cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6073/pasta/7b5d1fe9a3d17847a9cf5012da2a3456
title: Metabolism estimates from dissolved oxygen and inorganic carbon in the Upper Clark Fork River, MT, USA.

description: This package provides necessary supporting data and models for the manuscript titled "Divergent metabolism estimates from dissolved oxygen and inorganic carbon: implications for river carbon cycling". The entire dataset consists of sensor data collected at three reaches and metabolism estimates from different models. The sensor data include partial pressure of carbon dioxide in water, dissolved oxygen and temperature. At each reach, we established a two station approach, meaning at least one pair of sensor suits were distributed upstream and downstream. Results for metabolism estimates differ by solutes (i.e., oxygen or carbon based) and modelling approaches (i.e., single station or two station approach). In addition to data products, we also provide R packages for metabolism models.
DOI: 10.15468/dl.9376f7
title: Occurrence Download

description: A dataset containing 3989648 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ecuador",
 "StateProvince is one of (Cotopaxi, Pichincha)"
 ]
}

 The dataset includes 3989648 records from 520 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055375-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6073/pasta/eab9ada640979e96e08a407cab6f534b
title: Pollinator visitation, flower count, and seed set in Black Sand plots, 2020.

description: Anthropogenic climate change is altering interactions among numerous species, including plants and pollinators. Plant-pollinator interactions, crucial for the persistence of most plant and many insect species, are threatened by climate change-driven phenological shifts. Phenological mismatches between plants and their pollinators may affect pollination services, and simulations indicated that these mismatches may reduce floral resources available to up to 50% of insect pollinator species. Although alpine plants rely heavily on vegetative reproduction, seedling recruitment and seed dispersal are likely to be important drivers of alpine community structure. Similarly, advanced flowering may expose plants to increased risk of frost damage and shifted soil moisture regimes; phenologically advanced plants will experience these environmental factors differently, which may alter their floral resource production. These effects may be dependent upon topography. Some species of alpine plants on the Niwot Ridge have displayed advanced phenology under treatments of advanced snowmelt (Forrester, 2021). However, little is understood about how these differences in distribution and phenology affect pollinator community composition and plant fecundity. Here we strive to examine how experimentally-induced changes in the timing of flowering and number of flowers produced by plants impact plant-pollinator interactions and seed set. We also ask how topography and the number of flowers interact with early snowmelt to affect pollination rates and the diversity of pollinating insects. Finally, we ask how seed set of Geum rossii is affected by pollinator visitation at different times of the season, under experimentally advanced snowmelt versus unmanipulated snowmelt, and with visitation by different insect taxa. In summer 2020, we found that plots with advanced phenology experienced peaks in pollinator visitation rates and pollinator diversity earlier than plots with unmanipulated snowmelt. We expect this to be because of the advanced floral phenology of certain key species in these plots.References:Forrester, C.C. (2021). Advancing, Using, and Teaching Climate Change Ecology Research. [Doctoral dissertation, University of Colorado, Boulder]. ProQuest Dissertations and Theses.
DOI: 10.5281/zenodo.14590389
title: TALABALARDA VATANPARVARLIKNI ARTPEDAGOGIKA VOSITASIDA RIVOJLANTIRISH TEXNOLOGIYASI

description: Mazkur maqolada talabalar orasida vatanparvarlik tuyg‘usini rivojlantirish uchun artpedagogika vositalarini qo‘llash texnologiyalari tahlil qilinadi. Artpedagogika san’at va pedagogikaning integratsiyasi sifatida talabalarning estetik didi, milliy qadriyatlarga hurmati hamda Vatanga bo‘lgan mehrini shakllantirishda samarali ta’sir ko‘rsatadi. Ushbu tadqiqotda vatanparvarlikni rivojlantirish jarayonida san’atning musiqa, teatr, tasviriy san’at, kino va boshqa turlaridan foydalanish metodlari ko‘rib chiqiladi. Shuningdek, maqolada artpedagogikaning texnologik yondashuvlari, jumladan, interaktiv mashg‘ulotlar, ijodiy loyiha faoliyati va o‘quvchilarning amaliy ishtiroki orqali vatanparvarlikni shakllantirish bo‘yicha zamonaviy pedagogik modellarning ahamiyati ochib beriladi. Ushbu texnologiyalar talabalarning nafaqat ma’naviy-madaniy, balki shaxsiy sifatlarini rivojlantirishga ham xizmat qiladi.

Tadqiqotning amaliy ahamiyati shundan iboratki, olingan natijalar oliy ta’lim muassasalari, pedagoglar va psixologlar uchun o‘quv jarayonini yanada samarali tashkil etishda uslubiy asos sifatida foydalanilishi mumkin.
DOI: 10.5281/zenodo.14590390
title: TALABALARDA VATANPARVARLIKNI ARTPEDAGOGIKA VOSITASIDA RIVOJLANTIRISH TEXNOLOGIYASI

description: Mazkur maqolada talabalar orasida vatanparvarlik tuyg‘usini rivojlantirish uchun artpedagogika vositalarini qo‘llash texnologiyalari tahlil qilinadi. Artpedagogika san’at va pedagogikaning integratsiyasi sifatida talabalarning estetik didi, milliy qadriyatlarga hurmati hamda Vatanga bo‘lgan mehrini shakllantirishda samarali ta’sir ko‘rsatadi. Ushbu tadqiqotda vatanparvarlikni rivojlantirish jarayonida san’atning musiqa, teatr, tasviriy san’at, kino va boshqa turlaridan foydalanish metodlari ko‘rib chiqiladi. Shuningdek, maqolada artpedagogikaning texnologik yondashuvlari, jumladan, interaktiv mashg‘ulotlar, ijodiy loyiha faoliyati va o‘quvchilarning amaliy ishtiroki orqali vatanparvarlikni shakllantirish bo‘yicha zamonaviy pedagogik modellarning ahamiyati ochib beriladi. Ushbu texnologiyalar talabalarning nafaqat ma’naviy-madaniy, balki shaxsiy sifatlarini rivojlantirishga ham xizmat qiladi.

Tadqiqotning amaliy ahamiyati shundan iboratki, olingan natijalar oliy ta’lim muassasalari, pedagoglar va psixologlar uchun o‘quv jarayonini yanada samarali tashkil etishda uslubiy asos sifatida foydalanilishi mumkin.
DOI: 10.5281/zenodo.14586608
title: Aboveground, belowground biomass, and morphological fine root characteristics of temperate tree regeneration

description: Along a gradient of mean annual precipitation (mm a-1), mean annual temperature (°C a-1) and nitrogen deposition (kg N ha-1 a-1) in Germany, biomass allocation and fine root morphology of 4 temperate tree species (Fagus sylvatica, Quercus petraea, Pseudotsuga menziesii, Abies alba) were characterised. Variables measured were aboveground and belowground biomass (both in g), specific root length (cm mg-1),  root tip frequency (tip mg-1), root tissue density (g cm-3), and mycorrhization rate (%). Co-factors that also determined biomass partitioning and root morphology were tree age, tree height (cm), upper mineral soil field capacity (V%), upper mineral soil nitrogen content (mg g-1) and canopy cover (%). A research article describing patterns in data per species is published in Ecosystems, Springer.
DOI: 10.5281/zenodo.14586609
title: Aboveground, belowground biomass, and morphological fine root characteristics of temperate tree regeneration

description: Along a gradient of mean annual precipitation (mm a-1), mean annual temperature (°C a-1) and nitrogen deposition (kg N ha-1 a-1) in Germany, biomass allocation and fine root morphology of 4 temperate tree species (Fagus sylvatica, Quercus petraea, Pseudotsuga menziesii, Abies alba) were characterised. Variables measured were aboveground and belowground biomass (both in g), specific root length (cm mg-1),  root tip frequency (tip mg-1), root tissue density (g cm-3), and mycorrhization rate (%). Co-factors that also determined biomass partitioning and root morphology were tree age, tree height (cm), upper mineral soil field capacity (V%), upper mineral soil nitrogen content (mg g-1) and canopy cover (%). A research article describing patterns in data per species is published in Ecosystems, Springer.
DOI: 10.15472/gicx1c
title: Colección Zoológica del Instituto Nacional de Salud (INSZ)

description: La Colección Zoológica del Instituto Nacional de Salud (INSZ) hace parte del Grupo de Animales Venenosos de la Dirección de Producción. La Colección está compuesta por 838 registros biológicos que corresponden a ejemplares preservados en líquido de los phyla Arthropoda y Chordata, estos están agrupados en seis órdenes, 18 familias y 40 géneros. Son predominantes las serpientes, arañas y escorpiones de importancia médica del país, que han sido empleados en la extracción de sus venenos para la producción e investigación en antivenenos. Un 86.9% está identificado a nivel de especie, un 11.5% a género, un 1.4% a familia y un 0.1% a orden. Los registros se han realizado a partir del año 2005 y todos han sido colectados en Colombia, en los siguientes departamentos: Cundinamarca, Meta, Putumayo, Caldas, Santander, Tolima, Boyacá, Antioquia, La Guajira, Bolívar, Sucre, Casanare, Magdalena, Cauca, Norte de Santander, Cesar, Huila, Guaviare, Risaralda, Valle del Cauca y Amazonas.
DOI: 10.15468/dl.9gp394
title: Occurrence Download

description: A dataset containing 593668 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is North America",
 "TaxonKey is one of (Acer platanoides L., Adelges tsugae Annand, 1924, Agrilus planipennis Fairmaire, 1888, Alliaria petiolata (M.Bieb.) Cavara & Grande, Channa argus (Cantor, 1842), Crocodylus niloticus Laurenti, 1768, Dreissena polymorpha (Pallas, 1771), Faxonius rusticus (Girard, 1852), Frangula alnus Mill., Heracleum mantegazzianum Sommier & Levier, Heracleum sphondylium L., Hydrocharis morsus-ranae L., Impatiens glandulifera Royle, Kali tragus (L.) Scop., Lissachatina fulica (Bowdich, 1822), Lycorma delicatula (White, 1845), Myriophyllum spicatum L., Phragmites australis subsp. australis, Potamogeton crispus L., Pterois volitans (Linnaeus, 1758), Pueraria lobata (Willd.) Ohwi, Python bivittatus Kuhl, 1820, Reynoutria japonica Houtt., Reynoutria sachalinensis (F.Schmidt) Nakai, Reynoutria ×bohemica Chrtek & Chrtková, Rhamnus cathartica L., Rhinella marina (Linnaeus, 1758), Stratiotes aloides L., Trapa natans L., Vincetoxicum nigrum (L.) Moench, Vincetoxicum rossicum (Kleopow) Barbar.)",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 593668 records from 590 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055376-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kwm33k
title: Occurrence Download

description: A dataset containing 6037 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is EOD – eBird Observation Dataset",
 "TaxonKey is Malurus splendens (Quoy & Gaimard, 1830)",
 "Year 2018-2020"
 ]
}

 The dataset includes 6037 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034515-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.v4t8d9
title: Occurrence Download

description: A dataset containing 135 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Magnoliopsida, Liliopsida, Gnetopsida, Ginkgoopsida, Pinopsida, Cycadopsida, Cycadopsis Debey, 1848)",
 "BasisOfRecord is one of (Specimen, Human Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2000",
 "Geometry POLYGON ((99.14329 15.81982, 99.14382 15.819, 99.14431 15.81816, 99.14477 15.81728, 99.14517 15.81638, 99.14554 15.81546, 99.14586 15.81452, 99.14613 15.81357, 99.14636 15.8126, 99.14654 15.81161, 99.14667 15.81062, 99.14675 15.80962, 99.14679 15.80862, 99.14677 15.80762, 99.14671 15.80662, 99.1466 15.80563, 99.14644 15.80464, 99.14624 15.80367, 99.14598 15.8027, 99.14568 15.80176, 99.14534 15.80083, 99.14495 15.79992, 99.14451 15.79903, 99.14404 15.79817, 99.14352 15.79734, 99.14296 15.79654, 99.14237 15.79577, 99.14174 15.79504, 99.14107 15.79434, 99.14037 15.79369, 99.06575 15.72696, 99.06503 15.72635, 99.06428 15.72578, 99.0635 15.72525, 99.06269 15.72476, 99.06187 15.72432, 99.06102 15.72393, 99.06015 15.72359, 99.05928 15.72329, 99.05838 15.72305, 99.05748 15.72285, 98.56527 15.63013, 98.56436 15.62998, 98.56345 15.62989, 98.56254 15.62984, 98.56162 15.62985, 98.56071 15.62991, 98.5598 15.63002, 98.5589 15.63018, 98.55801 15.63039, 98.55712 15.63065, 98.55625 15.63096, 98.5554 15.63132, 98.55457 15.63172, 98.55375 15.63217, 98.55296 15.63267, 98.55219 15.63321, 98.55145 15.63379, 98.55074 15.63442, 98.55006 15.63508, 98.54942 15.63578, 98.5488 15.63652, 98.54822 15.63729, 98.54769 15.63809, 98.54719 15.63892, 98.54672 15.63977, 98.54631 15.64066, 98.54593 15.64156, 98.5456 15.64248, 98.54531 15.64342, 98.54507 15.64438, 98.54487 15.64535, 98.54472 15.64633, 98.54462 15.64731, 98.54457 15.6483, 98.54456 15.64929, 98.5446 15.65028, 98.54469 15.65127, 98.54482 15.65225, 98.545 15.65322, 98.54523 15.65418, 98.66435 16.10522, 98.66462 16.10616, 98.66494 16.10708, 98.6653 16.10798, 98.66571 16.10887, 98.66616 16.10973, 98.66665 16.11056, 98.66717 16.11136, 98.66774 16.11214, 98.66834 16.11288, 98.66898 16.11359, 98.66965 16.11426, 98.67035 16.11489, 98.67108 16.11548, 98.67183 16.11604, 98.67262 16.11655, 98.67342 16.11701, 98.67425 16.11743, 98.6751 16.1178, 98.67596 16.11813, 98.67684 16.11841, 98.67773 16.11863, 98.67863 16.11881, 98.67954 16.11894, 98.68045 16.11902, 98.68136 16.11904, 98.92704 16.11904, 98.92795 16.11902, 98.92886 16.11894, 98.92977 16.11881, 98.93066 16.11864, 98.93155 16.11841, 98.93243 16.11813, 98.93329 16.11781, 98.93413 16.11744, 98.93496 16.11702, 98.93576 16.11656, 98.93655 16.11605, 98.9373 16.11551, 98.93803 16.11492, 98.93873 16.11429, 98.9394 16.11362, 98.94003 16.11292, 98.94064 16.11218, 98.9412 16.11141, 99.14329 15.81982))"
 ]
}

 The dataset includes 135 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0181684-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/inscriptifact-ouc112036535
title: Cuneiform Tablet 1913.14.1684, Spurlock 1913.14.1684

description: [Text Description:] Administrative tablet ❧ [Text or Publication Number Note:] Spurlock 1913.14.1684; CDLI P421535 ❧ [Medium:] Clay ❧ [Script Note:] Non-Alphabetic Cuneiform ❧ [Physical Object Description:] Moderate Yellowish Pink (5YR 7.5/4) Yellowish Gray (10YR 8.5/2) ❧ [Physical Object Note:] 3.6 x 2.7 x 1.7 cm (16 g)
DOI: 10.15468/dl.6atudz
title: Occurrence Download

description: A dataset containing 307491 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year 1000-1779"
 ]
}

 The dataset includes 307491 records from 358 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0266039-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.64txpy
title: Occurrence Download

description: A dataset containing 13971 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Capra pyrenaica Schinz, 1838"
 ]
}

 The dataset includes 13971 records from 77 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0286965-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cj8jye
title: Occurrence Download

description: A dataset listing the 2 species recorded in GBIF matching the query:
{
 "and" : [
 "Country is Colombia",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Tapirus terrestris (Linnaeus, 1758)"
 ]
}

 The dataset's 2 records were derived from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034514-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jwtjuh
title: Occurrence Download

description: A dataset listing the 6163 species recorded in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ephemeroptera"
 ]
}

 The dataset's 6163 records were derived from 1046 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0286946-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/inscriptifact-ouc112036593
title: Cuneiform Tablet 1913.14.1684, Spurlock 1913.14.1684

description: [Text Description:] Administrative tablet ❧ [Text or Publication Number Note:] Spurlock 1913.14.1684; CDLI P421535 ❧ [Medium:] Clay ❧ [Script Note:] Non-Alphabetic Cuneiform ❧ [Physical Object Description:] Moderate Yellowish Pink (5YR 7.5/4) Yellowish Gray (10YR 8.5/2) ❧ [Physical Object Note:] 3.6 x 2.7 x 1.7 cm (16 g)
DOI: 10.15468/dl.snzmgc
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ctenichneumon panzeri suzukii (Matsumura, 1912)",
 "HasCoordinate is true",
 "Country is Japan",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0211223-220831081235567/datasets/export for details.
DOI: 10.25549/inscriptifact-ouc112034008
title: Cuneiform Tablet 1913.14.1675, Spurlock 1913.14.1675

description: [Text Description:] Administrative tablet ❧ [Text or Publication Number Note:] Spurlock 1913.14.1675; CDLI P421526 ❧ [Medium:] Clay ❧ [Script Note:] Non-Alphabetic Cuneiform ❧ [Physical Object Description:] Yellowish White (10YR 9/1.5) Pale Yellowish Pink (5YR 8.5/1.5) Moderate Yellowish Pink (5YR 7.5/3.5) ❧ [Physical Object Note:] 10.2 x 6.6 x 2.9 cm (217 g)
DOI: 10.15468/dl.nyj94p
title: Occurrence Download

description: A dataset containing 309551 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Anser fabalis (Latham, 1787)"
 ]
}

 The dataset includes 309551 records from 188 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0295139-200613084148143/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.28959431
title: ReGAIN Supplemental Figures

description: The rampant rise of multidrug-resistant (MDR) bacterial pathogens poses a serious health threat, necessitating innovative tools to unravel the complex genetic underpinnings of antimicrobial resistance. Despite strides in developing genomic tools for detecting resistance genes, a gap remains in analyzing organism-specific patterns of resistance gene co-occurrence. To address this deficiency, we developed the Resistance Gene Association and Inference Network (ReGAIN), a command-line platform that uses Bayesian network structure learning to identify and map resistance gene networks in bacterial pathogens. ReGAIN is able to detect resistance genes using well-established methods and offers insight into their complex interplay, critical for understanding MDR phenotypes. Focusing on bacterial pathogens, ReGAIN yields a queryable database for investigating resistance gene co-occurrence, enriching resistome analyses, and providing new insights into the dynamics of antimicrobial resistance. Furthermore, ReGAIN extends beyond antibiotic resistance genes to optionally include co-occurrence patterns among stress, heavy metal resistance, and virulence gene determinants, providing a robust overview of key gene relationships.
DOI: 10.15468/dl.d2tzxn
title: Occurrence Download

description: A dataset containing 208 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is ARG.6_1",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Sporophila hypoxantha"
 ]
}

 The dataset includes 208 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0062399-250920141307145/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.28959431.v1
title: ReGAIN command line software and supplemental figures.

description: The rampant rise of multidrug-resistant (MDR) bacterial pathogens poses a serious health threat, necessitating innovative tools to unravel the complex genetic underpinnings of antimicrobial resistance. Despite strides in developing genomic tools for detecting resistance genes, a gap remains in analyzing organism-specific patterns of resistance gene co-occurrence. To address this deficiency, we developed the Resistance Gene Association and Inference Network (ReGAIN), a command-line platform that uses Bayesian network structure learning to identify and map resistance gene networks in bacterial pathogens. ReGAIN is able to detect resistance genes using well-established methods and offers insight into their complex interplay, critical for understanding MDR phenotypes. Focusing on bacterial pathogens, ReGAIN yields a queryable database for investigating resistance gene co-occurrence, enriching resistome analyses, and providing new insights into the dynamics of antimicrobial resistance. Furthermore, ReGAIN extends beyond antibiotic resistance genes to include co-occurrence patterns among heavy metal and virulence gene determinants, providing a robust overview of key gene relationships.
DOI: 10.6084/m9.figshare.28959431.v2
title: ReGAIN Supplemental Figures

description: The rampant rise of multidrug-resistant (MDR) bacterial pathogens poses a serious health threat, necessitating innovative tools to unravel the complex genetic underpinnings of antimicrobial resistance. Despite strides in developing genomic tools for detecting resistance genes, a gap remains in analyzing organism-specific patterns of resistance gene co-occurrence. To address this deficiency, we developed the Resistance Gene Association and Inference Network (ReGAIN), a command-line platform that uses Bayesian network structure learning to identify and map resistance gene networks in bacterial pathogens. ReGAIN is able to detect resistance genes using well-established methods and offers insight into their complex interplay, critical for understanding MDR phenotypes. Focusing on bacterial pathogens, ReGAIN yields a queryable database for investigating resistance gene co-occurrence, enriching resistome analyses, and providing new insights into the dynamics of antimicrobial resistance. Furthermore, ReGAIN extends beyond antibiotic resistance genes to optionally include co-occurrence patterns among stress, heavy metal resistance, and virulence gene determinants, providing a robust overview of key gene relationships.