cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.14975004
title: Arctic Sea Ice and Land Parameter Correlations (ASILaC)

description: The ASILaC datasets presents monthly files of correlation statistics calculated between Sea Ice Area (SIA) in eight Arctic basins and terrestrial parameters in the Arctic region North of 60°N.

Data format: raster GeoTIFF

The terrestrial parameters are: 1. Permafrost Ground Temperature at 2m depth 2000-2019 (source: Obu et al. (2023))2. Maximum NDVI (MaxNDVI) based on MODIS 2000-2019 (Source: Tommervik (2025))3. Time Integrated NDVI (TINDVI) based on MODIS 2000-2019 (Source: Tommervik (2025))4. Snow Water Equivalent (SWE) 2000-2018 based on SSMI (Source: Luojus et al. (2021))

Sea ice area data for 2000-2019 have been obtained from OSI SAF (OSI SAF 2020).

De-trending has been applied to all parameters. The correlation (r) has been filtered at significance level p_value < 0.05. 

Each file referring to subbasins contains 6 bands: 

Band 1: minimum correlation valueBand 2: maximum correlation valueBand 3: associated basin with minimum correlation value Band 4: associated basin with maximum correlation value Band 5: mean correlation valueBand 6: standard deviation

Each file referring to the entire NH sea ice area contains 1 band: Band 1: correlation value

Bartsch, A., Tanguy, R., Bergstedt, H., von Baeckmann, C., Tømmervik, H., Macias-Fauria, M., Lemmetyinen, J., Rautiainen, K., Gruber, C., and Forbes, B. C.: Similarities between sea ice area variations and satellite-derived terrestrial biosphere and cryosphere parameters across the Arctic, The Cryosphere, 19, 4929–4967, https://doi.org/10.5194/tc-19-4929-2025, 2025.
DOI: 10.15468/dl.vchrba
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is CHN.28_1",
 "TaxonKey is Schoenoplectiella mucronata"
 ]
}

 The dataset includes 3 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002158-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zxusub
title: Occurrence Download

description: A dataset containing 324 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Alpinia malaccensis"
 ]
}

 The dataset includes 324 records from 38 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002159-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17026/ar/4omz9y
title: Replication Data for: Transect-rapport 5221: Leersum, Rijksstraatweg 22A-24 Gemeente Utrechtse Heuvelrug (UT) Een Archeologisch Inventariserend Veldonderzoek door middel van Proefsleuven (IVO-P)

description: Tijdens het onderzoek zijn 29 sporen en 24 vondsten aangetroffen binnen een totaaloppervlak van 760 
m2
. Binnen de werkputten is de landschappelijke en hoge archeologische verwachting van het 
vooronderzoek bevestigd. In het plangebied is sprake van een Laat-Prehistorisch grafveld dat 
vermoedelijk dateert uit het Laat-Neolithicum en/of de Bronstijd. Deze bestaat op zijn minst uit een 
Laat-Neolithisch (of Vroege Bronstijd-) Klokbekergraf (S2), een kringgreppel of ringsloot (S23) en een 
twaalftal vermoedelijke grafkuilen. De klokbeker uit het klokbekergraf is een van de kleinste 
klokbekers van Nederland. De sporen zijn aangetroffen in de top van de C-horizont van de sandrafzettingen. Deze wordt afgedekt door een BC-horizont (plaatselijk), een akkerlaag en een moderne 
bouwvoor. De vindplaats kan niet begrensd worden in het plangebied, aangezien de mogelijke 
grafkuilen en andere vindplaats-gerelateerde sporen verspreid liggen over het gehele plangebied. 
Naast sporen van een grafveld zijn er vondsten en sporen aangetroffen met een recentere datering. 
Deze kunnen niet gewaardeerd worden of zijn niet behoudenswaardig.
DOI: 10.17026/ar/kgznl5
title: Replication Data for: Transect-rapport 6020: Utrecht, Doorfietsroute Utrecht-Amersfoort Gemeente Utrecht (UT) Archeologisch bureauonderzoek (BO)

description: Op basis van het bureauonderzoek is een gespecificeerde archeologische verwachtingskaart gemaakt. 
Deze is opgenomen in bijlage 19. Het plangebied ligt op de overgang van het rivierengebied naar het 
dekzandgebied. In het westen van het plangebied (Alexander Numankade) worden bedding-, oeveren restgeulafzettingen van de Oud-Aa en Utrechtse Vecht in de ondergrond verwacht. In het oosten 
van de Alexander Numankade is de aanwezigheid van een restgeul in het plangebied aangetoond met 
boringen. Deze is ten zuiden van het plangebied in 1179 na Chr. verland volgens een 14C-datering. Uit 
onderzoek uit de omgeving blijkt ook dat ten noorden van de restgeul nauwelijks oeverafzettingen 
aanwezig zijn, die aantrekkelijk voor bewoning kunnen zijn geweest. Naar het westen toe buigt de 
restgeul iets af naar het zuiden waardoor het niet exact bekend is tot waar in de Alexander 
Numankade de restgeul nog in het plangebied kan worden aangetroffen of niet. Wel blijkt uit 
archeologische boringen en milieukundige boringen waar klei en dekzand aanwezig is. In het oosten 
van de Alexander Numankade is de restgeul dus aangetoond, en in het westen van de Alexander 
Numankade worden bedding-, restgeul, en oeverafzettingen verwacht. De oeverafzettingen kunnen 
vanaf de Bronstijd bewoond zijn geweest, hoewel in de direct omgeving nog geen vondsten uit de 
Bronstijd-Vroege-Middeleeuwen bekend zijn. Ter plaatse van intacte oeverafzettingen geldt een hoge 
archeologische verwachting op archeologische resten en/of sporen uit de periode Bronstijd-VroegeMiddeleeuwen. Ter plaatse van de restgeul geldt een hoge archeologische verwachting op 
watergerelateerde vondsten vanaf de Bronstijd.
DOI: 10.60719/aphrc-2025-018
title: Examining the Complex Dynamics Influencing Persistent Acute Malnutrition in Turkana and Samburu Counties – A Longitudinal Mixed Methods Study to Support Community Driven Activity Design (USAID Nawiri Wave VI), USAID Nawiri Wave VI

description: Acute malnutrition in infants and children less than 5 years is persistent in the arid and semi-arid lands (ASALs) of East Africa and the Sahel region despite years of investment. In the ASALs of Kenya, the situation is exacerbated by deep-rooted poverty and unequal access to basic services, sustained community conflicts, migration, poor seasonal rainfall/drought and other shocks. Nutrition specific and nutrition sensitive national and county level programs have either not been developed or not implemented effectively.

Objectives: To understand and map immediate, underlying, basic and systemic drivers of acute malnutrition for the development of overarching as well as micro-solutions for the sustainable reduction of persistent acute malnutrition and inform pilot studies and Phase 2 (second phase of USAID Nawiri project implementation) activities in Turkana and Samburu counties.

Methods: This study is a longitudinal mixed-methods observational study of children less than 3 years and their mothers and/or caregivers in Samburu and Turkana counties. Both quantitative and qualitative methods were utilized in the data collection processes. Data collection commenced in January 2021. Data analysis, learning and adapting was also ongoing so that results could inform pilots, theory of change review and Phase 2 activities throughout the study.

Study outcomes: To develop new interventions, and to adapt and contextualize existing interventions to prevent global acute malnutrition (GAM); strengthen social and behavior change (SBC) strategies around maternal, infant and young child nutrition (MIYCN), water and sanitation (WASH), community health systems, gender dynamics, livelihoods and resilience, and to inform improvements of the current nutrition surveillance system.
DOI: 10.15468/dl.ndd53k
title: Occurrence Download

description: A dataset containing 2583 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Enteromorpha compressa"
 ]
}

 The dataset includes 2583 records from 119 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002160-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17453495
title: Air Pollution Dataset Jakarta

description: Air Pollution Dataset in Jakarta that gathered from Satu Data Jakarta website (Satu Data Jakarta), consist of 6 variant of pollutant that are PM10, PM2.5, CO, NO2, SO2, and O3, spanning from 1st January 2024 until 31th August 2025.
DOI: 10.5281/zenodo.17453496
title: Air Pollution Dataset Jakarta

description: Air Pollution Dataset in Jakarta that gathered from Satu Data Jakarta website (Satu Data Jakarta), consist of 6 variant of pollutant that are PM10, PM2.5, CO, NO2, SO2, and O3, spanning from 1st January 2024 until 31th August 2025.
DOI: 10.5281/zenodo.17452375
title: RISEnergy_D3.2 Annex MD platform and Data repository/dataset list v.2

description: Annex to Deliverable 3.2 of project RISEnergy. Contains lists of: Metadata platforms, Data repository sites and Database services relevant to 10 renewabl energy sectors of concern by RISEnergy
DOI: 10.5281/zenodo.17452376
title: RISEnergy_D3.2 Annex MD platform and Data repository/dataset list v.2

description: Annex to Deliverable 3.2 of project RISEnergy. Contains lists of: Metadata platforms, Data repository sites and Database services relevant to 10 renewabl energy sectors of concern by RISEnergy
DOI: 10.15468/dl.h2f8m8
title: Occurrence Download

description: A dataset containing 1387 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Enteromorpha flexuosa"
 ]
}

 The dataset includes 1387 records from 93 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002161-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25345/c5m902g66
title: MassIVE MSV000099614 - XIAMENUNIVERSITY-QIUYAN-ykz0811
title: ykz0811 is a compound with distinct chemical characteristics, having a relative molecular mass of 252.14.
DOI: 10.15468/dl.wskzeq
title: Occurrence Download

description: A dataset containing 2404 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cornus kousa chinensis"
 ]
}

 The dataset includes 2404 records from 78 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002162-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.d4jqj2
title: Occurrence Download

description: A dataset containing 103 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is India",
 "TaxonKey is Strobilanthes kunthiana"
 ]
}

 The dataset includes 103 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002163-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bx8um2
title: Occurrence Download

description: A dataset containing 10 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Quasipaa acanthophora"
 ]
}

 The dataset includes 10 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002164-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17453385
title: Physiological Signal Analysis for Stress Recovery Modeling: Complete Dataset and Reproducible Code
DOI: 10.5281/zenodo.17453384
title: Physiological Signal Analysis for Stress Recovery Modeling: Complete Dataset and Reproducible Code
DOI: 10.15468/dl.9ufsm7
title: Occurrence Download

description: A dataset containing 1996 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Enteromorpha prolifera"
 ]
}

 The dataset includes 1996 records from 90 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002165-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17043/tarfala-lihtti-meteorology-2
title: Meteorological data from Lihtti, northern Sweden
DOI: 10.15468/dl.ryr2am
title: Occurrence Download

description: A dataset containing 852 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cornus kousa chinensis"
 ]
}

 The dataset includes 852 records from 41 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002166-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.g7jv3x
title: Occurrence Download

description: A dataset containing 356829 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Myanmar",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 356829 records from 531 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002144-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pueqgy
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is CHN.28_1",
 "TaxonKey is Thesium chinense"
 ]
}

 The dataset includes 6 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002167-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3886/e239223
title: Traffic Safety Facts Annual Report Tables

description: A Compilation of Motor Vehicle Traffic Crash Data, the
 National Highway Traffic Safety Administration (NHTSA) presents descriptive statistics
 about traffic crashes of all severities, from those that result in property damage to those
 that result in the loss of human life. Information from three of NHTSA’s primary data systems has been combined
 to create a single source for motor vehicle traffic crash statistics. The first data system,
 the Fatality Analysis Reporting System (FARS), is probably the better known of the three sources.
 Established in 1975, FARS contains data on the most severe traffic crashes, those in which someone was killed.
 The second source is the National Automotive Sampling System General Estimates System (NASS GES),
 which began operation in 1988. NASS GES contains data from a nationally representative sample of
 police-reported crashes of all severities, including those that result in death, injury, or property damage.
 The third source is the new Crash Report Sampling System (CRSS), which replaced NASS GES in 2016.
 CRSS is the redesigned nationally representative sample of police-reported traffic crashes.
 Note that 2018 and earlier year FARS data are final and generally not subject to change. However, minor revisions
 were made to the 2017 and 2018 FARS Final files. For more information refer to "About This Report" in the Introduction section.
 Although the 2023 data file is a full year's worth of data, it is subject to change
 when it is finalized. The current version of the 2023 FARS data file is referred to as the
 Annual Report File (ARF). The additional time between the Annual Report file and the Final file provides
 the opportunity for submission of important variable data requiring outside sources, which may lead to
 changes in the final counts. The updated final counts for 2023 will be reflected with the release of
 the 2024 Annual Report File.
 <br><b>Notes</b>: NASS GES was discontinued in 2016 and 
replaced with a new system called CRSS.
 The 2016 data year was the first data collection year of 
CRSS. However, the 2016 and later year estimates from CRSS are not 
comparable to 2015 and earlier year estimates from NASS GES.<br>GES and CRSS data are included here, FARS data are at https://www.datalumos.org/datalumos/project/239071/version/V1/view<br>
DOI: 10.3886/e239223v1
title: Traffic Safety Facts Annual Report Tables

description: A Compilation of Motor Vehicle Traffic Crash Data, the
 National Highway Traffic Safety Administration (NHTSA) presents descriptive statistics
 about traffic crashes of all severities, from those that result in property damage to those
 that result in the loss of human life. Information from three of NHTSA’s primary data systems has been combined
 to create a single source for motor vehicle traffic crash statistics. The first data system,
 the Fatality Analysis Reporting System (FARS), is probably the better known of the three sources.
 Established in 1975, FARS contains data on the most severe traffic crashes, those in which someone was killed.
 The second source is the National Automotive Sampling System General Estimates System (NASS GES),
 which began operation in 1988. NASS GES contains data from a nationally representative sample of
 police-reported crashes of all severities, including those that result in death, injury, or property damage.
 The third source is the new Crash Report Sampling System (CRSS), which replaced NASS GES in 2016.
 CRSS is the redesigned nationally representative sample of police-reported traffic crashes.
 Note that 2018 and earlier year FARS data are final and generally not subject to change. However, minor revisions
 were made to the 2017 and 2018 FARS Final files. For more information refer to "About This Report" in the Introduction section.
 Although the 2023 data file is a full year's worth of data, it is subject to change
 when it is finalized. The current version of the 2023 FARS data file is referred to as the
 Annual Report File (ARF). The additional time between the Annual Report file and the Final file provides
 the opportunity for submission of important variable data requiring outside sources, which may lead to
 changes in the final counts. The updated final counts for 2023 will be reflected with the release of
 the 2024 Annual Report File.
 <br><b>Notes</b>: NASS GES was discontinued in 2016 and 
replaced with a new system called CRSS.
 The 2016 data year was the first data collection year of 
CRSS. However, the 2016 and later year estimates from CRSS are not 
comparable to 2015 and earlier year estimates from NASS GES.<br>GES and CRSS data are included here, FARS data are at https://www.datalumos.org/datalumos/project/239071/version/V1/view<br>
DOI: 10.15468/dl.9uwwag
title: Occurrence Download

description: A dataset containing 26 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is CHN.28_1",
 "TaxonKey is Saussurea leucophylla"
 ]
}

 The dataset includes 26 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002169-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3tzc5y
title: Occurrence Download

description: A dataset containing 25 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is CHN.28_1",
 "TaxonKey is Rumex popovii"
 ]
}

 The dataset includes 25 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002171-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kmft6e
title: Occurrence Download

description: A dataset containing 2404 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cornus kousa chinensis"
 ]
}

 The dataset includes 2404 records from 78 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002170-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fsbmp8
title: Occurrence Download

description: A dataset containing 182 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Adenia pechuelii"
 ]
}

 The dataset includes 182 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002172-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bfyczh
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is CHN.28_1",
 "TaxonKey is Elytrigia intermedia"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002173-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.30453341
title: Data and code for "Spatial clustering of termites but not fungi drive global wood decay patterns"

description: Organisms self-organize into spatial patterns that determines ecosystem functioning1,2, ranging from clustering with higher functions in neighboring patches to overdispersion with disjunct hotspots of functions. Termites and fungi are key decomposers of deadwood globally3,4and their activities are spatially self-organized5,6. However, it remains unknown how decomposers’ spatial self-organization influences wood decomposition and its sensitivity to climate and human footprint7–9. By reanalyzing a global dataset4, we show that increasing termite occupancy – driven by temperature and precipitation seasonality – cause clustered patterns of decomposition rates, while increasing fungal occupancy – driven by precipitation and temperature – cause overdispersed patterns. Although climate poses stronger effects on decomposers’ spatial occupancy, human footprint promotes overdispersed patterns of decomposition via decreasing termite occupancy. Notably, clustered patterns by termites increase ecosystem-level decomposition rates via improving the per capita effect of termite occupancy, with the relative contribution (R2 = 8~18%) comparable to termite occupancy (13~18%) and temperature (18~19%). Overdispersed patterns by fungi lower the efficiency of fungal wood decay at ecosystem-scale. Our study alerts that anthropogenic pressures decelerate wood decomposition via disrupting the self-organization of termites. Since precipitation seasonality amplifies as the Earth warms up10, wood decomposition will be driven by both the range expansion4and clustered activities of termites.