cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5061/dryad.9w0vt4bnr
title: Goniopteris ×tico (Thelypteridaceae), a new hybrid fern from Costa Rica

description: Goniopteris ×tico, a new hybrid fern from La Selva Biological Station in
 Heredia Province, Costa Rica, is described based on morphology and
 analysis of target-capture DNA sequence data. The hybrid co-occurs with
 its two putative progenitors, Goniopteris mollis and Goniopteris
 nicaraguensis, and is readily recognizable by its intermediate leaf
 dissection and venation. It is also intermediate in pinnae size and shape
 and presents irregularly lobed pinnae. Despite the broad overlap in the
 geographic distribution of its parental taxa, Goniopteris ×tico is only
 known from two collections from a single area of the La Selva Biological
 Station, highlighting the importance of close observation of ferns from
 even well-collected areas.
description: # Goniopteris ×tico (Thelypteridaceae), a New Hybrid Fern from Costa Rica
 [https://doi.org/10.5061/dryad.9w0vt4bnr](https://doi.org/10.5061/dryad.9w0vt4bnr) This dataset includes FASTA files of multiple sequence alignments of 352 low-copy nuclear loci, as well as summary tables of the output of these analyses. ## Description of the data and file structure Accession names match supplementary data provided in the Zenodo repository: https://zenodo.org/records/7832162 **Table 1: Results of HybPhaser Analysis** **Key to column headers:** * Sample Number - Accession number from NCBI Sequence Read Archive * Voucher - Collector surname and collection number * Country - Country where voucher was collected * Taxon - species name * bp - Total base pair count * allele\_divergence - % sequence divergence calculated by HybPhaser * locus\_heterozygosity - Percentage of loci with heterozygosity scores above threshold * loci with &gt;0.5% SNPs - Percentage of loci with &gt;0.5% SNPs * loci with &gt;1% SNPs - Percentage of loci with &gt;1% SNPs * loci with &gt;2% SNPs - Percentage of loci with &gt;2% SNPs * NumReads - Total number of reads obtained from sample * ReadsMapped - Total number of reads mapped to target * PctOnTarget - Percentage of total reads mapped to target * GenesWithSeqs - Number of loci with sequences **Table 2: Results of HybPhaser Read Assignment** **Key to column headers:** * sample - Sample code of phased sample * bp - Total base pair count * bpoftarget - Total length of recovered sequence, relative to target sample (percentage) * paralogs\_all - Total number of paralogous loci recovered * paralogs\_each - Number of paralogous copies recovered * nloci - Total number of loci recovered * allele\_divergence - % sequence divergence calculated by HybPhaser * locus\_heterozygosity - Percentage of loci with heterozygosity scores above threshold * loci with &gt;0.5% SNPs - Percentage of loci with &gt;0.5% SNPs * loci with &gt;1% SNPs - Percentage of loci with &gt;1% SNPs * loci with &gt;2% SNPs - Percentage of loci with &gt;2% SNPs * Remaining columns - proportion of total reads mapped to all possible references using BWA ## Sharing/Access information Additional data available at the following Zenodo repository: * https://zenodo.org/records/7832162 ##
DOI: 10.5281/zenodo.18352118
title: A comprehensive collection of genomic and transcriptomic resources for Rhodnius kissing bugs, vectors of Chagas disease

description: Genome Assemblies of Rhodnius Species

This Zenodo repository contains the primary genome assemblies generated in this study for multiple Rhodnius species. Assemblies were generated using MaSuRCA, and represent draft genomes suitable for downstream genomic analyses.

Contents

All files are provided as gzipped FASTA files (.fasta.gz).




Species
Assembly file name
Sex
Biosample accession number
long read(PacBio/ONT)
short read(Illumina)


R. brethesi
primary.genome_RBAM.scf.fasta.gz
M
SAMN54734933
PacBio (7x)SRR36945516
53xSRR36945517


R. colombiensis
primary.genome_COLM.scf.fasta.gz
M
SAMN54734934
PacBio (7x)SRR36945497
49xSRR36945505


R. domesticus
primary.genome_DOMFM.scf.fasta.gz
M+F
SAMN54734936
ONT (18x)SRR36945493
40xSRR36945494


R. milesi
primary.genome_RMM.scf.fasta.gz
M
SAMN54735064
ONT (15x)SRR36945491
56xSRR36945492


R. montenegrensis
primary.genome_R8F.scf.fasta.gz
F
SAMN54734937
PacBio (7x)SRR36945514
18x (Filée et al. 2022)SRR6749989


R. nasutus
primary.genome_R7WU.scf.fasta.gz
F
SAMN54734938
PacBio (7x)SRR36945512
16x (Filée et al. 2022)SRR6749990


R. neglectus
primary.genome_R5WU.scf.fasta.gz
F
SAMN54734939
PacBio (7x)SRR36945510
23x (Filée et al. 2022)SRR6749979


R. neivai
primary.genome_NEIF_rm_conta.fasta.gz
F
SAMN54735065
ONT (17x)SRR36945508
72xSRR36945509


R. pallescens
primary.genome_PALM.scf.fasta.gz
M
SAMN54734940
PacBio (7x)SRR36945506
64xSRR36945507


R. pictipes
primary.genome_PICM.scf.fasta.gz
M
SAMN54734941
PacBio (7x)SRR36945503
79xSRR36945504




Usage Notes





These assemblies are draft genomes; users should apply their own quality control and filtering if necessary.




Corresponding raw sequencing data (ONT or PacBio long reads and Illumina WGS) are deposited at NCBI under BioProject PRJNA1405103 (see Supplementary Table 7 for accession numbers).



Citation

Please cite the associated publication when using these assemblies.
DOI: 10.5281/zenodo.18352117
title: A comprehensive collection of genomic and transcriptomic resources for Rhodnius kissing bugs, vectors of Chagas disease

description: Genome Assemblies of Rhodnius Species

This Zenodo repository contains the primary genome assemblies generated in this study for multiple Rhodnius species. Assemblies were generated using MaSuRCA, and represent draft genomes suitable for downstream genomic analyses.

Contents

All files are provided as gzipped FASTA files (.fasta.gz).




Species
Assembly file name
Sex
Biosample accession number
long read(PacBio/ONT)
short read(Illumina)


R. brethesi
primary.genome_RBAM.scf.fasta.gz
M
SAMN54734933
PacBio (7x)SRR36945516
53xSRR36945517


R. colombiensis
primary.genome_COLM.scf.fasta.gz
M
SAMN54734934
PacBio (7x)SRR36945497
49xSRR36945505


R. domesticus
primary.genome_DOMFM.scf.fasta.gz
M+F
SAMN54734936
ONT (18x)SRR36945493
40xSRR36945494


R. milesi
primary.genome_RMM.scf.fasta.gz
M
SAMN54735064
ONT (15x)SRR36945491
56xSRR36945492


R. montenegrensis
primary.genome_R8F.scf.fasta.gz
F
SAMN54734937
PacBio (7x)SRR36945514
18x (Filée et al. 2022)SRR6749989


R. nasutus
primary.genome_R7WU.scf.fasta.gz
F
SAMN54734938
PacBio (7x)SRR36945512
16x (Filée et al. 2022)SRR6749990


R. neglectus
primary.genome_R5WU.scf.fasta.gz
F
SAMN54734939
PacBio (7x)SRR36945510
23x (Filée et al. 2022)SRR6749979


R. neivai
primary.genome_NEIF_rm_conta.fasta.gz
F
SAMN54735065
ONT (17x)SRR36945508
72xSRR36945509


R. pallescens
primary.genome_PALM.scf.fasta.gz
M
SAMN54734940
PacBio (7x)SRR36945506
64xSRR36945507


R. pictipes
primary.genome_PICM.scf.fasta.gz
M
SAMN54734941
PacBio (7x)SRR36945503
79xSRR36945504




Usage Notes





These assemblies are draft genomes; users should apply their own quality control and filtering if necessary.




Corresponding raw sequencing data (ONT or PacBio long reads and Illumina WGS) are deposited at NCBI under BioProject PRJNA1405103 (see Supplementary Table 7 for accession numbers).



Citation

Please cite the associated publication when using these assemblies.
DOI: 10.5061/dryad.brv15dvgb
title: Data from: The effect of climate change on forest fire danger and severity in the Canadian boreal forests for the period 1976–2100

description: Recent climatic trends have increased forest fire activity in Canada. This
 study aimed to evaluate how forest fire conditions might evolve across the
 Canadian borael forests in the future and to inform discussion about the
 impact of climate change on fire danger and severity.
description: There are two data sources used in the manuscript: (1)
 observational data from meteorological stations across the Canadian boreal
 forests, (2) simulation data from 4 earth system models of CanESM2,
 HadGEM2-ES, CSIRO-Mk3.6.0, and MIROC-ESM-CHEM. Both sources are of daily
 climatic data of precipitation, temperatures, relative humidity, and wiond
 speed. The data were processed using bias-corrected spatial disaggregation
 downscaling method.
description: There are 5 files uploaded. (1) fwi26.txt.gz, RCP26 (2) fwi45.txt.gz,
 RCP45 (3) fwi85.txt.gz, RCP85 (4) msk20231028.txt (5)
 Shape\_Canadian\_Boreal\_Forests.7z mask20231028.txt is an ascii file
 covering the Canadian Boreal Forests. This file can be imported into
 GisMAP to generate a mask raster. Shape\_Canadian\_Boreal\_Forests.7z is a
 compressed shape file cover the Canadian Boreal Forests. fwi26.txt.gz,
 fwi45.txt.gz, and fwi85.txt.gz are the zipped file of FFMC and DSR daily
 surfaces. There are 6 fields in the files: Field 1: row number in the mask
 file of mask20231028.txt. Field 2: column number. Field 3: Years; 1, 2, 3,
 ... 95 correspoind to 2006, 2007, 2008, ..., 2100. Field 4: Days; 1, 2, 3,
 ..., 365 in a year. Field 5: Daily FFMC values. Field 6: Daily DSR values.
DOI: 10.5061/dryad.xwdbrv1kp
title: Abiotic and biotic contexts shape the effect of disturbance on non-native plant invasion

description: Making predictions about when and where a given mechanism of invasion will
 be weak or strong is crucial for the effective management of non-native
 species. Despite the importance of disturbance on invasion, our
 understanding of how variation in abiotic and/or biotic conditions may
 modify the disturbance-invasion relationship is scarce. Here, we aimed to
 evaluate how abiotic (soil type) and biotic (tree and shrub cover)
 contexts affect the disturbance-invasion relationship in disturbed and
 nearby non-disturbed communities in the semi-arid open forest of central
 Argentina (ca. 36° S) using field sampling. We found that abiotic context
 modulated non-native species success in disturbed communities, whereas
 both abiotic and biotic context modulated success in nearby non-disturbed
 communities. These findings suggest that the plant invasion-disturbance
 relationship is context-dependent. Our results hint at the possibility
 that the significance of disturbance in predicting invasion might diminish
 as the importance of abiotic filters increases.
description: # Abiotic and biotic contexts shape the effect of disturbance on
 non-native plant invasion 
 **Chiuffo&Hierro_Oikos2023_Dataset**. Dataset containing the data
 supporting the paper 'Abiotic and biotic contexts shape the effect of
 disturbance on non-native plant invasion' (Chiuffo and Hierro, Oikos
 2023). This dataset was collected in disturbed and nearby non-disturbed
 communities growing in sandy and sandy loam soils in the Parque Luro
 Provincial Reserve (36º 57’ S, 64º 17’ W), La Pampa province, Argentina.
 **Dataset includes:** * Environment (that is, closed woodland, open
 woodland, or grassland). * Site (i.e. number of replicates per
 environmental context). * Distance (-5: distance from disturbance border,
 survey conducted on disturbed communities, 0-300m: distances from
 disturbance). * Community (i.e. disturbed or non-disturbed). * Plot (plot
 number, 1-5 per distance). * Non-native cover (percentage). * Total cover
 (i.e. native and non-native species cover percentage). * Non-native
 richness (i.e. number of non-native species). * Native richness (i.e.
 number of native species). * Photosynthetic active radiation (PAR,
 percentage of full light). * Soil type (i.e. sandy or sandy loam). * x:
 latitude (decimal degrees). * y: longitude (decimal degrees).
DOI: 10.5061/dryad.xsj3tx9np
title: Data from: A virtual near-peer mentorship research program focused on healthcare disparities in the United States of America

description: To promote health equity, it is crucial to educate the next generation of
 healthcare workers about disparities early on during their education. We
 developed a virtual research program at a medical school in the United
 States of America with the goal of increasing the awareness of youth about
 the complexities of health inequities. The program was based on a
 near-peer mentorship where high school students were coached by medical
 student mentors under the oversight of an experienced faculty mentor. We
 evaluated the participants’ perspectives about the program using a mixed
 quantitative and qualitative method. Upon completion of the program, the
 participants were asked to complete a survey and rate their self-perceived
 knowledge, efficacy skills, and interest in addressing health disparities
 in the future. Additionally, the participants’ perspectives about the
 program were gathered using open-ended questions and analyzed using
 thematic analysis. Our preliminary findings indicate that the program
 enhanced the participant’s knowledge about the complexities of health
 disparities and their motivation to address them in the future. The
 near-peer mentorship model was valuable in the success of the program. The
 implications of enhancing intrinsic and extrinsic instincts through
 partnerships among educational settings, underserved communities,
 policymakers, and healthcare agencies are discussed.
description: An anonymous survey was distributed to high school and medical
 student coaches via REDCap hosted at our university. Some of the responses
 were based on a Likert Scale of 1-4, with 4 being the most positive
 outcome. In the manuscript, the average of Likert Scales was calculated
 for each question.
description: # Data set: A virtual near-peer mentorship research program focused on
 healthcare disparities in the United States of America
 [https://doi.org/10.5061/dryad.xsj3tx9np](https://doi.org/10.5061/dryad.xsj3tx9np) Two Excel files from REDCap are included in the data set. One includes the responses of the high school students and the other includes the responses of the medical students. ## Description of the data and file structure The questions of the survey are on the first row of the Excel file and the responses of each of the participants are summarized on each row after the first row. The responses to some of the questions use a Likert Scale of 1-4, and 4 representing the most positive outcome. ##
DOI: 10.5061/dryad.qbzkh18qd
title: AERPAW helikite spectrum monitoring at Packapalooza festival in Aug 2022

description: In this dataset, we conducted a spectrum monitoring experiment in an urban
 environment. The helikite flies up to an altitude of 400 feet throughout
 the day from noon to 9 p.m. during NC State’s Packapalooza festival in
 August, 2022. The spectrum is swept up to 6 GHz. Every sweep takes around
 1 minute, while after every 4 measurements, the 5th measurement takes
 close to 5 minutes due to another data collection activity running in
 parallel. The photo of a flying Helikite at the experiment site is shown
 in the dataset image. The helikite goes up and stays at an altitude of
 around 400 feet and goes down around an altitude of around 70 feet four
 times during the whole measurement period.
description: # AERPAW Helikite Spectrum Measurements at Packapalooza in Aug 2022
 Spectrum monitoring dataset by a helikite in an urban area, which is
 measured by AERPAW. The dataset is formatted by SigMF. Please find
 instructions in the readme. MATLAB post-processing code for the dataset is
 attached as well. ## Description of the data and file structure ###
 Contents 1. SigMF formatted power spectrum raw dataset in the folder named
 pow\_spec 2. SigMF formatted GPS logs in the folder named GPS\_logs 3.
 SigMF formatted spectrum monitoring logs in the folder named GPS\_logs 4.
 SigMF format to MATLAB format conversion Python code named
 'sigMF2mat\_PW\.py'\. 5. SigMF format to csv format conversion
 Python code named 'sigMF2csv\_GPS\.py' ### Running the code 1.
 Run 'sigMF2mat\_PW\.py' to get the original mat format power
 spectrum dataset\. The output files are located at
 '\.\\pow\_spec\\matfile'\. 2. Run 'sigMF2csv\_GPS\.py'
 to get a csv file for GPS logs\. The output files are located at
 '\.\\GPS\_logs\\csvfile'\. 3. Run
 'sigMF2csv\_spec\_log\.py' to get a csv file for spectrum
 monitoring logs\. The output files are located at
 '\.\\GPS\_logs\\csvfile'\. ### Raw data description 1. Power
 spectrum: Each mat file includes 'freqs'\(MHz\) and
 'powers'\(dBm\)\. The name of the mat files represent a
 timestamp\. 2. GPS logs: There are 4 columns in the generated csv file\.
 Columns from 1 to 4 represent longitude\, latitude\, altitude \(the unit
 is the meter\)\, timestamp \(the unit is the seconds from epoch time\)\,
 respectively\. 3. Spectrum monitoring logs: There is a single column in
 the generated csv file\. The column represents the timestamp of all center
 frequency shifts for sweeping the spectrum\. ### SigMF format This dataset
 is compatible with SigMF v1.0.1. SigMF webpage:
 https://github.com/gnuradio/SigMF/tree/sigmf-v1.x ### MATLAB
 Post\-processing code Run Post\_processing\_main.m after getting the
 original mat format power spectrum dataset and csv format logs files. ##
 Sharing/Access information Links to other publicly accessible locations of
 the data: * https://aerpaw.org/experiments/datasets/ ## Code/Software
 Python, MATLAB
DOI: 10.5061/dryad.mw6m9063f
title: AERPAW helikite spectrum measurements at Packapalooza Festival in Aug 2023

description: We conducted a spectrum monitoring experiment using a helikite in an urban
 environment. We float the helikite-mounted software-defined radio (SDR)
 and global positioning system (GPS) receivers around 90 minutes from noon
 during NC State’s Packapalooza festival in August 2023. The helikite holds
 a low altitude of around 5 m for 45 minutes and then flies up to around
 140 m. After the helikite holds height for a few minutes, it gradually
 goes down to the ground. The spectrum is swept up to 6 GHz. A single
 spectrum sweeping takes around 15 seconds and a total of 364 sweeping is
 executed during the experiment.
description: # AERPAW Helikite Spectrum Measurements at Packapalooza Festival in Aug
 2023 Spectrum monitoring dataset by a helikite in an urban area, which is
 measured by AERPAW. The dataset is formatted by SigMF. Please find
 instructions in the readme. MATLAB post-processing code for the dataset is
 attached as well. ## Description of the data and file structure ###
 Contents 1. SigMF formatted power spectrum raw dataset in the folder named
 pow\_spec 2. SigMF formatted GPS logs in the folder named GPS\_logs 3.
 SigMF formatted spectrum monitoring logs in the folder named GPS\_logs 4.
 SigMF format to MATLAB format conversion Python code named
 'sigMF2mat\_PW\.py'\. 5. SigMF format to csv format conversion
 Python code named 'sigMF2csv\_GPS\.py' ### Running the code 1.
 Run 'sigMF2mat\_PW\.py' to get the original mat format power
 spectrum dataset\. The output files are located at
 '\.\\pow\_spec\\matfile'\. 2. Run 'sigMF2csv\_GPS\.py'
 to get a csv file for GPS logs\. The output files are located at
 '\.\\GPS\_logs\\csvfile'\. 3. Run
 'sigMF2csv\_spec\_log\.py' to get a csv file for spectrum
 monitoring logs\. The output files are located at
 '\.\\GPS\_logs\\csvfile'\. ### Raw data description 1. Power
 spectrum: Each mat file includes 'freqs'\(MHz\) and
 'powers'\(dBm\)\. The name of the mat files represent a
 timestamp\. 2. GPS logs: There are 4 columns in the generated csv file\.
 Columns from 1 to 4 represent longitude\\\, latitude\\\, altitude \(the
 unit is the meter\)\\\, timestamp \(the unit is the seconds from epoch
 time\)\\\, respectively\. 3. Spectrum monitoring logs: There is a single
 column in the generated csv file\. The column represents the timestamp of
 all center frequency shifts for sweeping the spectrum\. ### SigMF format
 This dataset is compatible with SigMF v1.0.1. SigMF webpage:
 https://github.com/gnuradio/SigMF/tree/sigmf-v1.x ### MATLAB
 Post\-processing code Run Post\_processing\_main.m after getting the
 original mat format power spectrum dataset and csv format logs files. ##
 Sharing/Access information Links to other publicly accessible locations of
 the data: * https://aerpaw.org/experiments/datasets/ ## Code/Software
 Python, MATLAB
DOI: 10.5061/dryad.mgqnk9959
title: Collared pratincole nest success in Hungary

description: Agricultural intensification has affected wildlife across Europe,
 triggering steep declines and regional extinctions of farmland birds.
 Effective conservation activities are essential for the preservation of
 biodiversity in an agricultural landscape, but current efforts have not
 succeeded in halting these declines. Here we investigate a ground-nesting
 shorebird, the collared pratincole, Glareola pratincola, which
 has shifted its habitat use in Central Europe over the last 20 years from
 alkaline grasslands to intensively managed agricultural fields. We show
 that nesting success was different between three agricultural habitat
 types, with the highest nesting success in fallow lands and the lowest in
 row crops. Nesting success was also associated with the timing of breeding
 and breeding density, as nests produced early in the breeding season and
 those in high-breeding-density areas hatched more successfully than those
 produced later in the season and at low density. We implemented direct
 conservation measures including marking nests and negotiating with farmers
 to avoid cultivating the field between nest markers, controlling nest
 predators, and, most recently, creating suitable nesting sites and
 foraging areas for pratincoles. As a result of these conservation actions,
 nest survival increased from 11.2% to 83.5% and the size of the breeding
 population increased from 13 to 56 pairs during 2012–2021. Thus, we show
 that agricultural landscapes can continue to provide important habitats,
 and targeted conservation actions have the potential to reverse the
 declines of farmland species.
description: # Collared pratincole nest success in Hungary
 [https://doi.org/10.5061/dryad.mgqnk9959](https://doi.org/10.5061/dryad.mgqnk9959) ## Description of the data and file structure Datasets included: Data were collected during breeding period. 1 Year: - Current year of data collection. 2\. Colony code: \- Code of the current breeding site\. 3\. Location: \- Hungarian Cadastre name of the nesting site\. 4\. Habitat type: \- Type of the agricultural habitat\. 5\. Number of nests: \- Number of founded nests in the actual breeding site\. 6\. Number of hatched nests: \- Number of successfully hatched nests in the actual breeding site \(Nest success meant that at least one young hatched per nest\)\.