cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6086/d10x1r
title: Pre-dispersal seed predation obscures the detrimental effect of dust on wildflower reproduction - fruit data

description: Premise of the Research. Seed production by flowering plants depends on
 abiotic and biotic factors whose interacting effects may be hidden. We
 previously reported that exposure to dust from unpaved roads reduced the
 average amount of pollen on flowers of Ipomopsis aggregata, but did not
 consistently reduce mean seed set per fruit. Here we explore one possible
 explanation—that the expected detrimental effect of lower pollen loads on
 seed production was obscured because dust reduces not only pollination
 success but also attack by a pre-dispersal seed predator. Methodology.
 Over three consecutive summers we scored the fates of over 4,000 flowers,
 comparing those on hand-dusted I. aggregata plants to those on clean
 control plants in the same natural populations. We censused plants
 throughout each flowering season, marking phenological cohorts of flowers
 and examining them for eggs of the Anthomyiid fly Hylemya sp. We
 subsequently scored expanded fruits for seed loss to Hylemya larvae.
 Pivotal Results. Control plants consistently had higher egg loads and
 rates of seed loss to larvae than dusty plants. Furthermore, most eggs
 appeared early in the season when flowers are most likely to set fruit and
 ovule numbers are highest. In agreement with earlier studies,
 unparasitized fruits from dusty plants did not contain fewer seeds than
 fruits from control plants. But when we simulated a system without Hylemya
 by assigning each parasitized fruit the average number of seeds for
 unparasitized flowers in the same phenological cohort, control plants
 out-produced dusty plants. Conclusions. Pre-dispersal seed predation
 likely contributed to the previous lack of a negative effect of dust on
 seed set in I. aggregata. This study illustrates how exploring unexpected
 experimental outcomes can reveal important ecological interactions, and
 how the mechanistic understanding so gained can improve the ability to
 generalize results to other systems.
description: During the summers of 2016, 2017, and 2018, pairs of bolting
 <em>Ipomopsis aggregata</em> plants in a natural population
 near the Rocky Mountain Biological Laboratory in West-Central Colorado,
 USA, were matched by proximity and size and randomly assigned to receive a
 hand-dusting or control treatment that was administered throughout the
 flowering period. Once flowering began, plants were censused every 4 days
 to record the number of elongated buds and flowers present and their
 Hylemya egg loads and to mark their calyces with a dot of paint with a
 census-specific color. A yellow dot was also placed on calyces of flowers
 with one or more <em>Hylemya</em> eggs. All
 fruits were collected when mature. The fate (aborted, expanded,
 parasitized) of each fruit was recorded, and the number of full-sized
 seeds counted.
description: Two files have been uploaded: DustStudyFruitDataREADME.docx - This file contains variable definitions 2016-2018DustStudyFruitData.txt - This text file contains the data. Missing values are coded with a period.
DOI: 10.5061/dryad.hqbzkh1ff
title: Data from: Whole-genome duplication and host genotype affect rhizosphere microbial communities

description: The composition of microbial communities found in association with plants
 is influenced by host phenotype and genotype. Yet, the ways in which
 specific genetic architectures of host plants shape microbiomes is
 unknown. Genome duplication events are common in the evolutionary history
 of plants, influence many important plant traits, and, thus, they may
 affect associated microbial communities. Using experimentally induced
 whole genome duplication (WGD), we tested the effect of WGD on rhizosphere
 bacterial communities in Arabidopsis thaliana. We performed 16S rRNA
 amplicon sequencing to characterize differences between microbiomes
 associated with specific host genetic backgrounds (Columbia vs. Landsberg)
 and ploidy levels (diploid vs. tetraploid). We modeled relative abundances
 of bacterial taxa using the Dirichlet and multinomial distributions via a
 hierarchical Bayesian approach. We found that host genetic background and
 ploidy level affected rhizosphere community composition. We then tested to
 what extent microbiomes derived from a specific genetic background or
 ploidy level affected plant performance by inoculating sterile seedlings
 with microbial communities harvested from a prior generation. We found a
 negative effect of the tetraploid Columbia microbiome on growth of all
 four plant genetic backgrounds. These findings suggest an interplay
 between host genetic architecture and bacterial community assembly with
 potential ramifications for host fitness. Moreover, we uncovered an
 intriguing role of ploidy-level for shaping plant microbiomes. Given the
 prevalence of ploidy-level variation in both wild and managed plant
 populations, the effects on microbiomes of this aspect of host genetic
 architecture could be a widespread driver of differences in plant
 microbiomes.
description: Raw phenotypic and amplicon data are not provided here. Raw
 amplicon data can be found using the short read archive identifier in the
 preprint text. Analysis was performed primarily using R
 version 3.5. Packages and functions may have been deprecated
 since.
DOI: 10.5061/dryad.6m905qfzp
title: Environmental correlates of taxonomic and phylogenetic diversity in the Atlantic Forest

description: Aim: There is little consensus on which environmental variables are best
 at predicting multiple dimensions of diversity. We ask whether there are
 common environmental correlates of diversity, despite ecological
 differences, across nine clades of plants and animals distributed along a
 single rainforest domain. For that, we the compare environmental
 correlates of species richness, phylogenetic diversity, and phylogenetic
 endemism. Location: Brazilian Atlantic Forest Taxon: Five clades of
 plants: one within the Bromelioideae subfamily, three in the family
 Melastomataceae (the Miconieae tribe, the genus Bertolonia, and the tribe
 Cambessedesieae), and one in the family Bignoniaceae ( Fridericia and
 allies). Four clades of animals: clearwing butterflies of the tribe
 Ithomiini, treefrogs of the genus Boana, horned frogs of the genus
 Proceratophrys, and birds in the subfamily Thraupinae. Methods: Using
 curated occurrence localities and phylogenetic data, we generated maps of
 (i) species richness, (ii) phylogenetic diversity, (iii) residuals of
 phylogenetic diversity regressed on species richness, and (iv)
 phylogenetic endemism for all groups. We also compiled a set of 30
 environmental descriptors including records of current temperature and
 precipitation, climatic stability over time, and topography. Through a
 machine learning framework, we explored the environmental correlates of
 each of these diversity measures for each group. Results:  The
 environmental variables used here were strong predictors of diversity for
 all studied groups. However, models for phylogenetic endemism had lower
 predictive power. Although patterns of diversity are different among
 groups, correlates of diversity are consistent across taxa. For both
 species richness and phylogenetic diversity, current precipitation and
 precipitation stability over time were consistently ranked among the
 variables that strongly correlate with diversity patterns. The correlates
 of phylogenetic endemism were less homogenous across groups. The results
 also suggest that including climate stability over time is important when
 predicting diversity measures that reflect historical components. Main
 conclusions: Investigating environmental correlates of diversity for
 multiple clades and diversity measures in a single geographic area allows
 for a better understanding of common patterns across taxa. In this study,
 we identified common environmental correlates of the patterns of species
 richness and phylogenetic diversity, but not of phylogenetic endemism,
 across different Atlantic Forest groups.
DOI: 10.5061/dryad.sbcc2fr5t
title: Code for: A metapopulation model of social group dynamics and disease applied to Yellowstone wolves

description: Abstract The population structure of social species has important
 consequences for both their demography and transmission of their
 pathogens. We develop a new form of metapopulation model that tracks two
 key components of a species’ social system: average group size and number
 of groups within a population. While the model is general, we parameterize
 it to mimic the dynamics of the Yellowstone wolf population and two
 associated pathogens: sarcoptic mange and canine distemper. In the initial
 absence of disease, we show that group size is mainly determined by the
 birth, death rates, and the rates at which groups fission to form new
 groups. The total number of groups is determined by rates of fission and
 fusion, as well as upon environmental resources and rates of intergroup
 aggression. Incorporating pathogens into the models reduces the size of
 the host population, predominantly by reducing the number of social
 groups. Average group size responds in more subtle ways: infected groups
 decrease in size, but uninfected groups may increase when disease reduces
 the number of groups and thereby reduces intraspecific aggression. Our
 modeling approach allows for easy calculation of prevalence at multiple
 scales (within group, across groups, and population level), illustrating
 that aggregate population-level prevalence can be misleading for
 group-living species. The model structure is general, can be applied to
 other social species, and allows for a dynamic assessment of how pathogens
 can affect social structure and vice versa.   Significance How do
 social and infectious disease dynamics interact in group-living mammals? A
 significant cost to group living is increased transmission of pathogens.
 When a pathogen invades a group, members will be more vulnerable to
 mortality, Allee effects, and ultimately group extinction. The presence of
 a pathogen reduces the size of the population by reducing the number of
 social groups, allowing uninfected groups to grow larger from a reduction
 in inter-group aggression. Concomitantly, Allee effects are exacerbated in
 infected groups; this reduces the probability of pathogen persistence as
 infected groups die out more rapidly. Social structuring changes
 prevalence across scales and influences pathogen invasion and persistence.
 The models described here provide a new framework for understanding the
 dynamics of these interactions.   About Here is the R code
 associated with the paper Brandell et al.
 2021. A metapopulation model of social group dynamics
 and disease applied to Yellowstone wolves. Proceedings of the National
 Academy of Sciences. We provide code for the basic metapopulation models
 (central_allee.R) and the disease models: susceptible-infected-susceptible
 (SIS_model.R) and susceptible-infected-recovered (SIR_model.R).
 We have also included the parameters used (parameters.R) and the wolf
 count data used in Figure 1 of the main text (wolf_counts.csv).
DOI: 10.5061/dryad.pk0p2ngmq
title: Ancient plant DNA reveals High Arctic greening during the Last Interglacial

description: Summer warming is driving a greening trend across the Arctic, with the
 potential for large-scale amplification of climate change due to
 vegetation-related feedbacks (Pearson et al., 2013). Because observational
 records are sparse and temporally limited, past episodes of Arctic warming
 can help elucidate the magnitude of vegetation response to temperature
 change. The Last Interglacial (LIG; 129,000–116,000 years ago) was the
 most recent episode of Arctic warming on par with predicted 21st century
 temperature change (Otto-Bliesner et al., 2013; Post et al., 2019).
 However, high-latitude terrestrial records from this period are rare, so
 LIG vegetation distributions are incompletely known. Pollen-based
 vegetation reconstructions can be biased by long-distance pollen
 transport, further obscuring the paleoenvironmental record. Here, we
 present the first LIG vegetation record based on ancient DNA in lake
 sediment and compare it with fossil pollen. Comprehensive plant community
 reconstructions through the last and current interglacial (the Holocene)
 on Baffin Island, Arctic Canada, reveal coherent climate-driven community
 shifts across both interglacials. Peak LIG warmth featured a ~400-km
 northward range shift of dwarf birch, a key woody shrub that is again
 expanding northward. Greening of the High Arctic—documented here by
 multiple proxies—likely represented a strong positive feedback on
 high-latitude LIG warming. Authenticated ancient DNA from this lake
 sediment also extends the useful preservation window for the technique and
 highlights the utility of combining traditional and molecular approaches
 for gleaning paleoenvironmental insights to better anticipate a warmer
 future.
description: We extracted and analyzed sedimentary ancient DNA (sedaDNA) from
 a lake sediment core from Baffin Island, Arctic Canada, that spans the
 Holocene and Last Interglacial. We primarily used a metabarcoding
 approach, targeting the P6 loop of the chloroplast trnL (UAA) intron to
 identify vascular plant DNA through time. For select samples, we also
 prepared and sequenced single-stranded shotgun libraries. See
 "Materials and Methods" section of the publication for
 methodological details. 
description: The metabarcoding summary table,
 "CrumpEtAl2021_MetabarcodingSummaryTable.csv", includes
 post-filtered taxonomic results based on the metabarcoding methods
 outlined in the publication. The zipped .fastq files are demultiplexed
 (one file per sample) sequences with primers and adapters removed, but no
 further processing steps performed. See
 "README_CrumpEtAl2021_DNAmetabarcodingDataset.txt" and
 "README_CrumpEtAl2021_ShotgunDataset.txt" for additional usage
 notes.
DOI: 10.5281/zenodo.11496867
title: Historical Reconstruction Dataset of Hourly Expected On-Shore Wind Generation in Japan

description: Description

This is a historical reconstruction dataset of hourly expected wind generation based on dynamically downscaled atmospheric reanalysis for assessing the spatio-temporal impact of on-shore wind in Japan.

The dataset consists of a set of netCDF files with yearly archives of reconstruction results from 1958 to 2012; hourly expected on-shore wind power potential in Japan with a spatial resolution of approximately 5 km mesh has been reconstructed from the numerical weather model reanalysis results. The expected per-unit output values at each location were calibrated using a nonparametric machine learning model that learns statistical relationships between spatial/meteorological features of target locations and actual wind farm outputs.

A convenient way to handle this dataset would be to use a tool for manipulating netCDF files, such as CDO: Climate Data Operators.

Associated Publication



Yu Fujimoto, Masamichi Ohba, Yujiro Tanno, Daisuke Nohara, Yuki Kanno, Akihisa Kaneko, Yasuhiro Hayashi, Yuki Itoda, and Wataru Wayama, "Historical Reconstruction Dataset of Hourly Expected Wind Generation Based on Dynamically Downscaled Atmospheric Reanalysis for Assessing Spatio-Temporal Impact of On-Shore Wind in Japan", Big Earth Data, doi: 10.1080/20964471.2024.2374044 


Version history



Ver. 1.0: Released.

Ver. 1.1: The preprocessing of the source information used for dataset preparation has changed.

Ver. 1.2: The hyperparameter tuning scheme for the post-processing model has changed.
description: The reanalysis data used to generate this reconstruction dataset were provided by the Japan Meteorological Agency.



Kayaba, N. et al. (2016): Dynamical Regional Downscaling Using the JRA-55 Reanalysis (DSJRA-55). SOLA, 12, 1-5. http://doi.org/10.2151/sola.2016-001.
DOI: 10.5281/zenodo.8210141
title: Historical Reconstruction Dataset of Hourly Expected On-Shore Wind Generation in Japan

description: Description

This is a historical reconstruction dataset of hourly expected wind generation based on dynamically downscaled atmospheric reanalysis for assessing the spatio-temporal impact of on-shore wind in Japan.

The dataset consists of a set of netCDF files with yearly archives of reconstruction results from 1958 to 2012; hourly expected on-shore wind power potential in Japan with a spatial resolution of approximately 5 km mesh has been reconstructed from the numerical weather model reanalysis results. The expected per-unit output values at each location were calibrated using a nonparametric machine learning model that learns statistical relationships between spatial/meteorological features of target locations and actual wind farm outputs.

A convenient way to handle this dataset would be to use a tool for manipulating netCDF files, such as CDO: Climate Data Operators.

Associated Publication



Yu Fujimoto, Masamichi Ohba, Yujiro Tanno, Daisuke Nohara, Yuki Kanno, Akihisa Kaneko, Yasuhiro Hayashi, Yuki Itoda, and Wataru Wayama, "Historical Reconstruction Dataset of Hourly Expected Wind Generation Based on Dynamically Downscaled Atmospheric Reanalysis for Assessing Spatio-Temporal Impact of On-Shore Wind in Japan", Big Earth Data, doi: 10.1080/20964471.2024.2374044 


Version history



Ver. 1.0: Released.

Ver. 1.1: The preprocessing of the source information used for dataset preparation has changed.

Ver. 1.2: The hyperparameter tuning scheme for the post-processing model has changed.
description: The reanalysis data used to generate this reconstruction dataset were provided by the Japan Meteorological Agency.



Kayaba, N. et al. (2016): Dynamical Regional Downscaling Using the JRA-55 Reanalysis (DSJRA-55). SOLA, 12, 1-5. http://doi.org/10.2151/sola.2016-001.
DOI: 10.5061/dryad.tb2rbp000
title: An early dog from Southeast Alaska supports a coastal route for the first dog migration into the Americas

description: The oldest confirmed remains of domestic dogs in North America are from
 mid-continent archeological sites dated ~9,900 calibrated years before
 present (cal BP). Although this date suggests that dogs may not have
 arrived alongside the first Native Americans, the timing and routes for
 the entrance of New World dogs are unclear. Here, we present a complete
 mitochondrial genome of a dog from Southeast Alaska, dated to 10,150 ± 260
 cal BP. We compared this high-coverage genome with data from modern dog
 breeds, historical Arctic dogs, and American precontact dogs (PCDs) from
 before European arrival. Our analyses demonstrate that the ancient dog
 shared a common ancestor with PCDs that lived ~14,500 years ago and
 diverged from Siberian dogs around 16,000 years ago, coinciding with the
 minimum suggested date for the opening of the North Pacific coastal (NPC)
 route along the Cordilleran Ice Sheet and genetic evidence for the initial
 peopling of the Americas. This ancient Southeast Alaskan dog occupies an
 early branching position within the PCD clade, indicating it represents a
 close relative of the earliest PCDs that were brought alongside people
 migrating from eastern Beringia southward along the NPC to the rest of the
 Americas. The stable isotope δ13C value of this early dog indicates a
 marine diet, different from the younger mid-continent PCDs’ terrestrial
 diet. Although PCDs were largely replaced by modern European dog breeds,
 our results indicate that their population decline started ~2,000 years
 BP, coinciding with the expansion of Inuit peoples, who are associated
 with traditional sled-dog culture. Our findings suggest that dogs formed
 part of the initial human habitation of the New World, and provide
 insights into their replacement by both Arctic and European lineages.
DOI: 10.5061/dryad.tqjq2bvxx
title: Weak spatial-genetic structure in a native invasive, the southern pine beetle (Dendroctonus frontalis), across the eastern United States

description: The southern pine beetle, Dendroctonus frontalis, is a native pest of pine
 trees that has recently expanded its range into the northeastern United
 States. Understanding its colonization, dispersal, and connectivity will
 be critical for mitigating negative economic and ecological impacts in the
 newly invaded areas. Characterization of spatial-genetic structure can
 contribute to this; however, previous studies have reached different
 conclusions about regional population genetic structure, with one study
 reporting a weak east-west pattern, and the most recent reporting absence
 of structure. Here we systematically assessed several explanations for the
 absence of spatial-genetic structure. To do this, we developed nine new
 microsatellite markers and combined them with an existing 24-locus data
 matrix for the same individuals. We then reanalyzed this full dataset
 alongside datasets in which certain loci were omitted with the goal of
 creating more favorable signal to noise ratios. We also partitioned the
 data based on the sex of D. frontalis individuals, and then employed a
 broad suite of genotypic clustering and isolation-by-distance (IBD)
 analyses. We found that neither inadequate information content in the
 molecular marker set, nor unfavorable signal-to-noise ratio, nor
 insensitivity of the analytical approaches could explain the absence of
 structure. Regardless of dataset composition, there was little evidence
 for clusters (i.e., distinct geo-genetic groups) or clines (i.e.,
 gradients of increasing allele frequency differences over larger
 geographic distances), with one exception: significant IBD was repeatedly
 detected using an individual-based measure of relatedness whenever
 datasets included males (but not for female-only datasets). This is
 strongly indicative of broad-scale female-biased dispersal, which has not
 previously been reported for D. frontalis, in part owing to logistical
 limitations of direct approaches (e.g., capture-mark-recapture). Weak
 spatial-genetic structure suggests long-distance connectivity and that
 gene flow is high, but additional research is needed to understand range
 expansion dynamics in this species using alternate approaches.
description: Multiplex polymerase chain reaction (PCR) amplifications were
 performed for sets of three loci, each with a different 5’ fluorescent
 label on the forward primer and mostly non-overlapping allele size ranges.
 Amplified fragments were run on an ABI 3730 sequencer (Life Technologies)
 with a Liz 500 ladder (Gel Company, San Francisco CA) at Yale University’s
 DNA Analysis Facility on Science Hill. Genotype scoring was performed
 using GENEIOUS v10.0.5 (Kearse et al. 2012).
description: See "Garrick_etal_2021_PeerJ_Dryad_metadata.txt"
DOI: 10.34740/kaggle/dsv/14645240
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.2hx6w9
title: Occurrence Download

description: A dataset containing 459 species occurrences available in GBIF matching the query:
{
 "and" : [
 "CoordinateUncertaintyInMeters 0.0-5000.0",
 "TaxonKey is Enydra fluctuans"
 ]
}

 The dataset includes 459 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002756-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.