cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.9938921.v1
title: Supplementary Table 1. from A Laurasian origin for a pantropical bird radiation is supported by genomic and fossil data (Aves: Coraciiformes)

description: List of samples used in this study. Taxonomy follows International Ornithological Checklist v. 8.2 (Gill and Donsker 2018). Institutional abbreviations: AMNH, American Museum of Natural History; FMNH, Field Museum of Natural History; KUNHM, University of Kansas Biodiversity Institute; LSUMZ, Louisiana State University Museum of Natural Science; MSB, Museum of Southwestern Biology; UWBM, University of Washington Burke Museum of Natural History and Culture; ANWC, Australian National Wildlife Collection; NHMG, Natural History Museum of Geneva; USNM, National Museum of Natural History, Smithsonian Institution; MV, Museum Victoria; YPM, Yale Peabody Museum; UNAM, Universidad Nacional Autónoma de México; SNZPTKP, Smithsonian National Zoological Park; UMMZ, University of Michigan Museum of Zoology; WAM, Western Australia Museum; and IOZ, Institute of Zoology, Chinese Academy of Sciences; NCBI, GenBank, National Center for Biotechnology Information. 1 = sample excluded from the 75%–193 species dataset.
DOI: 10.6084/m9.figshare.9938864
title: Supplementary Table 5. from A Laurasian origin for a pantropical bird radiation is supported by genomic and fossil data (Aves: Coraciiformes)

description: Molecular dataset statistics.
DOI: 10.6084/m9.figshare.9938852
title: Supplementary Table 7. from A Laurasian origin for a pantropical bird radiation is supported by genomic and fossil data (Aves: Coraciiformes)

description: Biogeographical model selection using 9 areas (Fig. 1) and 7 maximum areas.
DOI: 10.6084/m9.figshare.9938864.v1
title: Supplementary Table 5. from A Laurasian origin for a pantropical bird radiation is supported by genomic and fossil data (Aves: Coraciiformes)

description: Molecular dataset statistics.
DOI: 10.6084/m9.figshare.9938852.v1
title: Supplementary Table 7. from A Laurasian origin for a pantropical bird radiation is supported by genomic and fossil data (Aves: Coraciiformes)

description: Biogeographical model selection using 9 areas (Fig. 1) and 7 maximum areas.
DOI: 10.6084/m9.figshare.9938837
title: Supplementary Table 4. from A Laurasian origin for a pantropical bird radiation is supported by genomic and fossil data (Aves: Coraciiformes)

description: Fossil taxa included in the biogeographical analysis, their closest crown group relative, stratigraphic age and distribution. Fossil taxa represent genera.
DOI: 10.6084/m9.figshare.9938846
title: Supplementary Table 3. from A Laurasian origin for a pantropical bird radiation is supported by genomic and fossil data (Aves: Coraciiformes)

description: Biogeographical coding of 188 ingroup Coraciiform species, four outgroup species, and nine fossil species. An “X” indicates that the species is present. Areas used to infer historical biogeography using BioGeoBears: A) North America; B) Caribbean islands, including Trinidad; C) South America; D) Palearctic, including arid Northern Africa; E) Sub-Saharan Africa and Madagascar; F) Indomalaya; G) Wallacea and the Philippines; H) New Guinea and Australia; I) Oceania, including the Bismarck Archipelago and New Zealand. Fossil species represent the distribution of their genus.
DOI: 10.6084/m9.figshare.9938837.v1
title: Supplementary Table 4. from A Laurasian origin for a pantropical bird radiation is supported by genomic and fossil data (Aves: Coraciiformes)

description: Fossil taxa included in the biogeographical analysis, their closest crown group relative, stratigraphic age and distribution. Fossil taxa represent genera.
DOI: 10.6084/m9.figshare.9938846.v1
title: Supplementary Table 3. from A Laurasian origin for a pantropical bird radiation is supported by genomic and fossil data (Aves: Coraciiformes)

description: Biogeographical coding of 188 ingroup Coraciiform species, four outgroup species, and nine fossil species. An “X” indicates that the species is present. Areas used to infer historical biogeography using BioGeoBears: A) North America; B) Caribbean islands, including Trinidad; C) South America; D) Palearctic, including arid Northern Africa; E) Sub-Saharan Africa and Madagascar; F) Indomalaya; G) Wallacea and the Philippines; H) New Guinea and Australia; I) Oceania, including the Bismarck Archipelago and New Zealand. Fossil species represent the distribution of their genus.
DOI: 10.6084/m9.figshare.9938819
title: Supplementary Table 1. from A Laurasian origin for a pantropical bird radiation is supported by genomic and fossil data (Aves: Coraciiformes)

description: List of samples used in this study. Taxonomy follows International Ornithological Checklist v. 8.2 (Gill and Donsker 2018). Institutional abbreviations: AMNH, American Museum of Natural History; FMNH, Field Museum of Natural History; KUNHM, University of Kansas Biodiversity Institute; LSUMZ, Louisiana State University Museum of Natural Science; MSB, Museum of Southwestern Biology; UWBM, University of Washington Burke Museum of Natural History and Culture; ANWC, Australian National Wildlife Collection; NHMG, Natural History Museum of Geneva; USNM, National Museum of Natural History, Smithsonian Institution; MV, Museum Victoria; YPM, Yale Peabody Museum; UNAM, Universidad Nacional Autónoma de México; SNZPTKP, Smithsonian National Zoological Park; UMMZ, University of Michigan Museum of Zoology; WAM, Western Australia Museum; and IOZ, Institute of Zoology, Chinese Academy of Sciences; NCBI, GenBank, National Center for Biotechnology Information. 1 = sample excluded from the 75%–193 species dataset.
DOI: 10.6084/m9.figshare.9938834
title: Supplementary Table 6. from A Laurasian origin for a pantropical bird radiation is supported by genomic and fossil data (Aves: Coraciiformes)

description: The five highest probabilities of inferred ancestral ranges, as given by the DEC+<i>j</i> model. Areas used to infer historical biogeography using BioGeoBears: A) North America; B) Caribbean islands, including Trinidad; C) South America; D) Palearctic, including arid Northern Africa; E) Sub-Saharan Africa and Madagascar; F) Indomalaya; G) Wallacea and the Philippines; H) New Guinea and Australia; I) Oceania, including the Bismarck Archipelago and New Zealand.
DOI: 10.6084/m9.figshare.9938819.v1
title: Supplementary Table 1. from A Laurasian origin for a pantropical bird radiation is supported by genomic and fossil data (Aves: Coraciiformes)

description: List of samples used in this study. Taxonomy follows International Ornithological Checklist v. 8.2 (Gill and Donsker 2018). Institutional abbreviations: AMNH, American Museum of Natural History; FMNH, Field Museum of Natural History; KUNHM, University of Kansas Biodiversity Institute; LSUMZ, Louisiana State University Museum of Natural Science; MSB, Museum of Southwestern Biology; UWBM, University of Washington Burke Museum of Natural History and Culture; ANWC, Australian National Wildlife Collection; NHMG, Natural History Museum of Geneva; USNM, National Museum of Natural History, Smithsonian Institution; MV, Museum Victoria; YPM, Yale Peabody Museum; UNAM, Universidad Nacional Autónoma de México; SNZPTKP, Smithsonian National Zoological Park; UMMZ, University of Michigan Museum of Zoology; WAM, Western Australia Museum; and IOZ, Institute of Zoology, Chinese Academy of Sciences; NCBI, GenBank, National Center for Biotechnology Information. 1 = sample excluded from the 75%–193 species dataset.
DOI: 10.6084/m9.figshare.9938834.v1
title: Supplementary Table 6. from A Laurasian origin for a pantropical bird radiation is supported by genomic and fossil data (Aves: Coraciiformes)

description: The five highest probabilities of inferred ancestral ranges, as given by the DEC+<i>j</i> model. Areas used to infer historical biogeography using BioGeoBears: A) North America; B) Caribbean islands, including Trinidad; C) South America; D) Palearctic, including arid Northern Africa; E) Sub-Saharan Africa and Madagascar; F) Indomalaya; G) Wallacea and the Philippines; H) New Guinea and Australia; I) Oceania, including the Bismarck Archipelago and New Zealand.
DOI: 10.6084/m9.figshare.9938804
title: Supplementary Table 5. from A Laurasian origin for a pantropical bird radiation is supported by genomic and fossil data (Aves: Coraciiformes)

description: Molecular dataset statistics.
DOI: 10.6084/m9.figshare.9938810
title: Supplementary Table 2. from A Laurasian origin for a pantropical bird radiation is supported by genomic and fossil data (Aves: Coraciiformes)

description: Fossils used for time-calibrating the coraciiform phylogeny. Fossils were used as minimum ages on nodes. For ages that indicate ranges from rock stratum, we used the youngest age.
DOI: 10.6084/m9.figshare.9938804.v1
title: Supplementary Table 5. from A Laurasian origin for a pantropical bird radiation is supported by genomic and fossil data (Aves: Coraciiformes)

description: Molecular dataset statistics.
DOI: 10.6084/m9.figshare.9938810.v1
title: Supplementary Table 2. from A Laurasian origin for a pantropical bird radiation is supported by genomic and fossil data (Aves: Coraciiformes)

description: Fossils used for time-calibrating the coraciiform phylogeny. Fossils were used as minimum ages on nodes. For ages that indicate ranges from rock stratum, we used the youngest age.
DOI: 10.6084/m9.figshare.9938786
title: Supplementary Table 3. from A Laurasian origin for a pantropical bird radiation is supported by genomic and fossil data (Aves: Coraciiformes)

description: Biogeographical coding of 188 ingroup Coraciiform species, four outgroup species, and nine fossil species. An “X” indicates that the species is present. Areas used to infer historical biogeography using BioGeoBears: A) North America; B) Caribbean islands, including Trinidad; C) South America; D) Palearctic, including arid Northern Africa; E) Sub-Saharan Africa and Madagascar; F) Indomalaya; G) Wallacea and the Philippines; H) New Guinea and Australia; I) Oceania, including the Bismarck Archipelago and New Zealand. Fossil species represent the distribution of their genus.
DOI: 10.6084/m9.figshare.9938786.v1
title: Supplementary Table 3. from A Laurasian origin for a pantropical bird radiation is supported by genomic and fossil data (Aves: Coraciiformes)

description: Biogeographical coding of 188 ingroup Coraciiform species, four outgroup species, and nine fossil species. An “X” indicates that the species is present. Areas used to infer historical biogeography using BioGeoBears: A) North America; B) Caribbean islands, including Trinidad; C) South America; D) Palearctic, including arid Northern Africa; E) Sub-Saharan Africa and Madagascar; F) Indomalaya; G) Wallacea and the Philippines; H) New Guinea and Australia; I) Oceania, including the Bismarck Archipelago and New Zealand. Fossil species represent the distribution of their genus.
DOI: 10.6084/m9.figshare.9938792
title: Supplementary Table 7. from A Laurasian origin for a pantropical bird radiation is supported by genomic and fossil data (Aves: Coraciiformes)

description: Biogeographical model selection using 9 areas (Fig. 1) and 7 maximum areas.
DOI: 10.6084/m9.figshare.9938774
title: Supplementary Table 6. from A Laurasian origin for a pantropical bird radiation is supported by genomic and fossil data (Aves: Coraciiformes)

description: The five highest probabilities of inferred ancestral ranges, as given by the DEC+<i>j</i> model. Areas used to infer historical biogeography using BioGeoBears: A) North America; B) Caribbean islands, including Trinidad; C) South America; D) Palearctic, including arid Northern Africa; E) Sub-Saharan Africa and Madagascar; F) Indomalaya; G) Wallacea and the Philippines; H) New Guinea and Australia; I) Oceania, including the Bismarck Archipelago and New Zealand.
DOI: 10.6084/m9.figshare.9938777
title: Supplementary Table 4. from A Laurasian origin for a pantropical bird radiation is supported by genomic and fossil data (Aves: Coraciiformes)

description: Fossil taxa included in the biogeographical analysis, their closest crown group relative, stratigraphic age and distribution. Fossil taxa represent genera.
DOI: 10.6084/m9.figshare.9938792.v1
title: Supplementary Table 7. from A Laurasian origin for a pantropical bird radiation is supported by genomic and fossil data (Aves: Coraciiformes)

description: Biogeographical model selection using 9 areas (Fig. 1) and 7 maximum areas.
DOI: 10.6084/m9.figshare.9938777.v1
title: Supplementary Table 4. from A Laurasian origin for a pantropical bird radiation is supported by genomic and fossil data (Aves: Coraciiformes)

description: Fossil taxa included in the biogeographical analysis, their closest crown group relative, stratigraphic age and distribution. Fossil taxa represent genera.
DOI: 10.6084/m9.figshare.9938774.v1
title: Supplementary Table 6. from A Laurasian origin for a pantropical bird radiation is supported by genomic and fossil data (Aves: Coraciiformes)

description: The five highest probabilities of inferred ancestral ranges, as given by the DEC+<i>j</i> model. Areas used to infer historical biogeography using BioGeoBears: A) North America; B) Caribbean islands, including Trinidad; C) South America; D) Palearctic, including arid Northern Africa; E) Sub-Saharan Africa and Madagascar; F) Indomalaya; G) Wallacea and the Philippines; H) New Guinea and Australia; I) Oceania, including the Bismarck Archipelago and New Zealand.
DOI: 10.5281/zenodo.4002042
title: Output dataset for the SIM4NEXUS Sweden national level case study

description: Complete baseline system dynamics model output for the national level Sweden case study of the SIM4NEXUS project. The data are provided split into three regions in Sweden. Aggregating across the regions gives national totals.
DOI: 10.5281/zenodo.4002041
title: Output dataset for the SIM4NEXUS Sweden national level case study

description: Complete baseline system dynamics model output for the national level Sweden case study of the SIM4NEXUS project. The data are provided split into three regions in Sweden. Aggregating across the regions gives national totals.
DOI: 10.6084/m9.figshare.12867038
title: Data for Evidence synthesis: Funding research for small-scale farmers in water scarce regions to achieve SDG 2.3

description: This dataset was created for the Ceres2030 Team 6, who conducted a semi-automatic systematic review of over 18,000 articles. The goal was to identify solutions for small farms to adapt to climate change - we focused on water scarce environments. This analysis is under review at the academic journal Nature Sustainability. A link to the article will be provided once published. The manuscript's current citation is:<br>Ricciardi, V., Wane, A., Singh Sidhu, B., Goode, C., Solomon, D., McCullough, E., Diekmann, F., Porciello, J., Jain, M., Randall, N., Mehrabi, Z.Evidence synthesis: Funding research for small-scale farmers in water scarce regions to achieve SDG 2.3. In Review. Nature Sustainability.<br>We use manually coded abstracts to build a natural language processing (NLP) model to include or exclude abstracts to our study. A deep learning model was developed using Bidirectional Encoder Representations from Transformers (BERT) and a cross entropy function to classify abstracts. This model performed better than other classifiers (e.g., optimized support vector machine (SVM) and naive bayes) across accuracy, precision, and recall metrics. This dataset is the predicted results.<br>This dataset is an input file for use in:https://github.com/vinnyricciardi/Ricciardi_etal_2020_ceres/blob/master/full_text_analysis.R<br><br>The data filename referred to in the code is: Validation Survey_February 17, 2020_12.13.csv<br>
DOI: 10.6084/m9.figshare.12867038.v4
title: Ricciardi et al 2020 Ceres Main Results

description: This dataset was created for the Ceres2030 Team 6, who conducted a semi-automatic systematic review of over 18,000 articles. The goal was to identify solutions for small farms to adapt to climate change - we focused on water scarce environments. This analysis is under review at the academic journal Nature Sustainability. A link to the article will be provided once published. The manuscript's current citation is:<br>Ricciardi, V., Wane, A., Singh Sidhu, B., Goode, C., Solomon, D., McCullough, E., Diekmann, F., Porciello, J., Jain, M., Randall, N., Mehrabi, Z.Evidence synthesis: Funding research for small-scale farmers in water scarce regions to achieve SDG 2.3. In Review. Nature Sustainability.<br>We use manually coded abstracts to build a natural language processing (NLP) model to include or exclude abstracts to our study. A deep learning model was developed using Bidirectional Encoder Representations from Transformers (BERT) and a cross entropy function to classify abstracts. This model performed better than other classifiers (e.g., optimized support vector machine (SVM) and naive bayes) across accuracy, precision, and recall metrics. This dataset is the predicted results.<br>This dataset is an input file for use in:https://github.com/vinnyricciardi/Ricciardi_etal_2020_ceres/blob/master/full_text_analysis.R<br><br>The data filename referred to in the code is: Validation Survey_February 17, 2020_12.13.csv<br>
DOI: 10.6084/m9.figshare.9938438
title: interaction, pollen receipt and pollen tube number datasets

description: archive interaction.csv:Interaction data of Bergamo et al. 2019 (Ecology Letters). Number of visits (n_visits) made by each pollinator group (visitor_type) to each plant species (sp_plant). Additional information is provided (plant generalization, plot, time of observation, observer, etc).<br><br>archive pollination_proxies.csv:Pollination proxies (pollen receipt and pollen tube number) and floral density data of Bergamo et al. 2019 (Ecology Letters). <br>Pollination proxies:Pollen receipt - CPPollen tubes - PTz-transformations - poll.grains.z and poll.tubes.z<br>Floral density variables:con_density - landscape level conspecific densityhp_density - plot level heterospecific densityplot_density - plot level conspecific density<br>Additional information:plant species (species); trail and plot information
DOI: 10.6084/m9.figshare.9938435
title: interactions.csv

description: Interaction data of Bergamo et al. 2019 (Ecology Letters). Number of visits (n_visits) made by each pollinator group (visitor_type) to each plant species (sp_plant). Additional information is provided (plant generalization, plot, time of observation, observer, etc).
DOI: 10.6084/m9.figshare.9938435.v1
title: interactions.csv

description: Interaction data of Bergamo et al. 2019 (Ecology Letters). Number of visits (n_visits) made by each pollinator group (visitor_type) to each plant species (sp_plant). Additional information is provided (plant generalization, plot, time of observation, observer, etc).
DOI: 10.6084/m9.figshare.9938438.v2
title: interaction, pollen receipt and pollen tube number datasets

description: archive interaction.csv:Interaction data of Bergamo et al. 2019 (Ecology Letters). Number of visits (n_visits) made by each pollinator group (visitor_type) to each plant species (sp_plant). Additional information is provided (plant generalization, plot, time of observation, observer, etc).<br><br>archive pollination_proxies.csv:Pollination proxies (pollen receipt and pollen tube number) and floral density data of Bergamo et al. 2019 (Ecology Letters). <br>Pollination proxies:Pollen receipt - CPPollen tubes - PTz-transformations - poll.grains.z and poll.tubes.z<br>Floral density variables:con_density - landscape level conspecific densityhp_density - plot level heterospecific densityplot_density - plot level conspecific density<br>Additional information:plant species (species); trail and plot information
DOI: 10.6084/m9.figshare.9938438.v1
title: pollen receipt and pollen tube number dataset

description: Pollination proxies (pollen receipt and pollen tube number) and floral density data of Bergamo et al. 2019 (Ecology Letters). <br>Pollination proxies:Pollen receipt - CPPollen tubes - PTz-transformations - poll.grains.z and poll.tubes.z<br>Floral density variables:con_density - landscape level conspecific densityhp_density - plot level heterospecific densityplot_density - plot level conspecific density<br>Additional information:plant species (species); trail and plot information
DOI: 10.6084/m9.figshare.9938381
title: Municipalities as enablers in urban experimentation

description: In the light of increasing urban challenges, municipalities are developing and advancing new forms of governing. One such example is ‘urban experimentation’, a process where city-based innovation processes are initiated to test solutions that – if deemed successful – are intended to be scaled up with the ambition to leverage a broader urban sustainability transition. Research on experimental governance has shown that municipalities can play various roles in these processes, including the role as enabler. The article contributes to the literature on the roles of public actors in urban experimentation on sustainability challenges by advancing understanding of the less studied ‘enabler’ role. We probe the politics of enabling by focusing on the policy instruments employed by municipalities. Our aim is to provide deeper insights into the everyday work of urban administrations when they act in the ‘enabler’ role. One particular approach of urban experimentation is Urban Living Labs (ULL), and this paper analyses ULL that address sustainability challenges. Along the four dimensions of nodality, authority, treasury, and organisation, we identify the politics of enabling in four ULL examples from Sweden and the Netherlands.
DOI: 10.6084/m9.figshare.9938375
title: Salonen_ea-ML_fossil_pollen-Supplementary_Data.xlsx

description: Data supplement related to the paper "Machine-learning based reconstructions of primary and secondary climate variables from North American and European fossil pollen data", submitted to Scientific Reports by Sakari Salonen et al.<br><br>This file contains the North American and European pollen-climate calibration datasets used in the paper. For further information, see the "Info" sheet of the Excel file.<br>
DOI: 10.6084/m9.figshare.9938381.v1
title: Municipalities as enablers in urban experimentation

description: In the light of increasing urban challenges, municipalities are developing and advancing new forms of governing. One such example is ‘urban experimentation’, a process where city-based innovation processes are initiated to test solutions that – if deemed successful – are intended to be scaled up with the ambition to leverage a broader urban sustainability transition. Research on experimental governance has shown that municipalities can play various roles in these processes, including the role as enabler. The article contributes to the literature on the roles of public actors in urban experimentation on sustainability challenges by advancing understanding of the less studied ‘enabler’ role. We probe the politics of enabling by focusing on the policy instruments employed by municipalities. Our aim is to provide deeper insights into the everyday work of urban administrations when they act in the ‘enabler’ role. One particular approach of urban experimentation is Urban Living Labs (ULL), and this paper analyses ULL that address sustainability challenges. Along the four dimensions of nodality, authority, treasury, and organisation, we identify the politics of enabling in four ULL examples from Sweden and the Netherlands.
DOI: 10.6084/m9.figshare.9938333
title: Data associated with the paper 'Exploiting open source 3D printer architecture for laboratory robotics to automate high-throughput time-lapse imaging for analytical microbiology'

description: This dataset is for data analysis associated with the article 'Exploiting Open Source 3D printer architecture for laboratory robotics to automate high-throughput time-lapse imaging for analytical microbiology'. It contains the raw images and Excel analysis of microtitre plates (MTP) and microcapillary film (MCF) for milk matrix experiments, POLIR quantification, and first experiment testing fluorescence on POLIR.