cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.8x8abg
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"equals","key":"GADM_LEVEL_2_GID","value":"CHN.1.14_1","matchCase":false},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010316-260108223611665/datasets/export for details.
DOI: 10.5281/zenodo.18250753
title: Calandrinia ciliata (Ruiz & Pav.) DC. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:43
DOI: 10.15468/dl.ycxkry
title: Occurrence Download

description: A dataset containing 16 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Blicca bjoerkna",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1925",
 "Year is less than or equal to 1929"
 ]
}

 The dataset includes 16 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010317-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18250752
title: Calandrinia ciliata (Ruiz & Pav.) DC. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:43
DOI: 10.11579/3013042
title: One Million Open-source Cislunar Orbits.

description: The dataset contains one million integrated cislunar orbit trajectories, for a time span of up to six years. The data was generated on LLNL HPC systems and is saved in the form of both HDF5 and CSVs.
DOI: 10.5281/zenodo.18250680
title: PubMed Base 2002-2024
title: Prueba
DOI: 10.5281/zenodo.18250679
title: PubMed Base 2002-2024
title: Prueba
DOI: 10.15468/dl.rwrgy8
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"equals","key":"GADM_LEVEL_2_GID","value":"USA.43.70_1","matchCase":false},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 4 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010318-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bgpz3v
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"equals","key":"GADM_LEVEL_2_GID","value":"CHN.1.15_1","matchCase":false},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010319-260108223611665/datasets/export for details.
DOI: 10.15468/dl.rf4fum
title: Occurrence Download

description: A dataset containing 1393 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Alopias superciliosus"
 ]
}

 The dataset includes 1393 records from 91 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010320-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rzarke
title: Occurrence Download

description: A dataset containing 4516 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is one of (USA.41_1, USA.34_1, USA.11_1, USA.1_1, USA.47_1)",
 "TaxonKey is Vulpes vulpes"
 ]
}

 The dataset includes 4516 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028997-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vsug9c
title: Occurrence Download

description: A dataset containing 5097 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is EOD – eBird Observation Dataset",
 "StateProvince is MInnesota",
 "TaxonKey is Bonasa umbellus (Linnaeus, 1766)",
 "Year is 2023"
 ]
}

 The dataset includes 5097 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012126-250415084134356/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.14288/1.0397986
title: Data: Avian cultural services peak in tropical wet forests

description: &lt;b&gt;Abstract&lt;/b&gt;&lt;br/&gt;&lt;p class="CxSpFirst" style="text-align:start;text-indent:0px;"&gt;&lt;span&gt;&lt;span style="font-style:normal;"&gt;&lt;span&gt;&lt;span style="font-weight:normal;"&gt;&lt;span style="letter-spacing:normal;"&gt;&lt;span&gt;&lt;span&gt;&lt;span style="white-space:normal;"&gt;&lt;span&gt;&lt;span&gt;&lt;span&gt;The current biodiversity crisis involves major shifts in biological communities at local and regional scales. The consequences for Earth’s life-support systems are increasingly well-studied, but knowledge of how community shifts affect cultural services associated with wildlife lags behind. We integrated bird census data (three years across 150 point-count locations) with questionnaire surveys (&gt;400 people) to evaluate changes in culturally important species across climate and land-use gradients in Costa Rica. For farmers, urbanites, and birdwatchers alike, species valued for identity, bequest, birdwatching, acoustic aesthetics, and education were more likely to occupy wetter regions and forested sites, whereas disliked species tended to occupy drier and deforested sites. These results suggest that regional climate drying and habitat conversion in the Neotropics are likely to threaten the most culturally important bird species. This study provides a novel and generalizable pathway for assessing the effects of environmental changes on cultural services and integrating the socio-cultural and ecological dimensions of biodiversity.&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/p&gt;
DOI: 10.14288/1.0402373
title: Replication Data for: Sweeping Effects Modify Taylor’s Frozen Turbulence Hypothesis for Scalars in the Roughness Sublayer

description: The data included here are useful in the application of the Ellipse Approximation method, which allows for the estimation of sweeping and advection velocities. This dataset is a collection of case studies selected from two weeks of data collected during a field campaign investigating turbulent exchange within and above a sloped vineyard in the Okanagan Valley, British Columbia. These case studies were selected because the predominate wind direction at all five measurement heights was aligned in the upslope direction (parallel to the vineyard rows; towards the east), and all of the deployed instruments were working properly.
DOI: 10.14288/1.0396744
title: A Random Forest Algorithm for Learning and Updating Fuel Types for Fire Research

description: Wildfire drives a tremendous amount of forest and land cover change in the central interior of British Columbia, Canada. Fuel type maps have been acknowledged as critical references to conduct landscape-level fire simulations as well as fire behavior predictions. Nonetheless, the current thematic maps are not updated on an annual basis and cannot be easily produced at a certain scale and speed. The objective of this research was to test the hypothesis – that machine learning algorithm can augment the current manual wildfire fuel types identification system and can help to update fuel types on an annual basis, in the meantime the accuracy of the algorithm can meet the standards of The Ministry of Forests, Lands, Natural Resource Operations and Rural Development (BC FLNRO).  The random forest algorithm was applied over a 40 000-km² landscape in central interior British Columbia that burned from a megafire in 2017. Fuel maps were obtained from the years 2013-2017, with the cross-validation overall accuracy reached 98.57% and the overall accuracy of confusion matrix tested on the validation set reached 92.35%. Various recommendations are given for future research using machine learning algorithms for fuel mapping such as assuring pre-processing procedure follows delicate standards, modifying the machine learning algorithm, and adopting other sources of remotely sensed data.
DOI: 10.14288/1.0397662
title: Adaptation across geographic ranges is consistent with strong selection in marginal climates and legacies of range expansion

description: &lt;b&gt;Abstract&lt;/b&gt;&lt;br/&gt;Every species experiences limits to its geographic distribution. Some evolutionary models predict that populations at range edges are less well-adapted to their local environments due to drift, expansion load, or swamping gene flow from the range interior. Alternatively, populations near range edges might be uniquely adapted to marginal environments. In this study, we use a database of transplant studies that quantify performance at broad geographic scales to test how local adaptation, site quality, and population quality change from spatial and climatic range centers towards edges. We find that populations from poleward edges perform relatively poorly, both on average across sites (15% lower population quality) and when compared to other populations at home (31% relative fitness disadvantage), consistent with these populations harboring high genetic load. Populations from equatorial edges also perform poorly on average (18% lower population quality) but, in contrast, outperform foreign populations (16% relative fitness advantage), suggesting that populations from equatorial edges have adapted to unique environments. Finally, we find that populations from sites that are thermally extreme relative to the species' niche demonstrate strong local adaptation, regardless of geographic position. Our findings indicate that both nonadaptive processes and adaptive evolution contribute to variation in adaptation across species' ranges.
DOI: 10.14288/1.0396659
title: Estimating Productivity on the University of British Columbia (UBC, Vancouver Campus) Farm in 2019 using Normalized Difference Vegetation Index (NDVI) Time Series

description: Remote sensing is an emerging tool in the agricultural sector with proven diverse applications, including monitoring indicators of soil health and crop productivity. These applications are currently predominantly limited to monocultural large-scale farms, and effectively monitoring small, diverse farms still presents many challenges. However, the high global prevalence of smallholder farms under diversified production warrants further research to expand the potential of remote sensing to small-scale farms. Using the 24-hectare University of British Columbia (UBC) Farm in Vancouver, British Columbia as a case study, this research calculated a Normalized Difference Vegetation Index (NDVI) time series from twelve monthly 3m resolution Planet satellite images from 2019 for the Farm’s annual production plots. NDVI was used as a proxy for soil coverage by vegetation and therein for productivity, and significance was tested for temporal and spatial variations in NDVI values. October was found to be the most productive month, while June was observed to be the least productive. There were no statistically significant differences in NDVI values across the farm plots. The seasonal trend detected from the time series may represent the stronger influences of climate on NDVI over different forms of vegetation. However, unexpected NDVI results may also more accurately reflect variations in activity across the farm throughout the year. This study lays the groundwork for future research with higher spectral, spatial, and temporal resolution imagery (perhaps collected via drones or ground-based robots) to enable finer-scaled analyses of spatial variations in vegetation coverage. These advancements will be necessary to provide more suitable data for informing small-scale farm soil and farm management protocols.
DOI: 10.14288/1.0396660
title: Mapping 'Blue Carbon' in Cambodian Mangroves: A Case Study Analysis for the Koh Rong Archipelago

description: Mangrove forests, and other coastal ecosystems, are recognized for their role in climate change mitigation due to their significant potential for carbon storage and carbon sequestration. These ecosystems are some of the most threatened ecosystems on earth and are at risk of loss and degradation because of anthropogenic activities. Carbon financing mechanisms offer a way to help implement, finance and support the conservation and restoration of coastal ecosystems. This study focuses on conducting a Tier 1 blue carbon assessment for the Koh Rong Archipelago in Cambodia. Satellite images from Landsat TM and Landsat 8 OLI were used to create land cover classification maps for the archipelago for 2009 and 2020, respectively. Mangrove extent was derived from the classified maps in order to analyze the decadal change in mangrove forests and subsequent blue carbon stock for the archipelago. The results of this study represent an initial blue carbon assessment for the archipelago that can be expanded upon in future studies.
DOI: 10.14288/1.0396664
title: The Impacts of Burn Severity on Forest Resiliency in British Columbia

description: Understanding how resilient forests are after wildfire events is important to forest management practices. The objective of this study was to use Landsat-8 data to understand how the burn severity of the Little Bobtail Lake wildfire has impacted forest regrowth several years later. This was done by deriving different vegetation indices to see how the changes in vegetation health were impacted by burn severity. Additionally, landscape pattern metrics were used to understand the changes in the spatial patterns of the burn severity and vegetation health over time. The results showed that the higher the burn severity, the greater the impact on vegetation health immediately after the wildfire, as well as a slower return to pre-fire conditions. When compared to the pre-fire values, the post-fire Normalized Difference Vegetation Index and the Tasseled Cap Greenness values showed an initial drop in the R2 value and then a rise in value four years after the wildfire. This differed from the Tasseled Cap Wetness values as the R2 showed a continual drop in value. When looking at the changes in the spatial patterns for vegetation health, the Sparse Vegetation class showed the greatest change for Core Area with a 3.72 hectare increase every year. When looking at burn severity, the High Severity class showed the greatest decrease in core area with a loss of 2.63 hectares every year. These results show that monitoring vegetation regrowth can be done using Landsat-8 derived vegetation health indices as well as with spatial pattern analysis.
DOI: 10.14288/1.0396681
title: Urban Green Space Analysis in University of British Columbia Vancouver Campus

description: Due to the rapid growth of urbanization, species biodiversity is threatened and the innate relationship between humans and nature begins to fade gradually. Urban green spaces play a vital role in reconnecting human and urbanized landscape with its unique characteristics. Meanwhile, virtual gaming technology with applied geographic information has made a spectacular process to promote interactions between humans and their surroundings. Five types of green space were identified in the University of British Columbia Vancouver campus: lawn, planting bed, planting bed on structure, athletic field, and urban forest. A novel approach of combining Light Detection and Ranging (LiDAR) data, ground-based inventory data, geographic information system (GIS) data, and geocoordinates derived from reality game Pokémon GO was applied to explore geospatial gaming technology’s application in mapping cultural use and biodiversity hotspots at a university campus. LiDAR-derived individual tree crown polygons contributed to estimate canopy cover. Manually delineated tree crown from the study area's orthophoto was used to compare the crown area accuracy with LiDAR technology. The point density heat map illustrated the study area's cultural interests, which were generated by Pokestops' geospatial coordinates. A dataset containing two green space assessments was conducted with various factors: native species ratio, species richness, canopy cover, and cultural interest. Both assessments highlighted the importance of urban forest. This green space type achieved 0.396 in the first assessment and 0.501 for the second assessment of cultural and biodiversity values.
DOI: 10.6084/m9.figshare.28851161.v1
title: Statistics Data Files - per season, hemisphere, and geomagnetic condition

description: These files contain all statistics calculated in the publication: trough width (in magnetic latitude degrees), positions of both polar and equatorward trough boundaries, TEC gradients along both boundaries, and minimum depth of the trough. Trough detection rate was calculated from these files using the number of valid values out of NaNs (see MorphologyPlots.ipynb). File format is .pickle as they contain Python VARIABLES and can be loaded and modified using the Python pickle library (see MorphologyPlots.ipynp to see loading).Each file is named as follows:NH or SH for hemisphere _ (stat type) _ geomagnetic condition + seasonGeomagnetic conditions go as: q = quiet, m = moderate, a = activeSeasons go as: w = winter, p = spring, s = summer, f = fallExample: NH_EqDiff_qw = Northern hemisphere equatorward TEC difference (gradient), quiet wintertimePLEASE NOTE: SEASON labels are according to NORTHERN HEMISPHERE, Southern hemisphere seasons are swapped! If one desires to look at the SH in winter, they must load the files ending with s for summer, etc.
DOI: 10.6084/m9.figshare.28851161
title: Statistics Data Files - per season, hemisphere, and geomagnetic condition

description: These files contain all statistics calculated in the publication: trough width (in magnetic latitude degrees), positions of both polar and equatorward trough boundaries, TEC gradients along both boundaries, and minimum depth of the trough. Trough detection rate was calculated from these files using the number of valid values out of NaNs (see MorphologyPlots.ipynb). File format is .pickle as they contain Python VARIABLES and can be loaded and modified using the Python pickle library (see MorphologyPlots.ipynp to see loading).Each file is named as follows:NH or SH for hemisphere _ (stat type) _ geomagnetic condition + seasonGeomagnetic conditions go as: q = quiet, m = moderate, a = activeSeasons go as: w = winter, p = spring, s = summer, f = fallExample: NH_EqDiff_qw = Northern hemisphere equatorward TEC difference (gradient), quiet wintertimePLEASE NOTE: SEASON labels are according to NORTHERN HEMISPHERE, Southern hemisphere seasons are swapped! If one desires to look at the SH in winter, they must load the files ending with s for summer, etc.
DOI: 10.14288/1.0396719
title: Pollinators Habitat Capability Analysis of the University of British Columbia (UBC) Vancouver Campus

description: Pollination is an essential ecosystem service for crop production, where species such as insects and birds help to transfer pollen for plants to reproduce. Many of the pollinators are fully dependent on the plants and trees as their food sources and habitat. From a perspective of an urban planner, we must be able to recognize the values brought by pollinators to our ecosystems. Thus, we are attempting to discover the relationship between species and their habitats as much as possible. Nevertheless, assessing and quantifying habitat for species is a particular difficult task when we are dealing with a complex structured urban landscape. This study has two main objectives: the first one is to delineate and assess the biodiversity hotspots as pollinators habitat to determine which to prioritize for planting design management, and the second one is to determine the difference in tree crown delineation using Light Detection and Ranging (LiDAR) point cloud and Orthophoto interpretation. As a result, we found that each delineation method has different limitations and advantages. With the implementation of habitat overlay analysis, the mean patch size of biodiversity hotspots is around 2100 m^2, indicating that most green spaces in urban landscapes tend to be more fragmented rather than shrinking in size.
DOI: 10.14288/1.0401965
title: Predictive Ecosystem Mapping of the Chinchaga Watershed Management Basin, North Eastern British Columbia

description: The purpose of this project was to identify and map the location of wetlands in the Chinchaga Watershed Management Basin within the Fort St. John Timber Supply Area. The Chinchaga study area covers 75,000 hectares (ha), and serves as an ecologically significant unit within the Fort St. John Timber Supply Area, representing the gentle, low relief terrain characteristic to Boreal Plains. The products created in this project are intended to provide input for the amendment of the Fort St. John Land & Resources Management Plan. Input data for this project consisted of Sentinel 2 spectral imagery, the provincial Digital Elevation Model, ClimateBC data, and Predictive Ecosystem Mapping provincial products. Both spectral and topographic indices were created to assist in model performance. A geographically stratified sampling approach was taken in order to generate 1012 points. These training points were attributed to allow for the prediction of three simplified land cover realms, as well as seven identified provincial Eco-Groups across the Chinchaga. Together, the explanatory variables and training points were fed into a Random Forest model, and the classes were predicted across the study area with 84.9% (Three Class) and 78.2% (Seven Class) overall accuracy, respectively. Included in this report are a brief discussion on explanatory variable contribution to model performance, as well as an analysis of sample design and its implications on class accuracies in the 7 Class prediction.