cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.5993250
title: Supplementary material for "High semi-natural vegetation cover and heterogeneity of field sizes promote bird beta-diversity at larger scales in Ethiopian Highlands"

description: <strong>Abstract</strong> The intensification of farming practices exerts detrimental effects on biodiversity. Most research has focused on declines in species richness at local scales (alpha-diversity) although species loss is exacerbated by biotic homogenization that operates at larger scales (i.e., affecting beta-diversity). The majority of studies have been conducted in temperate, industrialized countries while tropical areas remain poorly studied. Agricultural landscapes of sub-Saharan Africa are still largely dominated by small-scale subsistence farming, but strenuous efforts to intensify farming practices are currently spreading to meet a growing food demand. It is therefore crucial to understand how these intensified practices affect biodiversity to mitigate their negative impacts. We investigated how farming system (small- vs large-scale farming) and landscape complexity (semi-natural vegetation cover) drive bird species composition, community turnover, and beta-diversity patterns in Ethiopian Highlands’ agroecosystems. We evaluated the following hypotheses: (1) large-scale farming homogenizes bird communities, (2) community turnover is higher in small-scale farms, (3) interactive effects between landscape complexity and farming systems shape avian communities, (4) heterogeneity of field sizes increases community turnover at larger scales. Bird communities underwent greater compositional changes along the landscape complexity than along the agricultural intensity gradient. Contrary to our expectations, beta-diversity was not significantly lower within large-scale farms (no biotic homogenization), and complex landscapes that still offer a high amount of semi-natural vegetation promoted community turnover in both farming systems. Semi-natural vegetation cover mediated how avian communities responded to agricultural intensification: the compositional differences between small- and large-scale farms increased with vegetation cover, further promoting avian community heterogeneity at the landscape level. The heterogeneity in field sizes also enhanced bird community turnover, suggesting that a combination of both small- and large-scale farming systems within a given landscape unit would promote beta-diversity at larger scales, provided large-scale farms do not become dominant. Synthesis and applications: Landscape complexity shaped avian communities to a stronger degree than farming intensity, emphasizing the importance of semi-natural vegetation and landscape heterogeneity for the maintenance of diverse bird communities and for achieving multifunctional landscapes promoting biodiversity and associated ecosystem services on the High Ethiopian plateaus. <br>
DOI: 10.6084/m9.figshare.19962827
title: Data F1000 fix

description: Nanocrystal Usnic Acid: Formulation, Physicochemical Characterization, and Its Effect on MMP-13 and Collagen 2 Expression in Rabbit with Experimental Osteoarthritis.
DOI: 10.6084/m9.figshare.19962827.v2
title: Data F1000 fix

description: Nanocrystal Usnic Acid: Formulation, Physicochemical Characterization, and Its Effect on MMP-13 and Collagen 2 Expression in Rabbit with Experimental Osteoarthritis.
DOI: 10.6084/m9.figshare.19962827.v1
title: Nanocrystal Usnic Acid: Formulation, Physicochemical Characterization, and Its Effect on MMP-13 and Collagen 2 Expression in Rabbit with Experimental Osteoarthritis.

description: Nanocrystal Usnic Acid: Formulation, Physicochemical Characterization, and Its Effect on MMP-13 and Collagen 2 Expression in Rabbit with Experimental Osteoarthritis.
DOI: 10.5517/ccdc.csd.cc2gxc0s
title: CCDC 2291365: Experimental Crystal Structure Determination

description: Related Article: Patrick J. Murphy, Peter N. Horton, Michael B. Hursthouse|2002|University of Southampton, Crystal Structure Report Archive||1151|
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2gxc5y
title: CCDC 2291370: Experimental Crystal Structure Determination

description: Related Article: Simon Aldridge, Simon J. Coles, Michael B. Hursthouse|2002|University of Southampton, Crystal Structure Report Archive||1175|
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2gxc6z
title: CCDC 2291371: Experimental Crystal Structure Determination

description: Related Article: Simon Aldridge, Mark E. Light, Michael B. Hursthouse|2002|University of Southampton, Crystal Structure Report Archive||1176|
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2gxcj9
title: CCDC 2291381: Experimental Crystal Structure Determination

description: Related Article: Athanasia Dervisi, Peter N. Horton and Michael B. Hursthouse|2005|University of Southampton, Crystal Structure Report Archive||1051|
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2gxckb
title: CCDC 2291382: Experimental Crystal Structure Determination

description: Related Article: Carl Redshaw, Peter N. Horton, Michael B. Hursthouse|2003|University of Southampton, Crystal Structure Report Archive||1077|
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2gxcwn
title: CCDC 2291392: Experimental Crystal Structure Determination

description: Related Article: Athanasia Dervisi, Peter N. Horton, Michael B. Hursthouse and Simon J. Coles|2005|University of Southampton, Crystal Structure Report Archive||1057|
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2gxd1v
title: CCDC 2291397: Experimental Crystal Structure Determination

description: Related Article: Simon G. Carling, Lee Martin, Peter N. Horton and Michael B. Hursthouse|2004|University of Southampton, Crystal Structure Report Archive||1074|
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2gxdb4
title: CCDC 2291406: Experimental Crystal Structure Determination

description: Related Article: Simon J. Lancaster, Simon J. Coles and Michael B. Hursthouse|2004|University of Southampton, Crystal Structure Report Archive||1132|
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2gxf2x
title: CCDC 2291429: Experimental Crystal Structure Determination

description: Related Article: Robin B. Bedford, Simon J. Coles and Michael B. Hursthouse|2004|University of Southampton, Crystal Structure Report Archive||1090|
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.57764/eahb-sg85
title: EPI 7913: Topics in Epidemiology

description: This is the project for the EPI 7913 data science course.
DOI: 10.57764/x58f-5s54
title: EPI 7913: Topics in Epidemiology

description: This is the project for the EPI 7913 data science course.
DOI: 10.5281/zenodo.7641658
title: Model input files and output data for Pluto clathrate formation modeling

description: Geochemical and thermal modeling input files and data for "Timing and abundance of clathrate formation controls ocean evolution in outer solar system bodies"
DOI: 10.5281/zenodo.7641657
title: Model input files and output data for Pluto clathrate formation modeling

description: Geochemical and thermal modeling input files and data for "Timing and abundance of clathrate formation controls ocean evolution in outer solar system bodies"
DOI: 10.5066/p9ik5y45
title: A deep learning model and associated data to support understanding and simulation of salinity dynamics in Delaware Bay

description: Salinity dynamics in the Delaware Bay estuary are a critical water quality concern as elevated salinity can damage infrastructure and threaten drinking water supplies. Current state-of-the-art modeling approaches use hydrodynamic models, which can produce accurate results but are limited by significant computational costs. We developed a machine learning (ML) model to predict the 250 mg/L Cl- isochlor, also known as the salt front, using daily river discharge, meteorological drivers, and tidal water level data. We use the ML model to predict the location of the salt front, measured in river miles (RM) along the Delaware River, during the period 2001-2020, and we compare the ML model results to results from the hydrodynamic Coupled Ocean Atmospheric Wave Sediment Transport (COAWST) model. The ML model shows RMSE = 2.52 RM during the five-year holdout period, superior to three overlapping years of COAWST model predictions, RMSE = 5.36 RM, however the ML model struggles to predict extreme events. Further, we use functional performance and expected gradients, tools from information theory and explainable artificial intelligence, to show that the ML model learns physically realistic relationships between the salt front location and drivers (particularly discharge and tidal water level). These results demonstrate how an ML modeling approach can provide predictive and functional accuracy at a significantly reduced computational cost compared to process-based models. Additionally, these results provide support for using ML models for applications in operational forecasting, scenario testing, management decision making, hindcasting, and resulting opportunities to understand past behavior and develop hypotheses. In this model archive, we provide the scripts and configurations to fetch data for the machine learning model, to process the data for the machine learning model, to run the machine learning model and to analyze the functional performance of the machine learning model.
DOI: 10.6084/m9.figshare.24112728
title: Supplementary material: Exploring the role of student-run journals in shaping academic identity

description: Autobiographical Narratives of Journal Student Editors of <i>Current Issues in Education</i> (CIE) produced at Mary Lou Fulton Teachers College (MLFTC) at Arizona State University (ASU).
DOI: 10.6084/m9.figshare.24112728.v1
title: Supplementary material: Exploring the role of student-run journals in shaping academic identity

description: Autobiographical Narratives of Journal Student Editors of <i>Current Issues in Education</i> (CIE) produced at Mary Lou Fulton Teachers College (MLFTC) at Arizona State University (ASU).
DOI: 10.5517/ccdc.csd.cc2g3czy
title: CCDC 2267370: Experimental Crystal Structure Determination

description: Related Article: Philipp Rinke, Helmar Görls, Phil Liebing, Robert Kretschmer|2023|Organometallics|42|2287|doi:10.1021/acs.organomet.3c00278
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2g3d00
title: CCDC 2267371: Experimental Crystal Structure Determination

description: Related Article: Philipp Rinke, Helmar Görls, Phil Liebing, Robert Kretschmer|2023|Organometallics|42|2287|doi:10.1021/acs.organomet.3c00278
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2g3d11
title: CCDC 2267372: Experimental Crystal Structure Determination

description: Related Article: Philipp Rinke, Helmar Görls, Phil Liebing, Robert Kretschmer|2023|Organometallics|42|2287|doi:10.1021/acs.organomet.3c00278
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2g3d22
title: CCDC 2267373: Experimental Crystal Structure Determination

description: Related Article: Philipp Rinke, Helmar Görls, Phil Liebing, Robert Kretschmer|2023|Organometallics|42|2287|doi:10.1021/acs.organomet.3c00278
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.8329574
title: GO_SHIP_P16NS_2005_2006_515Y_926R

description: This dataset contains relative abundance and taxonomic information for planktonic organisms collected by filtering whole seawater (~1L P16S, ~2L P16N) collected at various depths onto 0.2 µm 25mm Supor filter filters during two latitudinal transects of the Pacific Ocean (P16S[http://bcodata.whoi.edu/CLIVAR_AEROSOL/CLIVAR_P16S_2005ado.pdf], P16N[http://bcodata.whoi.edu/CLIVAR_AEROSOL/CLIVAR_P16N_2006ado.pdf]) in 2005/2006. Samples were collected at sea by Elisa Halewood and Meredith Meyers (Carlson Lab, UCSB) as part of the GO-SHIP repeat hydrography program (then known as CLIVAR). Samples were stored as partially extracted lysates in sucrose lysis buffer at -80°C until analysis. DNA was isolated, purified, amplified, and sequenced by Jesse McNichol, Yubin Raut, & Bruce Yanpui Chan (Fuhrman Lab, USC) in 2020 and 2021. Relative abundance information was generated by PCR amplification of extracted DNA using a universal primer pair that amplifies both 16S and 18S simultaneously (515Y/926R) and subsequent denoising to amplicon sequence variants (ASVs) using a custom analysis pipeline based on qiime2 and DADA2 (Callahan et al., 2016; Bolyen et al., 2016; https://github.com/jcmcnch/eASV-pipeline-for-515Y-926R). The final dataset contains merged abundance information from both 16S and 18S ASVs using the same denominator. Merging of 16S and 18S ASV tables was accomplished using a dataset-specific correction factor that adjusts for a known bias against longer 18S sequences during Illumina sequencing (Yeh et al., 2021). Organisms quantified range from small Bacteria and Archaea to protists (photosynthetic and non-photosynthetic) as well as larger planktonic organisms such as Arthropods, Salps, and Jellyfish. Please note that some organisms will be quantified more than once using this approach, such as eukaryotic algae for which we have ASV information from both chloroplast 16S and nuclear 18S. This dataset also contains several environmental covariates, including nutrient and CTD data derived from publicly-accessible GO-SHIP records (CLIVAR and Carbon Hydrographic Data Office; https://cchdo.ucsd.edu/), DNA concentrations from extractions (a proxy for community biomass), community 18S fraction (a measure of whether the sample is prokaryote- or eukaryote-dominated), as well as manual assignments of whether a sample was from the euphotic or non-euphotic zone. Raw reads are available on NCBI. Relevant scripts, bioinformatic intermediates, and output files are available on OSF and github as part of the Global rRNA Metabarcoding of Plankton (GRUMP) umbrella project. The github page (https://github.com/jcmcnch/Global-rRNA-Univeral-Metabarcoding-of-Plankton) contains links to all relevant underlying data, including processing steps used to link environmental covariates with sequencing data, as well as dataset-specific correction factors for merging 16S and 18S data.
DOI: 10.5281/zenodo.8329573
title: GO_SHIP_P16NS_2005_2006_515Y_926R

description: This dataset contains relative abundance and taxonomic information for planktonic organisms collected by filtering whole seawater (~1L P16S, ~2L P16N) collected at various depths onto 0.2 µm 25mm Supor filter filters during two latitudinal transects of the Pacific Ocean (P16S[http://bcodata.whoi.edu/CLIVAR_AEROSOL/CLIVAR_P16S_2005ado.pdf], P16N[http://bcodata.whoi.edu/CLIVAR_AEROSOL/CLIVAR_P16N_2006ado.pdf]) in 2005/2006. Samples were collected at sea by Elisa Halewood and Meredith Meyers (Carlson Lab, UCSB) as part of the GO-SHIP repeat hydrography program (then known as CLIVAR). Samples were stored as partially extracted lysates in sucrose lysis buffer at -80°C until analysis. DNA was isolated, purified, amplified, and sequenced by Jesse McNichol, Yubin Raut, & Bruce Yanpui Chan (Fuhrman Lab, USC) in 2020 and 2021. Relative abundance information was generated by PCR amplification of extracted DNA using a universal primer pair that amplifies both 16S and 18S simultaneously (515Y/926R) and subsequent denoising to amplicon sequence variants (ASVs) using a custom analysis pipeline based on qiime2 and DADA2 (Callahan et al., 2016; Bolyen et al., 2016; https://github.com/jcmcnch/eASV-pipeline-for-515Y-926R). The final dataset contains merged abundance information from both 16S and 18S ASVs using the same denominator. Merging of 16S and 18S ASV tables was accomplished using a dataset-specific correction factor that adjusts for a known bias against longer 18S sequences during Illumina sequencing (Yeh et al., 2021). Organisms quantified range from small Bacteria and Archaea to protists (photosynthetic and non-photosynthetic) as well as larger planktonic organisms such as Arthropods, Salps, and Jellyfish. Please note that some organisms will be quantified more than once using this approach, such as eukaryotic algae for which we have ASV information from both chloroplast 16S and nuclear 18S. This dataset also contains several environmental covariates, including nutrient and CTD data derived from publicly-accessible GO-SHIP records (CLIVAR and Carbon Hydrographic Data Office; https://cchdo.ucsd.edu/), DNA concentrations from extractions (a proxy for community biomass), community 18S fraction (a measure of whether the sample is prokaryote- or eukaryote-dominated), as well as manual assignments of whether a sample was from the euphotic or non-euphotic zone. Raw reads are available on NCBI. Relevant scripts, bioinformatic intermediates, and output files are available on OSF and github as part of the Global rRNA Metabarcoding of Plankton (GRUMP) umbrella project. The github page (https://github.com/jcmcnch/Global-rRNA-Univeral-Metabarcoding-of-Plankton) contains links to all relevant underlying data, including processing steps used to link environmental covariates with sequencing data, as well as dataset-specific correction factors for merging 16S and 18S data.
DOI: 10.5066/p93261e5
title: Grand Calumet River Area of Concern Metabarcoding Data

description: The Grand Calumet River flows through northwestern Indiana and was designated an EPA Area of Concern (AOC) in 1987. There are multiple legacy pollutants in the river including but not limited to heavy metals and PCBs. To investigate potential causes and patterns of eutrophication in the river, water samples were collected for 16S rRNA microbial and eukaryotic 18S rRNA amplicon sequencing during April - September 2021. This data release describes the resulting sequencing data.
DOI: 10.5066/p9krgx06
title: Caligus Clemensi prevalence and counts on Clupea pallasii from Port Angeles Harbor, WA and from a controlled laboratory experiment conducted at USGS Marrowstone Marine Field Station, WA

description: We characterized a natural sea louse epizootic of Caligus clemensi and the effects of parasitism on Pacific herring Clupea pallasii in Port Angeles Harbor, WA, USA. Infestation prevalence on newly metamorphosed age0 Pacific herring reached 100% prevalence by mid-August. At this time, the mean louse intensity was 4.6 lice and a positive correlation occurred between louse intensity and Pacific herring body length. The epizootic then waned, with infestation prevalence decreasing to less than 25% and the mean parasite intensity falling below 1 louse by October. In controlled experiments, louse-induced mortality was negligible in controlled experiments. While skin injuries were not detected, motile lice preferentially aggregated around head and anterior dorsal areas. However, louse tropism became evenly distributed over the body as the parasite intensity increased. These results indicate that C. clemensi epizootics reach high prevalence, but also fade from mid-summer to early fall. Due to the predominant presence of motile copepod stages, we suggest that the epizootic fades because lice complete their life cycle and dislodge from the host, however, multiple explanations for epidemic fading are discussed.