In the study “CLIMATE-LIMITED VEGETATION CHANGE IN THE CONTERMINOUS UNITED STATES OF AMERICA”, published in the Global Change Biology journal, we evaluated the effects of climate conditions on vegetation composition and distribution in the conterminous United States (CONUS). To disentangle the direct effects of climate change from different non-climate factors, we applied "Liebig's law of the minimum" in a geospatial context, and determined the climate-limited potential for tree, shrub, herbaceous, and non-vegetation fractional cover change. We then compared these potential rates against observed change rates for the period 1986 to 2018 to identify areas of the CONUS where vegetation change is likely being limited by climatic conditions. This dataset contains the input and the resulting rasters for the study which include a) the observed rates of vegetation change, b) the climate derived potential vegetation rates of change, c) the difference between potential and observed values and d)...

This database compiles soybean phenology data to address significant variations in soybean adaptation and development caused by genetic improvements and regional climatic differences. The dataset includes growth staging information collected from field experiments conducted across 11 location-years in Arkansas, Minnesota, Ohio, Virginia, and Wisconsin (USA) during 2017 and 2018. It incorporates data from commercial soybean varieties spanning maturity groups 0 to 7.5. Growth stages were determined using Fehr and Caviness (1977) approach. This dataset is intended as a resource for the scientific community, students, and stakeholders, providing soybean phenological data to improve predictions and decision-making in areas such as input timing, yield estimation, irrigation management, cultivar selection, and phenotyping., This study examined changes in soybean phenology to determine growth stages, focusing on the influence of genetic improvements and regional climatic differences. The dataset includes data from field experiments conducted across 11 location-years in Arkansas, Minnesota, Ohio, Virginia, and Wisconsin (USA) during 2017 and 2018. The experiments followed a randomized complete block split-plot design with four replications. The commercial soybean varieties planted across these location-years ranged from maturity group 0 to 7.5. This dataset contains soybean phenology data assessed using the Fehr and Caviness (1977) approach. For that, we collected daily (minimum of three times per week) growth staging, plant growth characteristics (e.g., number of nodes), grain yield, and composition., , # Soybean phenology dataset for determining soybean growth stages

https://doi.org/10.5061/dryad.2bvq83c20

Description of the data and file structure

This dataset contains soybean phenology data assessed using the Fehr and Caviness (1977) approach. For that, we collected daily (minimum of three times per week) growth staging, plant growth characteristics (e.g., number of nodes), grain yield, and composition.

Files and variables

File: SeveroSilvaEtal_Phenology_Dataset_Dryad.xlsx

Description:Â This dataset contains five tabs within a single Excel file:

Variables

• readme: Provides detailed information about the field experiments, including descriptions of the variables measured and analyzed.
• GeneralInformation: Contains site information, including tillage type, site coordinates, planting and harvest dates, and seeding rate at each location-year.
• PhenologyData: Includes soybean growth stage data.
• **...

Data from: United States Cattle Market Location and Annual Market Sales Estimate Data

Overview

This dataset contains information on cattle market locations and estimated annual cattle sales in the United States from 2012 to 2016. The data were compiled to enhance the understanding of cattle market dynamics and improve modeling efforts related to livestock movement and disease spread.

Repository Contents

• MarketList_final.csv: Contains detailed information about each cattle market, including location data and unique identifiers.
• Market_Volume_Estimates.csv: Provides county-level annual cattle sales estimates, including known and predicted values where data were not available.

Data Description

MarketList_final.csv

• RecordID: Unique identifier for each record (matches MarketID column in the Carroll and Bansal de-duplicated market list).
• premises.CB: Premises designations from Carroll and Bansal [1].
• premises.Beck-Johnson: Corrected premises designations.
• FI...

The dataset is formatted as pairs of locations. The first spreadsheet line of a DATE/TIME/FROGID unique combination is the frog location. The second line of that unique DATE/TIME/FROGID combination is the random location 5m away from the frog. UTME and UTMN, cartesian coordinates for exact frog locations, have been removed from the dataset because of the sensitive nature of endangered animal locations. Please contact the authors if exact locations are needed.

Variable definitions:

DATE: Date in DD-MMM-YY format

TIME: Time of relocation in 24 hr format

FROGID: unique identifier for each frog. FROGIDs with multiple numbers (e.g., 503/017) were a single frog fitted with multiple transmitters.

USE: A binary indicator for the locations used by a frog (1) or the random location 5m away (0).

UTME/UTMN: location of frog and random location. Removed for protection of endangered species.

WATER: binary indicator for presence of standing or flowing liquid water at the location (y=...

This README file was generated on 2023-12-01 by Chase LaDue.

GENERAL INFORMATION

1. Title of Dataset: Data and R analysis code: Asian elephants distinguish sexual status and identity of unfamiliar elephants using urinary odours

2. Author Information A. Principal Investigator Contact Information Name: Chase LaDue Institution: Oklahoma City Zoo and Botanical Garden Address: 2000 Remington Place, Oklahoma City, OK USA Email: chase.ladue@gmail.com

   B. Co-investigator Contact Information Name: Rebecca Snyder Institution: Oklahoma City Zoo and Botanical Garden Address: 2000 Remington Place, Oklahoma City, OK USA Email: rsnyder@okczoo.org

3. Date of data collection: June to July 2023

4. Geographic location of data collection: Oklahoma City Zoo and Botanical Garden, USA

5. Information about funding sources that supported the collection of the data: No external funding.

SHARING/ACCESS Information

1. Licenses/restrictions placed on the data: CC0 1.0 Universal (CC0 1.0) P...

Potential alpine habitat in the western USA based on treeline elevation

https://doi.org/10.5061/dryad.sqv9s4n9m

An elevation surface was interpolated from points in the western USA and Canada identified as treelines on Google Earth imagery. The surface was intersected with a USGS 90 m digital elevation model (https://www.sciencebase.gov/catalog/item/542aebf9e4b057766eed286a), and all cells higher than the interpolated surface were recorded and mapped. Three products are included.

Description of the data and file structure

The first dataset, Final268Points, is a csv file of the 268 points identified as alpine treelines (Treeline Elevations). The data, in columns, include their latitude, longitude, and elevation as derived from Google Earth. The elevations of the points on the elevation surface generated by inverse distance weighting (IDW) and kriging (krig) are also listed. The second dataset, All90mPoints, is a compressed (zip) csv file of the c. 1.5 x 10^9 cells that were ...

This README_for_GUELL_ET_AL_DATASET.txt file was generated on 2023-03-15 by BRANDON A. GUELL

GENERAL INFORMATION

1. Title of Dataset: "Guell&Warkentin.xlsx" for the manuscript: "Phenology and environmental determinants of explosive breeding in gliding treefrogs: Diel timing of rainfall matters" submitted to Behavioral Ecology - manuscript number BEHECO-2023-0089.
2. Author Information A. Principal Investigator Contact Information Name: Karen M. Warkentin Institution: Boston University Address: 5 Cummington Mall, Boston, MA 02215, U.S.A. Email: kwarken@bu.edu
   A. Analyses Contact Information Name: Brandon A. Guell Institution: Boston University Address: 5 Cummington Mall, Boston, MA 02215, U.S.A. Email: bguell@bu.edu
3. Date of data collection (single date, range, approximate date): 1 March 2018 – 4 December 2021
4. Geographic location of data collection: Shampoo Pond in Piro, Osa Peninsula, Costa Rica (8°24´55´´N, 83°20´45´´W)
5. In...

Processed data for the analysis of human mobility changes on bird occupancy in NC

https://doi.org/10.5061/dryad.gb5mkkwxr

There are 3 types of data here including Google Community Mobility data, and processed data (data after extracting spatial covariates and merging with all covariates for the Occupancy Modeling as well as extracted predicted occupancy data that we used to create figures).

Description of the data and file structure

Google Community Mobility data: This is the dataset downloaded from https://www.google.com/covid19/mobility/ that measures the mobility changes throughout the world during the COVID-19 lockdown. Please visit the above website for more information about the data. Please see the "Anthropause_AMCR_02112024" R file (uploaded to Zenodo) for details on how we processed the raw data.

| Dataset name | Dataset description ...

See methods section of Zald et al. 2024. Thinning and prescribed burning increase shade-tolerant conifer regeneration in a fire excluded mixed-conifer forest. Forest Ecology and Management, 551(1) 121531. https://doi.org/10.1016/j.foreco.2023.121531

Area burned is an important variable for measuring wildfire activity. In the western United States (US), the timing and magnitude of area burned can be associated with meteorological and human activity to find the drivers of wildfire activity, but this type of research is dependent on the spatial and temporal resolution of available wildfire datasets. The Western US MTBS-Interagency (WUMI2) database is a dataset of wildfire events in the western United States (US) larger than 1 km2 for 1984 to 2020. WUMI2 includes the important Monitoring Trends in Burned Severity (MTBS) project (Eidenshink et al., 2007)—a Landsat satellite-based dataset of large fires (>4.04 km2)—and adds small (>1 to 4.04 km2) and large fires from government agency databases, including from the Fire Program Analysis (FPA) fire-occurrence database (Short et al., 2022). We performed extensive quality control to merge the datasets together and remove errors. The result is a western US-wide dataset with accurate fire frequency, timing, and area burned that can be used for analyses and modeling of wildfire activity. The current version of this data is WUMI2. The first iteration of the dataset (WUMI1) was published and described in Juang et al. (2022). Methods Version WUMI2 Updated August 1, 2024: Our WUMI2 fire database consists of 21,693 western US fire events from 1984 through 2020. A text file (west_US_fires_1984-2020_WUMI2.txt) provides a list of each fire event, including the fire’s name, discovery date, point location, total area burned, and forested area burned (see the corresponding readme.txt file for column labels). We also include NetCDF files of the 1-km map of forest fractional coverage (forest_type_frac.nc) and the 1-km maps of monthly burned area over 1984–2020 (burnarea_1984-2020_WUMI2.nc). Fires included in this database are from the Monitoring Trends in Burned Severity Product (MTBS) (Eidenshink et al., 2007), the Fire Program Analysis fire-occurrence database (FPA FOD 6th edition) of interagency fires (Short, 2022), and interagency fires from local databases (CalFire, ST/C&L, TRIBE), and interagency fires from government agency databases (BIA, BLM, BOR, DOD, DOE, NPS, FWS, FS, NPS). More information on methodology can be found in the Supporting Information in Juang et al. (2022). In addition to this methodology, the Fire Program Analysis fire-occurrence database (FPA FOD 6th edition) (Short, 2022) replaces our WUMI1 (Juang et al. (2022)) methodology for the government interagency fires from 1992-2020 for version WUMI2. As in WUMI1, we performed extensive quality control across all included datasets to remove errors in the various wildfire databases and merge the datasets together. Version WUMI1 (older) Updated August 16, 2021: Our WUMI1 fire database consists of 18,368 western US fire events from 1984 through 2019. A text file (west_US_fires_1984_2019.txt) provides a list of each fire event, including the fire’s name, discovery date, point location, total area burned, and forested area burned (see the corresponding readme.txt file for column labels). We also include NetCDF files of the 1-km map of forest fractional coverage (forest_type_frac.nc) and the 1-km maps of monthly burned area over 1984–2019 (burnarea_1984_2019.nc). Fires included in this database from the Monitoring Trends in Burned Severity Product (MTBS), fires from a state database (CalFire), fires from government interagency databases (BIA, BLM, BOR, NPS, FWS, FS). More information on methodology can be found in the Supporting Information in Juang et al. (2022).

The data is available as comma-separated-value (CSV) files and can be opened with any appropriate software.

This README file was generated on 2023-10-31 by Brad Taylor.

GENERAL INFORMATION

1. Title of Dataset: Data and code for: Facilitating the recovery of insect communities in restored streams by increasing oviposition habitat.

2. Author Information A. Principal Investigator Contact Information Name: Brad Taylor Institution: North Carolina State University Address: Raleigh, NC USA Email: bwtaylo3@ncsu.edu

   B. Associate or Co-investigator Contact Information Name: Samantha Dilworth (formerly Jordt) Institution: University of Wyoming Address: Laramie, WY USA Email: samanthajordt@gmail.com

3. Date of data collection (single date, range, approximate date): 2019-2020

4. Geographic location of data collection: western, North Carolina

5. Information about funding sources that supported the collection of the data: North Carolina Department of Environmental Quality

SHARING/ACCESS INFORMATION

1. Licenses/restrictions placed on the data: CC0 1.0 Univers...

This README file was generated on 2023-08-30 by Jennifer Merems. GENERAL INFORMATION

#

1. Title of Dataset: Fear before food: Scale-dependence in elk habitat selection
2. Author Information: A. Principal Investigator Contact Information Name: Timothy Van Deelen Institution: University of Wisconsin-Madison: Madison, WI USA Email: trvandeelen@wisc.edu

B. Corresponding Author Contact Information Name: Jennifer Merems Institution: University of Wisconsin-Madison: Madison, WI USA Email: merems@wisc.edu

1. Date of data collection (single date, range, approximate date): 2022-2023
2. Geographic location of data collection: Wisconsin, USA
3. Information about funding source that supported the collection of the data: Wisconsin Department of Natural Resources

#

SHARING/ACCESS INFORMATION

1. Licenses/restrictions placed on the data: Coordinates could not be given because location information for elk in Wisconsin is protected information. Coordinates are not needed to run the resource s...

Wojas et all_Corncrake eavesdroppingData was collected during three seasons of field work (2013, 2014, 2015) in Upper Nurzec River Valley in Northeast Poland. To create this data we used Avisoft SASLab Pro 5.2.x (Avisoft Bioacoustics, Berlin, Germany), STATA v. 14.2 (StataCorp, College Station, TX, USA) and IBM SPSS Statistics v. 24 (IBM Corp, Chicago, IL, USA). The final version is created in Microsoft Excel file. Column heading are describe in worksheet called ‘legend’.

Data for: Thermal Infrared Directs Host-seeking Behavior in Aedes Aegypti Mosquitoes

https://doi.org/10.5061/dryad.547d7wm

This deposit contains video recordings used in the manuscript "Thermal infrared directs host-seeking behavior in Aedes aegypti mosquitoes." Each video has a unique ID, which can be matched to a Source Data file. Videos are in .mp4 format and contained in zip files and grouped by their ID prefix (e.g., IR_43 is contained in IR_vids.zip).

Analysis code

MATLAB code for analyzing these videos can be found at the following link:

• https://github.com/Craig-Montell-Lab/Chandel_DeBeaubien_2023

Video guide

Some files use abbreviations corresponding to different experiments that were performed:

An: Anopheles

SI: silicon wafer

Ex: extended polyethylene film

OW: one-way choice

OW50: one-way choice with 50 ˚C plate

IR: infrared radiation

...

Dataset is ddRADseq from 86 individual Sistrurus catenatus (Eastern Massasauga Rattlesnake). Individuals were sequenced on Illumina HiSeq2500 and HiSeq4000 platforms, using single-end reads size selected from 300-600bp using EcoR1 and Pst1 for our restriction enzymes. Reads were aligned against a reference genome using ipyrad, and filtering done in PLINK 2.0, with all 2996 loci called in every individual.

This README file was generated on 2023-09-06 by Zoe Diaz-Martin.

GENERAL INFORMATION

1. Title of Dataset: Reproductive strategies and their consequences for divergence, gene flow, and genetic diversity in three taxa of Clarkia
2. Author Information A. Corresponding Author Contact Information Name: Zoe Diaz-Martin Institution: Spelman College Address: Atlanta, GA USA Email: zoediazmartin@spelman.edu

SHARING/ACCESS INFORMATION

1. Licenses/restrictions placed on the data: CC0 1.0 Universal (CC0 1.0) Public Domain
2. Links to publications that cite or use the data:

Diaz-Martin, Zoe, De Vitis, Marcello, et al. Species-specific effects of production practices on genetic diversity in plant reintroduction programs. Evolutionary Applications.

1. Links to other publicly accessible locations of the data: None
2. Links/relationships to ancillary data sets: None
3. Was data derived from another source? No A. If yes, list source(s): NA
4. Recommended citation f...

This dataset contains fish chorusing event logs used in the study "Fish chorusing patterns in California National Marine Sanctuaries", published in Marine Ecology Progress Series (Kim et al. 2025). The logs include the start and end times of fish chorusing events detected across nine passive acoustic monitoring sites located in the Monterey Bay, Channel Islands, and Chumash Heritage National Marine Sanctuaries from 2018–2022. Chorus detections are categorized by species, including bocaccio rockfish (Sebastes paucispinis), plainfin midshipman (Porichthys notatus), white seabass (Atractoscion nobilis), and two unidentified fish types.

Estimated roadway segment traffic data by vehicle class for the United States: A machine learning approach

Dataset DOI: 10.5061/dryad.gmsbcc2zz

Description of the Data and Available Formats

1. HPMS Network with Road Link Average Annual Daily Traffic (AADT):

Description: This dataset includes estimates for light-, medium-, and heavy-duty vehicle traffic across U.S. roadways. The data is derived from the 2018 Highway Performance Monitoring System (HPMS), managed by the Federal Highway Administration (FHWA). The HPMS provides essential information on average annual daily traffic (AADT), but it has limited representation of medium- and heavy-duty vehicles on non-interstate roads. To address this limitation, we applied random forest regression to estimate AADT for medium-duty vehicle (MDV) and heavy-duty vehicle (HDV) traffic in regions with sparse data. Light-duty vehicle (LDV) AADT was then estimated by subtracting the sum of MDV AADT and HDV AADT from the total AADT f...

This Wilkinson and Lopez-Martinez README.txt file was generated on 2024-11-5 by Giancarlo Lopez-Martinez

GENERAL INFORMATION

1. Title of Dataset: The lifelong effects of anoxia hormesis in solitary bees

2. Author Information Corresponding Investigator Name: Dr Giancarlo Lopez-Martinez Institution: North Dakota State University Email: giancarlo.lopez@ndsu.edu

   Co-investigator 1 Name: Michaelyne Wilkinson Institution: New Mexico State University

3. Date of data collection: 2021-2022

4. Geographic location of data collection: Fargo, ND

5. Funding sources that supported the collection of the data: National Science Foundation of the USA

6. Recommended citation for this dataset:

DATA & FILE OVERVIEW

1. Description of dataset

This is the accompanying dataset to a publication titled: The lifelong effects of anoxia hormesis in solitary bees (DOI: 10.1093/ee/nvaf013). The variables in this data set are Nx: normoxia, which refers to a no...