cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.20264013
title: Identification of degradation factors in mountain semiarid rangelands using spatial distribution modelling and ecological niche theory

description: This paper presents an approach to studying rangeland degradation by using remote sensing data, geographic information systems, and ecological niche theory. The role of environmental factors and land use in the spatial distribution of degraded rangelands in the Central Caucasus was assessed. Degradation stages were modelled in R using ENVIREM predictors, VIF test to select noncorrelated variables, ENMeval package to select the optimal model parameters, and the Maxent method to develop distribution models in the dismo package. Selected models had AUCtest, AUCtrain and CBI values close to 1, deltaAICc and AUCdiff values close to 0, and quite low AICc values. Environmental predictors of climate type (Thornthwaite aridity index and Emberger’s pluviothermic quotient) were explanatory variables for least disturbed rangelands, while topography (Terrain roughness index) largely explained the distribution of most disturbed grasslands. Quantitative (Schoener’s D) and graphical (Kernel density estimation, analysis of predictive maps) assessment revealed a significant overlap of ‘ecological niches’ and potential ranges of grasslands at different degradation stages, which indirectly supports the hypothesis of the important role of overgrazing in their degradation. Livestock management is likely to help restore disturbed mountain meadow steppes to steppe grasslands. Restoration of the arid shrub ecosystems to steppe grasslands or meadow steppes probably requires additional agricultural practices.
DOI: 10.6084/m9.figshare.20264013.v1
title: Identification of degradation factors in mountain semiarid rangelands using spatial distribution modelling and ecological niche theory

description: This paper presents an approach to studying rangeland degradation by using remote sensing data, geographic information systems, and ecological niche theory. The role of environmental factors and land use in the spatial distribution of degraded rangelands in the Central Caucasus was assessed. Degradation stages were modelled in R using ENVIREM predictors, VIF test to select noncorrelated variables, ENMeval package to select the optimal model parameters, and the Maxent method to develop distribution models in the dismo package. Selected models had AUCtest, AUCtrain and CBI values close to 1, deltaAICc and AUCdiff values close to 0, and quite low AICc values. Environmental predictors of climate type (Thornthwaite aridity index and Emberger’s pluviothermic quotient) were explanatory variables for least disturbed rangelands, while topography (Terrain roughness index) largely explained the distribution of most disturbed grasslands. Quantitative (Schoener’s D) and graphical (Kernel density estimation, analysis of predictive maps) assessment revealed a significant overlap of ‘ecological niches’ and potential ranges of grasslands at different degradation stages, which indirectly supports the hypothesis of the important role of overgrazing in their degradation. Livestock management is likely to help restore disturbed mountain meadow steppes to steppe grasslands. Restoration of the arid shrub ecosystems to steppe grasslands or meadow steppes probably requires additional agricultural practices.
DOI: 10.6084/m9.figshare.21280099
title: Performance of high-resolution precipitation datasets CHIRPS and TerraClimate in a Colombian high Andean Basin

description: High-resolution reanalysis products could improve the representativeness of rainfall on high Andean basins, but their performance must be locally validated. We addressed the performance, accuracy, and ability of TerraClimate and CHIRPSv.2 to represent 36 years of rainfall (1985–2020) from 23 stations in the Upper Chicamocha River, a Colombian basin of complex terrain and tropical hydrometeorology. Using several statistical metrics at monthly, seasonal and annual scales, we found how both datasets overestimate rainfall as a function of elevation, with better performance and accuracy from CHIRPS (r ∼0.76, R<sup>2</sup> ∼0.58, NSE ∼0.56, and low RMSE ∼33.7 mm/month, MAE ∼25.2 mm/month, ME ∼6.4 mm/month, and PBIAS ∼9.3), while TerraClimate overestimates inter-annual variability, especially between June and August. Seasonally, the datasets exhibit different spatial patterns and magnitudes, even after bias correction. The findings highlight the potential use and challenges of high-resolution datasets in basins with similar topography and hydrometeorology in the Andean region.
DOI: 10.6084/m9.figshare.21280099.v1
title: Performance of high-resolution precipitation datasets CHIRPS and TerraClimate in a Colombian high Andean Basin

description: High-resolution reanalysis products could improve the representativeness of rainfall on high Andean basins, but their performance must be locally validated. We addressed the performance, accuracy, and ability of TerraClimate and CHIRPSv.2 to represent 36 years of rainfall (1985–2020) from 23 stations in the Upper Chicamocha River, a Colombian basin of complex terrain and tropical hydrometeorology. Using several statistical metrics at monthly, seasonal and annual scales, we found how both datasets overestimate rainfall as a function of elevation, with better performance and accuracy from CHIRPS (r ∼0.76, R<sup>2</sup> ∼0.58, NSE ∼0.56, and low RMSE ∼33.7 mm/month, MAE ∼25.2 mm/month, ME ∼6.4 mm/month, and PBIAS ∼9.3), while TerraClimate overestimates inter-annual variability, especially between June and August. Seasonally, the datasets exhibit different spatial patterns and magnitudes, even after bias correction. The findings highlight the potential use and challenges of high-resolution datasets in basins with similar topography and hydrometeorology in the Andean region.
DOI: 10.15468/dl.f8m5fj
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Salvia saccifera Urb. & Ekman"
 ]
}

 The dataset includes 8 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0110612-230530130749713/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.20426058.v1
title: Three-dimensional visualization of thermal environments in urban canyons

description: Temperature distribution in urban canyons is dynamic, complex, and influenced by a range of heat resources such as radiant heat from reflected sunlight and convective heat from wind flow. While 2D data collection and presentation are the norm for UHI research, we propose using an unmanned aerial vehicle to measure temperatures at different horizontal and vertical locations in urban canyons to develop a 3D visualization of urban thermal environments. We implemented Gestalt laws and transparent and opaque color-coding to improve background recognition and visual closure as well as to better represent the spatiality of temperature data. Our design included grouped color pixels and an interactive temperature slider function. We investigated whether interface usage varied with the flexibility of closure, perceptual speed, and spatial relations of users. Responses from 102 participants indicated that users with flexibility in closure approved of the transparent colors and slider. The primary advantage of this visual model is the elimination of clutter. Visual clutter can cause users to lose their focus when searching a 2D representation of a 3D geographic space. In the proposed model, data hotspots and the boundaries produced by multiple aggregations and clustering enable users to readily and easily find the required information.
DOI: 10.15468/dl.g3vqq7
title: Occurrence Download

description: A dataset containing 793 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Glyphium elatum (Grev.) H.Zogg, Gnaphalium norvegicum Retz.)",
 "Geometry POLYGON((-9.36035 44.71551,-10.59082 42.81152,-11.82129 36.80928,-7.69043 36.17336,-3.38379 35.88905,3.12012 38.13456,9.18457 38.20366,11.7334 37.16032,12.78809 34.74161,17.09473 33.79741, 23.15918 34.23451,30.10254 32.62087,33.2666 32.99024,35.72754 35.03,33.00293 35.53223,28.69629 35.17381,28.34473 36.31513,25.7959 37.50973,24.91699 39.90974,28.78418 40.6473,30.71777 41.17865,36.87012 45.213,38.18848 46.98025,38.71582 47.7541,39.94629 47.93107,40.20996 49.61071,37.0459 50.34546,35.72754 50.40152,33.79395 52.26816,31.68457 51.94426,31.4209 53.27835,32.56348 53.43572,30.98145 54.77535,30.89355 55.52863,28.43262 56.02295,27.20215 57.65716,27.37793 58.30949,27.90527 59.17593,29.66309 59.88894,27.6416 60.58697,31.50879 62.75473,28.78418 69.83962,30.89355 70.28912,29.22363 71.55274,21.75293 71.30079,14.28223 70.14036,11.38184 67.47492,4.87793 63.66576,-5.53711 71.52491,-10.63477 71.69129,-21.5332 67.74276,-28.56445 65.36684,-24.3457 61.35461,-9.36035 44.71551))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2021"
 ]
}

 The dataset includes 793 records from 54 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0319230-210914110416597/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.20426058
title: Three-dimensional visualization of thermal environments in urban canyons

description: Temperature distribution in urban canyons is dynamic, complex, and influenced by a range of heat resources such as radiant heat from reflected sunlight and convective heat from wind flow. While 2D data collection and presentation are the norm for UHI research, we propose using an unmanned aerial vehicle to measure temperatures at different horizontal and vertical locations in urban canyons to develop a 3D visualization of urban thermal environments. We implemented Gestalt laws and transparent and opaque color-coding to improve background recognition and visual closure as well as to better represent the spatiality of temperature data. Our design included grouped color pixels and an interactive temperature slider function. We investigated whether interface usage varied with the flexibility of closure, perceptual speed, and spatial relations of users. Responses from 102 participants indicated that users with flexibility in closure approved of the transparent colors and slider. The primary advantage of this visual model is the elimination of clutter. Visual clutter can cause users to lose their focus when searching a 2D representation of a 3D geographic space. In the proposed model, data hotspots and the boundaries produced by multiple aggregations and clustering enable users to readily and easily find the required information.
DOI: 10.6084/m9.figshare.20348407
title: Exploring crop yield variability under different land management practices with spectral vegetation indices in the Ethiopian Blue Nile basin

description: An accurate crop yield forecast at a reasonable cost is required for increasing production and securing food. Therefore, spectral reflectance was measured with a spectroradiometer (λ 350–2500 nm) to predict grain yield (GY) and aboveground biomass yield (ABY) of teff and finger millet in Ethiopia. We calculated six spectral vegetation indices (SVIs): enhanced vegetation index (EVI), normalized difference VI (NDVI), soil-adjusted VI (SAVI), green (GNDVI), green chlorophyll VI (GCVI), and simple ratio (SR). Linear regression models fitted validation data with coefficient of determination (R<sup>2</sup>) of 0.73, and root mean square error (RMSE) of 0.11 for teff GY, R<sup>2</sup> of 0.45 and RMSE of 0.52 for teff ABY, R<sup>2</sup> of 0.92 and RMSE of 0.22 for finger millet GY, and R<sup>2</sup> of 0.90 and RMSE of 0.24 for finger millet ABY. The study demonstrates the potential of spectroradiometer-derived SVIs to predict finger millet and teff production in the catchment.
DOI: 10.6084/m9.figshare.20348407.v1
title: Exploring crop yield variability under different land management practices with spectral vegetation indices in the Ethiopian Blue Nile basin

description: An accurate crop yield forecast at a reasonable cost is required for increasing production and securing food. Therefore, spectral reflectance was measured with a spectroradiometer (λ 350–2500 nm) to predict grain yield (GY) and aboveground biomass yield (ABY) of teff and finger millet in Ethiopia. We calculated six spectral vegetation indices (SVIs): enhanced vegetation index (EVI), normalized difference VI (NDVI), soil-adjusted VI (SAVI), green (GNDVI), green chlorophyll VI (GCVI), and simple ratio (SR). Linear regression models fitted validation data with coefficient of determination (R<sup>2</sup>) of 0.73, and root mean square error (RMSE) of 0.11 for teff GY, R<sup>2</sup> of 0.45 and RMSE of 0.52 for teff ABY, R<sup>2</sup> of 0.92 and RMSE of 0.22 for finger millet GY, and R<sup>2</sup> of 0.90 and RMSE of 0.24 for finger millet ABY. The study demonstrates the potential of spectroradiometer-derived SVIs to predict finger millet and teff production in the catchment.
DOI: 10.6084/m9.figshare.20418614
title: Furthering the precision of RUSLE soil erosion with PSInSAR data: an innovative model

description: Soil erosion is a severe environmental problem worldwide, especially in tropical regions. The Revised Universal Soil Loss Equation (RUSLE), one of the universally accepted empirical soil erosion models, is quite commonly used in tropical climatic conditions to estimate the magnitude and severity of soil erosion. This study, apart from identifying the role of individual parameters in influencing the results of the RUSLE, also aims at refining the RUSLE results by incorporating the state-of-the-art technique Persistent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR) in a GIS environment by utilizing its ability to measure minute surface changes in millimetre levels. Apart from this novel approach of prioritising soil erosion classes using PSInSAR, the eroding surface conditions were also studied using low coherence value (&lt;0.75 in this study). The spatially and temporally averaged annual soil loss and net soil erosion (2015–2019), derived through RUSLE and transport limited sediment delivery (TLSD) approach, respectively, was improved by spatially integrating the PSInSAR velocity map. The integrated methodological framework is demonstrated for a tropical river basin in South India (Muvattupuzha River Basin [MRB]), which shows a mean rate of net soil loss of 6.8 ton/ha/yr, and nearly 8% of the area experiences deposition. Our approach to improve the accuracy of RUSLE-based soil erosion classes using PSInSAR techniques clearly demarcated the areas that call for utmost priority in implementing management practices. The corollary results show that the very severe soil erosion class is characterized by PSI velocity with higher negative values, followed by the successively lower classes. Results strongly suggest that RUSLE output can be improved as well as validated using a velocity map derived from radar data.
DOI: 10.6084/m9.figshare.20418614.v2
title: Furthering the precision of RUSLE soil erosion with PSInSAR data: an innovative model

description: Soil erosion is a severe environmental problem worldwide, especially in tropical regions. The Revised Universal Soil Loss Equation (RUSLE), one of the universally accepted empirical soil erosion models, is quite commonly used in tropical climatic conditions to estimate the magnitude and severity of soil erosion. This study, apart from identifying the role of individual parameters in influencing the results of the RUSLE, also aims at refining the RUSLE results by incorporating the state-of-the-art technique Persistent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR) in a GIS environment by utilizing its ability to measure minute surface changes in millimetre levels. Apart from this novel approach of prioritising soil erosion classes using PSInSAR, the eroding surface conditions were also studied using low coherence value (&lt;0.75 in this study). The spatially and temporally averaged annual soil loss and net soil erosion (2015–2019), derived through RUSLE and transport limited sediment delivery (TLSD) approach, respectively, was improved by spatially integrating the PSInSAR velocity map. The integrated methodological framework is demonstrated for a tropical river basin in South India (Muvattupuzha River Basin [MRB]), which shows a mean rate of net soil loss of 6.8 ton/ha/yr, and nearly 8% of the area experiences deposition. Our approach to improve the accuracy of RUSLE-based soil erosion classes using PSInSAR techniques clearly demarcated the areas that call for utmost priority in implementing management practices. The corollary results show that the very severe soil erosion class is characterized by PSI velocity with higher negative values, followed by the successively lower classes. Results strongly suggest that RUSLE output can be improved as well as validated using a velocity map derived from radar data.
DOI: 10.6084/m9.figshare.20418614.v1
title: Furthering the precision of RUSLE soil erosion with PSInSAR data: an innovative model

description: Soil erosion is a severe environmental problem worldwide, especially in tropical regions. The Revised Universal Soil Loss Equation (RUSLE), one of the universally accepted empirical soil erosion models, is quite commonly used in tropical climatic conditions to estimate the magnitude and severity of soil erosion. This study, apart from identifying the role of individual parameters in influencing the results of the RUSLE, also aims at refining the RUSLE results by incorporating the state-of-the-art technique Persistent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR) in a GIS environment by utilizing its ability to measure minute surface changes in millimetre levels. Apart from this novel approach of prioritising soil erosion classes using PSInSAR, the eroding surface conditions were also studied using low coherence value (&lt;0.75 in this study). The spatially and temporally averaged annual soil loss and net soil erosion (2015–2019), derived through RUSLE and transport limited sediment delivery (TLSD) approach, respectively, was improved by spatially integrating the PSInSAR velocity map. The integrated methodological framework is demonstrated for a tropical river basin in South India (Muvattupuzha River Basin [MRB]), which shows a mean rate of net soil loss of 6.8 ton/ha/yr, and nearly 8% of the area experiences deposition. Our approach to improve the accuracy of RUSLE-based soil erosion classes using PSInSAR techniques clearly demarcated the areas that call for utmost priority in implementing management practices. The corollary results show that the very severe soil erosion class is characterized by PSI velocity with higher negative values, followed by the successively lower classes. Results strongly suggest that RUSLE output can be improved as well as validated using a velocity map derived from radar data.
DOI: 10.15468/dl.hzcg5u
title: Occurrence Download

description: A dataset containing 3127 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Helianthus debilis Nutt.",
 "HasCoordinate is true",
 "Year is greater than or equal to 1900",
 "BasisOfRecord is one of (Human Observation, Specimen, Unknown evidence)"
 ]
}

 The dataset includes 3127 records from 79 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071265-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.th2wyz
title: Occurrence Download

description: A dataset containing 18 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Pterostichus macer (Marsham, 1802)",
 "Country is one of (Switzerland)"
 ]
}

 The dataset includes 18 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0346907-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.p8xe2h
title: Occurrence Download

description: A dataset containing 6028 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "Continent is Europe",
 "Year is greater than 1978",
 "Year is less than 2014",
 "HasGeospatialIssue is false",
 "TaxonKey is Aethionema saxatile (L.) R.Br."
 ]
}

 The dataset includes 6028 records from 119 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071264-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9yzufn
title: Occurrence Download

description: A dataset containing 1189 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Akodon cursor (Winge, 1887)"
 ]
}

 The dataset includes 1189 records from 29 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0346916-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qkyxww
title: Occurrence Download

description: A dataset containing 39555 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Barbastella barbastellus (Schreber, 1774)"
 ]
}

 The dataset includes 39555 records from 468 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0346951-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nq9rw8
title: Occurrence Download

description: A dataset containing 127 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (China, Chinese Taipei)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Entada phaseoloides (L.) Merr."
 ]
}

 The dataset includes 127 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071267-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4urh7u
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is one of (Epigomphus subsimilis Calvert, 1929)"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010265-240425142415019/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.544pm6
title: Occurrence Download

description: A dataset containing 45 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "Country is China",
 "Country is Hong Kong",
 "Country is Macao"
 ]
 },
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Viverricula indica (É.Geoffroy Saint-Hilaire, 1803)"
 ]
}

 The dataset includes 45 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0361337-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.