University Library, University of Illinois at Urbana-Champaign

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).

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.

This is the notebook and data for using CyberGISX to conduct analysis using Array of Things (AoT) data in the Chicago area. The notebook Spatial_interpolation.ipynb illustrates the spatial interpolation of temperature in the Chicago area using the dataset. And the notebook Urban_Informatics.ipynb helps to explore the dataset. The files included in this dataset functions as follows: 1) Spatial_interpolation.ipynb is a python based Jupyter notebook that enables users to conduct spatial interpolation with AoT data; 2) Urban_Informatics.ipynb is a Jupyter notebook that helps to explore the AoT dataset; 3) chicago-complete.weekly.2019-09-30-to-2019-10-06.tar includes all the high-frequency urban sensing data from AoT sensors from 2019 September 30th to 2019 October 6th collected in Chicago, US; 4) sensors.csv is a processed dataset including information about the temperature in Chicago, and it is used in Spatial_interpolation.ipynb.

In a set of field studies across four years, the effect of self-shading on photosynthetic performance in lower canopy sorghum leaves was studied at sites in Champaign County, IL. Photosynthetic parameters in upper and lower canopy leaves, carbon assimilation, electron transport, stomatal conductance, and activity of three C4-specific photosynthetic enzymes, were compared within a genetically diverse range of accessions varying widely in canopy architecture and thereby in the degree of self-shading. Accessions with erect leaves and high light transmission through the canopy are henceforth referred to as ‘erectophile’ and those with low leaf erectness, ‘planophile’. In the final year of the study, bundle sheath leakiness in erectophile and planophile accessions was also compared.

This dataset contains the RegCM4 simulations used in the article " Implementation of dynamic ageing of carbonaceous aerosols in regional climate model RegCM". This dataset was used to investigate the impact of a new aging parameterisation scheme implemented in a regional climate model RegCM4. The dataset contains two sets of simulations: Expt_fix and Expt_dyn. It consists of the seasonal mean and daily mean values of the variables that were used to create the visualizations of this study. The Expt_fix and Expt_dyn dataset contain 34 and 38 NetCDF files, respectively. The CERES_vs_2expts_new.mat file is the comparison between CERES shortwave downward flux at the surface and same model outputs from two experiments for clear sky and all sky conditions. -------------------------------------------------- The following information about the dataset was generated on 2021-01-08 by SUDIPTA GHOSH <b>GENERAL INFORMATION</b> <i>1. Date of data collection (single date, range, approximate date):</i> 2019-01-01 to 2019-12-31 <i>2. Geographic location of data collection:</i> Urbana-Champaign,Illinois, USA <i>3. Information about funding sources that supported the collection of the data:</i> This work is supported by the MoEFCC under the NCAP-COALESCE project [Grant No. 14/10/2014-CC]. The first author acknowledges DST-INSPIRE fellowship [IF150055] and Fulbright-Kalam Climate Doctoral fellowship. N. R. acknowledges funding from NSF AGS-1254428 and DOE grant DE-SC0019192. Department of Science and Technology, Funds for Improvement of Science and Technology infrastructure in universities and higher educational institutions (DST-FIST) grant (SR/FST/ESII-016/2014) are acknowledged for the computing support. <b>DATA & FILE OVERVIEW</b> <i>1. File List:</i> Expt_fix and Expt_dyn datasets contain the analysed seasonal means and daily means of the variables that have been used to create the visualizations of this study. Each of the Expt_fix and Expt_dyn datasets contains 34 and 38 NetCDF files, respectively. <i>2. Relationship between files, if important:</i> NA <i>3. Additional related data collected that was not included in the current data package:</i> No <b>METHODOLOGICAL INFORMATION</b> <i>1. Description of methods used for collection/generation of data: </i> The model RegCM4 code is freely available online from <a href="http://gforge.ictp.it/gf/project/regcm/">http://gforge.ictp.it/gf/project/regcm/</a>. The anthropogenic aerosol emissions considered for the simulations are taken from IIASA inventory. The data used can be easily accessed online <a href="http://clima-dods.ictp.it/regcm4/">http://clima-dods.ictp.it/regcm4/</a> website. TRMM observed precipitation data can be assessed from <a href="https://giovanni.gsfc.nasa.gov/giovanni/">https://giovanni.gsfc.nasa.gov/giovanni/</a> website. CRU temperature data is available at <a href="https://crudata.uea.ac.uk/cru/data/hrg/">https://crudata.uea.ac.uk/cru/data/hrg/</a>. CERES satellite surface shortwave downward fluxes are available at <a href="https://ceres.larc.nasa.gov/data/">https://ceres.larc.nasa.gov/data/</a> website. Input files for the RegCM4 model are archived in <a href="http://clima-dods.ictp.it/regcm4/">http://clima-dods.ictp.it/regcm4/</a> website. This dataset contains the RegCM4 simulations used in the article " Implementation of dynamic ageing of carbonaceous aerosols in regional climate model RegCM ". Two sets of simulations: Expt_fix and Expt_dyn consists of the output data . This dataset only contains the analysed seasonal mean and daily mean of the variables that have been used to create the visualizations of this study. Each of Expt_fix and Expt_dyn contains 34 and 38 NetCDF files respectively. This dataset was used to investigate the impact of a new aging parameterisation scheme implemented in a regional climate model RegCM4. <i>2. Methods for processing the data:</i> Seasonal Mean and daily average values were extracted from 6-hourly model output. <i>3. Instrument- or software-specific information needed to interpret the data:</i> CDO-1.7.1, Grads-2.0.a9, Matlab2016b <i>4. Standards and calibration information, if appropriate:</i> NA <i>5. Environmental/experimental conditions:</i> NA <i>6. Describe any quality-assurance procedures performed on the data:</i> NA <i>7. People involved with sample collection, processing, analysis and/or submission:</i> Sudipta Ghosh, Nicole Riemer, Graziano Giuliani, Filippo Giorgi, Dilip Ganguly, Sagnik Dey <b>DATA-SPECIFIC INFORMATION FOR: Expt_fix_data.tar.gz</b> <i>1. Number of variables:</i> 29 <i>2. Number of cases/rows:</i> NA <i>3. Variable List:</i> Mass concentration (Kg m-3) of BC, BC_HB, BC_HL, OC, OC_HB, OC_HL; Columnar burden (mg m-2)] of BC, BC_HL, BC_HB, OC; Dry deposition flux (mg m-2 day-1) of BC_HB, BC_HL, OC_HB, OC_HL; Wet deposition flux due washout (mg m-2 day-1) of BC_HB, BC_HL, OC_HB, OC_HL; Wet deposition flux due to rainout (mg m-2 day-1) of BC_HB, BC_HL OC_HB, OC_HL; AOD (unit less), precipitation (Kg m-2 s-1), temperature (K) , v-wind (m s-1), u-wind (m s-1), Surface shortwave downward flux (W m-2), Shortwave radiative forcing at the surface and top of atmosphere (W m-2) <b>DATA-SPECIFIC INFORMATION FOR: Expt_dyn_data.tar.gz</b> <i>1. Number of variables:</i> 30 <i>2. Number of cases/rows:</i> NA <i>3. Variable List:</i> Mass concentration (Kg m-3) of BC, BC_HB, BC_HL, OC, OC_HB, OC_HL; Columnar burden (mg m-2)] of BC, BC_HL, BC_HB, OC; Dry deposition flux (mg m-2 day-1) of BC_HB, BC_HL OC_HB, OC_HL; Wet deposition flux due washout (mg m-2 day-1) of BC_HB, BC_HL OC_HB, OC_HL; Wet deposition flux due to rainout (mg m-2 day-1) of BC_HB, BC_HL OC_HB, OC_HL; AOD (unit less); precipitation (Kg m-2 s-1); temperature (K); v-wind (m s-1); u-wind (m s-1); Surface shortwave downward flux (W m-2); Shortwave radiative forcing at the surface and top of atmosphere (W m-2); ageingscale (s-1) <b>DATA-SPECIFIC INFORMATION FOR: CERES_vs_2expts_new.mat</b> <i>1. Number of variables:</i> 12 <i>2. Number of cases/rows:</i> NA <i>3. Variable List:</i> Surface shortwave downward flux for clear sky (W/m-2) for CERES, Expt_fix, Expt_dyn (for winter JF and monsoon JJAS seasons); Surface shortwave downward flux for all sky conditions (W/m-2) for CERES, Expt_fix, Expt_dyn (for winter JF and monsoon JJAS seasons). <b>NOTE:</b> The following information applies for all three (3) files: <i> Missing data codes:</i> NA <i>Specialized formats or other abbreviations used:</i> NA

These data were used in the survival and cause-specific mortality analyses of translocated nuisance American black bear in Wisconsin published in Animal Conservation (Bauder, J.M., N.M. Roberts, D. Ruid, B. Kohn, and M.L. Allen. Accepted. Lower survival of nuisance American black bears (Ursus americanus) is not due to translocation. Animal Conservation). Included are CSV files including each bear's capture history and associated covariates and meta-data for each CSV file. Also included is an example R script of how to conduct the analyses (this R script is also included as supporting information with the published paper).

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.

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.

Coups d'état are important events in the life of a country. They constitute an important subset of irregular transfers of political power that can have significant and enduring consequences for national well-being. There are only a limited number of datasets available to study these events (Powell and Thyne 2011, Marshall and Marshall 2019). Seeking to facilitate research on post-WWII coups by compiling a more comprehensive list and categorization of these events, the Cline Center for Advanced Social Research (previously the Cline Center for Democracy) initiated the Coup D'état Project (CDP) as part of its Societal Infrastructures and Development (SID) project. More specifically, this dataset identifies the outcomes of coup events (i.e. realized or successful coups, unrealized coup attempts, or thwarted conspiracies) the type of actor(s) who initiated the coup (i.e. military, rebels, etc.), as well as the fate of the deposed leader. This is version 2.0.0 of this dataset. The first version, <a href="https://clinecenter.illinois.edu/project/research-themes/democracy-and-development/coup-detat-project-cdp ">v.1.0.0</a>, was released in 2013. Since then, the Cline Center has taken several steps to improve on the previously-released data. These changes include: <ol> <li>Filling in missing event data values</li> <li>Removing events with no identifiable dates</li> <li>Reconciling event dates from sources that have conflicting information</li> <li>Removing events with insufficient sourcing (each event now has at least two sources)</li> <li>Removing events that were inaccurately coded and did not meet our definition of a coup event</li> <li>Extending the time period covered from 1945-2005 to 1945-2019</li> <li>Removing certain variables that fell below the threshold of inter-coder reliability required by the project</li> <li>The spreadsheet ‘CoupInventory.xls’ was removed because of inadequate attribution and citation in the event summaries</li></ol> <b>Items in this Dataset</b> 1. <i>CDP v.2.0.2 Codebook.pdf</i> <ul><li>This 14-page document provides a description of the Cline Center Coup D’état Project Dataset. The first section of this codebook provides a succinct definition of a coup d’état used by the CDP and an overview of the categories used to differentiate the wide array of events that meet the CDP definition. It also defines coup outcomes. The second section describes the methodology used to produce the data. <i>Created November 2020. Revised February 2021 to add some additional information about how the Cline Center edited some values in the COW country codes."</i> </li></ul> 2. <i>Coup_Data_v2.0.0.csv</i> <ul><li>This CSV (Comma Separated Values) file contains all of the coup event data from the Cline Center Coup D’etat Project. It contains 29 variables and 943 observations. <i>Created November 2020</i></li></ul> 3. <i>Source Document v2.0.0.pdf</i> <ul><li>This 305-page document provides the sources used for each of the coup events identified in this dataset. Please use the value in the coup_id variable to identify the sources used to identify each particular event. <i>Created November 2020</i> </li></ul> 4. <i>README.md</i> <ul><li>This file contains useful information for the user about the dataset. It is a text file written in mark down language. <i>Created November 2020</i> </li></ul> <br> <b> Citation Guidelines</b> 1) To cite this codebook please use the following citation: Peyton, Buddy, Joseph Bajjalieh, Dan Shalmon, Michael Martin, and Jonathan Bonaguro. 2021. “Cline Center Coup D’état Project Dataset Codebook”. Cline Center Coup D’état Project Dataset. Cline Center for Advanced Social Research. V.2.0.2. February 23. University of Illinois Urbana-Champaign. doi: <a href="https://doi.org/10.13012/B2IDB-9651987_V2">10.13012/B2IDB-9651987_V3</a> 2) To cite the data please use the following citation: Peyton, Buddy, Joseph Bajjalieh, Dan Shalmon, Michael Martin, and Jonathan Bonaguro. 2020. Cline Center Coup D’état Project Dataset. Cline Center for Advanced Social Research. V.2.0.0. November 16. University of Illinois Urbana-Champaign. doi: <a href="https://doi.org/10.13012/B2IDB-9651987_V2">10.13012/B2IDB-9651987_V3</a>

Data from census of peer-reviewed papers discussing nosZ and published from 2013 to 2019. These data were reported in the manuscript titled, "Beyond denitrification: the role of microbial diversity in controlling nitrous oxide reduction and soil nitrous oxide emissions" published in Global Change Biology as an Invited Report.

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 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.

This dataset consists of microclimatic temperature and vegetation structure maps at a 3-meter spatial resolution across the Great Smoky Mountains National Park. Included are raster models for sub-canopy, near-surface, minimum and maximum temperature averaged across the study period, season, and month during the growing season months of March through November from 2006-2010. Also available are the topographic and vegetation inputs developed for the microclimate models, including LiDAR-derived vegetation height, LiDAR-derived vegetation structure within four height strata, solar insolation, distance-to-stream, and topographic convergence index (TCI).

High-speed X-ray videos of four E. abruptus specimens recorded at the Advanced Photron Source (Argonne National lab) in the Summer of 2018 and corresponding position data of landmarks tracked during the motion. See readme file for more details.

These datasets provide the basis of our analysis in the paper - The Potential Impact of a Clean Energy Society On Air Quality. All datasets here are from the model output (CAM4-chem). All the simulations were run to steady-state and only the outputs used in the analysis are archived here.

We measured the effects of fire or drought treatment on plant, microbial and biogeochemical responses in temperate deciduous forests invaded by the annual grass Microstegium vimineum with a history of either frequent fire or fire exclusion. Please note, on Documentation tab / Experimental or Sampling Design, “15 (XVI)” should be “16 (XVI)”.

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.

Dataset associated with Zenzal et al. Oikos submission: Retreat, detour, or advance? Understanding the movements of birds confronting the Gulf of Mexico. https://doi.org/10.1111/oik.07834 Four CSV files were used for analysis and are related to the following subsections under the “Statistics” heading in the “Materials and Methods” section of the journal article: 1. Departing the Edge = “AIC Analysis.csv” 2. Comparing Retreating to Advancing = “Advance and Retreat Analysis.csv” and “Wind Data at Departure.csv” 3. Food Abundance = “Fruit Data.csv” and “Arthropod Data.csv” <b>Description of variables:</b> Year: the year in which data were collected. Departure: the direction in which an individual departed the Bon Secour National Wildlife Refuge. “North” indicates an individual that departed ≥315° or <45°; “Circum” indicates an individual that departed east (45 – 134°) or west ( 225 – 314°); “Trans” indicates an individual that departed south (135 – 224°). Age: the age of an individual at capture. Individuals were aged as hatch year (HY) or after hatch year (AHY) according to Pyle (1997; see related article for full citation). Fat: the fat score of an individual at capture. Individuals were scored on a 6-point scale ranging from 0-5 following Helms and Drury (1960; see related article for full citation). Species: the standardized four letter alphabetic code used as an abbreviation for English common names of North American Birds. SWTH: Catharus ustulatus; REVI: Vireo olivaceus; INBU: Passerina cyanea; WOTH: Hylocichla mustelina; RTHU: Archilochus colubris. FTM_SD: stopover duration or number of days between first capture and departure from automated radio telemetry system coverage at the Bon Secour National Wildlife Refuge. TMB_SD: stopover duration or number of days between first and last detection from automated radio telemetry systems north of Mobile Bay, AL, USA. Mean speed north (km/hr): the northbound travel speed of individuals retreating from the Bon Secour National Wildlife Refuge by determining the time when the signal strength indicated the bird was directly east or west of the automated telemetry system and dividing the amount of time it took for an individual to move in an assumed straight path between the Refuge systems and those north of Mobile Bay, AL, USA. Mean speed south (km/hr): the southbound travel speed of individuals advancing from north of Mobile Bay, AL, USA by determining the time when the signal strength indicated the bird was directly east or west of the automated telemetry system and dividing the amount of time it took for an individual to move in an assumed straight path between the Refuge systems and those north of Mobile Bay, AL, USA. LN_FTM_DEP_TIME: the natural log of departure time from the Bon Secour National Wildlife Refuge. Departure time is defined as the number of hours before or after civil twilight. LN_TMB_DEP_TIME: the natural log of departure time from north of Mobile Bay, AL, USA. Departure time is defined as the number of hours before or after civil twilight. Paired_FTM_DEP_TIME: the departure time or number of hours before or after civil twilight from Bon Secour National Wildlife Refuge. Paired_TMB_DEP_TIME: the departure time or number of hours before or after civil twilight from north of Mobile Bay, AL, USA. Wind Direction: the direction from which the wind originated at the Bon Secour National Wildlife Refuge on nights when individuals were departing. “N” indicates winds from the north (≥315° or <45°); “E” indicates winds from the east (45 – 134°); “W” indicates winds from the west ( 225 – 314°); “S” indicates winds from the south (135 – 224°). Wind Speed (m/s): the wind speed on nights when individuals were departing the Bon Secour National Wildlife Refuge. Group: the direction the bird was traveling under specific wind conditions. Northbound individuals traveled north from Bon Secour National Wildlife Refuge. Southbound individuals traveled south from habitats north of Mobile Bay, AL, USA. Fruit: weekly mean number of ripe fruit per meter. Site: the site from which the data were collected. FTM is located within the Bon Secour National Wildlife Refuge. TMB is located within the Jacinto Port Wildlife Management Area. DOY: number indicating day of year (i.e., 1 January = 001….31 December = 365). Arthropod Biomass: estimated mean arthropod biomass from each sampling period. <b>Note:</b> Empty cells indicate unavailable data where applicable.

*This is the third version of the dataset*. New changes in this 3rd version: <i>1.replaces simulations where the initial condition consists of a sinusoidal channel with topographic perturbations with simulations where the initial condition consists of a sinusoidal channel without topographic perturbations. These simulations better illustrate the transformation of a nondendritic network into a dendritic one. 2. contains two additional simulations showing how total domain size affects the landscape's dynamism. 3. changes dataset title to reflect the publication's title</i> This dataset contains data from 18 simulations using a landscape evolution model. A landscape evolution model simulates how uplift and rock incision shape the Earth's (or other planets) surface. To date, most landscape evolution models exhibit "extreme memory" (paper: https://doi.org/10.1029/2019GL083305 and dataset: https://doi.org/10.13012/B2IDB-4484338_V1). Extreme memory in landscape evolution models causes initial conditions to be unrealistically preserved. This dataset contains simulations from a new landscape evolution model that incorporates a sub-model that allows bedrock channels to erode laterally. With this addition, the landscapes no longer exhibit extreme memory. Initial conditions are erased over time, and the landscapes tend towards a dynamic steady state instead of a static one. The model with lateral erosion is named LEM-wLE (Landscape Evolution Model with Lateral Erosion) and the model without lateral erosion is named LEM-woLE (Landscape Evolution Model without Lateral Erosion). There are 16 folders in total. Here are the descriptions: <i>>LEM-woLE_simulations:</i> This folder contains simulations using LEM-woLE. Inside the folder are 5 subfolders containing 100 elevation rasters, 100 drainage area rasters, and 100 plots showing the slope-area relationship. Elevation depicts the height of the landscape, and drainage area represents a contributing area that is upslope. Each folder corresponds to a different initial condition. Driver files and code for these simulations can be found at https://github.com/jeffskwang/LEM-wLE. <i>>MOVIE_S#_data:</i> There are 13 data folders that contain raster data for 13 simulations using LEM-wLE. Inside each folder are 1000 elevation rasters, 1000 drainage area rasters, and 1000 plots showing the slope-area relationship. Driver files and code for these simulations can be found at https://github.com/jeffskwang/LEM-wLE. <i>>movies_mp4_format:</i> For each data folder there are 3 movies generated that show elevation (a), drainage area (b), and erosion rates (c). These files are formatted in the mp4 format and are best viewed using VLC media player (https://www.videolan.org/vlc/index.html). <i>>movies_wmv_format:</i> This folder contains the same movies as the "movies_mp4_format" folder, but they are in a wmv format. These movies can be viewed using Windows media player or other Windows platform movie software. The associated publication for this dataset has not yet been published, and we will update this description with a link when it is.

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 dataset contains the amino acid and nucleotide alignments corresponding to the phylogenetic analyses of South et al. 2020 in Systematic Entomology. This dataset also includes the gene trees that were used as input for coalescent analysis in ASTRAL.

These datasets were performed to assess whether color pattern phenotypes of the polymorphic tortoise beetle, Chelymorpha alternans, mate randomly with one another, and whether there are any reproductive differences between assortative and disassortative pairings.

Dataset associated with Hoover et al AUK-19-093 submission: Local conspecific density does not influence reproductive output in a secondary cavity-nesting songbird. Excel CSV with all of the data used in analyses. Description of variables YEARS: year ORDINAL_DATE: number for what day of the year it is with 1 January = 1,……30 December = 365 SITE: acronym for each study site BOX: unique nest box identifier on each study site TREAT: designates whether nest box was in a high- or low- nest box density area within each study site ACTUAL_NO_NEIGHBORS: number of pairs of warblers using a nest box within 200 m of a given pair’s nest box CLUTCH_SIZE: number of warbler eggs in nest at the onset of incubation PROWN: number of warbler nestlings once eggs have hatched PROWF: number of warbler nestlings that fledged out of the nest box HATCH_SUCCESS: proportion of eggs in the nest that hatched FLEDG_SUCCESS: proportion of the nestlings that fledged from the nest box HATCH_SUCCESS2: binary category where “0” indicates there was some, and “1” indicates there was no hatching failure FLEDG_SUCCESS2: binary category where “0” indicates there was some, and “1” indicates there was no nestling failure (i.e. nestling death) BHCO_PARASIT2: binary category where “0” indicates no cowbird parasitism, and “1” indicates there was cowbird parasitism BHCOE: number of cowbird eggs in clutch BHCOF: number of cowbird nestlings that fledged from the nest PAIRID: unique number that identifies a male and female warbler that are together at a nest box and this number is the same in a subsequent nesting attempt or year if the same male and female are together again FEMALE_ID: unique identifier for each female which represents her leg band combination. Each letter represents a band with letters preceding the hyphen being on the right leg and after the hyphen the left leg FEM_AGE: binary category where “0” indicates a 1-year-old bird and “1” indicates a >1-year-old bird FEMALE_BREEDING_ATTEMPT: “1” indicates first, “2” indicates second,……..breeding attempt within a given year SECOND_ATTEMPT: for any female that fledged a brood in a given year, binary category where “0” represents that they did not, and “1” indicates that they did attempt a second brood that year F_TOT_PROWF: total reproductive output (number of warbler fledglings produced) for a given female in a given year MALE_ID: unique identifier for each male which represents his leg band combination. Each letter represents a band with letters preceding the hyphen being on the right leg and after the hyphen the left leg MALE_AGE2: binary category where “0” indicates a 1-year-old bird and “1” indicates a >1-year-old bird Provisioning_rate: total number of food provisions per nestling per hour by male and female warbler combined BROOD_MASS: average nestling mass (g) for the brood BROOD_TARSUS: average nestling tarsus length (mm) for the brood Brood_condition: unit-less index of nestling condition that uses the residuals of the BROOD_MASS/BROOD_TARSUS relationship A period (“.”) represents where data were not collected, not available, or because individual nest or female did not qualify for consideration of a category assignment. An empty cell represents no data available for this particular cell.

The dataset includes the data used in the study of Classical Topological Order in the Kinetics of Artificial Spin Ice. This includes the photoemission electron microscopy intensity measurement of artificial spin ice at different temperatures as a function of time. The data includes the raw data, the metadata, and the data cookbook. Please refer to the data cookbook for more information. Note: vertex_population.xlsx file in the meta_data_code folder can be disregarded.

Data were used to analyze patterns in predator-specific nest predation on shrubland birds in Illinois as related to landscape composition at multiple landscape scales. Data were used in a Journal of Applied Ecology research paper of the same name. Data were collected between 2011 and 2014 at sites in east-central and northeastern Illinois, USA as part of a Ph.D. research project on the relationship between avian nest predation and landscape characteristics, and how nest predation affects adult and nestling bird behavior.