cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5061/dryad.61dr5.2/1.2
title: CT scan data of wild turkey, Meleagris gallopavo OUVC 10599

description: This zip file contains DICOM images from an x-ray microcomputed tomography (µCT) scan of an injected Meleagris gallopavo (OUVC 10599). The arteries and veins were injected with a latex and barium solution and scanned on a GE eXplore Locus in vivo Small Animal MicroCT scanner (90µm slice thickness at 80kV and 450 µA) at the Ohio University µCT Scanning Facility.
DOI: 10.5061/dryad.6nd4k/1
title: Raw data for neighbor trees and soil variables

description: There are two spreadsheets with data. The spreadsheet "soil dataset" contains the raw soil data. The spreadsheet "tree dataset" contains the information about neighbour trees (species, position, size and defoliation index). After each data spreadsheet there is a spreadshet with the associated metadata, where a description of all the variables and units can be found.
DOI: 10.5061/dryad.86bq5/1
title: Tasmanian devil RAD data

description: The data file consists of 4 parts (1999, 2004, 2009 and 2013) each representing a sampling year for Tasmanian devils.
DOI: 10.5061/dryad.b8s71/1
title: Preliminary screening of chloroplast markers

description: Markers showing a high level of intraspecific variability are required for phylogeographic analysis. Eleven chloroplast markers and one nuclear marker were identified from the literature and screened for variation among individuals of Tilia americana s.l. (ranging from n = 5 to n = 14) in North America. Supplementary Table 1 lists the locations where T. americana specimens were collected for the screening. Supplementary Table 2 summarizes the screening results, and indicates that chloroplast markers rpL32-trnL and ndhF-rpL32 produced the largest amount of informative variation. These two markers were then sequenced across a much broader sampling of T. americana for the present study.
DOI: 10.5061/dryad.bh330/1
title: stevens_etal_2016_RSOS

description: These data were extracted from 19 years of data from the Kanyawara community of chimpanzees in Kibale National Park, Uganda from July 1988 to June 2006. The data rows are dyads of chimpanzees and columns are days. Cell values represent whether the dyad was observed together (1) or not (0) on that day. If neither chimpanzee was observed for more than 70% of the day or if the chimpanzees could not possibly have been in contact (e.g., at least one was not living), the values are blank.
DOI: 10.5061/dryad.gf87q/1
title: Data from Vink SN et al Soil conditioning affects interactions between native and invasive exotic perennials of semi-natural grasslands

description: Plant height, biomass and calculated relative interaction index (based on biomass data) for each treatment combination. Descriptions are provided as comments in the column header of the file.
DOI: 10.5061/dryad.j00p6/1
title: JuneMorphotypeData

description: Site-by-species matrix for June samples.  First column is the individual tank identification code, with the first letters representing a site identifier, the second letter representing the matrix type (O=open, HW=hardwood, P=pine), and the last letter representing the litter type (P=pine, M=maple, S=sedge).
DOI: 10.5061/dryad.j00p6/2
title: JulyMorphotypeData

description: Site-by-species matrix for July samples. First column is the individual tank identification code, with the first letters representing a site identifier, the second letter representing the matrix type (O=open, HW=hardwood, P=pine), and the last letter representing the litter type (P=pine, M=maple, S=sedge).
DOI: 10.5061/dryad.jg33m/1
title: OTU file

description: This file contains all the bacterial taxa (OTU = operational taxonomic unit of bacteria) that we could sequence on brown trout egg samples  in our study. This file is used to work with QIIME. There is a parallel file to this one that contains all the metadata (map file).
DOI: 10.5061/dryad.jg33m/4
title: Map file for QIIME analysis

description: This file contains all metadata to the OTU file, used with QIIME. it explains what the brown trout egg samples are and how they related to the OTU file.
DOI: 10.5061/dryad.jg33m/5
title: Embryo performance across treatments and families

description: This file contains all the data on embryo performance. This includes survival, time until hatching, bacterial diversities on the eggs, and origin of the embryo (mother and father).
DOI: 10.5061/dryad.jg33m/6
title: R script for analysis of embryo performance

description: This is an R script that was used to analyze embryo performance (input file is called "embryo_performance_submission.txt" and also provided here). Data was analyzed with the R-package "lme4".
DOI: 10.5061/dryad.k5st3/1
title: predictor and response data

description: Data on environmental and management predictors and vegetation responses.
DOI: 10.5061/dryad.k6j0h/1
title: otutable_first200_tax

description: Top 200 most reads OTUs with their taxonomy assignment and reads number
DOI: 10.5061/dryad.k6j0h/3
title: Bioinformatic command script

description: An example bioinformatic script
DOI: 10.5061/dryad.k6j0h/4
title: S1 fungus_CROP_R_script_nonrarefied

description: The HTML outputs of the R scripts using the non-rarefied CROP datasets
DOI: 10.5061/dryad.kk466/1
title: SNP data
DOI: 10.5061/dryad.m0n46/1
title: Host-use data and phylogenies for plant-feeding Hemiptera and Lepidoptera

description: We have included host-use information (in link form) for plant-feeding Hemiptera and Lepidoptera. There are 4 data files for each insect order, presenting the host-use information categorized by host plant genus, family and order. The fourth file is by plant order again, but this time a link is only included if that insect was observed on two genera in that plant order. We have also included molecular phylogenies for each insect order, produced using PHLAWD and the sequences available on genbank.
DOI: 10.5061/dryad.m35k6/26
title: ModelSel_WETA_2013_DynamicAll

description: AIC model selection table and associated coefficients for western tanager 2013 for all models combined. Column names for the model coefficients use the following notation: coefficient = parameter(covariate) and standard error = SEparameter(covariate). Parameter abbreviations are p = detection probability, psi = initial occupancy, col = colonization/settlement, ext = extinction/vacancy.  Parameter(Int) refers to the intercept. ‘nPars’ is the number of parameters estimated in the model. Each model is ranked by its AIC score, which represents how well the model fits the data. A lower ∆AIC (delta) value is indicative of a better model. The probability that the model (of the models tested) would best explain the data is indicated by AICwt.
DOI: 10.5061/dryad.m35k6/27
title: ModelSel_WIWA_2012_DynamicAll

description: AIC model selection table and associated coefficients for Wilson's warbler 2012 for all models combined. Column names for the model coefficients use the following notation: coefficient = parameter(covariate) and standard error = SEparameter(covariate). Parameter abbreviations are p = detection probability, psi = initial occupancy, col = colonization/settlement, ext = extinction/vacancy.  Parameter(Int) refers to the intercept. ‘nPars’ is the number of parameters estimated in the model. Each model is ranked by its AIC score, which represents how well the model fits the data. A lower ∆AIC (delta) value is indicative of a better model. The probability that the model (of the models tested) would best explain the data is indicated by AICwt.
DOI: 10.5061/dryad.m35k6/28
title: ModelSel_WIWA_2013_DynamicAll

description: AIC model selection table and associated coefficients for Wilson's warbler 2013 for all models combined. Column names for the model coefficients use the following notation: coefficient = parameter(covariate) and standard error = SEparameter(covariate). Parameter abbreviations are p = detection probability, psi = initial occupancy, col = colonization/settlement, ext = extinction/vacancy.  Parameter(Int) refers to the intercept. ‘nPars’ is the number of parameters estimated in the model. Each model is ranked by its AIC score, which represents how well the model fits the data. A lower ∆AIC (delta) value is indicative of a better model. The probability that the model (of the models tested) would best explain the data is indicated by AICwt.
DOI: 10.5061/dryad.m35k6/29
title: ModelSel_BRCR_2012_Detection

description: AIC model selection table and associated coefficients for brown creeper 2012 for all detection models. Column names for the model coefficients use the following notation: coefficient = parameter(covariate) and standard error = SEparameter(covariate). Parameter abbreviations are p = detection probability, psi = initial occupancy, col = colonization/settlement, ext = extinction/vacancy. Parameter(Int) refers to the intercept. ‘nPars’ is the number of parameters estimated in the model. Each model is ranked by its AIC score, which represents how well the model fits the data. A lower ∆AIC (delta) value is indicative of a better model. The probability that the model (of the models tested) would best explain the data is indicated by AICwt.
DOI: 10.5061/dryad.m35k6/30
title: ModelSel_BRCR_2013_Detection

description: AIC model selection table and associated coefficients for brown creeper 2013 for all detection models. Column names for the model coefficients use the following notation: coefficient = parameter(covariate) and standard error = SEparameter(covariate). Parameter abbreviations are p = detection probability, psi = initial occupancy, col = colonization/settlement, ext = extinction/vacancy. Parameter(Int) refers to the intercept. ‘nPars’ is the number of parameters estimated in the model. Each model is ranked by its AIC score, which represents how well the model fits the data. A lower ∆AIC (delta) value is indicative of a better model. The probability that the model (of the models tested) would best explain the data is indicated by AICwt.
DOI: 10.5061/dryad.m35k6/31
title: ModelSel_CBCH_2012_Detection

description: AIC model selection table and associated coefficients for chestnut-backed chickadee 2012 for all detection models. Column names for the model coefficients use the following notation: coefficient = parameter(covariate) and standard error = SEparameter(covariate). Parameter abbreviations are p = detection probability, psi = initial occupancy, col = colonization/settlement, ext = extinction/vacancy. Parameter(Int) refers to the intercept. ‘nPars’ is the number of parameters estimated in the model. Each model is ranked by its AIC score, which represents how well the model fits the data. A lower ∆AIC (delta) value is indicative of a better model. The probability that the model (of the models tested) would best explain the data is indicated by AICwt.
DOI: 10.5061/dryad.m35k6/32
title: ModelSel_CBCH_2013_Detection

description: AIC model selection table and associated coefficients for chestnut-backed chickadee 2013 for all detection models. Column names for the model coefficients use the following notation: coefficient = parameter(covariate) and standard error = SEparameter(covariate). Parameter abbreviations are p = detection probability, psi = initial occupancy, col = colonization/settlement, ext = extinction/vacancy. Parameter(Int) refers to the intercept. ‘nPars’ is the number of parameters estimated in the model. Each model is ranked by its AIC score, which represents how well the model fits the data. A lower ∆AIC (delta) value is indicative of a better model. The probability that the model (of the models tested) would best explain the data is indicated by AICwt.
DOI: 10.5061/dryad.m35k6/33
title: ModelSel_GCKI_2012_Detection

description: AIC model selection table and associated coefficients for golden-crowned kinglet 2012 for all detection models. Column names for the model coefficients use the following notation: coefficient = parameter(covariate) and standard error = SEparameter(covariate). Parameter abbreviations are p = detection probability, psi = initial occupancy, col = colonization/settlement, ext = extinction/vacancy. Parameter(Int) refers to the intercept. ‘nPars’ is the number of parameters estimated in the model. Each model is ranked by its AIC score, which represents how well the model fits the data. A lower ∆AIC (delta) value is indicative of a better model. The probability that the model (of the models tested) would best explain the data is indicated by AICwt.
DOI: 10.5061/dryad.m35k6/34
title: ModelSel_GCKI_2013_Detection

description: AIC model selection table and associated coefficients for golden-crowned kinglet 2013 for all detection models. Column names for the model coefficients use the following notation: coefficient = parameter(covariate) and standard error = SEparameter(covariate). Parameter abbreviations are p = detection probability, psi = initial occupancy, col = colonization/settlement, ext = extinction/vacancy. Parameter(Int) refers to the intercept. ‘nPars’ is the number of parameters estimated in the model. Each model is ranked by its AIC score, which represents how well the model fits the data. A lower ∆AIC (delta) value is indicative of a better model. The probability that the model (of the models tested) would best explain the data is indicated by AICwt.
DOI: 10.5061/dryad.mb605/10
title: ModelScript_HBD_SI

description: OpenBUGS script file for running the model (ModelCode_HBD_SI.txt) and calling the corresponding datasets (Dataset1_HBD.txt, Dataset2a_HBD.txt,Dataset2b_HBD.txt, Dataset3_HBD.txt, and Dataset4_HBD.txt) and initial / starting values (Initials_HBDa_S1.txt, Initials_HBDb_S1.txt,Initials_HBDc_S1.txt).
DOI: 10.5061/dryad.mb605/9
title: Initials_HBDc_SI

description: Initials (starting) values for third MCMC chain, to be used with the OpenBUGS / JAGS model code (ModelCode_HBD_SI.txt).
DOI: 10.5061/dryad.mp935/1
title: DataScriptsResults

description: This file contains the data and R scripts to: 1. fit vital rate models, 2. build population projection models, and 3. run stochastic simulations. The 'Results' directory also reports the results of vital rate models and simulations. Readme and metadata files are provided within the main, and 'Data' folders, respectively.
DOI: 10.5061/dryad.n5095/1
title: BMC Evolutionary Biology  EVOB-D-16-00044R3

description: Protein sequences, CDS nucleotide sequences and promoter sequences used in the analyses of the paper
DOI: 10.5061/dryad.nt0bd/1
title: bundle of scripts

description: These are the scripts, including the list of commands run, used in this paper.
DOI: 10.5061/dryad.p52kg/1
title: Data file for Dryad repository

description: Sheet 1 of the data file contains data describing plant growth rates. Column A identifies the individual plant. Column B show the light treatment (0=shade, 1=sun). Column C indicates ant treatment (0=ants present, 1-ants absent. Columns D through X are measurements of plant growth rate as an estimate of increased biomass over each 2 week period.
Sheet 2 of the data file contains data describing herbivory rates. Column A identifies the individual plant. Column B show the light treatment (0=shade, 1=sun). Column C indicates ant treatment (0=ants present, 1-ants absent. Columns D through X are measurements of plant herbivory rate as an estimate of % leaf area removal.
Sheet 3 of the data file contains data describing plant size. Column A identifies the individual plant. Column B show the light treatment (0=shade, 1=sun). Column C indicates ant treatment (0=ants present, 1-ants absent. Columns D through AB are measurements of plant size, taken as the total number of growing stems.
Sheet 4 of the data file contains data describing extrafloral nectar production. Column A identifies the individual plant. Column B show the light treatment (0=shade, 1=sun). Column C indicates ant treatment (0=ants present, 1-ants absent. Columns D through I are bi-monthly measurements of extrafloral nectar production, expressed as total sugar production from 5 leaves on each plant. 
Sheet 5 of the data file contains data from insect surveys conducted throughout the year long study. Column A shows the date that surveys were conducted. Column B identifies the individual plant. Column C shows the light treatment (0=shade, 1=sun). Column D indicates ant treatment (0=ants present, 1-ants absent. Column E indicates whether the survey was conducted during the day or at night (0=day, 1=night). Columns F through AY are different insects and they presence and abundance are indicated for each survey.
Sheet 6 of the data file contains data describing plant reproductive fitness. Column A shows the date that data were collected. Column B identifies the individual plant. Column C shows the light treatment (0=shade, 1=sun). Column D indicates ant treatment (0=ants present, 1-ants absent. Columns E, F, G, and H indicate numbers of flowers, fruit set, mature fruit, and seeds respectively.
DOI: 10.5061/dryad.r08vm/1
title: Python code for Markov chain model

description: Python code used to compute exact stationary probability distribution of genotypic states.
DOI: 10.5061/dryad.r08vm/2
title: Python code for simulator of gametic phase disequilibrium

description: Python code used to simulate gametic phase disequilibrium between two independent loci for different levels of clonality.
DOI: 10.5061/dryad.r08vm/3
title: Single locus analysis

description: Datasets obtained from the single locus markov chain model + R scripts for producing the figures presented within the article.
DOI: 10.5061/dryad.r08vm/4
title: Two loci analysis

description: Datasets obtained from the simulator of gametic phase disequilibrium between two loci + R script for producing the figures presented in the paper
DOI: 10.5061/dryad.sv71c/10
title: Supplementary Table 3. Regression statistics for the SDD analyses of early Pliensbachian ammonites of the western Tethys and adjacent areas without null-similarity values and endemic species

description: Regression statistics for the SDD analyses of early Pliensbachian ammonites of the western Tethys and adjacent areas without null-similarity values and endemic species. At the locality/species and cluster/species levels, only assemblages with at least, respectively 4 species and 7 species were retained in the analyses. Abbreviations: n, number of taxa; N, number of sites; r2, coefficient of determination associated to the linear regressions; p, p-value associated to the linear regressions calculated using 10.000 randomizations; pM, p-value estimating the linear association between D and ln(S) calculated with a Mantel permutation test.
DOI: 10.5061/dryad.sv71c/12
title: Supplementary Table 1. Palaeocoordinates of the 100 studied fossil localities, together with the palaeogeographic distances separating them and the clusters of fossil localities

description: Palaeocoordinates of the 100 studied fossil localities, together with the palaeogeographic distances separating them and the clusters of fossil localities. Four localities were removed compared to the initial dataset of Dommergues et al. (2009), due to their poorly constrained palaeolocations: Ag-CHEL, Bu-KOTE, Gl-JAME and It-TAOR.
DOI: 10.5061/dryad.sv71c/6
title: Supplementary Fig. 6. SDD calculated at the cluster/species level for the NWE province and the MED province for each chronozone of the early Pliensbachian, after grouping the species according to the relative whorl height of their shell

description: Similarity distance decay calculated at the cluster/species level for the NWE province (A-F) and the MED province (G-L) for each chronozone of the early Pliensbachian, after grouping the species according to the relative whorl height of their shell (H / D, H = last-whorl height, D = shell diameter), in order to determine whether a relationship between shell shape and long-distance dispersal exists. For each province, the lower graphs represent the most evolute species and the upper graphs the most involute ones. Only clusters with at least 3 species are considered in these analyses. The black lines are the Ordinary Least-Square linear regressions and the SDD rates are the values of their slopes.
DOI: 10.5061/dryad.sv71c/7
title: Supplementary Fig. 7. Morphospaces of early Pliensbachian ammonite species

description: Morphospaces of early Pliensbachian ammonite species. They correspond to principal component analyses based on the variance-covariance matrices of classical shell parameters (relative height (H / D), relative width (W / D), and relative umbilical diameter (U / D; see Brosse et al. 2013). The convex hulls delimitate species characterizing the NWE province (blue) and the MED province (orange). The MANOVA performed on the PCA scores for each morphospace indicates that there is no significant difference in the shell shape between NWE and MED species.
DOI: 10.5061/dryad.sv71c/9
title: Supplementary Table 2. Results of Mantel permutation tests between the Sørensen and Simpson dissimilarity matrices and between the Sørensen and nestedness-resultant component matrices

description: Results of Mantel permutation tests (Mantel 1967; Manly 2007) between the Sørensen and Simpson dissimilarity matrices (upper table) and between the Sørensen and nestedness-resultant component matrices (lower table). All matrices were computed using the package betapart (Baselga and Orme 2012) in R v.3.0.2. (R Development Core Team, 2010). Only localities with at least 4 species, and clusters with at least 7 species and 3 clades were retained in the analyses. Abbreviations:  n, number of taxa; N, number of sites; r, correlation coefficient associated to the Mantel tests; p, p-value associated to the Mantel tests calculated using 1000 permutations.
DOI: 10.5061/dryad.v1jr7/1
title: WORLD

description: Phytophthora cinnamomi records used in model (ex-Australia)
DOI: 10.5061/dryad.v1jr7/2
title: QLD

description: Phytophthora cinnamomi records used in model from Queensland, Australia
DOI: 10.5061/dryad.v9p27/4
title: validation_constant_19C

description: Target and actual temperatures logged for a 19 degrees Celsius constant-temperature validation scheme. We logged actual chamber temperatures every minute for 30 days.
DOI: 10.5061/dryad.v9p27/5
title: validation_constant_22C

description: Target and actual temperatures logged for a 22 degrees Celsius constant-temperature validation scheme. We logged actual chamber temperatures every minute for 30 days.
DOI: 10.5061/dryad.v9p27/6
title: validation_constant_25C

description: Target and actual temperatures logged for a 25 degrees Celsius constant-temperature validation scheme. We logged actual chamber temperatures every minute for 30 days.
DOI: 10.5061/dryad.v9p27/7
title: validation_ectotherm_regime

description: Target and actual temperatures logged for a fluctuating-temperature validation scheme based on the body temperature regime of a small ectotherm. We logged actual chamber temperatures every minute for 7 days.
DOI: 10.5061/dryad.v9p27/8
title: validation_sinewave

description: Target and actual temperatures logged for a sine-wave temperature validation scheme fluctuating between 10-25C over 24 hours. We logged actual chamber temperatures every minute for 30 days.
DOI: 10.17632/pwrf48zvfx.1
title: A state-of the-art survey & testbed of Fuzzy AHP (FAHP) applications -- Tetbed

description: In this state-of-the-art survey of Fuzzy AHP, we reviewed 192 application papers (scientific journals only) and classified them on the basis of the area of application, the identified theme, the year of publication, and so forth. Since 21% of the reviewed papers (41 out of 192) come from “Expert Systems with Applications”, we think it is judicious to submit this survey in this journal. We also believe that one of the key originalities of the proposed state-of-the-art survey (unlike previous literature surveys) lies in the fact that all results are made available online at the following URL: http://fahptestbed.sntiotlab.lu/