cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10580847
title: Data from: Global patterns in the impacts of consumers on coastal wetland microalgae

description: Provided here are the datasets and R code for the study entitled "Global patterns in the impacts of consumers on coastal wetland microalgae".

Summary of the study: Microalgae are key primary producers in aquatic ecosystems. Despite anthropogenic impacts on aquatic food webs, however, the impacts of changes in consumer assemblages on microalgae remain poorly understood. Using meta-analysis of 653 measurements of microalgal responses to consumer exclusion or addition treatments, we assessed global patterns in the top-down impact of consumers on microalgae in coastal wetlands. Consumers reduced the abundance of microalgae worldwide by 46% on average, but there were great variations in consumer effects. Consumers tended to have stronger effects on diatoms than on cyanobacteria and in unvegetated rocky shores and sandflats than vegetated salt marshes and mangrove forests. Consumer effects on microalgae were weaker at higher water temperatures and lower latitudes, and stronger at high consumer densities and in longer studies. Our analysis reveals prevalent but variable consumer impacts on microalgae in coastal wetlands globally and highlights that the processes mediating this variation may differ from those controlling macroalgae and vascular plants. We suggest that a better understanding of variation in the impact of consumers on microalgae will help manage the positive and negative effects of microalgae under increasing global anthropogenic alterations of food webs.

#####Files######

1) Liu_Metadata.csv This CSV file contains the metadata for the two spreadsheets2) Liu_Consumer_Effects_on_Microalgae.csv This CSV file contains all the data used in our main analysis3) Liu_Subset_for_Diatom_and_Cyanobacteria.csv This CSV file contains the data for analyzing consumer effects on diatoms versus cyanobacteria.4) Liu_Code.docx This Word file contains the R code (version 1) used.
DOI: 10.5281/zenodo.10580848
title: Data from: Global patterns in the impacts of consumers on coastal wetland microalgae

description: Provided here are the datasets and R code for the study entitled "Global patterns in the impacts of consumers on coastal wetland microalgae".

Summary of the study: Microalgae are key primary producers in aquatic ecosystems. Despite anthropogenic impacts on aquatic food webs, however, the impacts of changes in consumer assemblages on microalgae remain poorly understood. Using meta-analysis of 653 measurements of microalgal responses to consumer exclusion or addition treatments, we assessed global patterns in the top-down impact of consumers on microalgae in coastal wetlands. Consumers reduced the abundance of microalgae worldwide by 46% on average, but there were great variations in consumer effects. Consumers tended to have stronger effects on diatoms than on cyanobacteria and in unvegetated rocky shores and sandflats than vegetated salt marshes and mangrove forests. Consumer effects on microalgae were weaker at higher water temperatures and lower latitudes, and stronger at high consumer densities and in longer studies. Our analysis reveals prevalent but variable consumer impacts on microalgae in coastal wetlands globally and highlights that the processes mediating this variation may differ from those controlling macroalgae and vascular plants. We suggest that a better understanding of variation in the impact of consumers on microalgae will help manage the positive and negative effects of microalgae under increasing global anthropogenic alterations of food webs.

#####Files######

1) Liu_Metadata.csv This CSV file contains the metadata for the two spreadsheets2) Liu_Consumer_Effects_on_Microalgae.csv This CSV file contains all the data used in our main analysis3) Liu_Subset_for_Diatom_and_Cyanobacteria.csv This CSV file contains the data for analyzing consumer effects on diatoms versus cyanobacteria.4) Liu_Code.docx This Word file contains the R code (version 1) used.
DOI: 10.5281/zenodo.10580961
title: Impact of spatial transformations on landscape features of CEC 2022 basic benchmark problems
DOI: 10.5281/zenodo.10580962
title: Impact of spatial transformations on landscape features of CEC 2022 basic benchmark problems
DOI: 10.5281/zenodo.10048260
title: Triangle Travel Survey Shopping Travel Analysis data

description: This Zenodo repository contains data used in the Triangle Travel Survey shopping analysis project, funded by the STRIDE UTC. Due to privacy concerns, the original data cannot be reproduced here (qualified researchers can contact the Institute for Transportation Research and Education at NC State to request access). This repository contains aggregated outputs that may be useful for some further analyses. Most files include our preferred marginal distance approach, as well as values calculated using the "shopping destination" method wherein the lengths of trips going to stores are summed, and the "round-trip" method where all shopping is assumed to generate round trips. In the previous version, the round-trip method means reported here did not remove households with the longest trip more than 100 miles, as is done in the topline results, but this has been corrected.

Please contact Matt Bhagat-Conway <mwbc@unc.edu> with any questions.

- `daily_hh_shopping_travel_by_tract.csv` - this contains tract-level estimates of daily shopping travel, for all tracts with more than five households. Note that since shopping travel does not occur every day, some tracts with small sample sizes may exhibit high variance.

- `distance_by_density.csv` - this contains marginal shopping distance, disaggregated by housing unit density (in units/sq. mi.)

- `distance_by_hhsize.csv` - this contains all three shopping distance metrics, disaggregated by household size.

- `distance_by_income.csv` - this contains all three shopping distance metrics, disaggregated by income.

- `distance_by_number_of_workers.csv` - this contains all three shopping distance metrics, disaggregated by number of workers.

- `distance_by_received_packages.csv` - this contains all three shopping metrics, disaggregated by whether the household received packages on the travel day

 

 This work was sponsored by a grant from the Southeastern Transportation Research, Innovation, Development, and Education Center (STRIDE).

The Triangle Travel Survey is funded by the Capital Area Metropolitan Planning Organization (MPO), the Durham-Chapel Hill-Carrboro MPO, GoTriangle, and the North Carolina Department of Transportation.
DOI: 10.5281/zenodo.10048261
title: Triangle Travel Survey Shopping Travel Analysis data

description: This Zenodo repository contains data used in the Triangle Travel Survey shopping analysis project, funded by the STRIDE UTC. Due to privacy concerns, the original data cannot be reproduced here (qualified researchers can contact the Institute for Transportation Research and Education at NC State to request access). This repository contains aggregated outputs that may be useful for some further analyses. Most files include our preferred marginal distance approach, as well as values calculated using the "shopping destination" method wherein the lengths of trips going to stores are summed, and the "round-trip" method where all shopping is assumed to generate round trips. Note that round-trip method means reported here do not remove households with the longest trip more than 100 miles, as is done in the topline results.
Please contact Matt Bhagat-Conway <mwbc@unc.edu> with any questions.
- `daily_hh_shopping_travel_by_tract.csv` - this contains tract-level estimates of daily shopping travel, for all tracts with more than five households. Note that since shopping travel does not occur every day, some tracts with small sample sizes may exhibit high variance.
- `distance_by_density.csv` - this contains marginal shopping distance, disaggregated by housing unit density (in units/sq. mi.)
- `distance_by_hhsize.csv` - this contains all three shopping distance metrics, disaggregated by household size.
- `distance_by_income.csv` - this contains all three shopping distance metrics, disaggregated by income.
- `distance_by_number_of_workers.csv` - this contains all three shopping distance metrics, disaggregated by number of workers.
- `distance_by_received_packages.csv` - this contains all three shopping metrics, disaggregated by whether the household received packages on the travel day
 
 This work was sponsored by a grant from the Southeastern Transportation Research, Innovation, Development, and Education Center (STRIDE).
The Triangle Travel Survey is funded by the Capital Area Metropolitan Planning Organization (MPO), the Durham-Chapel Hill-Carrboro MPO, GoTriangle, and the North Carolina Department of Transportation.
DOI: 10.5281/zenodo.10580963
title: Triangle Travel Survey Shopping Travel Analysis data

description: This Zenodo repository contains data used in the Triangle Travel Survey shopping analysis project, funded by the STRIDE UTC. Due to privacy concerns, the original data cannot be reproduced here (qualified researchers can contact the Institute for Transportation Research and Education at NC State to request access). This repository contains aggregated outputs that may be useful for some further analyses. Most files include our preferred marginal distance approach, as well as values calculated using the "shopping destination" method wherein the lengths of trips going to stores are summed, and the "round-trip" method where all shopping is assumed to generate round trips. In the previous version, the round-trip method means reported here did not remove households with the longest trip more than 100 miles, as is done in the topline results, but this has been corrected.

Please contact Matt Bhagat-Conway <mwbc@unc.edu> with any questions.

- `daily_hh_shopping_travel_by_tract.csv` - this contains tract-level estimates of daily shopping travel, for all tracts with more than five households. Note that since shopping travel does not occur every day, some tracts with small sample sizes may exhibit high variance.

- `distance_by_density.csv` - this contains marginal shopping distance, disaggregated by housing unit density (in units/sq. mi.)

- `distance_by_hhsize.csv` - this contains all three shopping distance metrics, disaggregated by household size.

- `distance_by_income.csv` - this contains all three shopping distance metrics, disaggregated by income.

- `distance_by_number_of_workers.csv` - this contains all three shopping distance metrics, disaggregated by number of workers.

- `distance_by_received_packages.csv` - this contains all three shopping metrics, disaggregated by whether the household received packages on the travel day

 

 This work was sponsored by a grant from the Southeastern Transportation Research, Innovation, Development, and Education Center (STRIDE).

The Triangle Travel Survey is funded by the Capital Area Metropolitan Planning Organization (MPO), the Durham-Chapel Hill-Carrboro MPO, GoTriangle, and the North Carolina Department of Transportation.
DOI: 10.17632/zb6xhm92jg.1
title: Método Fuzzy TOPSIS implementado em MATLAB

description: Método fuzzy TOPSIS baseado em Chen (2000) - https://www.sciencedirect.com/science/article/abs/pii/S0165011497003771
DOI: 10.17632/7498rcbndw.1
title: Método Fuzzy AHP implementado em MATLAB

description: Método Fuzzy AHP baseado em Chan (1996) - "Applications of the extent analysis method on fuzzy AHP".
DOI: 10.48443/je35-bc57
title: Macroinvertebrate collection (DP1.20120.001)
title: RELEASE-2024

description: This data product contains the quality-controlled, native sampling resolution data from NEON's aquatic macroinvertebrate collection and field metadata, as well as associated taxonomic, morphometric, and count analyses data provided by a contracted lab. Benthic field samples are collected in wadeable streams, rivers, and lakes three times per year during the growing season using the type of sampler most suitable to the habitat types present at the site. Samples are preserved in ethanol in the field and shipped to a contracting lab for analysis. For additional details, see the user guide, protocols, science design, and lab SOPs listed in the Documentation section in this data product's details webpage.

Latency:
The expected time from data and/or sample collection in the field to data publication is as follows, for each of the data tables (in days) in the downloaded data package. See the Data Product User Guide for more information.

inv_fieldData: 30

inv_persample: 210

inv_taxonomyProcessed: 210

inv_taxonomyRaw: 210

inv_pervial: 210

inv_identificationHistory: 7
description: Benthic macroinvertebrate samples are collected three times per year at wadeable stream, river, and lake sites during aquatic biology bout windows, roughly in spring, summer, and fall. Samples are collected using the most appropriate sampler for the habitat type, including Surber, Hess, hand corer, modified kicknet, D-frame sweep, and petite ponar samplers. In wadeable streams, samples are collected in the two most dominant habitat types (e.g. riffles, runs, pools, step pools). In lakes, samples are collected near the buoy, and nearshore sensors using a petite ponar, and in littoral areas using a D-frame sweep. In rivers, samples are collected near the buoy and two other deep-water locations using a petite ponar sampler, and in littoral areas using a D-frame sweep or large-woody debris sampler. Samples are preserved in ethanol in the field, returned to the domain support facility for a preservative change where a small volume of glycerol is added to help keep invertebrates from getting brittle. Samples are shipped to a taxonomy lab for sorting and identification, including count of each taxon per size class (to nearest mm) and identification to lowest practical taxon (genus or species). Instrumentation:
DOI: 10.48443/gkx2-x153
title: Macroinvertebrate metabarcoding (DP1.20126.001)
title: RELEASE-2024

description: This data product contains the quality-controlled, native sampling resolution data from NEON's aquatic Macroinvertebrate metabarcoding sampling protocol, as well as associated metadata provided by a contracted lab. Benthic field samples are collected in wadeable streams, rivers, and lakes, three times per year during the growing season using the type of sampler most suitable to the habitat types present at the site. Samples are preserved in ethanol in the field and shipped to a contracting lab for analysis. For additional details, see the user guide, protocols, and science design listed in the Documentation section in this data product's details webpage.

Queries for this data product return a downloadable data package with laboratory methods and DNA extraction, PCR amplification, and sequencing metadata for samples from the queried sites and date range. Queries for the expanded package will also include a table containing links to the raw sequence data files.

Latency:
The expected time from data and/or sample collection in the field to data publication is as follows, for each of the data tables (in days) in the downloaded data package. See the Data Product User Guide for more information.

inv_fieldData: 30

inv_dnaExtraction: 240

inv_markerGeneSequencing: 240

inv_pcrAmplification: 240

inv_dnaRawDataFiles: 240

inv_metabarcodeTaxonomy: 240

inv_metabarcodeTaxonList: 240

inv_metabarcodeSummary: 240

inv_dnaStandardTaxon: 240

inv_dnaExtractionStandard: 240

inv_markerGeneSequencingStandard: 240

inv_pcrAmplificationStandard: 240

inv_dnaRawDataFilesStandard: 240

inv_metabarcodeTaxonomyStandard: 240
description: Benthic macroinvertebrate metabarcodingsamples are collected three times per year at wadeable stream, river, and lake sites during aquatic biology bout windows, roughly in spring, summer, and fall, at the same time and location as morphological taxonomy samples. Samples are collected using the most appropriate sampler for the habitat type, including Surber, Hess, hand corer, modified kicknet, D-frame sweep, and petite ponar samplers. In wadeable streams, samples are collected in the most dominant habitat type (e.g. riffles, runs, pools, step pools). In lakes and rivers, samples are collected in littoral areas using a D-frame sweep. Samples collected during the mid-summer sampling bout (Bout 2) are sent to an external facility for homogenization and high-throughput sequencing. Samples collected during the spring and fall (Bout 1 and Bout 3) are preserved in ethanol and shipped to the NEON Biorepository for archiving. Instrumentation:
DOI: 10.17632/83mk4gkcgz.1
title: Internet Appendix. The Impact of the Introduction of a Three-Tier Banking System on the Economic Performance of Banks in Russia

description: Internet Appendix for article "The Impact of the Introduction of a Three-Tier Banking System on the Economic Performance of Banks in Russia"
DOI: 10.48443/a9nb-rh97
title: Mosquito sequences DNA barcode (DP1.10038.001)
title: RELEASE-2024

description: This data product contains the quality-controlled laboratory metadata and QA results for NEON's cytochrome oxidase I (COI) barcoding of mosquito sequences. The DNA barcoding procedure involves the removal of leg tissue from pinned specimens, extracting and sequencing DNA from the tissue, and matching that sequence data to sequences from previously identified voucher specimens. DNA analysis serves a number of purposes, including verification of taxonomy of specimens that do not receive expert identification, clarification of the taxonomy of rare or cryptic species, and characterization of diversity using molecular markers. For additional details on mosquito collection, see protocol [NEON.DOC.014049](http://data.neonscience.org/api/v0/documents/NEON.DOC.014049vH): TOS Protocol and Procedure: Mosquito Sampling and science design [NEON.DOC.000908](http://data.neonscience.org/api/v0/documents/NEON.DOC.NEON.DOC.000908vA): TOS Science Design for Terrestrial Microbial Diversity. Queries for this data product will return metadata tables formatted for submission to the Barcode of Life Database. These queries will also provide links to the actual sequence data, which are publicly available on the [Barcode of Life Data System](http://www.boldsystems.org/) (BOLD) website. The sequence data can be obtained by following the links from the NEON data portal, or by directly querying NEON data sets on the BOLD server. From the NEON portal, the link "BOLD Project: Mosquito sequences DNA barcode" redirects to a page on the BOLD public data portal for the queried data. This is a dynamic link and will automatically update based on the user query.

Latency:
The expected time from data and/or sample collection in the field to data publication is as follows, for each of the data tables (in days) in the downloaded data package. See the Data Product User Guide for more information.

mos_BOLDcollectionData: 255

mos_BOLDspecimenDetails: 255

mos_BOLDtaxonomy: 255

mos_BOLDvoucherInfo: 255
description: Mosquito legs will be collected from up to 10 individuals per species per domain. These tissues will be preserved in an appropriate tissue vial and up to 95 tissue samples per domain will be shipped to an external lab. DNA will be extracted and target sequences amplified via PCR. Barcodes of cytochrome oxidase I will be generated per specimen. Instrumentation:
DOI: 10.5281/zenodo.10580919
title: Theory of universal diode effect in three-terminal Josephson junctions - code and data
DOI: 10.17632/53b2mm7bt7.1
title: Treatment Pathway

description: Data associated with article "The Impact of High-Level Governance"
DOI: 10.17632/gy83nnn3zj.1
title: Psychological states before and after Motocross race

description: This field research aimed to investigate feeling states, perceived arousal, anxiety, and negative- and positive affect in the anticipatory and recovery race periods and their relationship to expected and perceived performance.
DOI: 10.48443/3cyq-6v47
title: Mosquitoes sampled from CO2 traps (DP1.10043.001)
title: RELEASE-2024

description: This data product contains the quality-controlled, native sampling resolution data from NEON's mosquito sampling protocol. Mosquito abundance and diversity are sampled at regular intervals by NEON field technicians at all terrestrial sites. For additional details on protocol, see the TOS Protocol and Procedure: Mosquito Sampling. Following collection, all samples are sent to a professional taxonomist who determines the species composition and sex of mosquitoes from a representative subsample. Identified mosquitoes are then processed for pathogen analysis or preserved for final archiving. Products resulting from this sampling and processing include: records of when mosquitoes were sampled, taxonomic and abundance data for a subset of mosquitoes captured, and information about the material archived from the sample. For additional details, see the user guide, protocols, and science design listed in the Documentation section in this data product's details webpage.

Latency: The expected time from data and/or sample collection in the field to data publication is as follows, for each of the data tables (in days) in the downloaded data package. See the Data Product User Guide for more information.

mos_archivepooling: 360

mos_barcoding: 420

mos_expertTaxonomistIDProcessed: 240

mos_expertTaxonomistIDRaw: 240

mos_sorting: 240

mos_subsampling: 360

mos_trapping: 30

mos_identificationHistory: 7
description: When adult mosquitoes are active, sampling occurs (via CDC light traps) every two weeks at core sites and every four weeks at gradient sites. Before 2018, a sampling bout consisted of two trapping nights and the intervening day for up to ten plots per site. Beginning in 2018, a sampling bout consists of approximately 24 hours of trapping (one night and one daytime interval) at up to ten plots per site. Instrumentation:
DOI: 10.17632/4csbv2n4by.1
title: smy-data

description: Raw data from general test, EEM and FT-ICR MS.
DOI: 10.48443/mvdb-k902
title: Nitrate in surface water (DP1.20033.001)
title: RELEASE-2024

description: Nitrate is measured using an optical sensor at the downstream (S2) sensor station in streams and on the buoy at lake and river sites. It is reported as a mean value from 20 measurements made during a sampling burst every 15 minutes. Some older data may have been processed as the mean value from 50 measurements, but as of late 2018, the algorithm was updated to 20 measurements and older data will eventually be re-processed to use 20 measurements.

Latency:
Data collected in any given month are published during the second full week of the following month.
description: The stream sensor stations measure PAR at water surface, water level, temperature, water quality, and at downstream stations, nitrate. The buoys are comprised of sensor sets which measure meteorological parameters over a water surface along with submerged sensors that measure physical and chemical parameters of the water. Some of these sensors are unique to the buoy subsystem and others are shared with other NEON subsystems, such as the wadeable stream sensor sets or terrestrial towers. Due to power, space, and data storage constraints on the buoy, the configuration of sensors deployed on a buoy may be different than those in other parts of NEON. Instrumentation: Seabird - SUNA V2 UV nitrate sensor
DOI: 10.17632/y2jscpzh6f.1
title: Sudden Stops and Optimal Policy in a Two-agent Economy

description: Replication codes for article "Sudden Stops and Optimal Policy in a Two-agent Economy" by Nina Biljanovksa and Alexandros Vardoulakis, accepted for publication at the Journal of International Economics
DOI: 10.17632/m2tk5hcd7w.1
title: Health spending in Argentina

description: Health spending in Argentina, 2017-2020
DOI: 10.17632/jnbwt93f4y.1
title: Health coverage in Argentina, 2022

description: Health coverage in Argentina, 2022