cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3886/e192087v1-162941
title: Data and Code for: Equity Concerns are Narrowly Framed

description: Distributional decisions regularly involve multiple payoff components. In a
series of experiments, we show that individuals sometimes exhibit narrow equity
concerns: applying fairness preferences narrowly, on a specific component of
payoffs, rather than on broader payoff consequences. This behavior results
in different distributional decisions depending on which payoff component we
frame individuals to consider. We document narrow equity concerns in an
exceedingly simple setting—in which payoff components are tokens worth 1
cent and 2 cents—and in context-rich applications including tax policy and
worker compensation.

 
 
 <br>
description: N/A
description: Response Rates: N/A -- not survey data
description: Presence of Common Scales: N/A
description: We recruited online participants from Amazon’s Mechanical Turk (MTurk) and from Prolific. MTurk participants must reside in the United States and have an approval rating of at least 95% from at least 100 prior submissions. Prolific participants must choose the United States when asked for their nationality and have an approval rating of at least 95% from at least 100 prior submissions. <br>
description: We recruited online participants from Amazon’s Mechanical Turk (MTurk) and from Prolific. MTurk participants must reside in the United States and have an approval rating of at least 95% from at least
100 prior submissions. Prolific participants must
choose the United States when asked for their nationality and have an approval rating of at least 95%
from at least 100 prior submissions. 
 
 . Smallest Geographic Unit: United States
description: web-based survey;
DOI: 10.57841/casdc.0004475
title: 2022-2023年阿尔泰山跨境保护地油气通道地区地缘环境评价与风险识别数据集
DOI: 10.15468/dl.p9jg9a
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-87.66931 -1.56781,-88.86533 -9.87938,-76.85119 -9.9961,-76.15899 -1.25347,-87.66931 -1.56781))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Merluccius gayi peruanus Ginsburg, 1954"
 ]
}

 The dataset includes 5 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055471-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6073/pasta/48edac6904eb1aff4c1223d970c050b4
title: Soil organic carbon and associated uncertainty at 90 m resolution for peninsular Spain

description: Soil organic carbon (SOC) must be quantified and monitored to assess soil management practices, adapt policies, and evaluate environmental impacts. However, due to SOC spatial variability, soil surveys become a very challenging task because of the high costs of acquiring data, operational complexity, and updating. Digital soil mapping based on machine learning approaches in combination with remote sensing techniques have enabled soil carbon spatial distribution to be significantly improved, even with limited soil samples. A legacy soil database of 8,361 georeferenced profiles and a selection of environmental data-driven covariates intimately related to soil-forming factors (e.g., biota, climate, parent material) were used to generate SOC maps. Modeling of data was based on three supervised learning approaches: quantile regression forest, ensemble machine learning and auto-machine learning. For the final SOC spatial distribution maps, each pixel was assigned the prediction from the most accurate model, i.e., lowest uncertainty.
 We applied this modeling technique to generate cost-effective, high-resolution maps (90 m pixel resolution) of SOC distribution, and its associated spatially explicit uncertainty, in peninsular Spain. These maps showed 15.7 g.kg-1 mean SOC concentration at 0-30 cm and 3.6 g.kg-1 at 30-100 cm depth. The total SOC stock at its effective depth was 3.8 Pg C, storing the 74% in the upper 30 cm (2.82 Pg C). The correlation between SOC observed and predictions final values showed R2=0.68 for SOCc and R2=0.54 for SOCs at the upper 30cm. 
 The methodology proposed in this study aims to improve benchmark SOC estimates in support of the National GHG Emissions Inventory Report
DOI: 10.15468/dl.x9gcky
title: Occurrence Download

description: A dataset containing 229 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Procapra gutturosa (Pallas, 1777)"
 ]
}

 The dataset includes 229 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055474-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uayr3r
title: Occurrence Download

description: A dataset containing 91139 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Ramphocelus carbo (Pallas, 1764)",
 "Year 2010-2020"
 ]
}

 The dataset includes 91139 records from 100 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055473-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nbdazv
title: Occurrence Download

description: A dataset containing 692 species occurrences available in GBIF matching the query:
{
 "and" : [
 "CoordinateUncertaintyInMeters is greater than or equal to 1100.0",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Culex tritaeniorhynchus Giles, 1901"
 ]
}

 The dataset includes 692 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055476-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2687cm
title: Occurrence Download

description: A dataset containing 954038 species occurrences available in GBIF matching the query:
{
 "Country" : [
 "is Dominican Republic"
 ]
}

 The dataset includes 954038 records from 934 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055467-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6073/pasta/db83e4bb2f3fb8c9be1fafa5956957d0
title: Stream water chemistry data for Arikaree cirque, 1984 - ongoing.

description: This is a summary of major ion concentrations for stream water samples collected from the stream draining the Arikaree Cirque. Sampling location varied from the channel at the lip of the cirque, where it is first exposed by snowmelt, at the beginning of the season to the outlet from the pond at the foot of the glacier (usually around early July).
DOI: 10.6073/pasta/effe6d9f1a764ebaccb7ae9b28cba7a5
title: Stream water chemistry data for Green Lake 5 outlet, 1984 - ongoing.

description: This is a summary of major ion concentrations for stream water samples collected from the outlet stream at Green Lake 5.
DOI: 10.6073/pasta/277121f0334757746d9d52ce2c2e82ab
title: Stream water chemistry data for Green Lake 4, 1982 - ongoing.

description: This is a summary of major ion concentrations for water samples collected at Green Lake 4. Under summer conditions (June - October) samples were from the outlet stream from the lake; in winter (November - May) they were from the lake, beneath ice cover.
DOI: 10.6073/pasta/5534a25d64cd018f9c96a6a4c2f49315
title: Stream water chemistry data for Martinelli basin, 1984 - ongoing.

description: This is a summary of major ion concentrations for water samples from the outlet stream of the Martinelli Basin. Water usually flows seasonally from May to September.
DOI: 10.6073/pasta/9173009d00ed4602fcda5a529ee4a603
title: Stream water chemistry data for Saddle Stream site, 1994 - ongoing.

description: This is a summary of major ion concentrations for stream water samples collected at the Saddle Stream site, at the outflow of the Saddle Stream below Niwot Ridge.
DOI: 10.6073/pasta/e2abf6afe49c0a58bab46e13fc4eb55f
title: Streamflow data for outlet from Navajo meadow, 1994 - 2014

description: This is a summary of discharges from the stream draining Navajo meadow
 in the Green Lakes Valley. The samples were collected from the stream
 5 m upstream of outlet from Navajo meadow. Data includes daily
 summaries of flows calculated for a 24 hour day starting at 12:00 MST
 on the date recorded.
DOI: 10.6073/pasta/c193b3d06d941a074a9d407a3548c4b2
title: Streamflow data for Green Lake 5 outlet, 2006 - 2017

description: This is a summary of discharges from the stream draining Green Lake 5
 in the Green Lakes Valley. The samples were collected from the Creek
 15 m downstream of outlet from Green Lake 5. Data includes daily
 summaries of flows calculated for a 24 hour day starting at 12:00 MST
 on the date recorded.
DOI: 10.6073/pasta/817f8beba7b66e35790aa118cca50114
title: Streamflow for Martinelli basin, 1982 - ongoing.

description: This is a summary of discharges from the Martinelli Basin and is
 based on stage records from the outlet channel 30 m below the road
 at the foot of the basin.
DOI: 10.6073/pasta/7de15f073c80e868423bf81970d2d5a0
title: Streamflow data for Saddle stream, 1999 - ongoing.

description: This is a summary of discharges from the stream draining Niwot Ridge
 Saddle to the south and is based on stage records gauged at a timber
 weir with a 120 degree V-notch plate, located 30 m upstream of Green
 Lakes road. It consists of daily flow volumes.
DOI: 10.6073/pasta/d9a922df7747ce82ee1dd5c22026c07a
title: Streamflow for Green Lake 4, 1981 - ongoing.

description: This is a summary of discharges from the upper Green Lakes Basin
 based on stage records from the outlet of Green Lake 4, and consists
 of daily flow volumes.
DOI: 10.6073/pasta/25b45064d0e2fd8578aad055609c0ca3
title: Data Package for the 2022 Great Lakes Winter Grab

description: The data package contains the results from a multi-institutional winter limnology sampling campaign on the Laurentian Great Lakes. Researchers from 19 institutions sampled 49 locations in all five of the Great Lakes over a period of 24 days in February-March 2022. This dataset contains information on diverse physical, chemical, and biological parameters.
 
 Great Lakes Winter Grab ArcGIS Storymap showing all locations of sampling sites and select photos:
 https://storymaps.arcgis.com/stories/8ff1c332dd944ba9a744dc0e0fc18906
DOI: 10.15468/dl.cywf2v
title: Occurrence Download

description: A dataset containing 229 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Procapra gutturosa (Pallas, 1777)"
 ]
}

 The dataset includes 229 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055477-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.n99c7v
title: Occurrence Download

description: A dataset containing 128007 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Mimus saturninus (Lichtenstein, 1823)",
 "Year 2010-2020"
 ]
}

 The dataset includes 128007 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055472-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6073/pasta/0a364f23bb5bf2c5b4fcc9a7648d9d74
title: MCR LTER: Coral Reef: Benthic Water Temperature, ongoing since 2005

description: A continuous time series of benthic water temperature is measured with bottom-mounted 
 thermistors at six sites around the shores of Moorea, on the fringing reef, backreef, and forereef. 
 The forereef temperature is recorded with SBE 39s or SBE 56s at 10, 20, 30 and 40 m, 
 starting between 2005 to 2007, except FOR00 starting in 2010. These are ongoing except the 40 m 
 deployments were discontinued after August 2019.
 
 The backreef SBE 39s/56s are mounted on plates at 1 m depth at LTER 1 and at 2 m depth at the other five sites. 
 
 Onset HOBOs are deployed on the fringing reef at one shallow 1 m depth and one deeper depth 
 varying by site as follows: 6 m at LTER 1, 4 m at LTER 2, 7 m at LTER 3, 6 m at LTER 4, 
 3 m at LTER 5 and 4 m at LTER 6. The mounting plate is fixed to the reef and depths do not vary through time. 
 
 These depths are not measured by the thermistors and should be considered categorical. 
 
 Throughout the timeseries, temperature measurements have been taken every 2 minutes by SBE 39s 
 and SBE 56s, and every 8 minutes by the Onset HOBOs. Prior to July 2021 temperature data were subjected 
 to a low-pass filter to remove noise and temperature was resampled to a 20 minute time step. 
 Beginning in July 2021 data are raw temperature values sampled every two minutes (SBE 39s and SBE 56s) 
 or eight minutes (Onset HOBOs) depending on the instrument.
 
 This material is based upon work supported by the U.S. National Science Foundation under
 Grant No. OCE 16-37396 (and earlier awards) as well as a generous gift from the Gordon and
 Betty Moore Foundation. Research was completed under permits issued by the French Polynesian
 Government (Délégation à la Recherche) and the Haut-commissariat de la République en
 Polynésie Francaise (DTRT) (Protocole d'Accueil 2005-2023). This work represents a
 contribution of the Moorea Coral Reef (MCR) LTER Site.
DOI: 10.6073/pasta/b4e1b51f686adaee7f637d1b0049be5c
title: Animal Gut Microbiome (AGM) Data from 91 Published Studies for 224 Animal Species

description: Diversity and heterogeneity often are conflated but are fundamentally different. An aphorism proposed by Shavit and Ellison (2021; J. Phil. 118: 525–548) for distinguishing them is that “a zoo is diverse whereas an ecosystem is heterogeneous.” That is, a zookeeper measuring diversity simply enumerates the different types of animals; interactions are not expected to occur between animals separated by fences or other barriers. In contrast, measures of heterogeneity ought to include both interspecific interactions and relationships between species and their heterogeneous habitats. Here, we use cross-scale, dual scaling-law analyses of heterogeneity and diversity of animal gut microbiomes (AGMs) to address three objectives: (i) estimate the spatial heterogeneity and diversity of animal-gut microbiomes; (ii) analyze influences of phylogeny and diets on scaling of diversity and heterogeneity; (iii) explore mechanistic differences between diversity and heterogeneity in AGMs. From 4903 AGM samples collected from 318 animal species covering all six classes of vertebrates and four major classes of invertebrates, we estimated that ≈640,000 operational taxonomic units (OTUs or “species”) make up the pool of microbial species that could inhabit animal guts, among which ≈8000 are relatively common and ≈800 are dominant. The gut of any single animal, however, includes only 0.01–0.5% of the total species pool. We extended Ma’s diversity-area relationship for scaling diversity and extend Taylor’s Power Law and Luna et al.’s (2020; Diversity 12: 86) interaction diversity for scaling heterogeneity. At the community scale, phylogeny significantly influenced heterogeneity, but diets did not. Phylogeny and diets had limited influence on diversity at both community and landscape scales. Although two common measures of diversity—beta diversity and unevenness—commonly are synonymized with heterogeneity, our data lead us to conclude that diversity and heterogeneity measure two very different properties. Further, differences in scaling of diversity and heterogeneity are a result of heterogeneity being primarily the result of evolved dispersal behavior and interspecific interactions, whereas diversity results from abundances controlled on ecological time scales.
DOI: 10.15468/dl.vtwzhq
title: Occurrence Download

description: A dataset containing 316028 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Thraupis palmarum (Wied-Neuwied, 1821)",
 "Year 2010-2020"
 ]
}

 The dataset includes 316028 records from 250 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055475-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dgky7b
title: Occurrence Download

description: A dataset containing 27 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is CHN.1_1",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Papilio xuthus Linnaeus, 1767"
 ]
}

 The dataset includes 27 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055480-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57841/casdc.0004476
title: 2022-2023年阿尔泰山跨境保护地交通廊道沿线生物多样性及其影响因素数据集
DOI: 10.15468/dl.j8ncdj
title: Occurrence Download

description: A dataset containing 693 species occurrences available in GBIF matching the query:
{
 "and" : [
 "CoordinateUncertaintyInMeters is greater than or equal to 1000.0",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Culex tritaeniorhynchus Giles, 1901"
 ]
}

 The dataset includes 693 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055481-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xwv3vs
title: Occurrence Download

description: A dataset containing 18 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "TaxonKey is Mormodes luxata Lindl."
 ]
}

 The dataset includes 18 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055482-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6073/pasta/8e958d6009ef7229dcbbf953d0bac7fd
title: Green stormwater infrastructure projects voluntarily installed in Baltimore City through 2019

description: Much of the green stormwater infrastructure (GSI) in Baltimore,
 Maryland, USA, has been installed voluntarily by nonprofits and
 community groups, yet no comprehensive record of these installations
 previously existed. We worked with nonprofit stakeholders and
 Baltimore’s Department of Public Works to compile such a record, using
 both information provided by these agencies and publicly available
 data sources such as annual reports and newspaper articles. This
 dataset includes all voluntary green stormwater infrastructure
 projects that we were able to identify by the end of 2019, with the
 first known installation completed in 2001. The dataset includes two
 data tables, one with project-level information, and one with the
 locations of individual GSI facilities included in each project.
DOI: 10.6073/pasta/ed8e2529ed68f9c697385d1bcf6eaf44
title: Baltimore Ecosystem Study: Stewardship Mapping And Assessment Project (STEW-MAP) survey results 2011 and 2019

description: Addressing the challenges of sustainable and equitable city management in the 21st century requires innovative 
solutions and integration from a range of dedicated actors. In order to form and fortify partnerships of 
multi-sectoral collaboration, expand effective governance, and build collective resiliency it is important to 
understand the network of existing stewardship organizations. The term ‘stewardship’ encompasses a spectrum of 
local agents dedicated to the evolving process of community care and restoration. Groups involved in stewardship 
across Baltimore are catalysts of change through a variety of conservation, management, monitoring, transformation, 
education, and advocacy activities for the local environment – many with common goals of joint resource management, 
distributive justice, and community power sharing. The “environment” here is intentionally broadly defined as land, air, water, energy and more. 
 The Stewardship Mapping and Assessment Project (STEW-MAP) is a method of data collection and visualization 
that tracks the characteristics of organizations and their financial and informational flows across sectors and 
geographic boundaries. The survey includes questions about three facets of environmental stewardship groups: 
1) organizational characteristics, 2) collaboration networks, and 3) stewardship “turfs” where each organization works. 
The data have been analyzed alongside landcover and demographic data and used in multi-city studies 
incorporating similar datasets across major urban areas of the U.S. Additional information about the growing 
network of cities conducting stewmap can be found here: https://www.nrs.fs.usda.gov/STEW-MAP/
 Romolini, Michele; Grove, J. Morgan; Locke, Dexter H. 2013. Assessing and comparing relationships between urban environmental 
stewardship networks and land cover in Baltimore and Seattle. Landscape and Urban Planning. 120: 190-207. https://www.fs.usda.gov/research/treesearch/44985
 Johnson, M., D. H. Locke, E. Svendsen, L. Campbell, L. M. Westphal, M. Romolini, and J. Grove. 2019. Context matters: 
influence of organizational, environmental, and social factors on civic environmental stewardship group intensity. Ecology and Society 24(4): 1. https://doi.org/10.5751/ES-10924-240401
 Ponte, S. 2023. Social-ecological processes and dynamics of urban forests as green stormwater infrastructure in Maryland, 
USA. Doctoral dissertation, University of Maryland, College Park, MD.
DOI: 10.6073/pasta/9ce8e2bc0fc472544c621e4658bdc6a4
title: CO2 concentrations and emissions from subtropical headwater streams, São Carlos, Brazil, 2018

description: The data were collected in the municipalities of São Carlos, Itirapina, and Brotas in the state of São Paulo, southeastern Brazil. Six sandy/rocky-bottom headwater streams (1st to 2nd order) were selected based on the main land use in the catchment. Three streams drained sugarcane plantations, and three streams drained native vegetation catchments (Cerrado vegetation). The catchment drainage areas were determined using digital elevation models. Land use was classified based on satellite images from LANDSAT using ArcGIS software.
 The data were collected to study the impact of different land uses (sugarcane plantations vs. native vegetation) on the headwater streams. These streams have previously been studied for methane dynamics, indicating a focus on understanding environmental and ecological impacts. Three samples were collected from each stream during spring, summer, and winter using the headspace extraction technique. Due to access issues, samples from one stream were not collected in spring and summer 2018. Syringes filled with ultrapure nitrogen were used to collect stream water samples, which were then shaken to equilibrate gases. The gas was analyzed using a Shimadzu GC-2014 gas chromatograph equipped with various detectors. Concentrations were compared with standards to calculate CO2 levels, and CO2 emissions were calculated based on gas transfer velocity and dissolved concentrations.