cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5061/dryad.vhhmgqnqg
title: Habitat openness and edge avoidance predict saltmarsh sparrow abundance better than habitat area

description: The Saltmarsh Sparrow (Ammospiza caudacuta) is a tidal marsh bird facing
 rapid population decline throughout its range, largely caused by
 degradation and loss of breeding habitat. Thus there is a need to preserve
 tidal marshes in the northeastern United States, but to do so requires an
 understanding of the habitat features that support robust populations.
 Previous studies have shown Saltmarsh Sparrow abundance increases with
 marsh size, but in similar bird species, area sensitivity is more directly
 linked to edge avoidance. Whether additional landscape features affect the
 abundance of Saltmarsh Sparrows is unknown. We explored how the height of
 objects on the horizon, an index of habitat openness, affected abundance
 of Saltmarsh Sparrows. Our primary goal was to determine whether the angle
 to the highest point on the horizon (“angle to maximum horizon”) predicted
 abundance better than marsh area or distance to the marsh edge. We used
 N-mixture models to evaluate the combination of spatial factors that best
 predicted Saltmarsh Sparrow abundance while also accounting for
 survey-level variables that could influence detection probability. We
 found that the interaction between distance to edge and angle to maximum
 horizon best predicted abundance. Taller objects on the horizon were
 negatively correlated with bird abundance, and this effect was strongest
 within 50 m of the marsh edge. When we considered the predictive powers of
 patch area, distance to edge, and angle to maximum horizon individually,
 angle to maximum horizon was the best single predictor. We found the
 highest abundance of Saltmarsh Sparrows at point locations where the angle
 to maximum horizon was 0.0°, and at angles greater than 12° the predicted
 abundance fell below one bird per survey point. We propose that managers
 should prioritize marsh openness and experimentally test the effect of
 marsh edge manipulations when making conservation decisions for this
 rapidly declining species.
description: This dataset includes the abundance counts of Saltmarsh Sparrows
 and the site and survey covariates for all surveys included in the
 analysis
DOI: 10.6086/d1d965
title: Data from: Task partitioning in ants lacking discrete morphological worker subcastes

description: Task partitioning allows for efficient coordination of behavior in social
 insect colonies. Many task allocation studies focus on social insect
 species with discrete morphological worker subcastes, such as those
 possessing major and minor workers with strongly differentiated body
 plans. Much less is known about task partitioning among size-variable
 workers lacking discrete morphological subcastes. We investigated task
 fidelity and its correlation with worker size in Formica species with
 differing degrees of body size variation. During a mark-recapture study
 that focused on three worker tasks (honeydew collection, nest building,
 and protein foraging) across 2 days, 98.6% of 3570 recaptured workers
 exhibited task fidelity. In species with high levels of worker size
 variation, worker size is strongly correlated with task performance. This
 size-task correlation is weaker, but still present, in species with less
 variably sized workers. Our results suggest that Formica use size-based
 task partitioning, a form of morphological polyethism. We expect social
 insects with and without discrete morphological worker subcastes to differ
 in ontogeny, evolutionary history, and degree of behavioral flexibility.
 Identifying the scope of variation in task partitioning mechanisms will
 facilitate comparative studies, thereby elucidating evolutionary histories
 and outcomes of alternative strategies.
description: <strong>Formica_Task_Data.xlsx</strong>
 Species, location, behavioral, and morphometric data for all
 colonies used in this study. Behavioral data: from a mark-recapture
 experiment focused on task performance and fidelity among
 <em>Formica </em>workers. Morphometric data: head-width
 measurements of a subset of <em>Formica </em>workers for which
 behavioral data was collected.
DOI: 10.6078/d1z69f
title: Integrative taxonomy and geographic sampling underlie successful species delimitation

description: Species delimitation requires a broad assessment of population-level
 variation using multiple lines of evidence, a process known as integrative
 taxonomy. More specifically, studies of species limits must address
 underlying questions of what limits the distribution of populations, how
 traits vary in association with different environments, and whether the
 observed trait differences may lead to speciation through reproductive
 isolation. While genomic data have revolutionized the process of
 delimiting species, such data should be analyzed along with phenotypic,
 behavioral, and ecological traits that shape individuals across geographic
 and environmental space. The integration of multiple traits promotes
 taxonomic stability and should be a major guiding principle for species
 delimitation. Equally important, however, is thorough geographic sampling
 to adequately represent population-level variation — both in allopatry and
 across putative contact zones. We discuss the importance of both of these
 factors in the context of species concepts and traits, and present
 different examples from birds that illustrate criteria for species
 delimitation. In addition, we review a decade of proposals for
 species-level taxonomic revisions considered by the American
 Ornithological Society’s North American Classification Committee, and
 summarize the basis for decisions on whether to split or lump species.
 Finally, we present recommendations and discuss challenges (specifically
 permits, time, and funding) for species delimitation studies. This is an
 exciting time to be studying species delimitation in birds: many
 species-level questions remain, and methodological advances along with
 increased access to data enable new approaches to studying age-old
 problems in avian taxonomy.
description: This dataset was collected by compiling records of specimens and
 audio recordings of Artemisiospiza nevadensis and A. belli archived at the
 Museum of Vertebrate Zoology and used in various publications by the lead
 author (C. Cicero).
description: The data values are coded as 0 and 1 for absence and presence
 (respectively) of genetic/morphological and song data. Populations are
 numbered for internal use, but each number represents a set of individuals
 that were grouped together into a population for analyses.
DOI: 10.15468/dl.b7pjcb
title: Occurrence Download

description: A dataset containing 14504 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Bryophyta, Marchantiophyta, Anthocerotophyta)",
 "BasisOfRecord is one of (Specimen)",
 "Country is Brazil",
 "StateProvince is Rio Grande do Sul"
 ]
}

 The dataset includes 14504 records from 78 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002215-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5061/dryad.xsj3tx9bf
title: Association of specific biotypes in patients with Parkinson's disease and disease progression

description: Objective To identify biotypes in newly diagnosed Parkinson’s disease
 patients and test whether these biotypes could explain inter-individual
 differences in longitudinal progression. Methods In this longitudinal
 analysis, we use a data-driven approach clustering PD patients from the
 Parkinson’s Progression Markers Initiative (PPMI) (n = 314, age = 61.0 ±
 9.5, 34.1% female, 5 years follow-up). Voxel-level neuroanatomical
 features were estimated using deformation-based morphometry (DBM) of
 T1-weighted MRI. Voxels whose deformation values were significantly
 correlated (P &lt; 0.01) with clinical scores (MDS-UPDRS-Parts I-III,
 MDS-UPDRS-total, tremor score, and postural instability and gait
 difficulty score) at baseline were selected. Then, these neuroanatomical
 features were subjected to hierarchical cluster analysis. Changes in the
 longitudinal progression and neuroanatomical pattern were compared between
 different biotypes. Results Two neuroanatomical biotypes were identified:
 (i) biotype 1 (n = 114) with subcortical brain volume as smaller than
 heathy controls; (ii) biotype 2 (n = 200) with subcortical brain volumes
 larger than heathy controls. Biotype 1 had more severe motor impairment,
 autonomic dysfunction, and very much worse REM sleep behavior disorder
 than biotype 2 at baseline. Although disease duration at initial visit and
 follow-up were similar between biotypes, PD patients with smaller
 subcortical brain volume had poorer prognosis, with more rapid decline in
 several clinical domains and in dopamine functional neuroimaging over an
 average of five years. Conclusion Robust neuroanatomical biotypes exist in
 PD with distinct clinical and neuroanatomical pattern. These biotypes can
 be detected at diagnosis, and predict the course of longitudinal
 progression, which should benefit trial design and evaluation.
description: All
 deidentified clinical and imaging data are available on the PPMI website
 (http://www.ppmi-info.org) and from the corresponding author on reasonable
 request.
DOI: 10.15468/dl.mpwypv
title: Occurrence Download

description: A dataset containing 793 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Geotria australis",
 "HasCoordinate is true",
 "DecimalLatitude is greater than -90",
 "DecimalLatitude is less than 90",
 "DecimalLongitude is greater than -180",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 2015"
 ]
}

 The dataset includes 793 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002216-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5061/dryad.547d7wm4v
title: Emerging challenges for sustainable development and forest conservation in Sarawak, Borneo

description: The forests of Borneo—the third largest island on the planet—sustain some
 of the highest biodiversity and carbon storage in the world. The forests
 also provide vital ecosystem services and livelihood support for millions
 of people in the region, including many indigenous communities. The
 Pan-Borneo Highway and several hydroelectric dams are planned or already
 under construction in Sarawak, a Malaysian state comprising part of the
 Borneo. This development seeks to enhance economic growth and regional
 connectivity, support community access to services, and promote industrial
 development. However, the implications of the development of highway and
 dams for forest integrity, biodiversity and ecosystem services remained
 largely unreported. We assessed these development projects using
 fine-scale biophysical and environmental data and found several
 environmental and socioeconomic risks associated with the projects. The
 highway and hydroelectric dam projects will impact 32 protected areas
 including numerous key habitats of threatened species such as the
 proboscis monkey (Nasalis larvatus), Sarawak surili (Presbytis
 chrysomelas), Bornean orangutans (Pongo pygmaeus) and tufted ground
 squirrel (Rheithrosciurus macrotis). Under its slated development
 trajectory, the local and trans-national forest connectivity between
 Malaysian Borneo and Indonesian Borneo would also be substantially
 diminished. Nearly ~161 km of the Pan-Borneo Highway in Sarawak will
 traverse forested landscapes and ~55 km will traverse carbon-rich
 peatlands. The 13 hydroelectric dam projects will collectively impact ~1.7
 million ha of forest in Sarawak. The consequences of planned highway and
 hydroelectric dams construction will increase the carbon footprint of
 development in the region. Moreover, many new road segments and
 hydroelectric dams would be built on steep slopes in high-rainfall zones
 and forested areas, increasing both construction and ongoing maintenance
 costs. The projects would also alter livelihood activities of downstream
 communities, risking their long-term sustainability. Overall, our findings
 identify major economic, social and environmental risks for several
 planned road segments in Sarawak— such as those between Telok Melano and
 Kuching; Sibu and Bintulu; and in the Lambir, Limbang and Lawas
 regions—and dam projects— such as Tutoh, Limbang, Lawas, Baram, Linau, Ulu
 Air and Baleh dams. Such projects need to be reviewed to ensure they
 reflect Borneo’s unique environmental and forest ecosystem values, the
 aspirations of local communities and long-term sustainability of the
 projects rather than being assessed solely on their short-term economic
 returns.
description: Please refer to the Metadata.txt files within each 7z archive for
 additional information.
DOI: 10.5061/dryad.cvdncjt16
title: Predation risk shapes the degree of placentation in natural populations of live-bearing fish

description: The placenta is a complex life-history trait that is ubiquitous across the
 tree of life. Theory proposes that the placenta evolves in response to
 high performance-demanding conditions by shifting maternal investment from
 pre- to post-fertilization, thereby reducing a female’s reproductive
 burden during pregnancy. We test this hypothesis by studying populations
 of the fish species Poeciliopsis retropinna in Costa Rica. We found
 substantial variation in the degree of placentation among natural
 populations associated with predation risk: females from high predation
 populations had significantly higher degrees of placentation compared to
 low predation females, while number, size and quality of offspring at
 birth remained unaffected. Moreover, a higher degree of placentation
 correlated with a lower reproductive burden and hence likely an improved
 swimming performance during pregnancy. Our study advances an adaptive
 explanation for why the placenta evolves by arguing that an increased
 degree of placentation offers a selective advantage in high predation
 environments.
description: See README file for further instructions
DOI: 10.5061/dryad.j6q573n9c
title: OdoBD: An online database for the dragonflies and damselflies of Bangladesh

description: Combining scientific data over a long-time period is necessary for
 generating large-scale datasets, which are an essential component of
 comparative analysis for understanding evolutionary processes.
 Furthermore, monitoring temporal and spatial distributions of animals at a
 global and regional scale is essential for studying climate change driven
 extinction risks. Regional and global datasets focusing on different
 animal groups are on the rise to meet such challenges. Although being one
 of the earliest and best-known insect groups, the data on Odonata remains
 rudimentary and dispersed, especially in the South Asian region.
 Bangladesh, being located within a biodiversity hotspot, possesses a large
 number of odonate species and many of them are endemic to the South Asian
 region. We have developed an online database for the Odonata of Bangladesh
 by compiling and digitizing data from our last four years of field
 studies, from previously published research articles and field guides, and
 also by collecting data from citizen scientists. The Odonata of Bangladesh
 database (accessible at http://www.odobd.org) contains phenotypic,
 genotypic, photographic, taxonomic, biogeographic and faunistic data of
 the Odonata of Bangladesh. The database will be a valuable resource for
 understanding diversity, distributions, extinction risks and conservation
 planning of the Odonata of Bangladesh. Finally, phenotypic, spatial and
 temporal data of Odonata of Bangladesh datasets can be integrated with
 other regional datasets for analyzing macroevolutionary trends and to
 monitor the effect of climate change on odonates.
DOI: 10.5061/dryad.fn2z34tqj
title: Characterizing and classifying neuroendocrine neoplasms through microRNA sequencing and data mining

description: Neuroendocrine neoplasms (NENs) are clinically diverse and incompletely
 characterized cancers that are challenging to classify. MicroRNAs (miRNAs)
 are small regulatory RNAs that can be used to classify cancers. Recently,
 a morphology-based classification framework for evaluating NENs from
 different anatomic sites was proposed by experts, with the requirement of
 improved molecular data integration. Here, we compiled 378 miRNA
 expression profiles to examine NEN classification through comprehensive
 miRNA profiling and data mining. Following data preprocessing, our final
 study cohort included 221 NEN and 114 non-NEN samples, representing 15 NEN
 pathological types and five site-matched non-NEN control groups.
 Unsupervised hierarchical clustering of miRNA expression profiles clearly
 separated NENs from non-NENs. Comparative analyses showed that miR-375 and
 miR-7 expression is substantially higher in NEN cases than non-NEN
 controls. Correlation analyses showed that NENs from diverse anatomic
 sites have convergent miRNA expression programs, likely reflecting
 morphologic and functional similarities. Using machine learning
 approaches, we identified 17 miRNAs to discriminate 15 NEN pathological
 types and subsequently constructed a multi-layer classifier, correctly
 identifying 217 (98%) of 221 samples and overturning one histologic
 diagnosis. Through our research, we have identified common and
 type-specific miRNA tissue markers and constructed an accurate miRNA-based
 classifier, advancing our understanding of NEN diversity.
description: Sequencing-based miRNA expression profiles from 378 clinical samples, comprising 239 neuroendocrine neoplasm (NEN) cases and 139 site-matched non-NEN controls, were used in this study. Expression profiles were either compiled from published studies (n=149) or generated through small RNA sequencing (n=229). Prior to sequencing, total RNA was isolated from formalin-fixed paraffin-embedded (FFPE) tissue blocks or fresh-frozen (FF) tissue samples. Small RNA cDNA libraries were sequenced on HiSeq 2500 Illumina platforms using an established small RNA sequencing (Hafner et al., 2012 <i>Methods</i>) and sequence annotation pipeline (Brown et al., 2013 <i>Front Genet</i>) to generate miRNA expression profiles. Scaling our existing approach to miRNA-based NEN classification (Panarelli et al., 2019 <i>Endocr Relat Cancer</i>; Ren et al., 2017 <i>Oncotarget</i>), we constructed and cross-validated a multi-layer classifier for discriminating NEN pathological types based on selected miRNAs.
description: Diagnostic histopathology and small RNA cDNA library preparation information for all samples are presented in <b>Table S1 </b>of the associated manuscript.
DOI: 10.5066/p1uk4wu4
title: Water chemistry data for samples collected at groundwater and surface-water sites in the San Ardo Oil Field study area, March 2019–May 2021, Monterey County, California

description: The California State Water Resources Control Board (State Water Board) initiated the Oil and Gas Regional Monitoring Program (RMP) to assess effects of oil and gas development on groundwater designated for any beneficial use. The U.S. Geological Survey (USGS) is the technical lead in conducting the RMP through the California Oil, Gas, and Groundwater (COGG) Program, working in cooperation with the State Water Board, and in partnership with other State and local agencies. The USGS collected and analyzed groundwater (GW) and surface water (SW) for the San Ardo Oil Field study area, the area within the San Ardo Oil Field administrative boundary and the surrounding five-kilometer buffer zone, in Monterey County, California. Eighteen groundwater, two stream, and two spring samples were collected from March 2019 through May 2021. Groundwater samples were collected from one public-supply well, five monitoring wells, two irrigation wells, one livestock well, five oil-field water supply wells, and four domestic wells. Samples were collected using established water data-collection protocols and procedures and analyzed for (1) water-quality indicators, (2) major and minor ions, (3) nutrients,  (4) trace elements, (5) volatile organic compounds (VOCs), (6) naturally-occurring radioactive material (radium isotopes), (7) geochemical and age-dating tracers, (8) dissolved organic carbon (DOC), (9) dissolved standard and hydrocarbon gases (methane through hexane), and (10) dissolved noble gases and atmospheric gases. In total, 185 constituents, water-quality indicators, or properties are included in this data release. Quality-control (QC) samples were used to assess the quality of laboratory results.
DOI: 10.25934/pr00012555.0
title: Available datapackage for study 'Transforming Community Engagement to Increase SARS-CoV-2 Testing in Underserved Populations in Baton Rouge (TEST UP-BR)'

description: Vivli is an independent, non-profit organization that has developed a global data-sharing and analytics platform to serve all elements of the international research community. Our mission is to promote, coordinate, and facilitate scientific sharing and reuse of clinical research data through the creation and implementation of a sustainable global data-sharing enterprise. The Vivli platform includes an independent data repository, in-depth search engine and a cloud-based, secure analytics platform.
DOI: 10.5061/dryad.866t1g1n1
title: Data from: Skewness and index futures return

description: In this paper, we show that the individual skewness, defined as the
 average of monthly skewness across firms, performs very well at predicting
 the return of S\&P 500 index futures. This result holds after
 controlling for the liquidity risk or for the current business cycle
 conditions. We also find that individual skewness performs very well at
 predicting index futures returns out-of-sample.
description: This excel document contains the main data for the paper:
 "Skewness and Index Futures Return". The
 Matlab code for result replication is available at Qunzi Zhang's
 website: https://sites.google.com/site/zhangqunzi/
DOI: 10.5066/p135zukn
title: Daily coastal low cloudiness, precipitable water, related atmospheric variables, and model code for Southern California (1996–2020)

description: Low-level stratiform clouds modulate California's coastal climate during the warm season. Previous work describing the seasonal and daily variability of coastal low cloudiness (CLC) suggests that in July, August, and September southern California's CLC is under the influence of an additional driver, which has less impact in northern California. In this work, we introduce the link in which free-tropospheric moisture dictated by North American Monsoon (NAM) processes can impact southern California CLC. We use in situ and remote sensing observations, as well as reanalysis and single column model simulations to identify and investigate this previously missing component.