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18 results for “2015-2018”
Impacts of Hemlock Woolly Adelgid After Preventative Treatment in Lincoln MA 2015-2018
In 2007 the town of Lincoln, MA treated the hemlock stand at the Codman estate with root injections of imidacloprid to suppress the invasive insect Hemlock Wooly Adelgid (HWA). This hemlock grove is unique for this area of Massachusetts and dominated by eastern hemlock of approximately 2 feet in diameter with many trees reaching heights of over 120 feet. The treatment goal was to conserve the trees and the stand’s cathedral-like characteristics. To accomplish this goal, every big canopy tree was treated.
Academics for Land Protection in New England (ALPINE) GIS Data 2015-2018
Academics for Land Protection in New England (ALPINE) is a network of academic institutions committed to increasing the pace of land protection in New England to address the region’s environmental challenges and to support nature and people. ALPINE seeks to expand the role that academic institutions play in conserving the New England landscape by sharing experiences and resources among faculty and staff, students, administrations, and alumni. This dataset contains point locations of colleges that are participants in ALPINE and parcels of natural land owned by participating schools who submitted data to the ALPINE coordinator.
Herbivore dung and parasite counts, Ol Pejeta Conservancy and Mpala Research Centre, Kenya (2015-2018)
Data package contains two datasets of dung surveys, one dataset of parasite egg measurements, and two camera trap datasets collected from Mpala Research Centre and Ol Pejeta Conservancy, Laikipia County, Kenya from November 2015-September 2018. Datasets are provided as part of the publication `Watering sources aggregate parasites with increasing effects in more arid conditions`. Source data files for figures in the manuscript are also provided here.
Annual Article Processing Charges (APCs) and number of gold and hybrid open access articles in Web of Science indexed journals published by Elsevier, Sage, Springer-Nature, Taylor & Francis and Wiley 2015-2018
<p><strong>Dataset of annual Article Processing Charges (APCs) for 6,252 journals from 2015 to 2018. </strong>The dataset contains annual APCs for journals indexed in the Web of Science (WoS) and published by the oligopoly of academic publishers (Elsevier, Sage, Springer-Nature, Taylor & Francis, Wiley). It also includes an estimate of the total APCs paid by the academic community based on the number of gold and hybrid articles published between 2015 and 2018. The dataset was created using publication data from WoS, OA status from Unpaywall and annual APC prices from open datasets (<a href="https://doi.org/10.5281/ZENODO.3841568">Matthias, 2020</a>; <a href="https://doi.org/10.5683/SP2/84PNSG">Morrison, 2021</a>) and historical fees retrieved via the Internet Archive Wayback Machine. </p> <p>Detailed methods and findings are reported in the following journal article</p> <p>Butler, L.-A., Matthias, L., Simard, M.-A., Mongeon, P., & Haustein, S. (2023). The Oligopoly's Shift to Open Access. How the Big Five Academic Publishers Profit from Article Processing Charges. <em>Quantitative Science Studies</em>. Preprint: <a href="https://doi.org/10.5281/zenodo.8322555">https://doi.org/10.5281/zenodo.8322555</a></p> <p><strong>Description of included files (v1):</strong></p> <p><em>APCs.csv: </em>contains the annual APCs for gold and hybrid OA journals indexed in Web of Science published by the oligopoly of academic publishers (Elsevier, Sage, Springer-Nature, Taylor & Francis, Wiley) between 2015 and 2018 including the total estimate of APCs paid per journal per year. It contains APC data for 18,846 journal-year-OA status combinations.</p> <p><em>countries.csv</em>: contains the fractionalized number of annual gold and hybrid OA articles by oligopoly publishers between 2015 and 2018 and the total estimate of fractionalized APCs paid per country per journal per year.</p> <p><em>oecd.csv</em>: contains the fractionalized number of annual gold and hybrid OA articles by oligopoly publishers between 2015 and 2018 and the total estimate of fractionalized APCs per discipline per journal per year.</p> <p><em>ReadMe.csv</em>: contains a description of the variables used in <em>APCs.csv</em>, <em>countries.csv</em> and <em>oecd.csv</em>.</p> <p> </p>
Deschampsia biomass, soil microbes and endophyte root colonization for snowmelt and microbial innoculation transplant experiment in the Green Lakes Valley, 2015-2018
As organisms shift their geographic distributions in response to climate change, biotic interactions have emerged as an important factor driving the rate and success of range expansions. Plant-microbe interactions are an understudied but potentially important factor governing plant range shifts. We studied the distribution and function of microbes present in high-elevation unvegetated soils, areas that plants are colonizing as climate warms, snow melts earlier and the summer growing season lengthens. Using a manipulative snowpack and microbial inoculation transplant experiment, we tested the hypothesis that growing season length and microbial community composition interact to control plant elevational range shifts. We predicted that a lengthening growing season combined with dispersal to patches of soils with more mutualistic microbes and fewer pathogenic microbes would facilitate plant survival and growth in previously unvegetated areas. We identified negative effects on survival of the common alpine bunchgrass Deschampsia cespitosa in both short and long growing seasons, suggesting an optimal growing season length for plant survival in this system that balances time for growth with soil moisture levels. Importantly, growing season length and microbes interacted to affect plant survival and growth, such that microbial community composition increased in importance in suboptimal growing season lengths. Further, plants grown with microbes from unvegetated soils grew as well or better than plants grown with microbes from vegetated soils. These results suggest that the rate and spatial extent of plant colonization of unvegetated soils in mountainous areas experiencing climate change could depend on both growing season length and soil microbial community composition, with microbes potentially playing more important roles as growing seasons lengthen.
Oxygen Fluxes on Virginia Tidal Flats, 2015-2018
Bare tidal flats along the eastern USA coast are increasingly undergoing state changes to one of two systems: human-restored Crassostrea virginica oyster reefs or invasive Agarophyton (Gracilaria) macroalgal mats, with little known about how these changes impact ecosystem metabolism. This dataset details aquatic eddy covariance (AEC) benthic oxygen fluxes, along with physical drivers such as flow speed and light, of 3 oyster reefs, 2 macroalgal beds, and 1 bare mudflat located at the Virginia Coast Reserve (VCR). The oyster reef data spans 4 years (2015 - 2018) and all seasons, while the mudflat and Agaraphyton data are from summers 2015 and 2017, respectively. These flux data are used to calculate the metabolism (R, GPP, NEM) of these systems, in order to better understand how state changes have impacted carbon cycling on the Virginia coast.
Datos curados de variables de producción por departamento colombiano (2015-2018).
<p>El siguiente dataset contiene información sobre el rendimiento (t/ha), producción (t), área cosechada (ha), área sembrada (ha) y temperatura (ºC) de cada departamento colombiano por semestre desde 2015 hasta el primer semestre de 2018.</p>
MAVIS Twitter dataset: A collection of tweets and sentiment analysis in Spanish about vaccines and diseases during the period 2015-2018
<p>MAVIS dataset comprises a full knowledge base regarding Twitter messages published in Spanish during the period 2015-2018, in the context of sentiment analysis of specific vaccines and their related diseases. Such diseases and vaccines are summarized as follows:</p> <ul> <li>Invasive meningococcal disease (“EMI” in Spanish): Bexsero, Trumenba, Nimenrix</li> <li>Invasive pneumococcal disease (“ENI” in Spanish)</li> <li>Influenza</li> <li>Hepatitis</li> <li>Rotavirus: Rotarix, Rotateq</li> <li>Measles (“Sarampión” in Spanish) and MMR (“Triple vírica” in Spanish)</li> <li>Sepsis</li> <li>Whooping cough (“Tosferina” in Spanish)</li> <li>Chickenpox (“Varicela” in Spanish): Varivax, Varilrix; and Shingles (“Zoster” in Spanish)</li> <li>Human papillomavirus infection (“VPH” in Spanish): Cervarix, Gardasil</li> </ul> <p>Tweets have been manually classified as having a negative or non-negative sentiment by 5 experts. Moreover, an automatic classification has been performed by 3 different tools: IBM Watson (now Watson Tone Analyzer, <a href="https://www.ibm.com/watson/services/tone-analyzer/">https://www.ibm.com/watson/services/tone-analyzer/</a>), Google Cloud Natural Language (<a href="https://cloud.google.com/natural-language">https://cloud.google.com/natural-language</a>), and Meaning Cloud (<a href="https://www.meaningcloud.com/">https://www.meaningcloud.com/</a>). IBM Watson and Google Cloud Natural Language returned a numerical sentiment score ranging from -1 to 1, while Meaning Cloud returned a categorical variable with the values ‘P+’, ‘P’, ‘NEU’, ‘N’ and ‘N+’, which were converted to 1, 2, 3, 4 and 5 respectively.</p> <p>With these variables (IBM Watson, Google Cloud Natural Language, and Meaning Cloud annotations and the experts’ classification as the target label), a machine learning metamodel was developed. Tweets were also annotated with the sentiment output given by this classifier. </p> <p>The provided data includes intrinsic tweets information, intrinsic information regarding the users that posted the tweets, the keywords mentioned in each tweet, and the annotations that the experts, the tools, and the model gave to each tweet.</p> <p><strong>Funding</strong>: This dataset was obtained with funding from MSD, Spain under MAVIS Study (VEAP ID: 7789).</p> <p><strong>Current studies using this dataset at the moment of the publication</strong>:</p> <ul> <li>Rodríguez-González et al., “Creating a metamodel based on machine learning to identify the sentiment of vaccine and disease-related messages in Twitter: the MAVIS study” in 2020 IEEE 33st International Symposium on Computer-Based Medical Systems (CBMS), Jul. 2020, p. 6. DOI: 10.1109/CBMS49503.2020.00053</li> <li>Rodríguez-González et al., "Identifying Polarity in Tweets from an Imbalanced Dataset about Diseases and Vaccines Using a Meta-Model Based on Machine Learning Techniques" in Applied Sciences, 2020, 10. DOI: 10.3390/app10249019</li> </ul>
Distribution of invasive alien species of Union concern (Regulation (EU) 1143/2014) in Belgium for the reporting period 2015-2018
<p><strong>Aims and scope</strong></p> <p>Member State authorities are required to report on the distribution in their territory of each of the invasive alien species (IAS) of Union concern. These are species with documented biodiversity impacts sensu the European Union Regulation on the prevention and management of the introduction and spread of Invasive Alien Species in Europe (IAS Regulation No 1143/2014) (European Union 2014). This distribution represents the official reporting under Article 24(1) of R.1143/2014 on invasive alien species for the period 2015–2018. Baseline distribution of these species has previously been reported and published (Adriaens et al. 2018, ).</p> <p>Data were compiled from various datasets holding invasive species observations such as data from research institutes and research projects (9%), citizen science observatories (68%) and a range of other sources (23%) such as governmental agencies, water managers etc. More specifically the dataset includes:</p> <ul> <li>The citizen science recording portals www.waarnemingen.be and www.observation.be which has a specific alert system for IAS where nature volunteers can report their observations (Adriaens et al. 2018);</li> <li>Data from the Research Institute for Nature and Forest (INBO), the Flemish government institute that coordinates N2000, WFD and BIrd Directive and IAS monitoring in the terrestrial, estuarine and freshwater environment;</li> <li>Data from the Flemish Environment Agency which performs management of muskrat and invasive water plants in Flanders, gathered with a dedicated smartphone app since 2015;</li> <li>Data from the Flemish provinces and Rato vzw that manage water plants, muskrat, giant hogweed etc.;</li> <li>Some smaller datasets from cities;</li> <li>Data from the Brussels Capital Region from the Brussels Environment data portal;</li> <li>Plant inventories of the ‘contrats de rivière’ along watercourses in Wallonia, making use of a dedicated application to collect data directly from the field (fulcrum);</li> <li>The government reporting portals for IAS of the ‘Observatoire wallon de la flore, de la faune et des habitats (Service Public de Wallonie)’;</li> <li>Some validated data from specific datasets on gbif (iNaturalist, Natusfera, Naturgucker).</li> </ul> <p>Data were normalized using a custom mapping of the original data files to Darwin Core (Wieczorek et al. 2012) where possible. Species names were mapped to the GBIF Backbone Taxonomy (GBIF 2016) using the species API (http://www.gbif.org/developer/species). The mapping was assisted by dedicated software (SMARTIE) which was specifically written for the purpose of aggregating IAS data from various sources. Appropriate selection of records was performed based on the cut-off dates (see data range) and record content validation (see validation procedure). Data were then joined with GRID10k layer Belgium based on GRID10k cellcodes (ETRS_1989_LAEA). The technical format is in line with the <a href="http://cdr.eionet.europa.eu/help/ias_regulation/material/IAS-species-distribution-user-manual">guidelines</a> provided to the member states for the compilation of reports on Species Distribution (SD) of Invasive Alien Species of Union concern.</p> <p><strong>File description</strong></p> <p>The dataset contains a shapefiles (<em>T1_Belgium_Union_List_Species.shp</em>) with the distribution of the species of Union Concern at 10km<sup>2</sup> (European Terrestrial Reference System projection - 1989 ETRS_1989_LAEA) level. The attributes table contains <em>Cellcode </em>(ETRS<sup> </sup>grid cell code) and <em>Species </em>(scientific name + authority).</p> <p><strong>Date range</strong></p> <p>The data reflects the distribution of the IAS of Union concern in Belgium in the first reporting period for the EU Regulation hence comprises observations of Union List invasive species between January 2015 (2015-01-01) and December 2018 (2018-12-31). </p> <p><strong>Validation procedure</strong></p> <p>Record validation was performed to exclude dubious records, wrong identifications etc. This was done based on the IdentificationVerificationStatus field (to which validation information from original data were mapped) if available. In general, non-validated data were not considered. Data were validated in the original datasets based on evidence (e.g. pictures), on the observer’s experience, or based on a set of predefined rules (e.g. automated validation based on geographic filtering). Data from research institutes were generally considered validated. A few casual records of EU list species that were clearly planted were discarded manually. When the original dataset did not mention any validation status, records were not considered validated and therefore not taken into account unless for Chinese mitten crab <em>Eriocheir sinensis</em>, ruddy duck <em>Oxyura jamaicensis</em>, raccoon <em>Procyon lotor</em>, Siberian ground squirrel <em>Tamias sibiricus</em>, sacred ibis <em>Threskiornis aethiopicus</em>, Egyptian goose <em>Alopochen aegyptiaca, </em>Himalayan balsam <em>Impatiens glandulifera</em>, giant hogweed <em>Heracleum mantegazzianum, </em>muskrat <em>Ondatra zibethicus </em>and red-eared slider <em>Trachemys spp</em>. For these species, it was assumed all records were correct as they originate from dedicated sampling (<em>E. sinensis</em>) within research projects, were gathered by public bodies (e.g. muskrat), or represent species that are readily recognizable by people in the field. Data provided by EASIN in the care package and GBIF data were carefully checked.</p> <p>A visual check was performed on the resulting distribution maps by representatives of the Belgian national scientific council on invasive alien species, an official consultative structure coordinating scientific input and data aggregation between Belgian regions and institutions with regards to technical implementation of the Regulation No 1143/2014 on invasive alien species.</p> <p><strong>Data providers</strong></p> <p>The providers of the invasive species data for this exercise (individuals and their respective organizations) are listed in the "data providers" section of the dataset metadata. Much of the primary occurrence data that formed the basis for this aggregated dataset will be published as open data on the Global Biodiversity Information Facility (GBIF).</p>
Mammalian herbivores restrict the altitudinal range limits of three alpine grass species (transplant and herbivore exclusion experiment and demographic data from natural populations), West Elk Mountains, Colorado, USA 2015-2018
Though rarely experimentally tested, biotic interactions have long been hypothesized to limit low-elevation range boundaries of species. We tested the effects of herbivory on three alpine-restricted plant species by transplanting plants below (novel), at the edge (limit), or in the center (core) of their current elevational range and factorially fencing-out above- and belowground mammals in the West Elk Mountains, Colorado, USA from 2015-2018. Herbivore damage was greater in range limit and novel habitats than in range cores. Exclosures increased plant biomass and reproduction more in novel habitats than in range cores, suggesting demographic costs of novel interactions with herbivores. We then used demographic models to project population growth rates, which increased 5-20% more under herbivore exclosure at range limit and novel sites than in core habitats. Our results identify mammalian herbivores as key drivers of the low-elevation range limits of alpine plants and indicate that upward encroachment of herbivores could trigger local extinctions by depressing plant population growth.
OSMO soil health dataset 2015-2018
<p>This is soil health data collected from 24 Finnish fields between 2015-2018. The fields were chosen to represent fields with poor and good productivity on a given farm. The dataset is coded based on farm code (two letters) and field code: 0 poor field, no interventions; 1 poor field, improved soil management; K good field.</p> <p>Fields were monitored for soil nutrients, soil physical quality and some biological parameters (aggregate stability, earthworms, arthropods, soil carbon dioxide burst respiration).</p> <p>The overview dataset contains the parameters used for monitoring development in soil health in the fields, the additional dataset present plant tissue nutrient concentrations and soil structure evaluation as well as a comparison of organic matter analysis from three laboratories and a comparison of two aggregate stability assessment methods. </p> <p>More information on the study can be found in the two reports (in Finnish, w. English abstracts):</p> <p>http://hdl.handle.net/10138/229450</p> <p>http://hdl.handle.net/10138/309062</p>
Central Valley InSAR Data - 2015 -2016 -2017-2018
<p>InSAR range change data, cumulative since 2/2015.</p> <p>The files are in ascii and are of the form</p> <p>Decimal degrees longitude, Decimal degrees latitude, Range change (cm)</p> <p>.</p> <p>.</p> <p>.</p>
Semi-quantitative microcystin concentration measured in surface water samples collected by the Citizen-Led Environmental Observatory (CLEO) from multiple nearshore sites in Lake Lillinonah, Connecticut, USA, 2015-2018
Included in this data package are cyanobacterial toxin data from the Citizen-Led Environmental Observatory (CLEO), a volunteer water quality monitoring program run by Friends of the Lake (FOTL, friendsofthelake.org) and Fairfield University at Lake Lillinonah, Connecticut, USA. The program has been operational since 2008 (toxin data available form 2015-2018). Trained volunteer monitors collect routine surface water samples from multiple nearshore sites twice a month from Memorial Day through Labor Day. In addition, spot samples are taken whenever a significant algae bloom is present at the collection site. These samples are analyzed for microcystin concentrations. Routine water samples are also analyzed for levels of the total nitrogen and phosphorus concentrations. Additionally, CLEO volunteers collect data on water temperature, Secchi disk depth, water color, presence of floating woody debris, recreation potential, trash, particle type and surface scum every 1-3 days during the same period. These data are available in EDI packages EDI567 (general water quality) and EDI568 (nutrients).
Tree cone presence and abundance from Niwot Ridge, Rollins Pass, and Rocky Mountain National Park, 2015-2018.
These data were collected to examine the determinants of individual tree cone presence and cone abundance for Engelmann spruce (Picea engelmannii) and subalpine fir (Abies lasiocarpa) in the southern Rocky Mountains, USA. We monitored > 1600 Engelmann spruce and subalpine fir trees for cone presence (an indicator of reproductive maturity) and a subset of those trees for cone abundance (an indicator of seed production) from 2016-2018 in the Colorado Front Range. Cone presence was observed in 1-3 years (2015 or 2016-2018) in 15 plots and cone abundance was observed in 10 of 15 plots in three years (2016-2018). We measured the following for > 24 live trees for each species in each plot: cone presence and/or cone abundance, diameter at breast height, age, height class. For each plot, we measured stand density, basal area, and age of oldest tree to estimate the timing of stand initiation. This database includes three datasets: 1) description of plots (e.g. elevation, aspect, size), 2) cone presence data, and cone abundance data. See Andrus et al. 2020 for more details. References Andrus, R. A., Harvey, B. J., Hoffman, A., and Veblen, T. T.. 2020. Reproductive maturity and cone abundance vary with tree size and stand basal area for two widely distributed conifers. Ecosphere 11( 5):e03092. 10.1002/ecs2.3092
Multiplex IgG antibody response and malaria parasitemia among children ages 1-59 months in the MORDOR Niger trial, 2015-2018
Open the record for dataset details and reuse information.
Post-fire Recovery of Soil Organic Layer Carbon in Canadian Boreal Forests, 2015-2018
This dataset provides site moisture, soil organic layer thickness, soil organic carbon, nonvascular plant functional group, stand dominance, ecozone, time-after-fire, jack pine proportion, and deciduous proportion for 511 forested plots spanning ~140,000 km2 across two ecozones of the Northwest Territories, Canada (NWT). The plots were established during 2015-2018 across 41 wildfire scars and unburned areas (no burn history prior to 1965), with 317 plots in the Plains and 194 plots in the Shield regions. At each plot, two adjacent 30-m transects were established 2 m apart, running north from the plot origin. Soil organic layer (SOL) depth (cm) was measured every 3 m and the mean was taken from the 10 measurements to calculate a plot-level SOL thickness. Three soil organic layer profiles were destructively sampled at 0, 12, and 24 m using a corer that was custom designed for NWT soils. Within the transects, all stems taller than 1.37 m were identified to species to calculate tree density (stems / m2). Nonvascular plant percent cover was identified to functional group at five, 1-m2 quadrats spaced 6 m apart along the belt transect. A subset of 2,067 of 5,137 total increments from 1,803 profiles from 421 plots were analyzed for total percent C using a CHN analyzer. Time-after-fire was established using fire history records. For older plots where no known fire history is recorded, tree age was used. Data are for the period 2015-06-11 to 2018-08-24 and are provided in comma-separated values (CSV) format.
cDNA sequencing of Plasmodium falciparum field parasites 2015-2018
GEO Series GSE169520. Plasmodium falciparum. 380 samples. Type: Expression profiling by high throughput sequencing.
Tabellarische Auswertung Book of Abstracts DHd-Jahreskonferenzen 2015-2018: Anzahl der Beiträge pro Institution (2019)
<p>Supplementary Data für: Ulrike Wuttke, Infrastrukturelle Erfolgsfaktoren für einen universitären Digital Humanities Schwerpunkt, Masterarbeit TH Köln, 2019. urn:nbn:de:hbz:79pbc-opus-13968 (CC BY-SA)</p> <p>Datengrundlage für die Auswertung sind die Books of Abstracts der DHd-Jahreskonferenzen 2015-2018. Data Collection and Analysis 2019.</p> <p>Mehr Informationen: siehe Wuttke_2020_AuswertungBOADHdKonferenzen_Readme.txt</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.