cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10370000
title: Climate model and proxy input data for PaleoDA South America reconstruction

description: This repository contains  input data needed to run the paleoclimate reconstruction code for  "A continental reconstruction of hydroclimatic variability in South America during the past 2000 years", submitted to Climate of the Past in February 2024 [https://egusphere.copernicus.org/preprints/2024/egusphere-2024-545/].  The Github repository is located here: https://github.com/mchoblet/paleoda_sa/tree/main

Structure:

model_data: One File for each Model (GISS, CCSM (isoGSM), CESM, ECHAM5, iHADCM3) and variable (prec,tsurf,d18O, SPEI). Monthly resolution.

proxy_data: One File for each proxy record type (Trees and corals contain a separate file for annual and djf linear regression parameters, the proxy data as such is the same). The data has yearly resolution, and thus also contains NaNs for when a year is not covered by a proxy. Note, that these time series are resampled to a regular resolution in the multi-time scale PaleoDA code.

Climate Model Data:

The original data can be found in https://zenodo.org/records/6610684. The data in this repository here has been slightly modified and regridded for easier processing by the reconstruction algorithm.  When using the data here, please also cite https://zenodo.org/records/6610684 and the publication 

"Investigating stable oxygen and carbon isotopic variability in speleothem records over the last millennium using multiple isotope-enabled climate models", by 

Janica C. Bühler, Josefine Axelsson, Franziska A. Lechleitner, Jens Fohlmeister, Allegra N. LeGrande, Madhavan Midhun, Jesper Sjolte, Martin Werner, Kei Yoshimura, and Kira Rehfeld (https://cp.copernicus.org/articles/18/1625/2022/cp-18-1625-2022.html)

Climate Proxy Data:

A regional proxy record subselection for South America. See References in Appendix A Choblet et al. (https://egusphere.copernicus.org/preprints/2024/egusphere-2024-545/). The DOI of each record is stored as Metadata.

How were these files created?

The steps are documented in the the Github repository https://github.com/mchoblet/paleoda_sa/tree/main (data_preprocessing). The SPEI drought index has ben computed from modeled precipitation and temperature using Thornthwaite's method (using the Climate Indices package, https://github.com/monocongo/climate_indices).

Manuscript revision in July 2024:



Added historical documentary indices time series and the Puyehue lake record. For technical reasons in the PaleoDA algorithm, it is kept apart from the other lake records. The reconstruction code on Github has been updated for including these datasets.
DOI: 10.5281/zenodo.10370001
title: Climate model and proxy input data for PaleoDA South America reconstruction

description: This repository contains  input data needed to run the paleoclimate reconstruction code for  "A continental reconstruction of hydroclimatic variability in South America during the past 2000 years", submitted to Climate of the Past in February 2024 [https://egusphere.copernicus.org/preprints/2024/egusphere-2024-545/].  The Github repository is located here: https://github.com/mchoblet/paleoda_sa/tree/main

Structure:

model_data: One File for each Model (GISS, CCSM (isoGSM), CESM, ECHAM5, iHADCM3) and variable (prec,tsurf,d18O, SPEI). Monthly resolution.

proxy_data: One File for each proxy record type (Trees and corals contain a separate file for annual and djf linear regression parameters, the proxy data as such is the same). The data has yearly resolution, and thus also contains NaNs for when a year is not covered by a proxy. Note, that these time series are resampled to a regular resolution in the multi-time scale PaleoDA code.

Climate Model Data:

The original data can be found in https://zenodo.org/records/6610684. The data in this repository here has been slightly modified and regridded for easier processing by the reconstruction algorithm.  When using the data here, please also cite https://zenodo.org/records/6610684 and the publication 

"Investigating stable oxygen and carbon isotopic variability in speleothem records over the last millennium using multiple isotope-enabled climate models", by 

Janica C. Bühler, Josefine Axelsson, Franziska A. Lechleitner, Jens Fohlmeister, Allegra N. LeGrande, Madhavan Midhun, Jesper Sjolte, Martin Werner, Kei Yoshimura, and Kira Rehfeld (https://cp.copernicus.org/articles/18/1625/2022/cp-18-1625-2022.html)

Climate Proxy Data:

A regional proxy record subselection for South America. See References in Appendix D Choblet et al. [LINK]. The DOI of each record is stored as Metadata.

How were these files created?

The steps are documented in the the Github repository https://github.com/mchoblet/paleoda_sa/tree/main (data_preprocessing). The SPEI drought index has ben computed from modeled precipitation and temperature using Thornthwaite's method (using the Climate Indices package, https://github.com/monocongo/climate_indices).
DOI: 10.25345/c50c4sw8v
title: MassIVE MSV000095319 - GNPS_koolengroup_mircorganisms_B
title: LC-MS/MS of fungi studied in the metabolomics and mass spectrometry research group (MMSRG) at the State University of Amazonas, Brazil.
DOI: 10.15468/dl.ftf8eh
title: Occurrence Download

description: A dataset containing 482 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-73.54007 9.43119,-73.41952 9.43105,-73.42051 9.53436,-73.54109 9.53317,-73.54007 9.43119))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 482 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022524-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.12734475
title: Investigating M-Health Acceptance by Citizens in Indonesia: Moderating Effects of E-Health Literacy
DOI: 10.5281/zenodo.12734476
title: Investigating M-Health Acceptance by Citizens in Indonesia: Moderating Effects of E-Health Literacy
DOI: 10.6073/pasta/e793fb8629b1a9058b2dda19633223f7
title: Dissecting the smell of fear from conspecific and heterospecific prey: Investigating the processes that induce anti-predator defenses.

description: Prey use chemical cues from predation events to obtain information about predation risk to alter their phenotypes. Though we know how many prey respond to predators, we still have a poor understanding of the processes and chemical cues involved during a predation event. We examined how gray treefrog tadpoles (Hyla verisciolor) altered their behavior and morphology when raised with cues from different stages of predator attack, predators fed different amounts of prey, and predators consuming different combinations of treefrog tadpoles or snails (Helisoma trivolvis). We found that starved predators and predators fed snails induced no defensive responses whereas tadpoles exposed to a predator consuming gray treefrogs induced greater hiding, lower activity, and relatively deeper tails. We also found that the tadpoles did not respond to crushed, chewed, or digested conspecifics, but they did respond to consumed (i.e. chewed + digested) conspecifics. When we increased the treefrog biomass consumed by predators, tadpoles frequently increased their defenses when only tadpoles were consumed and always increased their defenses when the total diet biomass was held constant via the inclusion of snails. When predators experienced temporal variation in diet composition, including cues from snails to cause additional digestive cues or chemical noise, there was no effect on tadpole phenotypes. Our results suggest that amphibian prey rely on cues from both chewing and digestion of conspecifics and that the presence of cues from digested heterospecifics play little or no role in adding chemical noise or increased digestive enzymes and by-products that interfere with induced defenses.
DOI: 10.15468/dl.xydvsq
title: Occurrence Download

description: A dataset containing 215 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Bassariscus sumichrasti (Saussure, 1860)"
 ]
}

 The dataset includes 215 records from 32 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022525-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.s7tx8f
title: Occurrence Download

description: A dataset containing 130 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is South America",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Cheilolejeunea ovalis (Lindenb. & Gottsche) W.Ye, R.L.Zhu & Gradst."
 ]
}

 The dataset includes 130 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022526-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2q3kxd
title: Occurrence Download

description: A dataset containing 1411 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-73.56437 9.42364,-73.45535 9.42683,-73.45903 9.5349,-73.45903 9.5349,-73.46256 9.59575,-73.49698 9.59393,-73.56931 9.59446,-73.56858 9.5219,-73.56437 9.42364))",
 "HasCoordinate is true",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 1411 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022527-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.35qdry
title: Occurrence Download

description: A dataset containing 812 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Continent is Europe",
 "OccurrenceStatus is Present",
 "TaxonKey is Arion distinctus Mabille, 1868"
 ]
}

 The dataset includes 812 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022528-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.7545020
title: MESA input/output for Evolutionary and Observational Consequences of Dyson Sphere Feedback

description: MESA inlists, extras, and output for Evolutionary and Observational Consequences of Dyson Sphere Feedback, published in the Astrophysical Journal, 2022.

Paper DOI: 10.3847/1538-4357/ac3421

Files included for Irradiated star experiments (recreating the work of Tout et al. (1989) in MESA) in irradiatedstar.zip:



src/



run_star_extras.f: MESA extension allowing for a constant temperature bath to irradiate a star.



inlists/



inlist_zams: Create a zero age main sequence star.

inlist_irrad_tams: Evolve a star from ZAMS to TAMS in a constant temperature irradiation bath.

inlist_irrad_hefl: Attempt to evolve a star from TAMS to the helium flash in a constant temperature irradiation bath. Note: This model crashes before the helium flash for many parameter choices.



plots/



tout_recreation_plot.ipynb: Python Jupyter notebook for generating the Figure 1 in the paper.

lifetimes.pdf: My MESA recreation of Figure 5 from Tout et al. (1989).



LOGS/



*_history: MESA output for the evolution of a given stellar mass to a given age in a given temperature bath.




Files included for Dyson Sphere Feedback experiments in dsfeedback.zip:



src/



run_star_extras.f: MESA extension allowing for a fraction of a star's luminosity to be dumped back onto the outer layer as extra heat.



inlists/



inlist_sphere_tams: Evolve a selected model to the end of the main sequence with a given DS feedback fraction.

inlist_zams: Create a zero age main sequence star.

inlist_zams_lowmass: Create a zero age main sequence star with a timestep limit that helps with lower mass stars.

inlist_zamstoage: Evolve a star normally from ZAMS to a selected age (0.6Gyr used here for 2Msun).

inlist_zamstosolarage: Evolve a star normally from ZAMS to 4.6 Gyr (used before DS application for 1Msun and lower stars).



plots/



ds_feedback_plots.ipynb: Python Jupyter notebook for generating the figures 2-9 in the paper.

newplots/*: Plots generated from the notebook



LOGS/



*_history: MESA output for the evolution of a given stellar mass, to a given age, and DS feedback level

*_profile: MESA output for the structure of a given stellar mass, at one given age, and DS feedback level




Email me at mhuston@berkeley.edu if you have any comments or questions!

MESA version: 12778

MESA SDK version: x86_64-macos-20.4.1
DOI: 10.5281/zenodo.7545021
title: MESA input/output for Evolutionary and Observational Consequences of Dyson Sphere Feedback

description: MESA inlists, extras, and output for Evolutionary and Observational Consequences of Dyson Sphere Feedback, published in the Astrophysical Journal, 2022.

Paper DOI: 10.3847/1538-4357/ac3421

Files included for Irradiated star experiments (recreating the work of Tout et al. (1989) in MESA) in irradiatedstar.zip:



src/



run_star_extras.f: MESA extension allowing for a constant temperature bath to irradiate a star.



inlists/



inlist_zams: Create a zero age main sequence star.

inlist_irrad_tams: Evolve a star from ZAMS to TAMS in a constant temperature irradiation bath.

inlist_irrad_hefl: Attempt to evolve a star from TAMS to the helium flash in a constant temperature irradiation bath. Note: This model crashes before the helium flash for many parameter choices.



plots/



tout_recreation_plot.ipynb: Python Jupyter notebook for generating the Figure 1 in the paper.

lifetimes.pdf: My MESA recreation of Figure 5 from Tout et al. (1989).



LOGS/



*_history: MESA output for the evolution of a given stellar mass to a given age in a given temperature bath.




Files included for Dyson Sphere Feedback experiments in dsfeedback.zip:



src/



run_star_extras.f: MESA extension allowing for a fraction of a star's luminosity to be dumped back onto the outer layer as extra heat.



inlists/



inlist_sphere_tams: Evolve a selected model to the end of the main sequence with a given DS feedback fraction.

inlist_zams: Create a zero age main sequence star.

inlist_zams_lowmass: Create a zero age main sequence star with a timestep limit that helps with lower mass stars.

inlist_zamstoage: Evolve a star normally from ZAMS to a selected age (0.6Gyr used here for 2Msun).

inlist_zamstosolarage: Evolve a star normally from ZAMS to 4.6 Gyr (used before DS application for 1Msun and lower stars).



plots/



ds_feedback_plots.ipynb: Python Jupyter notebook for generating the figures 2-9 in the paper.

newplots/*: Plots generated from the notebook



LOGS/



*_history: MESA output for the evolution of a given stellar mass, to a given age, and DS feedback level

*_profile: MESA output for the structure of a given stellar mass, at one given age, and DS feedback level




Email me at mhuston@berkeley.edu if you have any comments or questions!

MESA version: 12778

MESA SDK version: x86_64-macos-20.4.1
DOI: 10.15468/dl.3ga9kp
title: Occurrence Download

description: A dataset containing 1321 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Living Specimen",
 "Continent is Europe",
 "DatasetKey is one of (Birds ringed by Revtangen Bird Observatory 1936-2018, Southwest Norway, Recoveries of birds ringed by Revtangen Bird Observatory (Southwest Norway), 1936-2018)",
 "HasCoordinate is true",
 "TaxonKey is Erithacus rubecula (Linnaeus, 1758)",
 "Year 2012-2018"
 ]
}

 The dataset includes 1321 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022530-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xyvy6r
title: Occurrence Download

description: A dataset containing 5956 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "TaxonKey is Rhinella horribilis (Wiegmann, 1833)"
 ]
}

 The dataset includes 5956 records from 59 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022531-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2duwhu
title: Occurrence Download

description: A dataset containing 174162 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Material sample, Material citation, Specimen, Occurrence evidence)",
 "Geometry POLYGON((-97.52226 25.94756,-98.13809 24.2643,-98.09703 22.6221,-97.60437 21.18517,-96.49589 19.46086,-95.55162 18.47554,-93.99153 18.10604,-92.51355 18.63976,-93.00621 20.56935,-93.45781 21.67783,-95.10001 23.32003,-95.42845 25.78334,-97.52226 25.94756))",
 "OccurrenceStatus is Present",
 "TaxonKey is Arthropoda"
 ]
}

 The dataset includes 174162 records from 293 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022529-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ks3q83
title: Occurrence Download

description: A dataset containing 747 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is Steatoda grossa (C.L.Koch, 1838)",
 "PhylumKey is Arthropoda",
 "Year is greater than or equal to 1992",
 "Year is less than or equal to 2012",
 "Geometry POLYGON((-26 34, 42 34, 42 70, -26 70, -26 34))"
 ]
}

 The dataset includes 747 records from 77 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025185-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.md5uaq
title: Occurrence Download

description: A dataset containing 718 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Vachellia campechiana (Mill.) Seigler & Ebinger"
 ]
}

 The dataset includes 718 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025186-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3217/fwv1r-d5458
title: 3D Model of the Shey Sumdo Monastery

description: As part of ongoing FWF research projects on Buddhist architecture in the Western Himalayas at Graz University of Technology, it was possible to secure significant documentation and materials relating to sacred buildings in Dolpo in Western Nepal in recent years, led by the Institute of Architectural Theory, History of Art and Cultural Studies (akk). Provoked by the outstanding performance of modern surveying technologies, a cooperation was started with our institute (Institute of Engineering Geodesy and Measurement Systems, IGMS) in order enhance existing methodologies of conventional building research by the integration of modern surveying methods, within the frame of an FWF project “Buddhist Architecture in Western Himalayas” (https://archresearch.tugraz.at/).

The aim of this interdisciplinary work was to explore significant Buddhist temple sites in Upper Dolpo, a remote area in Nepal, and to document several sites using modern 3D laser scanning technology. The derived models show a high level of detail and confidence, both from the outside and inside of the temple. Thus, they provide a solid data foundation for studying architectural connections in topologies of different sites and for further building research within the scientific community.

In order to reach a high accuracy level (within a few millimeters), the documentation strategy in the project was based on a combination of highly accurate laser scan data (Leica RTC360) and photogrammetric images. The individual laser scans were pre-registered in the field, and afterwards post-processed in the Leica Register 360 software. The registration was based on cloud-to-cloud registrations (in order to have a high mobility in the measurement setups), and – where possible - on stable reference points. The coordinates of these ground control points were determined using a geodetic total station (available only 2022) with redundant measurements in local geodetic network configuration.

This DOI represents the whole dataset gathered at the site in the fieldwork in 2022/2023. An overview of the site (JPG) and a down-sampled 3D model are provided herein for general distribution in order to avoid hidden inventory and provide these data to the commited scientific community. Please contact the authors if the complete data set and/or raw data (point cloud) is required for scientific research.
DOI: 10.3217/sn49f-rj787
title: 3D Model of the Shey Sumdo Monastery

description: As part of ongoing FWF research projects on Buddhist architecture in the Western Himalayas at Graz University of Technology, it was possible to secure significant documentation and materials relating to sacred buildings in Dolpo in Western Nepal in recent years, led by the Institute of Architectural Theory, History of Art and Cultural Studies (akk). Provoked by the outstanding performance of modern surveying technologies, a cooperation was started with our institute (Institute of Engineering Geodesy and Measurement Systems, IGMS) in order enhance existing methodologies of conventional building research by the integration of modern surveying methods, within the frame of an FWF project “Buddhist Architecture in Western Himalayas” (https://archresearch.tugraz.at/).

The aim of this interdisciplinary work was to explore significant Buddhist temple sites in Upper Dolpo, a remote area in Nepal, and to document several sites using modern 3D laser scanning technology. The derived models show a high level of detail and confidence, both from the outside and inside of the temple. Thus, they provide a solid data foundation for studying architectural connections in topologies of different sites and for further building research within the scientific community.

In order to reach a high accuracy level (within a few millimeters), the documentation strategy in the project was based on a combination of highly accurate laser scan data (Leica RTC360) and photogrammetric images. The individual laser scans were pre-registered in the field, and afterwards post-processed in the Leica Register 360 software. The registration was based on cloud-to-cloud registrations (in order to have a high mobility in the measurement setups), and – where possible - on stable reference points. The coordinates of these ground control points were determined using a geodetic total station (available only 2022) with redundant measurements in local geodetic network configuration.

This DOI represents the whole dataset gathered at the site in the fieldwork in 2022/2023. An overview of the site (JPG) and a down-sampled 3D model are provided herein for general distribution in order to avoid hidden inventory and provide these data to the commited scientific community. Please contact the authors if the complete data set and/or raw data (point cloud) is required for scientific research.