows indicate total stratigraphic range; grey arrows indicate regional stratigraphic range. Abbreviations: P, Peru; WI, Western Indian Ocean; AB, Aquitaine Basin; CWA, Caribbean, Western Atlantic Ocean; PT, Paratethys, CWT: Central Western Tethys; EA, Eastern Atlantic; CWM, Central Western Mediterranean; WP, Western Pacific Ocean; J, Java, Indo-Pacific; S, Sumatra, Indo-Pacific; EP, Eastern Pacific Ocean. Grey squares regroup accepted genera and putative genera within Bursa.
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