cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/9dcb8jmbts.1
title: Dataset: Daily Air Quality Index and Pollutant Concentrations for Mumbai, India

description: This dataset provides daily air quality measurements and Air Quality Index values for Mumbai, India, derived from multiple Maharashtra Pollution Control Board monitoring stations. The data spans from June 2019 to January 2026 and represents long term urban air quality conditions across different regions of the city.

The dataset is organized into station level files and aggregated outputs. Individual station files contain daily pollutant concentrations and AQI values computed independently for each monitoring location, including Kurla, Bandra, Bandra Kurla Complex, Sion, and Chhatrapati Shivaji International Airport. These stations capture spatial variability in air pollution across residential, commercial, industrial, and traffic influenced zones of Mumbai.

Hourly air quality measurements were sourced from the OpenAQ platform and aggregated to daily values. PM2.5, PM10, NO2, and SO2 concentrations are calculated as daily means from hourly data. CO and O3 concentrations are calculated as the daily maximum of rolling 8 hour averages, following the Central Pollution Control Board methodology. Daily AQI is computed using CPCB breakpoint tables, where the final AQI for each day is defined as the maximum sub index among available pollutants, and the dominant pollutant is recorded.

The files included are:
- Station specific daily AQI datasets for five MPCB monitoring locations in Mumbai
- A combined stations dataset with all station observations stacked by date and station
- A city averaged daily dataset representing mean air quality across Mumbai

Missing values indicate days or pollutants not reported by a station. The temporal coverage varies by station due to differences in commissioning dates, maintenance outages, and data availability. The dataset preserves these gaps to maintain transparency and support rigorous data quality handling.

This dataset is suitable for long term air quality trend analysis, spatial variability studies, exposure assessment, policy evaluation, and machine learning applications related to air pollution forecasting in Mumbai.
DOI: 10.5061/dryad.m0cfxpp7h
title: Widespread reticulate evolution in an adaptive radiation

description: A fundamental assumption of evolutionary biology is that phylogeny follows
 a bifurcating process. However, hybrid speciation and introgression are
 becoming more widely documented in many groups. Hybrid inference studies
 have been historically limited to small sets of taxa, while exploration of
 the prevalence and trends of reticulation at deep time scales remains
 unexplored. We study the evolutionary history of an adaptive radiation of
 109 gemsnakes in Madagascar (Pseudoxyrhophiinae) to identify potential
 instances of introgression. Using several network inference methods, we
 find twelve reticulation events within the 22-million-year evolutionary
 history of gemsnakes, producing 28% of the diversity for the group,
 including one reticulation that resulted in the diversification of an 18
 species radiation. These reticulations occur at nodes with high gene tree
 discordance. Hybridization events occurred between north-south distributed
 parentals that share similar ecologies. Younger hybrids occupy
 intermediate contact zones between the parentals, showing that
 post-speciation dispersal in this group has not eroded the spatial
 signatures of introgression. Reticulations accumulated consistently over
 time, despite drops in overall speciation rates during the Pleistocene.
 This suggests that while bifurcating speciation may decline as the result
 of species accumulation and environmental change, speciation by
 hybridization may be more robust to these processes.
DOI: 10.17632/w62gr5drs7
title: AutoBivClaims_518

description: Each dataset contains a random bivariate sample of property damage (resulting from third party liability) and of all bodily injury claims settled within a one-year period (n=518 and n=767).
DOI: 10.17632/w62gr5drs7.1
title: AutoBivClaims_518

description: Each dataset contains a random bivariate sample of property damage (resulting from third party liability) and of all bodily injury claims settled within a one-year period (n=518 and n=767).
DOI: 10.17632/y6p778djzj
title: Dataset: Daily Air Quality Index and Pollutant Concentrations for Pune, India

description: This dataset contains daily air quality measurements and Air Quality Index values for Pune, India, compiled from multiple Maharashtra Pollution Control Board monitoring stations across the city. The data spans from June 2019 to January 2026 and reflects long term air quality conditions across residential, educational, traffic influenced, and peri urban areas of Pune.

The dataset includes station level daily records from five monitoring locations: Revenue Colony Shivajinagar, Savitribai Phule Pune University, Karve Road, Katraj Dairy, and Park Street Wakad Pimpri Chinchwad. Each station captures local air pollution characteristics influenced by land use, traffic density, and surrounding activities, allowing spatial comparison within the city.

Hourly air quality measurements were obtained from the OpenAQ platform and aggregated to daily values. PM2.5, PM10, NO2, and SO2 concentrations are calculated as daily means from hourly observations. CO and O3 concentrations are calculated as the daily maximum of rolling 8 hour averages, following the Indian National Air Quality Index methodology defined by the Central Pollution Control Board. Daily AQI values are computed using CPCB pollutant breakpoint tables, where the final AQI for each day is defined as the maximum sub index among available pollutants, and the dominant pollutant is reported.

In addition to station specific datasets, the collection includes a combined stations file that aggregates all station level daily observations into a single table for cross station analysis. A city averaged dataset is also provided, representing the daily mean pollutant concentrations and AQI across all available stations in Pune for each date. 

The dataset preserves missing values to reflect periods when a pollutant or station did not report data. Temporal coverage varies by station due to differences in installation dates, maintenance interruptions, and data availability. No gap filling or interpolation has been applied.

This dataset is suitable for air quality trend analysis, spatial variability studies, public health exposure assessment, policy evaluation, and machine learning applications related to air pollution forecasting and urban environmental analysis in Pune.
DOI: 10.5061/dryad.mgqnk993k
title: Incorporating pressure-volume traits into the leaf economics spectrum

description: Dataset associated with the article 'Incorporating pressure-volume
 traits into the leaf economics spectrum' (Nadal et al. 2023 [Eco
 Lett, accepted]). We provide theoretical and empirical evidence for the
 coordination of the turgor loss point and associated pressure-volume
 traits (osmotic potential at full turgor, leaf capacitance, leaf
 elasticity, leaf saturated water content, modulus of elasticity) with
 photosynthesis (light-saturated net CO2 assimilation) and leaf mass per
 area (LMA) and its two components (leaf thickness and density). The
 complete dataset comprehends a total of 45 data entries from 37 species,
 including ferns and angiosperms (woody and herbaceous species), most of
 them measured on the campus of University of the Balearic Islands; this
 complements the data presented in Nadal et al. (2018 [Eco Lett 21 (9),
 1372-1379]). For the 20 species from Nadal et al. (2018), we also provide
 data regarding their N and C content, leaf anatomy (from optical and TEM
 images) and cell wall composition.
description: See article '<em>Incorporating pressure-volume traits
 into the leaf economics spectrum</em>' (Nadal et al. 2023
 [<em>Eco Lett</em>, accepted])
description: Data files are presented in .csv format
DOI: 10.17632/y6p778djzj.1
title: Dataset: Daily Air Quality Index and Pollutant Concentrations for Pune, India

description: This dataset contains daily air quality measurements and Air Quality Index values for Pune, India, compiled from multiple Maharashtra Pollution Control Board monitoring stations across the city. The data spans from June 2019 to January 2026 and reflects long term air quality conditions across residential, educational, traffic influenced, and peri urban areas of Pune.

The dataset includes station level daily records from five monitoring locations: Revenue Colony Shivajinagar, Savitribai Phule Pune University, Karve Road, Katraj Dairy, and Park Street Wakad Pimpri Chinchwad. Each station captures local air pollution characteristics influenced by land use, traffic density, and surrounding activities, allowing spatial comparison within the city.

Hourly air quality measurements were obtained from the OpenAQ platform and aggregated to daily values. PM2.5, PM10, NO2, and SO2 concentrations are calculated as daily means from hourly observations. CO and O3 concentrations are calculated as the daily maximum of rolling 8 hour averages, following the Indian National Air Quality Index methodology defined by the Central Pollution Control Board. Daily AQI values are computed using CPCB pollutant breakpoint tables, where the final AQI for each day is defined as the maximum sub index among available pollutants, and the dominant pollutant is reported.

In addition to station specific datasets, the collection includes a combined stations file that aggregates all station level daily observations into a single table for cross station analysis. A city averaged dataset is also provided, representing the daily mean pollutant concentrations and AQI across all available stations in Pune for each date. 

The dataset preserves missing values to reflect periods when a pollutant or station did not report data. Temporal coverage varies by station due to differences in installation dates, maintenance interruptions, and data availability. No gap filling or interpolation has been applied.

This dataset is suitable for air quality trend analysis, spatial variability studies, public health exposure assessment, policy evaluation, and machine learning applications related to air pollution forecasting and urban environmental analysis in Pune.
DOI: 10.17632/pgwffkvkjw
title: Early Monitoring Dataset for Pine Wilt Disease (PWD)

description: This dataset contains close-range, time-series hyperspectral data, disease progression data, and high-definition RGB photographs acquired following the artificial inoculation of pine trees with the pine wood nematode. This study primarily utilized these data to conduct early dynamic monitoring of Pine Wilt Disease (PWD), to elucidate the dynamic patterns of its early development, and to determine the optimal timing for early detection.The dataset is composed of two main parts: code and data. The code section includes scripts for time-series sensitivity analysis, Mann-Kendall (M-K) trend and change-point detection, time-series analysis based on chromaticity indicators, and time-series correlation analysis between disease progression and typical spectral indicators. The data section primarily includes: the basic sample data used to calculate the Average Time-series Sensitivity Index (ATSI); the basic sample data for the M-K trend and change-point tests; on-site high-definition RGB photographs and their corresponding HSV space standard data; and the measured data of PWD infection progression.
DOI: 10.15468/dl.ezh5b6
title: Occurrence Download

description: A dataset containing 1774 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Fraxinus chinensis"
 ]
}

 The dataset includes 1774 records from 29 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003468-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5061/dryad.q83bk3jnd
title: Data from: Rtapas: An R package to assess cophylogenetic signal between two evolutionary histories

description: Cophylogeny represents a framework to understand how ecological and
 evolutionary process influence lineage diversification. The recently
 developed algorithm Random Tanglegram Partitions provides a directly
 interpretable statistic to quantify the strength of cophylogenetic signal
 and incorporates phylogenetic uncertainty into its estimation, and maps
 onto a tanglegram the contribution to cophylogenetic signal of individual
 host-symbiont associations. We introduce Rtapas, an R package to perform
 Random Tanglegram Partitions. Rtapas applies a given global-fit method to
 random partial tanglegrams of a fixed size to identify the associations,
 terminals, and internal nodes that maximize phylogenetic congruence. This
 new package extends the original implementation with a new algorithm that
 examines the contribution to phylogenetic incongruence of each
 host-symbiont association and adds ParaFit, a method designed to test for
 topological congruence between two phylogenies, to the list of global-fit
 methods than can be applied. Rtapas facilitates and speeds up
 cophylogenetic analysis, as it can handle large phylogenies (100+
 terminals) in affordable computational time as illustrated with two
 real-world examples. Rtapas can particularly cater for the need for causal
 inference in cophylogeny in two domains: (i) Analysis of complex and
 intricate host-symbiont evolutionary histories and (ii) assessment of
 topological (in)congruence between phylogenies produced with different DNA
 markers and specifically identify subsets of loci for phylogenetic
 analysis that are most likely to reflect gene-tree evolutionary histories.
description: <strong>Supplementary Figures
 and Tables</strong> SuppMat.pdf <strong>Amphipod_trematode_example</strong> Phylogenetic trees, association matrix and R script to perform the amphipod-trematode example Amph_Trem.zip <strong>Nuclear_organellar_example</strong> Phylogenetic trees and R script to carry out the nuclear-organellar example in Orchids Nucl_Plast.zip <strong>Mamals_Fleas_example</strong> Phylogenetic trees, association matrix and R script to carry out the mammals-fleas example  Mam_Fleas.zip
DOI: 10.17632/pgwffkvkjw.1
title: Early Monitoring Dataset for Pine Wilt Disease (PWD)

description: This dataset contains close-range, time-series hyperspectral data, disease progression data, and high-definition RGB photographs acquired following the artificial inoculation of pine trees with the pine wood nematode. This study primarily utilized these data to conduct early dynamic monitoring of Pine Wilt Disease (PWD), to elucidate the dynamic patterns of its early development, and to determine the optimal timing for early detection.The dataset is composed of two main parts: code and data. The code section includes scripts for time-series sensitivity analysis, Mann-Kendall (M-K) trend and change-point detection, time-series analysis based on chromaticity indicators, and time-series correlation analysis between disease progression and typical spectral indicators. The data section primarily includes: the basic sample data used to calculate the Average Time-series Sensitivity Index (ATSI); the basic sample data for the M-K trend and change-point tests; on-site high-definition RGB photographs and their corresponding HSV space standard data; and the measured data of PWD infection progression.
DOI: 10.17632/xyrnmsmw5d
title: Argo floats on the Breid Bay, East Antarctica

description: Argo float data (ID 7900893) were used to provide vertical profiles of temperature and salinity along the float trajectory.
DOI: 10.17632/xyrnmsmw5d.2
title: Argo floats on the Breid Bay, East Antarctica

description: Argo float data (ID 7900893) were used to provide vertical profiles of temperature and salinity along the float trajectory.
DOI: 10.5061/dryad.4tmpg4ffj
title: Data from: Modelling harvest of Greenland barnacle geese and its implications in mitigating human-wildlife conflict

description: Arctic-breeding goose populations have increased in recent decades and
 their expansion into agricultural areas has caused increasing conflict
 with farmers due to the damage they cause. Lethal control and scaring are
 common management strategies of conflict mitigation. Management typically
 focuses on local/national scales, making addressing the impact of
 localised control on the wider population challenging, particularly when
 populations move over large areas and cross international borders. We
 construct an integrated population model (IPM) to assess the cumulative
 impact of all shooting harvest (hunting and derogation shooting) on the
 Greenland barnacle goose, Branta leucopsis. We use data from monitoring
 schemes throughout the migratory flyway and use population projections to
 evaluate the impact of potential future shooting strategies on abundance.
 Our model suggests flyway abundance has declined since its 2012 peak,
 consistent with an increase in harvest rate and low productivity. Harvest
 rate increase was most pronounced on Islay (rising from 2% to 7% from 2011
 to 2017), suggesting this was a probable cause of flyway abundance
 decline.  Islay abundance has declined since derogation shooting
 began in 2000, whilst abundance at other wintering sites has increased.
 This may indicate that declines in Islay abundance may be due to both
 shooting mortality and emigration from Islay. Should future flyway-level
 harvest rates increase, further declines in abundance could be expected,
 and are likely to be more pronounced if harvests are extended to the
 entire winter range. Conversely, should harvest rates decline, an increase
 in abundance is predicted. Projections can therefore be used to allocate
 flyway-level harvest rates to alleviate local pressure without hindering
 flyway-level management objectives. Synthesis and applications. Our
 findings demonstrate the impact of local harvests on global abundance,
 emphasising the importance of internationally coordinated monitoring and
 management strategies of migratory species. IPMs provide a framework for
 adaptation to incorporate additional data when they become available and
 enable comparisons of future harvest scenarios to inform management
 strategies throughout the flyway.
DOI: 10.17632/2nt5tjbybm
title: Reflections on Synergetics

description: Fuller believes human inventiveness and design science can support life utilizing natural rules as population grows. This research emphasises system interconnectedness, design cooperation, and social dynamics. Fuller's ideas have influenced creative problem-solving and design across industries.
DOI: 10.17632/2nt5tjbybm.2
title: Reflections on Synergetics

description: Fuller believes human inventiveness and design science can support life utilizing natural rules as population grows. This research emphasises system interconnectedness, design cooperation, and social dynamics. Fuller's ideas have influenced creative problem-solving and design across industries.
DOI: 10.5061/dryad.vhhmgqnz5
title: On the fast track: Hybrids adapt more rapidly than parental populations in a novel environment

description: Rates of hybridization are predicted to increase due to climate change and
 human activity that cause redistribution of species and bring previously
 isolated populations into contact. At the same time, climate change leads
 to rapid changes in the environment, requiring populations to adapt
 rapidly in order to survive. A few empirical cases suggest hybridization
 can facilitate adaptation despite its potential for incompatibilities and
 deleterious fitness consequences. Here we use simulations and Fisher’s
 Geometric model to evaluate the conditions and time frame of adaptation
 via hybridization in both diploids and haplodiploids. We find that hybrids
 adapt faster to new environments compared to parental populations in
 nearly all simulated scenarios, generating a fitness advantage that can
 offset intrinsic incompatibilities and last for tens of generations,
 regardless of whether the population was diploid or haplodiploid. Our
 results highlight the creative role of hybridization and suggest that
 hybridization may help contemporary populations adapt to the changing
 climate. However, adaptation by hybrids may well happen at the cost of
 reduced biodiversity, if previously isolated lineages collapse into one.
description: This dataset contains a collection of SLiM 3.6 (Haller & Messer, 2019) simulation scripts
 used for the paper "Kulmuni, Wiley, Otto. 2023. On the fast track:
 hybrids adapt more rapidly than parental populations in a novel
 environment".
description: SLiM 3.6 (Haller & Messer,
 2019)
DOI: 10.17632/8bgv7k3rms
title: Date 2
DOI: 10.17632/8bgv7k3rms.1
title: Date 2
DOI: 10.25338/b8rp9m
title: Cross-sectional study of the effects of disability on the mismatch of desires versus choices for transportation modes and residential location

description: This data set contains the cleaned survey data, focus group
 transcriptions, and a readme file for this project. It is meant to further
 understanding of the extent to which disability may affect the choices and
 desires that adults in California have for transportation mode usage
 frequencies, activity frequencies, and neighborhood features. PII has
 generally been redacted.
description: The focus group was conducted through videoconferencing online on
 2021 November 9 for 1.5 hours with 19 simultaneous participants. Another
 participant in the same week responded to the same questions by email.
 Apart from redactions of PII, the focus group has been fully
 transcribed. The survey was hosted on and disseminated
 through Qualtrics from 2022 April through July. Rows were removed if they
 corresponded to ineligible participants, nonsensical responses, or
 logically inconsistent responses. Columns corresponding to questions that
 could provide PII have been redacted.
description: The survey data is a CSV file. All other files are TXT files. All
 can be opened using free software text editors at the very
 least.
DOI: 10.5061/dryad.d7wm37q53
title: Biases and distribution patterns in hard-bodied microscopic animals (Acari: Halacaridae): Size doesn’t matter, but generalism and sampling effort do

description: Aim The interplay between distribution ranges, species traits, and
 sampling and taxonomic biases remain elusive amongst microscopic animals.
 This ignorance obscures our understanding of the diversity patterns of a
 major component of biodiversity. Here, we used marine Halacaridae to
 explore whether differences between marine provinces can explain their
 distribution patterns or if differential sampling efforts across regions
 prevent any macroecological inference. Furthermore, we test if certain
 functional traits influence their distribution patterns. Location Europe.
 Results Whereas geographical variables provided a better explanation for
 differences in species composition, sampling effort and distance from
 marine biological stations accounted for the majority of differences in
 European Halacaridae richness. Species occurring in more habitats showed
 broader geographical ranges and accumulated more records. Species traits
 like body size affected the distribution of halacarid species. Main
 conclusions We propose that the sampling effort of halacarid mites in
 Europe might be explained by two different cognitive biases: the
 convenience of selecting certain sampling localities compared to others,
 and the tendency of zoologists to scrutinize habitats where their target
 organisms are more common.
description: See README.md file. In re-using the data, please cite the
 original publication in Diversity and Distribution.