Dataset Search Results

This dataset provides instructions for procedures to use heat transfer analyses to estimate thermal conditions in artificial roosts for bats. The dataset contains scripts to employ in the program GNU Octave, example meteorology data, and example text files specifying roost dimensions and material properties.

Includes two files (.csv) behind all analyses and results in the paper published with the same title. <b>1) 'sites.species.counts'</b> is the raw 2018-2022 data from Angella Moorehouse (Illinois Nature Preserves Commission) including her 456 identified pollinator species and her raw counts per site (there may be a few errors of identification or naming, and there will always be name changes over time). Headers in columns F through Q correspond to the remnant-site labels in Figure 1 and Table 1 of the paper. Columns R to AB are the “nonremnant” sites, which have not been uniquely labelled since the specific sites aren't referenced anywhere in the manuscript. <b>2) 'C.scores'</b> has the 265 species assigned empirical C values (empirical.C) along with the four sets of expert C values and their confidence ranks (low, medium, high), and the Illinois/Indiana conservation ranks (S-ranks), following the methods described in the paper. Other headers in these files: - taxa.code: four-letter abbreviation for genus and specific name - genus: genus name - species: specific epithet - common.name: English name - group: general pollinator taxa group - empirical.C: empirically estimated conservatism score - expert#.C: conservatism score assigned by each of four experts - expert#.conf: expert's confidence in their conservatism score Blank cells in the site-species abundance matrix indicates species absence (or non-detection) Blank cells in C.scores.csv indicates missing S-ranks and unassigned C-scores (with associated missing confidence ranks) where experts lacked knowledge or confidence

Data collected at 71 study sites from 2023 to 2024 for Reves, Olivia P. (2025): Using Environmental DNA Metabarcoding to Inform Biodiversity Conservation in Agricultural Landscapes. Master's thesis, University of Illinois Urbana-Champaign. Files include study site information, taxa by site matrices for vertebrates from environmental DNA metabarcoding using multiple mitochondrial DNA primers (COI, 12S), and bird species audibly detected by a phone app at study sites.

Data was generated from a field and lab study to determine the influence of thermal variation in livewells on largemouth bass recovery from angling tournaments. The field study data includes temperature data from inside angler livewells during a tournament day. This was collected across four tournaments. The laboratory data was generated from a series of experiments simulating tournament practices and trends in thermal variation within livewells observed in the field proponent. Following simulation, blood was collected to determine levels of analytes consistent with primary, secondary, and tertiary stress response in largemouth bass. Reflex impairment was also included.

These data files were used for phylogenomic analyses of Darnini and related Membracidae (Hemiptera: Auchenorrhyncha) in the referenced article by Gonzalez-Mozo et al. - The "mem_50p_alignment.fas" file contains the aligned, concatenated nucleotide sequence data for 51 species and 492 genetic loci included in the phylogenetic analyses ("N" indicates missing data and "-" indicates an alignment gap). - The file "Table1.rtf" lists the included species, country of origin and genbank accession number. Species newly sequenced for this study have a Sample ID with prefix "DAR"; previously sequenced species for which data were downloaded from genbank have "NCBI" indicated in the same column of the table. - The file "partition_def.txt" lists the 492 genetic loci included in the alignment with their exact positions indicated by the range of numbers given at the end of each line (e.g., locus "uce-1" occupies positions 1-280 in the alignment). - The substitution model file "mem_50p.model" contains information on the substitution models used in the partitioned maximum likelihood analysis, including the models used for different data partitions and parameter values, as output by the phylogenetic software IQ-TREE. - Individual tree files in Newick format (plain text) are provided for the phylogeny from concatenated analysis with the best likelihood score ("mem_50p_bestLikelihoodScore"), concatenated likelihood analysis with gene concordance factors ("mem_50p_gcf") and site concordance factors ("mem_50p_scf"). - The tree file from the ASTRAL analysis is "mem_50p_astral". - The zip archive entitled “IQ-TREE analysis results.zip” includes output from the maximum likelihood analysis of the concatenated nucleotide sequence data, including the following: (1) main output file “mem_50p.iqtree” summarizing model selection, partitioning schemes, likelihood scores, and run parameters; (2) “mem_50p.mldist” including pairwise ML distances between taxa; (3) “mem_50p.best_scheme.nex” with the best partitioning scheme identified by ModelFinder in NEXUS format and (4) “mem_50p.best_scheme” the RAxM-compatible version of the same file. - The “Ultrafast bootstrap results.zip” zip archive contains: (1) “mem_50p.ufboot” with the bootstrap replicate trees; (2) “mem_50p.contree” with the majority-rule consensus tree with support values; (3) “mem_50p.splits.nex”, with split support values across the replicates; (4) “mem_50p.log” is the log file. - The “gene_trees.zip” zip archive contains the individual gene trees as input for subsequent coalescent gene tree analysis in the phylogenetic program ASTRAL. - The file "DarniniAHE_Character Matrix.csv" contains the data for 6 morphological characters for which the ancestral states were reconstructed using the phylogenetic results from analysis of anchored-hybrid data (see article text for details). - The file "scriptACRDarnini.txt" contains the commands used to reconstruct ancestral morphological characters states using the corHMM 2.8 R package. See the Methods section of the article for more details.

Please cite as: Wuebbles, D., J. Angel, K. Petersen, and A.M. Lemke, (Eds.), 2021: An Assessment of the Impacts of Climate Change in Illinois. The Nature Conservancy, Illinois, USA. https://doi.org/10.13012/B2IDB-1260194_V1 Climate change is a major environmental challenge that is likely to affect many aspects of life in Illinois, ranging from human and environmental health to the economy. Illinois is already experiencing impacts from the changing climate and, as climate change progresses and temperatures continue to rise, these impacts are expected to increase over time. This assessment takes an in-depth look at how the climate is changing now in Illinois, and how it is projected to change in the future, to provide greater clarity on how climate change could affect urban and rural communities in the state. Beyond providing an overview of anticipated climate changes, the report explores predicted effects on hydrology, agriculture, human health, and native ecosystems.

This repository contains the data and computational analysis notebooks that were used in the following manuscript. For more information on the methods and contributing authors, please refer to the original manuscript. "Beyond A and B Compartments: how major nuclear locales define nuclear genome organization and function Omid Gholamalamdari et al. 2024"

The immunofluorescence and segmented images of three nuclear locales, (nuclear periphery, nuclear speckles, and nucleolus) in four human cells lines (H1-hESC, HCT116, HFFc6, and K562). For each of the cell lines, this dataset includes original, cropped, and binary 4D images (3D + antibody) in addition to max projected thumbnails of cell nuclei.

Coagulation testing (VCM Vet™) was performed on 57 horses with acute abdominal pain at admission to the University of Illinois Veterinary Teaching Hospital. Additional clinical data were recorded retrospectively. ROC analysis was performed to determine the optimal number of abnormal coagulation parameters for coagulopathy diagnosis based on survival. General linear regression (GLM) and random forest (RF) classification models were developed to predict short-term survival. A training cohort of 40 horses was used for model development, and model performance was determined using the remaining 17 horses.

This page contains the data for the publication "The pioneer transcription factor Zelda controls the exit from regeneration and restoration of patterning in Drosophila" published in the journal Science Advances.

Zika virus (ZIKV) infection has been linked to neurological disorders such as microcephaly in children. Cases of Guillain-Barré Syndrome (GBS), a peripheral nervous system (PNS) disorder, have been reported in adults with ZIKV infection. These ZIKV-related GBS cases often exhibit atypical clinical features compared to classic GBS, including central nervous system (CNS) involvement. This dataset comprises two patient groups and a healthy control group. The first patient group includes adults with confirmed ZIKV infection, presenting both PNS-related GBS symptoms and CNS manifestations. The second group consists of adults with GBS but without ZIKV infection. The final group includes healthy, unaffected individuals.

These are the datasets underlying the figures in the manuscript "Methods of active surveillance for hard ticks and associated tick-borne pathogens of public health importance in the contiguous United States: A Comprehensive Systematic Review". The review considered only publications reporting on active tick or tick-borne pathogen surveillance in the contiguous United States published between 1944 and 2018. For the purposes of this review, we were only concerned with studies of Ixodidae (hard ticks) and/or studies of tick-borne pathogens (in humans, animals, or hard ticks) of public health importance to humans. Study designs included cross-sectional, serological, epidemiological, ecological, or observational studies. Only peer-reviewed publications published in the English language were included. Studies were excluded if they focused on a tick that is not a vector of a human pathogen or on a pathogen that does not cause disease in humans, if the tick or tick-borne pathogen findings were incidental, or if they did not include quantitative surveillance data. For the purpose of this study, we defined surveillance data as information on ticks or pathogens provided through active sampling in natural areas; it should be noted that this does not match the strict definition used by the CDC, which requires sustained sampling efforts across time. Studies were also excluded if they: explored regions other than the contiguous US; focused on treatment, vaccine, or therapeutics development and/or diagnostics of human disease; focused on tick or pathogen genetics; focused on experimental studies with ticks or hosts; were tick control and/or management studies; performed only passive surveillance; were review articles; were not peer reviewed; were in a language other than English; the full text was not available; and if the disease was not a risk to the general public. In addition, for articles which reported data that had previously been published, we only included previously unreported information collected by the authors, and we referenced the specific period of collection for these data to ensure we were not double-recording data. Due to publication delays, we also performed a non-systematic review of the literature of articles published between 2019 – 2023 on tick and tickborne pathogen surveillance methods conducted in the contiguous United States. Keyword search was performed in PubMed Central and Web of Science Core Collection databases. The search algorithm keywords included tick(s), Amblyomma, Dermacentor, Ixodes, Rhipicephalus, Acari Ixodidea, tick host(s), Lyme disease, Rocky Mountain Spotted Fever, Spotted Fever Group, Rickettsiosis, Ehrlichiosis, Anaplasmosis, Borreliosis, Tularemia, Babesiosis, tick-borne pathogen, Powassan, Heartland, Bourbon, Colorado tick fever, Pacific Coast tick fever, tick surveillance, surveillance, (sero)epidemiology, prevalence, distribution, ecology, United States. The search algorithm utilized is provided as follows: TI= ((ticks OR Ixodes OR Amblyomma OR Dermacentor OR Rhipicephalus OR "Acari Ixodidi" OR "tick hosts" OR "tick host") OR ("Lyme Disease" OR "Rocky Mountain Spotted Fever" OR "Spotted Fever Group" OR Rickettsiosis OR Rickettsial OR Ehrlichiosis OR Anaplasmosis OR Borreliosis OR Tularemia OR Babesiosis OR Borrelia OR Ehrlichia OR Anaplasma OR Rickettsia OR Babesia OR "tick-borne pathogen" OR "tick borne pathogen")) AND TS= ("tick surveillance" OR surveillance OR epidemiology OR seroepidemiology OR ecology) AND CU=("United States of America" OR "USA" OR "United States" OR United-States). These datasets are the collated data underlying the figures in the manuscript. For more details, please see the publication. The following are explanations for variables used in all the CSV files: Tick: Species of tick collected Tick_Method: Method of collecting ticks Pathogen: Species of pathogen tested for Path_Method: Method of testing for pathogens Decade: Decade of publication n: Number of publications STATE: state in which study was conducted COUNTY: county in which study was conducted 1944 - 2018 (Was surveillance performed?): was there at least one publication included with a publication date within the 1944-2018 period in this geographic region? 2019 - 2023 (Was surveillance performed?): was there at least one publication included with a publication date within the 2019-2023 period in this geographic region?

Data for the invertebrate analysis in chapter 2 of Jacob Ridgway's thesis: "Neonicotinoids and Fungicides Alter Soil Invertebrate Abundance and Richness Within Restored Prairie"

ICoastalDB, which was developed using Microsoft structured query language (SQL) Server, consists of water quality and related data in the Illinois coastal zone that were collected by various organizations. The information in the dataset includes, but is not limited to, sample data type, method of data sampling, location, time and date of sampling and data units.

This dataset contains white-tailed deer (Odocoileus virginianus) land cover utility score (deer LCU score) data for every TRS (township, range, and section), township-range, and county in Illinois, USA, based on annual National Land Cover Database (NLCD) data released for all years between 2000 and 2023. LCU data is provided in CSV files for each spatial scale, with TRS data split into 2 CSV files due to size limits. Rasters (TIF) showing all deer habitat in Illinois are also provided to show the location, quality, and quantity of deer habitat. A metadata file is also included for additional information.

This dataset contains raw data of plasma glucose, insulin, c-peptide, GLP-1, and FGF21 collected as part of a study aimed to study alcohol pharmacokinetics in women who underwent metabolic surgery.

The files are plain text and contain the original data used in phylogenetic analyses of of Typhlocybinae (Bin, Dietrich, Yu, Meng, Dai and Yang 2022: Ecology & Evolution, in press). The three files with extension .phy are text files with aligned DNA sequences in the standard PHYLIP format and correspond to Matrix 1 (amino acid alignment), Matrix 2 (nucleotide alignment of first two codon positions of protein-coding genes) and Matrix 3 (nucleotide alignment of protein-coding genes plus 2 ribosomal genes) described in the Methods section. An additional text file in NEXUS format (.nex extension) contains the morphological character data used in the ancestral state reconstruction (ASCR) analysis described in the Methods. NEXUS is a standard format used by various phylogenetic analysis software. For more information on data file content, see the included "readme" files.

The Membracoidea_morph_data_Final.nex text file contains the original data used in the phylogenetic analyses of Dietrich et al. (Insect Systematics and Diversity, in review). The text file is marked up according to the standard NEXUS format commonly used by various phylogenetic analysis software packages. The file will be parsed automatically by a variety of programs that recognize NEXUS as a standard bioinformatics file format. The complete taxon names corresponding to the 131 genus names listed under “BEGIN TAXA” are listed in Table 1 in the included PDF file “Taxa_and_characters”; the 229 morphological characters (names abbreviated under under “BEGIN CHARACTERS” are fully explained in the list of character descriptions following Table 1 in the same PDF). The data matrix follows “MATRIX” and gives the numerical values of characters for each taxon. Question marks represent missing data. The lists of characters and taxa and details on the methods used for phylogenetic analysis are included in the submitted manuscript.

The following files include specimen information, DNA sequence data, and additional information on the analyses used to reconstruct the phylogeny of the leafhopper genus Neoaliturus as described in the Methods section of the original paper: 1. Taxon_sampling.csv: contains data on the individual specimens from which DNA was extracted, including sample code, taxon name, collection data (locality, date and name of collector) and museum unique identifier. 2. Alignments.zip: a ZIP archive containing 432 separate FASTA files representing the aligned nucleotide sequences of individual gene loci used in the analysis. 3. Concatenated_Matrix.fa: is a FASTA file containing the concatenated individual gene alignments used for the maximum likelihood analysis in IQ-TREE. 4. Genes_and_Loci.rtf: identifies the individual genes and loci used in the analysis. The partition name is the same as the name of the individual alignment file in the zipped Alignments folder. 5. Partitions_best_scheme.nex: is a text file in the standard NEXUS format that indicates the names of the individual data partitions and their locations in the concatenated matrix, and also indicates the substitution model for each partition. 6. (New in this version 2) Scripts & Description.zip includes 8 custom shell or perl scripts used to assemble the DNA sequence data by perform reciprocal blast searches between the reference sequences and assemblies for each sample, extract the best sequences based on the blast searches, screen the hits for each locus and keep only the best result, and generate the nucleotide sequence dataset for the predicted orthologues (see the file description.txt for details). 7. (New in this version 2) Full_genetic_distances_matrix.csv shows the genetic distances between pairs of samples in the datset (proportion of nucleotides that differ between samples).

The following seven zip files are compressed folders containing the input datasets/trees, main output files and the scripts of the related analyses performed in this study. I. ancestral_microhabitat_reconstruction.zip: contains four files, including two input files (microhabitats.csv, timetree.tre) and a script (simmap_microhabitat.R) for ancestral states reconstruction of microhabitat by make.simmap implemented in the R package phytools v1.5, as well as the main output file (ancestral_microhabitats.csv). 1. ancestral_microhabitats.csv: reconstructed ancestral microhabitats for each node. 2. microhabitats.csv: microhabitats of the studies species. 3. simmap_microhabitat.R: the R script of make.simmap for ancestral microhabitat reconstruction 4. timetree.tre: dated tree used for ancestral state reconstruction for microhabitat and morphological characters II. ancestral_morphology_reconstruction.zip: contains six files, including an input file (morphology.csv) and a script (simmap_morphology.R) for ancestral states reconstruction of morphology by make.simmap implemented in the R package phytools v1.5, as well as four main output files(forewing_ancestral_state.csv, frontal_sutures_ancestral_state.csv, hind_wing_ancestral_state.csv, ocellus_ancestral_state.csv). 1. forewing_ancestral_state.csv: reconstructed ancestral states of the development of the forewing for each node. 2. frontal_sutures_ancestral_state.csv: reconstructed ancestral states of the development of frontal sutures for each node. 3. hind_wing_ancestral_state.csv: reconstructed ancestral states of the development of the hind wing for each node. 4. morphology.csv: the states of the development of ocellus, forewing, hing wing and frontal sutures for each studies species. 5. ocellus_ancestral_state.csv: reconstructed ancestral states of the development of the ocellus for each node. 6. simmap_morphology.R: the R script of make.simmap for ancestral state reconstruction of morphology III. biogeographic_reconstruction.zip: contains four files, including three input files (dispersal_probablity.txt, distributions.csv, timetree_noOutgroup.tre) used for a stratified biogeographic analysis by BioGeoBEARS in RASP v4.2 and the main output file (DIVELIKE_result.txt). 1. dispersal_probablity.txt: relative dispersal probabilities among biogeographical regions at different geological epochs. 2. distributions.csv: current distributions of the studied species. 3. DIVELIKE_result.txt: BioGeoBEARS result of ancestral areas based on the DIVELIKE model. 4. timetree_noOutgroup.tre: the dated tree with the outgroup lineage (Eurymelinae) excluded. IV. coalescent_analysis.zip: contains a folder and two files, including a folder (individual_gene_alignment) of input files used to construct gene trees, an input file (MLtree_BS70.tre) used for the multi-species coalescent analysis by ASTRAL v 4.10.5 and the main output file (coalescent_species_tree.tre). 1. coalescent_species_tree.tre: the species tree generated by the multi-species coalescent analysis with the quartet support, effective number of genes and the local posterior probability indicated. 2. individual_gene_alignment: a folder containing 427 FASTA files, each one represents the nucleotide alignment for a gene. Hyphens are used to represent gaps. These files were used to construct gene trees using IQ-TREE v1.6.12. 3. MLtree_BS70.tre: 165 gene trees with the average SH-aLRT and ultrafast bootstrap values of ≥ 70%. This file was used to estimate the species tree by ASTRAL v 4.10.5. V. divergence_time_estimation.zip: contains five files, including two input files (treefile_rooted_noBranchLength.tre, treefile_rooted.tre) and two control files (baseml.ctl, mcmctree.ctl) used for divergence time estimation by BASEML and MCMCTREE in PAML v4.9, as well as the main output file (timetree_with95%HPD.tre). 1. baseml.ctl: the control file used for the estimation of substitution rates by BASEML in PAML v4.9. 2. mcmctree.ctl: the control file used for the estimation of divergence times by MCMCTREE in PAML v4.9. 3. timetree_with95%HPD.tre: dated tree with the 95% highest posterior density confidence intervals indicated. 4. treefile_rooted_noBranchLength.tre: the maximum likelihood tree based on the concatenated nucleotide dataset with calibrations for the crown and internal nodes. Branch length and support values were not indicated. 5. treefile_rooted.tre: the maximum likelihood tree based on the concatenated nucleotide dataset with a secondary calibration on the root age. Branch support values were not indicated. VI. maximum_likelihood_analysis_aa.zip: contains three files, including two input files (concatenated_aa_partition.nex, concatenated_aa.phy) used for the maximum likelihood analysis by IQ-TREE v1.6.12 and the main output file (MLtree_aa.tre). 1. concatenated_aa_partition.nex: the partitioning schemes for the maximum likelihood analysis using concatenated_aa.phy. This file partitions the 52,024 amino acid positions into 427 character sets. 2. concatenated_aa.phy: a concatenated amino acid dataset with 52,024 amino acid positions. Hyphens are used to represent gaps. This dataset was used for the maximum likelihood analysis. 3. MLtree_aa.tre: the maximum likelihood tree based on the concatenated amino acid dataset, with SH-aLRT values and ultrafast bootstrap values indicated. VII. maximum_likelihood_analysis_nt.zip: contains three files, including two input files (concatenated_nt_partition.nex, concatenated_nt.phy) used for the maximum likelihood analysis by IQ-TREE v1.6.12 and the main output file (MLtree_nt.tre). 1. concatenated_nt_partition.nex: the partitioning schemes for the maximum likelihood analysis using concatenated_nt.phy. This file partitions the 156,072 nucleotide positions into 427 character sets. 2. concatenated_nt.phy: a concatenated nucleotide dataset with 156,072 nucleotide positions. Hyphens are used to represent gaps. This dataset was used for the maximum likelihood analysis as well as divergence time estimation. 3. MLtree_nt.tre: the maximum likelihood tree based on the concatenated nucleotide dataset, with SH-aLRT values and ultrafast bootstrap values indicated. VIII. Taxon_sampling.csv: contains the sample IDs (1st column) which were used in the alignments and the taxonomic information (2nd to 6th columns).

The complete data for the publication "RNA helicase MOV10 suppresses fear memory and dendritic arborization and regulates microtubule dynamics in hippocampal neurons," excluding sequencing data deposited in GEO, is provided here.

This is the data set for a publication titled, "Coupling carbon dioxide gas within a bubble curtain enhances its effectiveness to deter fish." The current study sought to quantify whether adding carbon dioxide gas (CO2) to a bubble curtain would enhance its efficacy to block fish. For this, a choice tank was outfitted with bubble curtains infused with either compressed air alone, or with two different concentrations of CO2 [30 or 100 mg/L]. Passage rates and position of common carp (an invasive Cyprinid) and black bullhead (a native Ictalurid) exposed to these treatments were compared. The data set consists of data from each of the experiments performed during the study.

These data represent the raw data from the paper “Influence of light availability and water depth on competition between Phalaris arundinacea and herbaceous vines” published in Wetlands by Annie H. Huang and Jeffrey W. Matthews. The data are archived in one file: Huang&Matthews_mesocosm_data_archive. This file includes raw data collected during a greenhouse experiment described in the paper.

Data from a study on the behavior of blue-winged and golden-winged warblers. We were investigating vocalizations and how the species reconizes each other. There are banding, behavioral data from a playback study, and song data.