University Library, University of Illinois at Urbana-Champaign

This dataset contains RNASim1000, Cox1-Het datasets as well as analyses of RNASim1000, Cox1-Het, and 1000M1(HF).

- The research objectives were to evaluate the effect of dietary supplementation of white (WSH) and red (RSH) sorghum grains on gastrointestinal health of felines through the determination of apparent total tract macronutrient digestibility (ATTD), fecal characteristics, fermentative end-products, and microbiota, compared with a traditional corn-based diet (Control). <br />- Nine, intact, male domestic shorthaired cats (average age: 0.8 ± 0.00 yr; average weight: 4.5 ± 0.23 kg) were used in a triplicated 3 × 3 Latin square design. Total DNA from fresh fecal samples was extracted using Mo-Bio PowerSoil kits (MO BIO Laboratories, Inc., Carlsbad, CA). Amplification of the 292 bp-fragment of V4 region from the 16S rRNA gene was completed using a Fluidigm Access Array (Fluidigm Corporation, South San Francisco, CA). Paired-end Illumina sequencing was performed on a MiSeq using v3 reagents (Illumina Inc., San Diego, CA) at the Roy J. Carver Biotechnology Center at the University of Illinois. <br />- Filenames are composed of animal name identifier, supplement (C=control; RS=red sorghum grain; WS= white sorghum grain) and period replicate number (P1, P2 and P3).

- The objective of this study was to evaluate macronutrient apparent total tract digestibility (ATTD), gastrointestinal tolerance, and fermentative end-products in extruded, canine diets. <br />- Five diets were formulated to be isocaloric and isonitrogenous with either garbanzo beans (GBD), green lentils (GLD), peanut flour (PFD), dried yeast (DYD), or poultry by-product meal (CON) as the primary protein sources. Ten adult, intact, female beagles (mean age: 4.2 ± 1.1 yr, mean 28 weight: 11.9 ± 1.3 kg) were used in a replicated, 5x5 Latin square design with 14 d periods. Total DNA from fresh fecal samples was extracted using Mo-Bio PowerSoil kits (MO BIO Laboratories, Inc., Carlsbad, CA). Amplification of the 292 bp-fragment of V4 region from the 16S rRNA gene was completed using a Fluidigm Access Array (Fluidigm Corporation, South San Francisco, CA). Paired-end Illumina sequencing was performed on a MiSeq using v3 reagents (Illumina Inc., San Diego, CA) at the Roy J. Carver Biotechnology Center at the University of Illinois. <br />- Filenames are composed of animal name identifier, diet (CON=control; DY= dried yeast; GB= garbanzo beans; GL= green lentils; PF= peanut flour) and period replicate number (P1, P2, P3, P4, and P5).

- The aim of this research was to evaluate the novel dietary fiber source, miscanthus grass, in comparison to traditional fiber sources, and their effects on the microbiota of healthy adult cats. Four dietary treatments, cellulose (CO), miscanthus grass fiber (MF), a blend of miscanthus fiber and tomato pomace (MF+TP), or beet pulp (BP) were evaluated.<br /><br />- The study was conducted using a completely randomized design with twenty-eight neutered adult, domesticated shorthair cats (19 females and 9 males, mean age 2.2 ± 0.03 yr; mean body weight 4.6 ± 0.7 kg, mean body condition score 5.6 ± 0.6). Total DNA from fresh fecal samples was extracted using Mo-Bio PowerSoil kits (MO BIO Laboratories, Inc., Carlsbad, CA). Amplification of the 292 bp-fragment of V4 region from the 16S rRNA gene was completed using a Fluidigm Access Array (Fluidigm Corporation, South San Francisco, CA). Paired-end Illumina sequencing was performed on a MiSeq using v3 reagents (Illumina Inc., San Diego, CA) at the Roy J. Carver Biotechnology Center at the University of Illinois. <br />- Filenames are composed of animal name identifier, diet (BP= beet pulp; CO= cellulose; MF= miscanthus grass fiber; TP= blend of miscanthus fiber and tomato pomace).

This dataset includes three files. Descriptions of the files are given as follows: <b>FILENAME: PubMed_retracted_publication_full_v3.tsv</b> - Bibliographic data of retracted papers indexed in PubMed (retrieved on August 20, 2020, searched with the query "retracted publication" [PT] ). - Except for the information in the "cited_by" column, all the data is from PubMed. ROW EXPLANATIONS - Each row is a retracted paper. There are 7,813 retracted papers. COLUMN HEADER EXPLANATIONS 1) PMID - PubMed ID 2) Title - Paper title 3) Authors - Author names 4) Citation - Bibliographic information of the paper 5) First Author - First author's name 6) Journal/Book - Publication name 7) Publication Year 8) Create Date - The date the record was added to the PubMed database 9) PMCID - PubMed Central ID (if applicable, otherwise blank) 10) NIHMS ID - NIH Manuscript Submission ID (if applicable, otherwise blank) 11) DOI - Digital object identifier (if applicable, otherwise blank) 12) retracted_in - Information of retraction notice (given by PubMed) 13) retracted_yr - Retraction year identified from "retracted_in" (if applicable, otherwise blank) 14) cited_by - PMIDs of the citing papers. (if applicable, otherwise blank) Data collected from iCite. 15) retraction_notice_pmid - PMID of the retraction notice (if applicable, otherwise blank) <b>FILENAME: PubMed_retracted_publication_CitCntxt_withYR_v3.tsv</b> - This file contains citation contexts (i.e., citing sentences) where the retracted papers were cited. The citation contexts were identified from the XML version of PubMed Central open access (PMCOA) articles. - This is part of the data from: Hsiao, T.-K., & Torvik, V. I. (manuscript in preparation). Citation contexts identified from PubMed Central open access articles: A resource for text mining and citation analysis. ROW EXPLANATIONS - Each row is a citation context associated with one retracted paper that's cited. - In the manuscript, we count each citation context once, even if it cites multiple retracted papers. COLUMN HEADER EXPLANATIONS 1) pmcid - PubMed Central ID of the citing paper 2) pmid - PubMed ID of the citing paper 3) year - Publication year of the citing paper 4) location - Location of the citation context (abstract = abstract, body = main text, back = supporting material, tbl_fig_caption = table/figure captions) 5) IMRaD - IMRaD section of the citation context (I = Introduction, M = Methods, R = Results, D = Discussions/Conclusion, NoIMRaD = not identified) 6) sentence_id - The ID of the citation context in a given location. For location information, please see column 4. The first sentence in the location gets the ID 1, and subsequent sentences are numbered consecutively. 7) total_sentences - Total number of sentences in a given location 8) intxt_id - Identifier of a cited paper. Here, a cited paper is the retracted paper. 9) intxt_pmid - PubMed ID of a cited paper. Here, a cited paper is the retracted paper. 10) citation - The citation context 11) progression - Position of a citation context by centile within the citing paper. 12) retracted_yr - Retraction year of the retracted paper 13) post_retraction - 0 = not post-retraction citation; 1 = post-retraction citation. A post-retraction citation is a citation made after the calendar year of retraction. <b>FILENAME: 613_knowingly_post_retraction_cit.tsv</b> - The 613 post-retraction citation contexts that we determined knowingly cited the 7,813 retracted papers in "PubMed_retracted_publication_full_v3.tsv". ROW EXPLANATIONS - Each row is a citation context. COLUMN HEADER EXPLANATIONS 1) pmcid - PubMed Central ID of the citing paper 2) pmid - PubMed ID of the citing paper 3) pub_type - Publication type collected from the metadata in the PMCOA XML files. 4) pub_type2 - Specific article types. Please see the manuscript for explanations. 5) year - Publication year of the citing paper 6) location - Location of the citation context (abstract = abstract, body = main text, back = supporting material, tbl_fig_caption = table/figure captions) 7) intxt_id - Identifier of a cited paper. Here, a cited paper is the retracted paper. 8) intxt_pmid - PubMed ID of a cited paper. Here, a cited paper is the retracted paper. 9) citation - The citation context 10) retracted_yr - Retraction year of the retracted paper 11) cit_purpose - Purpose of citing the retracted paper. This is from human annotations. Please see the manuscript for further information about annotation. 12) longer_context - A extended version of the citation context. (if applicable, otherwise blank) Manually pulled from the full-texts in the process of annotation. <b>FILENAME: Annotation manual.pdf</b> - The manual for annotating the citation purposes in column 11) of the 613_knowingly_post_retraction_cit.tsv.

These datasets contain modeling files and GIS data associated with a risk assessment study for the Cambrian-Ordovician sandstone aquifer system in Illinois from predevelopment (1863) to the year 2070. Modeling work was completed using the Illinois Groundwater Flow Model, a regional MODFLOW model developed for water supply planning in Illinois, as a base model. The model is run using the graphical user interface Groundwater Vistas 7.0. The development and technical details of the base Illinois Groundwater Flow Model, including hydraulic property zonation, boundary conditions, hydrostratigraphy, solver settings, and discretization, are described in Abrams et al. (2018). Modifications to this base model (the version presented here) are described in Mannix et al. (2018), Hadley et al. (2020) and Abrams and Cullen (2020). Modifications include removal of particular multi-aquifer wells to improve calibration, changing Sandwich Fault Zone properties to achieve calibration at production wells within and near the fault zone, and the incorporation of demand scenarios based on a participatory modeling project with the Southwest Water Planning Group. The zipped folder of model files contains MODFLOW input (package) files, Groundwater Vistas files, and a head file for the entire model run. The zipped folder of GIS data contains rasters of: simulated drawdown in the St. Peter sandstone from predevelopment to 2018, simulated drawdown in the Ironton-Galesville sandstone from predevelopment to 2018, simulated head difference between the St. Peter and Ironton-Galesville sandstone units in 2018, simulated head above the top of the St. Peter sandstone for the years 2029, 2050, and 2070, and simulated head above the top of the Ironton-Galesville sandstone for the years 2029, 2050, and 2070. Raster outputs were derived directly from the simulated heads in the Illinois Groundwater Flow Model. Rasters are clipped to the 8 county northeastern Illinois region (Cook, DuPage, Grundy, Kane, Kendall, Lake, McHenry, and Will counties). Well names, historic and current head targets, and spatial offsets for the Illinois Groundwater Flow Model are available upon request via a data license agreement. Please contact authors to set this up if needed.

West Nile virus data, aggregated by 55 1-km hexagons, within the NWMAD jurisdiction Cook County, IL. The data incorporates deidentified human illness, mosquito infection and abundance, socio-economic data, and other abiotic and biotic predictors by epi-weeks 18-38 for the years 2005-2016.

This dataset contains simulation results from PartMC-MOSAIC-CAPRAM used in the article "Evaluating the impacts of cloud processing on resuspended aerosol particles after cloud evaporation using a particle-resolved model". There are seven folders: one for urban plume simulation to provide the initial particle population for cloud processing, the other four folders are for the four cloud cycles simulated and the last two are for the coagulation cases. Within the urban plume simulation, there are 25 NetCDF less hourly output from PartMC-MOSAIC simulations containing the gas and particle information. Within the four cloud cycle folders, there are 25 subdirectories that contain the cloud processing results for the aerosol population from the urban plume environment. For each subdirectory, there are 30 NetCDF les out- put every minute from PartMC-MOSAIC-CAPRAM simulations containing aerosol and gas information after aqueous chemistry. Another two folders are for the cases considering Brownian coagulation and sedimentation coalescence. Each contained 90 NetCDF les, produced from repeating the 30-minutes simulations for three times to consider the coagulation randomness. This dataset was used to investigate the effects of cloud processing on aerosol mixing state and CCN properties.

This archive contains the datasets used in the paper "Recursive MAGUS: scalable and accurate multiple sequence alignment". - 16S.3, 16S.T, 16S.B.ALL - HomFam - RNASim These can also be found at https://sites.google.com/eng.ucsd.edu/datasets/alignment/pastaupp

DNN weights used in the evaluation of the ApproxTuner system. Link to paper: https://dl.acm.org/doi/10.1145/3437801.3446108

Video recorded by Louise Barker using a Cannon Powershot camera documents late-season combat behavior in Agkistrodon contortrix. Recorded in Beaufort County, North Carolina, 11.1 km SE of downtown Washington on 21 October 2020.

Femoral skeletal traits (cross-sectional properties, maximum distal metaphyseal breadth of the femur, and maximum superior/inferior femoral head diameter) of 219 Taiwanese subadult individuals (aged 0 to 17) as used in the manuscript "Allometric scaling and growth: evaluation and applications in subadult body mass estimation."

Terrorism is among the most pressing challenges to democratic governance around the world. The Responsible Terrorism Coverage (or ResTeCo) project aims to address a fundamental dilemma facing 21st century societies: how to give citizens the information they need without giving terrorists the kind of attention they want. The ResTeCo hopes to inform best practices by using extreme-scale text analytic methods to extract information from more than 70 years of terrorism-related media coverage from around the world and across 5 languages. Our goal is to expand the available data on media responses to terrorism and enable the development of empirically-validated models for socially responsible, effective news organizations. This particular dataset contains information extracted from terrorism-related stories in the Summary of World Broadcasts published between 1979 and 2019. It includes variables that measure the relative share of terrorism-related topics, the valence and intensity of emotional language, as well as the people, places, and organizations mentioned. This dataset contains 3 files: 1. "ResTeCo Project SWB Dataset Variable Descriptions.pdf" A detailed codebook containing a summary of the Responsible Terrorism Coverage (ResTeCo) Project BBC Summary of World Broadcasts (SWB) Dataset and descriptions of all variables. 2. "resteco-swb.csv" This file contains the data extracted from terrorism-related media coverage in the BBC Summary of World Broadcasts (SWB) between 1979 and 2019. It includes variables that measure the relative share of topics, sentiment, and emotion present in this coverage. There are also variables that contain metadata and list the people, places, and organizations mentioned in these articles. There are 53 variables and 438,373 observations. The variable "id" uniquely identifies each observation. Each observation represents a single news article. Please note that care should be taken when using "resteco-swb.csv". The file may not be suitable to use in a spreadsheet program like Excel as some of the values get to be quite large. Excel cannot handle some of these large values, which may cause the data to appear corrupted within the software. It is encouraged that a user of this data use a statistical package such as Stata, R, or Python to ensure the structure and quality of the data remains preserved. 3. "README.md" This file contains useful information for the user about the dataset. It is a text file written in markdown language Citation Guidelines 1) To cite this codebook please use the following citation: Althaus, Scott, Joseph Bajjalieh, Marc Jungblut, Dan Shalmon, Subhankar Ghosh, and Pradnyesh Joshi. 2020. Responsible Terrorism Coverage (ResTeCo) Project BBC Summary of World Broadcasts (SWB) Dataset Variable Descriptions. Responsible Terrorism Coverage (ResTeCo) Project BBC Summary of World Broadcasts (SWB) Dataset. Cline Center for Advanced Social Research. December 16. University of Illinois Urbana-Champaign. doi: https://doi.org/10.13012/B2IDB-2128492_V1 2) To cite the data please use the following citation: Althaus, Scott, Joseph Bajjalieh, Marc Jungblut, Dan Shalmon, Subhankar Ghosh, and Pradnyesh Joshi. 2020. Responsible Terrorism Coverage (ResTeCo) Project Summary of World Broadcasts (SWB) Dataset. Cline Center for Advanced Social Research. December 16. University of Illinois Urbana-Champaign. doi: https://doi.org/10.13012/B2IDB-2128492_V1

Three datasets: species_abundance_data, species_traits, and environmental_data. The three datasets were collected in the Fortuna Forest Reserve (8°45′ N, 82°15′ W) and Palo Seco Protected Forest (8°45′ N, 82°13′ W) located in western Panama. The two reserves support humid to super-humid rainforests, according to Holdridge (1947). The species_abundance_data and species_traits datasets were collected across 15 subplots of 25 m2 in 12 one-hectare permanent plots distributed across the two reserves. The subplots were spaced 20 m apart along three 5 m wide transects, each 30 m apart. Please read Prada et al. (2017) for details on the environmental characteristics of the study area. Prada CM, Morris A, Andersen KM, et al (2017) Soils and rainfall drive landscape-scale changes in the diversity and functional composition of tree communities in a premontane tropical forest. J Veg Sci 28:859–870. https://doi.org/10.1111/jvs.12540

Data sets from "Comparing Methods for Species Tree Estimation With Gene Duplication and Loss." It contains data simulated with gene duplication and loss under a variety of different conditions.

This is the first version of the dataset. This dataset contains anonymize data collected during the experiments mentioned in the publication: “I can show what I really like.”: Eliciting Preferences via Quadratic Voting that would appear in April 2021. Once the publication link is public, we would provide an update here. These data were collected through our open-source online systems that are available at (experiment1)[https://github.com/a2975667/QV-app] and (experiment 2)[https://github.com/a2975667/QV-buyback] There are two folders in this dataset. The first folder (exp1_data) contains data collected during experiment 1; the second folder (exp2_data) contains data collected during experiment 2.

The file contains biomass and count data of food items encountered in the digestive tract of collected green-winged teal from the Illinois River Valley during spring 2016-2018. The file also contains biomass of food items collected from core samples collected at sites where the green-winged teal were collected. Together, the consumed and availability food data are used to calculate diet selection. The data also contains information on the teal, collection, sites, and other covariates used in analysis. Lastly, the dataset contains biomass of food items collected in medium (#35) and small (#60) sieves for 2018 core samples.

This dataset contains model output from the Community Earth System Model, Version 2 (CESM2; Danabasoglu et al. 2020). These data were used for analysis in Impacts of Large-Scale Soil Moisture Anomalies in Southeastern South America, published in the Journal of Hydrometeorology (DOI: 10.1175/JHM-D-20-0116.1). See this publication for details of the model simulations that created these data. Four NetCDF (.nc) files are included in this dataset. Two files correspond to the control simulation (FHIST_SP_control) and two files correspond to a simulation with a dry soil moisture anomaly imposed in southeastern South America (FHIST_SP_dry; see the publication mentioned in the preceding paragraph for details on the spatial extent of the imposed anomaly). For each simulation, one file corresponds to output from the atmospheric model (file names with "cam") of CESM2 and the other to the land model (file names with "clm2"). These files are raw CESM output concatenated into a single file for each simulation. All files include data from 1979-01-02 to 2003-12-31 at a daily resolution. The spatial resolution of all files is about 1 degree longitude x 1 degree latitude. Variables included in these files are listed or linked below. Variables in atmosphere model output: Vertical velocity (omega) Convective precipitation Large-scale precipitation Surface pressure Specific humidity Temperature (atmospheric profile) Reference temperature (temp. at reference height, 2 meters in this case) Zonal wind Meridional wind Geopotential height Variables in land model output: See https://www.cesm.ucar.edu/models/cesm1.2/clm/models/lnd/clm/doc/UsersGuide/history_fields_table_40.xhtml Note that not all of the variables listed at the above link are included in the land model output files in this dataset. This material is based upon work supported by the National Science Foundation under Grant No. 1454089. We acknowledge high-performance computing support from Cheyenne (doi:10.5065/D6RX99HX) provided by NCAR's Computational and Information Systems Laboratory, sponsored by the National Science Foundation. The CESM project is supported primarily by the National Science Foundation. We thank all the scientists, software engineers, and administrators who contributed to the development of CESM2. References Danabasoglu, G., and Coauthors, 2020: The Community Earth System Model Version 2 (CESM2). Journal of Advances in Modeling Earth Systems, 12, e2019MS001916, https://doi.org/10.1029/2019MS001916.

Total nitrogen leaching rates were calculated over the Mississippi Atchafalaya River Basin (MARB) using an integrated economic-biophysical modeling approach. Land allocation for corn production and total nitrogen application rates were calculated for crop reporting districts using the Biofuel and Environmental Policy Analysis Model (BEPAM) for 5 RFS2 policy scenarios. These were used as input in the Integrated BIosphere Simulator-Agricultural Version (Agro-IBIS) and the Terrestrial Hydrologic Model with Biogeochemistry (THMB) to calculate the nitrogen loss. Land allocation and total nitrogen application simulations were simulated for the period 2016-2030 for 303 crop reporting districts (https://www.nass.usda.gov/Data_and_Statistics/County_Data_Files/Frequently_Asked_Questions/county_list.txt). The final 2030 values are reported here. Both are stored in csv files. Units for land allocation are million ha and nitrogen application are million kg. The nitrogen leaching rates were modeled with a spatial resolution of 5' x 5' using the North American Datum of 1983 projection and stored in NetCDF files. The 30-year average is calculated over the last 30 years of the 45 years being simulated. Leaching rates are calculated in kg-N/ha.

Adey_Larson_Behavior.csv: Results of behavioral assays for rusty crayfish Faxonius rusticus collected from six lakes in Vilas County, Wisconsin in summer 2018. Crayfish_ID is an individual crayfish ID or identifier that matches to individuals in Adey_Larson_Isotope. Collection is how organisms were collected (trapped = baited trapping, snorkel = by hand). Lake is the study lake crayfish were collected from. Length is crayfish carapace length in mm. CPUE is crayfish catch-per-unit effort from baited trapping in that lake during summer 2018. Shelter_Occupancy, Exploration, Feeding_Snail, Feeding_Detritus, Feeding_Crayfish, and Aggressiveness are behavioral assay scores for individual crayfish. Shelter_Occupancy is frequency of observation intervals (12 maximum) in which crayfish were observed in shelter over a 12 hour period. Exploration is time for crayfish to explore a new area measured in seconds (maximum possible time 1200 seconds or 20 minutes). Feeding_Snail, Feeding_Detritus, and Feeding_Crayfish is the time for crayfish to take a food item (snail, detritus, or snail in the presence of another crayfish) measured in seconds (maximum possibe time 1200 seconds or 20 minutes). Aggressiveness is the response to an approach with a novel object scored as a fast retreat (-2), slow retreat (-1), no visible response (0), approach without threat display (1), approach with threat display (2), interaction with closed chelae (3), or interaction with open chelae (4). Three repeated aggressiveness measures were made per individual (Aggresiveness1, Aggresiveness2, Aggresiveness3), which were summed for inclusion in subsequent analyses (Aggresiveness_Sum). More detailed behavioral assay methods can be found in Adey 2019 Masters thesis. Adey_Larson_Isotope.csv: Stable isotope (13C, 15N) values for rusty crayfish Faxonius rusticus and snail or mussel primary consumers from six lakes in Vilas County, Wisconsin collected during summer 2018. Crayf is an individual crayfish ID or identifier that matches to the same individual crayfish in Adey_Larson_Behavior. Lake is the study lake. Collection is how organisms were collected (trapped = baited trapping, snorkel = by hand). Sample type indicates whether isotope values are for crayfish, snail, or mussel. d13C and d15N are stable isotope values.

Datasets that accompany Beilke, Blakey, and O'Keefe 2021 publication (Title: Bats partition activity in space and time in a large, heterogeneous landscape; Journal: Ecology and Evolution).

Dataset associated with "Hiding in plain sight: genetic confirmation of putative Louisiana Fatmucket Lampsilis hydiana in Illinois" as submitted to Freshwater Mollusk Biology and Conservation by Stodola et al. Images are from cataloged specimens from the Illinois Natural History Survey (INHS) Mollusk Collection in Champaign, Illinois that were used for genetic research. File names indicate the species as confirmed in Stodola et al. (i.e., Lampsilis siliquoidea or Lampsilis hydiana) followed by the INHS Mollusk Collection catalog number, followed by the individual specimen number, followed by shell view (interior or exterior). If no specimen number is noted in the file name, there is only one specimen for that catalog number. For example: Lsiliquoidea_46515_1_2_3_exterior. Images were created by photographing specimens on a metric grid in an OrTech Photo-e-Box Plus with a Nikon D610 single lens reflex camera using a 60mm lens. Post-processing of images (cropping, image rotation, and auto contrast) occurred in Adobe Photoshop and saved as TIFF files using no image compression, interleaved pixel order, and IBM PC Byte Order. One additional partial lot, INHS Mollusk Catalog No. 37059 (shown with both interior and exterior view in one image), is included for reference but was not genetically sequenced. A .csv file contains an index of all specimens photographed. SPECIES: species confirmed using genetic analyses GENE: cox1 or nad1 mitochondrial gene ACCESSION: GenBank accession number INHS CATALOG NO: Illinois Natural History Survey Mollusk Collection Catalog number WATERBODY: waterbody where specimen was collected PUTATIVE SPECIES: species determination based on morphological characters prior to genetic analysis Phylogenetic sequence data (.nex files) were aligned using BioEdit (Hall, T.A. 1999. BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. Nucleic Acids Symposium Series 41:95-98.). Pertinent methodology for the analysis are contained within the manuscript submittal for Stodola et al. to Freshwater Mollusk Biology and Conservation. In these files, "N" is a standard symbol for an unknown base.

The file “Fla.fasta”, comprising 10526 positions, is the concatenated amino acid alignments of 51 orthologues of 182 bacterial strains. It was used for the maximum likelihood and maximum parsimony analyses of Flavobacteriales. Bacterial species names and strains were used as the sequence names, host names of insect endosymbionts were shown in brackets. The file “16S.fasta” is the alignment of 233 bacterial 16S rRNA sequences. It contains 1455 positions and was used for the maximum likelihood analysis of flavobacterial insect endosymbionts. The names of endosymbiont strains were replaced by the name of their hosts. In addition to the species names, National Center for Biotechnology Information (NCBI) accession numbers were also indicated in the sequence names (e.g., sequence “Cicadellidae_Deltocephalinae_Macrostelini_Macrosteles_striifrons_AB795320” is the 16S rRNA of Macrosteles striifrons (Cicadellidae: Deltocephalinae: Macrostelini) with a NCBI accession number AB795320). The file “Sulcia_pep.fasta” is the concatenated amino acid alignments of 131 orthologues of “Candidatus Sulcia muelleri” (Sulcia). It contains 41970 positions and presents 101 Sulcia strains and 3 Blattabacterium strains. This file was used for the maximum likelihood analysis of Sulcia. The file “Sulcia_nucleotide.fasta” is the concatenated nucleotide alignment corresponding to the sequences in “Sulcia_pep.fasta” but also comprises the alignment of 16S rRNA. It has 127339 positions and was used for the maximum likelihood and maximum parsimony analyses of Sulcia. Individual gene alignments (16S rRNA and 131 orthologues of Sulcia and Blattabacterium) are deposited in the compressed file “individual_gene_alignments.zip”, which were used to construct gene trees for multispecies coalescent analysis. The names of Sulcia strains were replaced by the name of their hosts in “Sulcia_pep.fasta”, “Sulcia_nucleotide.fasta” and the files in “individual_gene_alignments.zip”. In all the alignment files, gaps are indicated by “-”.

Data from an a field experiment at El Velo, Chiriqui, Republic of Panama. Data contain information about functional traits of seedlings growing in different treatments including type of forest, nitrogen addition and organic matter.