cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5061/dryad.dbrv15f7w
title: Data from: Will trees or grasses profit from changing rainfall regimes in savannas?

description: • Increasing rainfall variability is widely expected under future climate
 change scenar- ios. How will savanna trees and grasses be affected by
 growing season dry spells and altered seasonality and how tightly coupled
 are tree-grass phenologies with rainfall? • We measured tree and grass
 responses to growing season dry spells and dry season rainfall. We also
 tested if the phenologies of 17 deciduous woody species and the Soil
 Adjusted Vegetation Index of grasses were related to rainfall between 2019
 and 2023. • Tree and grass growth was significantly reduced during growing
 season dry spells. Tree growth was strongly related to growing season soil
 water potentials and limited to the wet season. Grasses can rapidly
 recover after growing season dry spells and grass evapotranspiration was
 significantly related to soil water potentials in both the wet and dry
 seasons. Tree leaf flushing commenced before the rainfall onset date
 with little subsequent leaf flushing. Grasses grew when moisture
 became available regardless of season. • Our findings suggest that
 increased dry spell length and frequency in the growing season may slow
 down tree growth in some savannas, which together with longer growing
 seasons may allow grasses an advantage over C3 plants that are advantaged
 by rising CO2 levels.
description: # Will trees or grasses profit from changing rainfall regimes in savannas?
 These datasets accompany
 the article published in New Phytologist with the same title. 1\) Tree
 growth rates (Trees_growth.csv) 2\) Grass evapotranspiration rates
 (Grass_evapotranspiration.csv) 3\) Historical rainfall data
 (Skukuza_rainfall.csv) 4\) Daily soil water potentials
 (Daily_soil_kpa.csv) Give a brief summary of dataset contents,
 contextualized in experimental procedures and results. ## Description of
 the data and file structure 1\) Tree growth rates Date = date Species =
 species rep = species replicate diam_increase = increase in stem diameter
 rain.year = rainfall year including the 2021 and 2022 rainfall years 2\)
 Grass evapotranspiration rates Date = date lysname = Lysimeter ID ET0 =
 daily evapotranspiration rain.year = rainfall year including the 2021 and
 2022 rainfall years (g.m*−*2.day*−*1) 3\) Historical rainfall data
 (Skukuza_rainfall.csv) has the following columns: Station = weather
 station Date = date Year = year Month = month Day = day mm = rainfall
 amount rain.year = rainfall year DORY = day of rainfall year 4\) Daily
 soil water potentials (Daily_soil_kpa.csv) date = date kpa_10 = soil water
 potential at 10 cm kpa_20 = soil water potential at 20 cm kpa_30 = soil
 water potential at 30 cm
DOI: 10.5281/zenodo.15484009
title: Fine-Scale Bioregionalization in a Complex Island System: A Freshwater Perspective from the Greater Antilles
title: Biorregionalización A Escala Fina En Un Sistema Insular Complejo: Una Perspectiva De Agua Dulce Desde Las Antillas Mayores

description: This repository contains the Supporting Information and analysis script (.Rmd) associated with the article “Fine-Scale Bioregionalization in a Complex Island System: A Freshwater Perspective from the Greater Antilles", published in Journal of Biogeography (https://doi.org/10.1111/jbi.70140). A Spanish-language version of the abstract is also included.
description: The isolated nature of islands makes them particularly vulnerable to climate change. The freshwater fishes of the Greater Antilles remain understudied and are further threatened by habitat fragmentation and the introduction of exotic invasive species. A practical solution to protect this diversity is to develop a spatially explicit framework to inform conservation actions. We test whether biogeographically significant subregions can be identified within the Greater Antilles. We compiled a dataset of 1,704 freshwater fish occurrence records across the Greater Antilles based on museum vouchers and the authors’ fieldwork. River basins were used as analytical units for hierarchical agglomerative clustering both among and within islands. We also combined genetic data to examine phylogeographic patterns and uncover potential substructure within islands. Ninety-two percent of the freshwater fish fauna of the Greater Antilles is endemic. Although diversity is unevenly distributed among and within islands, patterns of species richness and weighted endemism partially align across islands. The region is not a single biogeographic unit but consists of multiple subregions of biogeographic significance, where river basins from the same island are more similar to each other than to basins from other islands, with Hispaniola as the only exception. The Greater Antilles comprise a mosaic of biogeographically meaningful subregions, each harboring unique, highly vulnerable, and often range-restricted species assemblages. The patterns recovered reflect a complex interplay among the region’s geological history, multiple colonization events, and diversification processes. Our proposed areas of endemism represent testable hypotheses for investigating the evolutionary history of freshwater taxa in the region. These areas also provide natural management units that can serve as geographic targets for conservation prioritization and policymaking for freshwater ecosystems across the Greater Antilles.
DOI: 10.5281/zenodo.15484010
title: Fine-Scale Bioregionalization in a Complex Island System: A Freshwater Perspective from the Greater Antilles
title: Biorregionalización A Escala Fina En Un Sistema Insular Complejo: Una Perspectiva De Agua Dulce Desde Las Antillas Mayores

description: This repository contains the Supporting Information and analysis script (.Rmd) associated with the article “Fine-Scale Bioregionalization in a Complex Island System: A Freshwater Perspective from the Greater Antilles", published in Journal of Biogeography (https://doi.org/10.1111/jbi.70140). A Spanish-language version of the abstract is also included.
description: The isolated nature of islands makes them particularly vulnerable to climate change. The freshwater fishes of the Greater Antilles remain understudied and are further threatened by habitat fragmentation and the introduction of exotic invasive species. A practical solution to protect this diversity is to develop a spatially explicit framework to inform conservation actions. We test whether biogeographically significant subregions can be identified within the Greater Antilles. We compiled a dataset of 1,704 freshwater fish occurrence records across the Greater Antilles based on museum vouchers and the authors’ fieldwork. River basins were used as analytical units for hierarchical agglomerative clustering both among and within islands. We also combined genetic data to examine phylogeographic patterns and uncover potential substructure within islands. Ninety-two percent of the freshwater fish fauna of the Greater Antilles is endemic. Although diversity is unevenly distributed among and within islands, patterns of species richness and weighted endemism partially align across islands. The region is not a single biogeographic unit but consists of multiple subregions of biogeographic significance, where river basins from the same island are more similar to each other than to basins from other islands, with Hispaniola as the only exception. The Greater Antilles comprise a mosaic of biogeographically meaningful subregions, each harboring unique, highly vulnerable, and often range-restricted species assemblages. The patterns recovered reflect a complex interplay among the region’s geological history, multiple colonization events, and diversification processes. Our proposed areas of endemism represent testable hypotheses for investigating the evolutionary history of freshwater taxa in the region. These areas also provide natural management units that can serve as geographic targets for conservation prioritization and policymaking for freshwater ecosystems across the Greater Antilles.
DOI: 10.5061/dryad.h70rxwdr6
title: Study on the mating systems of wild rice Oryza rufipogon and O. nivara and their effects on population genetic variation

description: As the wild ancestors of Asian cultivated rice, Oryza rufipogon Griff. and
 O. nivara Sharma et Shastry serve as valuable germplasms for rice
 breeding. Mating systems are important in shaping the level and pattern of
 population genetic variation, and are crucial for germplasm conservation.
 We genotyped 12 simple sequence repeats (SSR) markers for a large number
 of maternal plants and seeds collected from O. rufipogon and O. nivara
 populations distributed in Southeast Aisa and South China. Based on the 12
 SSR markers, we estimated the outcrossing rates and other parameters of
 the mixed-mating model for the two wild rice species. We also assessed the
 level of genetic diversity and population structure for parental
 populations of O. rufipogon and O. nivara. Our study could facilitate in
 situ and ex situ conservation, and the utilization of these valuable
 germplasm resources.
description: A total of 12 <em>O. rufipogon </em>populations were
 sampled, of which eight were collected from China, and the other four were
 collected from Cambodia (2), Nepal (1), and Vietnam (1). Four populations
 of <em>O. nivara </em>were collected from Laos (2), Cambodia
 (1), and Nepal (1). For each population, 11-31 maternal plants were
 collected with 5-20 seeds per plant. Leaves of maternal plants and
 seedings were dried using silica gel. The total genomic DNA was extracted
 using the CTAB method. Totally 12 SSR markers were selected from the 125
 SSR primer pairs developed in the study by McCouch et al. (2002).
 Polymerase chain reactions (PCR) was carried out in a T-personal thermal
 cycler. The amplified products were subjected to fragment analysis on an
 ABI 3730XL analyzer (Applied Biosystems). SSR genotyping was conducted
 using the GeneMarker software (SoftGenetics, State College, Pennsylvania,
 USA).
description: # Study on the mating systems of wild rice Oryza rufipogon and O. nivara
 and their effects on population genetic variation
 [https://doi.org/10.5061/dryad.h70rxwdr6](https://doi.org/10.5061/dryad.h70rxwdr6) ## Description of the data and file structure This file contains SSR genotypes of the two wild rice species (*Oryza rufipogon* and *O. nivara*) and their progenies. There are three Microsoft Excel sheets in the file. The first sheet contains the SSR genotypes of the maternal parents, i.e. the maternal populations of *O. rufipogon* and *O. nivara*. The second sheet contains the SSR genotypes of progenies of *O. rufipogon*, and the third sheet contains the SSR genotypes of progenies of *O. nivara*. Each cell contains one SSR allele, so two consecutive cells represent a SSR genotype. The missing data were coded as 0.
DOI: 10.15468/dl.dmdwca
title: Occurrence Download

description: A dataset containing 386 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-105.50166 47.70970,-94.55601 47.70970,-94.55601 52.88038,-105.50166 52.88038,-105.50166 47.70970))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Ambystoma mavortium"
 ]
}

 The dataset includes 386 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003856-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5061/dryad.5hqbzkhct
title: Generation of KRAS knockout pancreatic cancer cell line PANC1

description: We used CRISPR to inactivate mutant KRAS and STAT3 in PANC1 (KRASG12D)
 pancreatic cancer cell line. Gene expression analysis of KRAS intact vs.
 knockout cells identified sets of genes involved in protein synthesis,
 cell differentiation, and metabolic processes, while the expression of
 MAPK/ERK target genes remained unperturbed.
description: # PANC1 pancreatic cancer cell line
 We used CRISPR to
 inactivate mutant KRAS and STAT3 in PANC1 (KRASG12D) pancreatic cancer
 cell line. Gene expression analysis of KRAS intact vs. knockout cells
 identified sets of genes involved in protein synthesis, cell
 differentiation, and metabolic processes, while the expression of MAPK/ERK
 target genes remained unperturbed. Methods Cell line construction For
 CRISPR/Cas9-mediated knockouts, we used sgRNAs specific for KRAS and
 STAT3. Knockout efficiency was measured by Western blotting. Multiple
 technical replicates were obtained for each CRISPR targeted gene. Genomic
 DNA from clonal cell lines was collected using QiaAmp DNA Mini Kit
 (Qiagen). PCR products for sequencing were amplified using Taq DNA
 polymerase (Invitrogen) and cloned into a pBluescript vector. At least
 10-15 bacterial colonies were sequenced per cell line. For RNA isolation,
 cells were harvested with TRIzol reagent (Invitrogen). Cells were
 maintained in DME medium supplemented with 5% fetal bovine serum (FBS).
  RNA sequencing RNA sequencing of tumor cells with basic bioinformatics
 and statistical analyses were performed by Novogene Corp. The FPKM counts
 represent fragments per kilobase of transcript per million mapped reads.
 Funding National Cancer Institute ## Description of the data and file
 structure Data are presented in FPKM format. Data include parental intact
 (Pa1), KRAS knockout (PaKKO), STAT3 knockout (PaSTAT3KO), and KRAS/STAT3
 double knockout derivatives (PaDKO).
DOI: 10.5061/dryad.z8w9ghxks
title: Gene expression analysis of KRAS knockout pancreatic cancer cell line CFPAC1

description: We used CRISPR to inactivate mutant KRAS in CFPAC1 (KRASG12V) pancreatic
 cancer cell lines. Gene expression analysis of KRAS intact vs. knockout
 cells identified sets of genes involved in protein synthesis, cell
 differentiation, and metabolic processes, while the expression of MAPK/ERK
 target genes remained unperturbed.
description: For CRISPR/Cas9-mediated knockouts, we used sgRNAs specific for
 KRAS. Knockout efficiency was measured by Western blotting. Multiple
 technical replicates were obtained for each CRISPR targeted gene. Genomic
 DNA from clonal cell lines was collected using QiaAmp DNA Mini Kit
 (Qiagen). PCR products for sequencing were amplified using Taq DNA
 polymerase (Invitrogen) and cloned into a pBluescript vector. At least
 10-15 bacterial colonies were sequenced per cell line. For RNA isolation,
 cells were harvested with TRIzol reagent (Invitrogen). Cells were
 maintained in DME medium supplemented with 5% fetal bovine serum
 (FBS). RNA sequencing of tumor cells with basic bioinformatics and
 statistical analyses were performed by Novogene Corp. The FPKM counts
 represent fragments per kilobase of transcript per million mapped
 reads.
description: # Gene expression analysis of KRAS knockout pancreatic cancer cell line
 CFPAC1 Cell line
 construction For CRISPR/Cas9-mediated knockouts, we used sgRNAs specific
 for KRAS. Knockout efficiency was measured by Western blotting. Multiple
 technical replicates were obtained for each CRISPR targeted gene. Genomic
 DNA from clonal cell lines was collected using QiaAmp DNA Mini Kit
 (Qiagen). PCR products for sequencing were amplified using Taq DNA
 polymerase (Invitrogen) and cloned into a pBluescript vector. At least
 10-15 bacterial colonies were sequenced per cell line. For RNA isolation,
 cells were harvested with TRIzol reagent (Invitrogen). Cells were
 maintained in DME medium supplemented with 5% fetal bovine serum (FBS).
 RNA sequencing RNA sequencing of tumor cells with basic bioinformatics and
 statistical analyses were performed by Novogene Corp. The FPKM counts
 represent fragments per kilobase of transcript per million mapped reads.
 ## Description of the data and file structure Data are presented in FPKM
 format. Data include parental control CFPAC1 cells (CFP\_fpkm), KRAS KO
 CFPAC1 cells (CFP\_KRASKO\_fpkm), and log2 fold differences in gene
 expression (KOvsWT\_log2FoldChange).
DOI: 10.5061/dryad.pnvx0k6w1
title: Predicted room temperature electrical conductivity of molecular mixtures

description: In the associated manuscript, we propose the MolSets machine learning
 model for molecular mixture properties. Using the MolSets architecture, we
 train a model on a dataset curated by Bradford et al. (2023) to predict
 the room temperature (298 K) electrical conductivity of mixtures. Here, we
 report the model-predicted conductivities of all equal-weight binary
 mixtures among 28 types of small molecules, combined with 30 types of Li+
 salts (1 mol·kg-1), totaling 11,340 candidate lithium battery
 electrolytes. Note that the current model has a limitation of not taking
 salt solubility into account. This dataset is for demonstration purposes
 and should be used with caution.
description: # Predicted room temperature electrical conductivity of molecular mixtures
 [https://doi.org/10.5061/dryad.pnvx0k6w1](https://doi.org/10.5061/dryad.pnvx0k6w1) This dataset reports the machine learning-predicted room temperature (298 K) electrical conductivity for 11,340 molecular mixtures. ## Description of the data and file structure Every mixture consists of two types of molecules and one salt. The data is organized in a spreadsheet format. The columns are organized as follows: * The first two columns, "Solvent 1/2" contain the SMILES strings of constituent molecules in the mixture. * "Weights" and "Molar Mass" columns contain the weight fractions and molar masses (g/mol) of constituent molecules, respectively. * The "Salt" column contains the SMILES string of the salts, whose amount (kg/mol) in the mixture is reported in the "Molality" column. * The last column contains the predicted logarithm conductivities, in the unit of log (S/cm). ## Sharing/Access information The data is generated by a machine learning predictive model. The model adopts the "MolSets" architecture, which is proposed in the preprint "MolSets: Molecular graph deep sets learning for mixture property modeling" (see Related Works: arXiv:2312.16473). An implementation of the model is available on GitHub (see Related Works). Data used to train the current model is acquired from the publication: Bradford et al., (2023) *ACS Cent. Sci.* 9(2): 206–216.
DOI: 10.5061/dryad.8sf7m0cwp
title: Herbivore exclusion stabilizes alpine grassland biomass production across spatial scales

description: There is growing evidence that land-use management practices such as
 livestock grazing can strongly impact the local diversity, functioning and
 stability of grassland communities. However, whether these impacts depend
 on environmental condition and propagate to larger spatial scales remains
 unclear. Using an 8-yr grassland exclosure experiment conducted at nine
 sites in the Tibetan Plateau covering a large precipitation gradient, we
 found that herbivore exclusion increased the temporal stability of alpine
 grassland biomass production at both the local and larger (site) spatial
 scales. Higher local community stability was attributed to greater
 stability of dominant species, whereas higher stability at the larger
 scale was linked to higher spatial asynchrony of productivity among local
 communities. Additionally, sites with higher mean annual precipitation had
 lower dominant species stability and lower grassland stability at both
 spatial scales considered. Our study provides novel evidence that
 livestock grazing can impair grassland stability across spatial scales and
 climatic gradients.
description: # Herbivore exclusion stabilizes alpine grassland biomass production
 across spatial scales
 [https://doi.org/10.5061/dryad.8sf7m0cwp](https://doi.org/10.5061/dryad.8sf7m0cwp) Herbivore_exclusion_stabilizes_alpine_grassland_biomass_production_across_spatial_scales.xlsx Nine paired observation sites (fenced and grazed) in the Qinghai-Tibet Plateau, seven variables utilized in the article and four climatic factors, including annual precipitation, annual precipitation variability, annual mean temperature, and annual mean temperature variability. ## Description of the data and file structure Seven variables, including species richness,  species asynchrony, dominant species Stability, alpha Diversity,  bray Curtis dissimilarity, spatial Asynchrony, and gamma stability were caculated by a 8- year observed data in 9 sites. Column names: F —Fencing; 0—no, 1—yes SR —Species Richness (Unit: number of species m-2) BRAY—Bray Curtis dissimilarity (No unit) SY— Species Asynchrony (No unit) AS —Alpha Stability (No unit) SPA —Spatial Asynchrony (No unit) GS—Gamma Stability (No unit) DS—Dominant species Stability (No unit) RAIN—Mean Annual Precipitation (Unit: mm) RSD—SD of Mean Annual Precipitation (Unit: mm) TEM—Mean Annual Temperature (Unit: ℃) TEMSD—SD of Mean Annual Temperature  (Unit: ℃) ## Sharing/Access information This is a section for linking to other ways to access the data, and for linking to sources the data is derived from, if any. Links to other publicly accessible locations of the data: * This is a section for linking to other ways to access the data, and for linking to sources the data is derived from, if any. Links to other publicly accessible locations of the data: * [https://doi.org/10.5061/dryad.8sf7m0cwp](https://doi.org/10.5061/dryad.8sf7m0cwp)
DOI: 10.15468/dl.dzhbzy
title: Occurrence Download

description: A dataset containing 18 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lecointea marcano-bertii",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 18 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003858-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8weeaf
title: Occurrence Download

description: A dataset containing 296 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "TaxonKey is Gomphomacromia"
 ]
}

 The dataset includes 296 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003859-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.