cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25675/10217/179811
title: Spatial and temporal estimates of population exposure to wildfire smoke during the Washington State 2012 wildfire season using blended model, satellite, and in-situ data: process data and code archive

description: Includes 4 datafiles in the 'Data' subdirectory: 1) sites.npz-in-situ measurements made by the Washington Department of Ecology, USA EPA (from the AQS network), and Canadian surface measurements provided by Kathleen McClean and Dr. Sarah Henderson at University of British Columbia. All files were downloaded and processed by Dr. Bonne Ford, and William Lassman; 2) PyKrige.npz-kriged estimates of PM2.5, produced by William Lassman; 3) MODIS_regrid.npz: Downloaded from the NASA MODIS website (https://lpdaac.usgs.gov/) by Dr. Bonne Ford, and post-processed by William Lassman; 4) WRF-Chem.npz: Produced by Dr. Bonne Ford and William Lassman under the guidance of Dr. Gabi Pfister; There are also a number of python scripts (in the 'Code' subdirectory; All python codes were written by William Lassman under the guidance of Dr. Jeff Pierce.
description: In the western U.S., smoke from wild and prescribed fires can severely degrade air quality. Due to changes in climate and land-management, wildfires have increased in frequency and severity, and this trend is expected to continue. Consequently, wildfires are expected to become an increasingly important source of air pollutants in the western U.S. Hence, there is a need to develop a quantitative understanding of wildfire-smoke-specific health effects. A necessary step in this process is to determine who was exposed to wildfire smoke, the concentration of the smoke during exposure, and the duration of the exposure. Three different tools have been used in past studies to assess exposure to wildfire smoke: in-situ measurements, satellite-based observations, and chemical-transport model (CTM) simulations. Each of these exposure-estimation tools have associated strengths and weakness. We investigate the utility of blending these tools together to produce estimates of PM2.5 exposure from wildfire smoke during the Washington 2012 fire season. For blending, we use a ridge-regression model and a geographically weighted ridge-regression model. We evaluate the performance of the three individual exposure-estimate techniques and the two blended techniques using leave-one-out cross-validation. We find that predictions based on in-situ monitors are more accurate for this particular fire season than the CTM simulations and satellite-based observations because of the large number of monitors present; therefore, blending provides only marginal improvements above the in-situ observations. However, we show that in hypothetical cases with fewer surface monitors, the two blending techniques can produce substantial improvement over any of the individual tools.
DOI: 10.25675/10217/186049
title: Mapbook atlas of riparian vegetation for 2006, 2016, and the change between years

description: Models of riparian vegetation were created by digital image sampling to collect environmental response data. National Agriculture Imagery Program (NAIP) imagery at the time step and a scripted Google Earth Engine image visualization and data collection interface was used to ocularly interpret the presence and absence of riparian vegetation. Final models were applied using Landsat composite imagery and associated vegetation indices with the digitally collected occurrence locations. The random forest algorithm was used within Google Earth Engine to develop models for 2006 and 2016 by Environmental Protection Agency (EPA) ecoregion III. Models were constrained to valley bottoms across the Colorado River Basin. A change map was created by differencing 2006 and 2016 results for a gain, loss and persistence map. Detailed methods can be found in Woodward et al. (In prep).
description: Users of these maps and other analysis products are solely responsible for interpretations made from these products. The Natural Resource Ecology Laboratory makes every effort to ensure this map is free of errors but does not warrant the map or its features are either spatially or temporally accurate or fit for a particular use. The Natural Resource Ecology Laboratory provides this map without any warranty, either express or implied.
description: An ArcGIS created Mapbook atlas of the results of modeling riparian vegetation across the Colorado River Basin. The atlas includes an overview of the Colorado River Basin with these model results as well as an indexed tile-by-tile map of the results for a more detailed view. Detailed methods can be found in Woodward et al. (In prep).
DOI: 10.25675/10217/235435
title: Library Web Site Usage Statistics: Digital Repository, 2008-2018

description: This dataset contains usage statistics collected via Google Analytics for CSU Libraries’ DSpace digital repository (Mountain Scholar, previously known as the Digital Collections of Colorado) from 2015-2018, as well as its predecessor, a DigiTool digital repository, from 2008-2015. These statistics were originally generated and documented by Greg Vogl (Middleware Developer, Academic Computing and Networking Services, formerly Library Technology Services staff), and stored on a website (https://lib2.colostate.edu/dspace-statistics/) which was discontinued in 2021. The usage statistics reports were downloaded by Marcus Longwell (Library Developer and Application Administrator), and this documentation was created by Mara Sedlins (Data Management Specialist).
DOI: 10.34740/kaggle/dsv/6058187
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.25675/10217/235433
title: Dataset associated with "Analysis of Kenya's Atmospheric Moisture Sources and Sinks"

description: The data are a gridded set of files that contain data on the evaporative sources that provide precipitation to Kenya, and the destinations to which Kenya's evaporation will later fall as precipitation. The data are further described in the README document and the original publication.
description: Achievement of the United Nations Sustainable Development Goals (SDGs) are contingent on understanding the potential interactions among human and natural systems. In Kenya, the goal of conserving and expanding forest cover to achieve SDG 15 ‘Life on land’ may be related to other SDGs because it plays a role in regulating some aspects of Kenyan precipitation. We present a 40-year analysis of the sources of precipitation in Kenya, and the fate of the evaporation that arises from within Kenya. Using MERRA2 climate reanalysis and the Water Accounting Model 2-layers, we examine the annual and seasonal changes in moisture sources and sinks. We find that most of Kenya’s precipitation originates as oceanic evaporation, but that 10% of its precipitation originates as evaporation within Kenya. This internal recycling is concentrated in the mountainous and forested Kenyan highlands, with some locations recycling more than 15% of evaporation, to Kenyan precipitation. We also find that 75% of Kenyan evaporation falls as precipitation elsewhere over land, including 10% in Kenya, 25% in the Democratic Republic of the Congo, and around 5% falling in Tanzania and Uganda. Further, we find a positive relationship between increasing rates of moisture recycling and fractional forest cover within Kenya. By beginning to understand both the seasonal and biophysical interactions taking place, we may begin to understand the types of leverage points that exist for integrated atmospheric water cycle management. These findings have broader implications for disentangling environmental management and conservation and have relevance for large-scale discussions about sustainable development.
DOI: 10.25675/10217/187173
title: Supporting data for the manuscript, "Agricultural harvesting emissions of ice nucleating particles"

description: Ice nucleating particle (INP) concentrations were measured with the Colorado State University Continuous Flow Diffusion Chamber (CFDC) and the Ice Spectrometer (IS) during the harvesting of various crops in Kansas and Wyoming. Real-time heating was used to determine the percentage of organic and mineral components that make up the INPs. Post-treatments of IS samples were also used to isolate the heat-labile and heat-stable organics, and bacteria from mineral INP components of wheat emissions. Concentrations of biological particles were made in real time with a Wideband Integrated Bioaerosol Sensor (WIBS). The CFDC, IS, WIBS, and SEM-EDX data used in this paper are included in this archive.
DOI: 10.25675/10217/87153
title: SGS-LTER GIS layer with detailed information on CPER boundary on Central Plains Experimental Range, Nunn, Colorado, USA 2012

description: This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Repository (http://hdl.handle.net/10217/100254). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection.
DOI: 10.25675/10217/87152
title: SGS-LTER GIS layer with detailed information on pasture boundaries on Central Plains Experimental Range, Nunn, Colorado, USA 2012

description: This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Repository (http://hdl.handle.net/10217/100254). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection.
DOI: 10.25675/10217/233938
title: Dataset associated with "Trifluoroacetic acid deposition from emissions of HFO-1234yf in India, China, and the Middle East"

description: TFA deposition and TFA rainwater concentration simulated by the chemical transport models – GEOS-Chem and WRF-Chem, over India, China, and the Middle East for 2015.
description: We have investigated trifluoroacetic acid (TFA) formation from emissions of HFO-1234yf, its dry and wet deposition, and rainwater concentration over India, China, and the Middle East with GEOS-Chem and WRF-Chem models. We estimated the TFA deposition and rainwater concentrations between 2020 and 2040 for four previously published HFO-1234yf emission scenarios to bound the possible levels of TFA. We evaluated the capability of GEOS-Chem to capture the wet deposition process by comparing calculated sulfate in rainwater with observations. Our calculated TFA amounts over the U.S., Europe, and China were comparable to those previously reported when normalized to the same emission. A significant proportion of TFA was found to be deposited outside the emission regions. The mean and the extremes of TFA rainwater concentrations calculated for the four emission scenarios from GEOS-Chem and WRF-Chem were orders of magnitude below the no observable effect concentration. The ecological and human health impacts now and continued use of HFO-1234yf in India, China, and the Middle East are estimated to be insignificant based on the current understanding, as summarized by Neale et al. (2021).
DOI: 10.25675/10217/192200
title: Supporting data for the manuscript "Modeling the formation and composition of secondary organic aerosol from diesel exhaust using parameterized and semi-explicit chemistry and thermodynamic models"

description: The dataset includes organic aerosol mass and composition (i) measurements from Eluri et al. (2017) and (ii) model predictions from two different frameworks: the statistical oxidation model (SOM) and the volatility basis set (VBS). The dataset is limited to the information presented in the figures.
description: Laboratory-based studies have shown that combustion sources emit volatile organic compounds that can be photo-oxidized in the atmosphere to form secondary organic aerosol (SOA). In some cases, this SOA can exceed direct emissions of primary organic aerosol (POA). Jathar et al. (2017a) recently reported on experiments that used an oxidation flow reactor (OFR) to measure the photochemical production of SOA from a diesel engine operated at two different engine loads (idle, load), two fuel types (diesel, biodiesel), and two aftertreatment configurations (with and without an oxidation catalyst and particle filter). In this work, we used two different SOA models, the Volatility Basis Set (VBS) model and the Statistical Oxidation Model (SOM), to simulate the formation and composition of SOA for those experiments. Leveraging recent laboratory-based parameterizations, both frameworks accounted for a semi-volatile and reactive POA; SOA production from semi-volatile, intermediate volatility, and volatile organic compounds (SVOC, IVOC and VOC); NOx -dependent parameterizations; multigenerational gas-phase chemistry; and kinetic gas–particle partitioning. Both frameworks demonstrated that for model predictions of SOA mass to agree with measurements across all engine load–fuel–aftertreatment combinations, it was necessary to model the kinetically limited gas–particle partitioning in OFRs and account for SOA formation from IVOCs, which were on average found to account for 70% of the model-predicted SOA. Accounting for IVOCs, however, resulted in an average underprediction of 28% for OA atomic O:C ratios. Model predictions of the gas-phase organic compounds (resolved in carbon and oxygen space) from the SOM compared favorably to gas-phase measurements from a chemical ionization mass spectrometer (CIMS), substantiating the semi-explicit chemistry captured by the SOM. Model–measurement comparisons were improved on using SOA parameterizations corrected for vapor wall loss. As OFRs are increasingly used to study SOA formation and evolution in laboratory and field environments, models such as those developed in this work can be used to interpret the OFR data.
DOI: 10.25675/10217/234378
title: Pingree Park Meteorological Data 2003 to 2008

description: This dataset contains meteorological data from Pingree Park from 2003 to 2008. The variables are air temperature, relative humidity, vapor pressure, wind speed, direction, maximum wind velocity and timing, shortwave radiation, soil temperature (5cm, 10cm, 20cm), and soil moisture (5cm, 10cm, 20cm).
DOI: 10.25625/4ppdvq/0xo4eb
title: MK_WL_CL_RM_ResearchData_RingVortex_Fluids.tar.gz

description: :unav
DOI: 10.25625/4ppdvq
title: Research Data for Ring Vortex paper

description: Researchdata for "Ring Vortex Dynamics Following Jet Formation of a Bubble Expanding and Collapsing Close to a Flat Solid Boundary Visualized via Dye Advection in the Framework of OpenFOAM"
DOI: 10.25675/10217/177222
title: Canine lymphoma case control database

description: Zip file includes: data and readme file.
description: Authors are from Purdue University. Department of Comparative Pathobiology and Colorado State University. Department of Clinical Sciences.
description: These data were collected by the Veterinary Medical Database and include demographic information about 67,712 dogs seen at veterinary teaching hospitals in North America between 1989 and 2011. 18,826 of these dogs were diagnosed with lymphoma (cases) and the control series were matched to case dogs by institution of admission, age, and year of admission in up to a 3:1 ratio.
description: Cases 1990-2009; controls 1989-2011.
DOI: 10.25675/10217/234027
title: Dataset associated with “An in-frame deletion mutation in the degron tail of auxin co-receptor IAA2 confers resistance to the herbicide 2,4-D in Sisymbrium orientale”

description: Output files from protein docking analysis of the wild-type IAA2 protein and the mutant IAA2 version containing a nine amino acid deletion. These residues were used as docking parameters in HADDOCK 2.4 (https://wenmr.science.uu.nl/haddock2.4/). Docking calculations were performed under expert level, deactivating the DNA/RNA functions and activating the Surface Contact Restrains to enforce contact between the molecules. Degron residues KNNN of SoIAA2 were assigned semiflexible properties during docking whereas the shorter connection in SoIAA2Δ9 was not allowed to be flexible to preserve the structural integrity of PB1. The binding affinities of the SoIAA2/TIR1 and SoIAA2Δ9/TIR1 biological complexes were calculated using PRODIGY (https://bianca.science.uu.nl/prodigy/) for all top 4 poses from the best HADDOCK clusters. Plots are in .html format and protein models are in .pdb format. Files are in TGZ after gzip compression.
description: The natural auxin indole-3-acetic acid (IAA) is a key regulator of many aspects of plant growth and development. Synthetic auxin herbicides such as 2,4-D mimic the effects of IAA by inducing strong auxinic signaling responses in plants. To determine the mechanism of 2,4-D resistance in a Sisymbrium orientale (Indian hedge mustard) weed population, we performed a transcriptome analysis of 2,4-D-resistant (R) and -susceptible (S) genotypes that revealed an in-frame 27-nucleotide deletion removing 9 amino acids in the degron tail (DT) of the auxin co-receptor Aux/IAA2 (SoIAA2). The deletion allele co-segregated with 2,4-D resistance in recombinant inbred lines. Further, this deletion was also detected in several 2,4-D resistant field populations of this species. Arabidopsis transgenic lines expressing the SoIAA2 mutant allele were resistant to 2,4-D and dicamba. The IAA2-DT deletion reduced binding to TIR1 in vitro with both natural and synthetic auxins, causing reduced association and increased dissociation rates. This novel mechanism of synthetic auxin herbicide resistance assigns a new in planta function to the DT region of this Aux/IAA co-receptor for its role in synthetic auxin binding kinetics and reveals a potential biotechnological approach to produce synthetic auxin resistant crops using gene editing.
DOI: 10.25675/10217/185889
title: Data associated with Geomorphic controls on floodplain soil organic carbon in the Yukon Flats, interior Alaska, from reach to river basin scales

description: The dataset describes floodplain soil samples taken from the Yukon Flats region in interior Alaska, which were analyzed for organic carbon concentration, soil texture, and soil moisture. Statistical models were used to assess the geomorphic controls on floodplain soil organic carbon. These data were collected in the Yukon Flats Region during Summer 2014 and Summer 2015.
description: Floodplains accumulate and store organic carbon (OC) and release OC to rivers, but studies of floodplain soil OC come from small rivers or small spatial extents on larger rivers in temperate latitudes. Warming climate is causing substantial change in geomorphic process and OC fluxes in high latitude rivers. We investigate geomorphic controls on floodplain soil OC concentrations in active-layer mineral sediment in the Yukon Flats, interior Alaska. We characterize OC along the Yukon River and four tributaries in relation to geomorphic controls at the river basin, segment, and reach scales. Average OC concentration within floodplain soil is 2.8% (median = 2.2%). Statistical analyses indicate that OC varies among river basins, among planform types along a river depending on the geomorphic unit, and among geomorphic units. OC decreases with sample depth, suggesting that most OC accumulates via autochthonous inputs from floodplain vegetation. Floodplain and river characteristics, such as grain size, soil moisture, planform, migration rate, and riverine DOC concentrations, likely influence differences among rivers. Grain size, soil moisture, and age of surface likely influence differences among geomorphic units. Mean OC concentrations vary more among geomorphic units (wetlands = 5.1% vs. bars = 2.0%) than among study rivers (Dall River = 3.8% vs. Teedrinjik River = 2.3%), suggesting that reach-scale geomorphic processes more strongly control the spatial distribution of OC than basin-scale processes. Investigating differences at the basin and reach scale is necessary to accurately assess the amount and distribution of floodplain soil OC, as well as the geomorphic controls on OC.
DOI: 10.25675/10217/233662
title: Dataset associated with: "Intentional mentoring should increase inclusivity in ecology"

description: Focus group interview transcripts and indications of where co-authors wrote memos while coding the dataset. These focus group transcripts are from interviews conducted in August 2019. The focus groups interviews were conducted at Colorado State University. All interviews were in accordance with IRB approval from Colorado State University.
description: High quality mentoring relationships can be pivotal to recruitment, retention, and long-term persistence in ecology majors and careers. The graduate-undergraduate student mentoring relationship can become uniquely important during activities like ecological fieldwork. However, graduate students often have little experience as research mentors, which can lead to negative research experiences for undergraduate mentees. Given the potential for mentoring relationships to impact people’s decisions on pursuing ecological studies and/or careers, we created and piloted a mentoring professional development program designed around intentional mentoring. Intentional mentoring requires that mentors preemptively identify what skills and knowledge their mentee should develop as well as the practices to help mentees develop these competencies. Our rationale for using intentional mentoring was that it has the potential to increase mentors’ and mentees’ awareness of issues around diversity, equity, inclusion, and social justice (DEIJ) in research experiences, in addition to developing professional competencies. To evaluate our program, we conducted focus group interviews with graduate and undergraduate student participants following a multi-week mentoring training workshop, the primary aspect of the program. Participants described an increased valuation of intentional mentoring and a desire to be more intentional in their mentoring relationships. Graduate student mentors described an increased desire to be more intentional mentors, whereas undergraduate mentees described an increased desire to seek mentors with whom they could develop intentional relationships. Undergraduates also better recognized the importance of academic mentors. Based on our evaluation, we posit that intentional mentoring can increase the retention and persistence of students with diverse identities in ecology by fostering a sense of belonging. We advocate the implementation of mentoring training workshops as a part of academic ecological programs to increase inclusion in our discipline.