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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: de Vries, Joost; Poulton, Alex J.; Young, Jeremy R.; Monteiro, Fanny M.; +5 Authors

    CASCADE is a global dataset for 139 extant coccolithophore taxonomic units. CASCADE includes a trait database (size and cellular organic and inorganic carbon contents) and taxonomic-specific global spatiotemporal distributions (Lat/Lon/Depth/Month/Year) of coccolithophore abundance and organic and inorganic carbon stocks. CASCADE covers all ocean basins over the upper 275 meters, spans the years 1964-2019 and includes 33,119 taxonomic-specific abundance observations. Within CASCADE, we characterise the underlying uncertainties due to measurement errors by propagating error estimates between the different studies. Full details of the data set are provided in the associated Scientific Data manuscript. The repository contains five main folders: 1) "Classification", which contains YAML files with synonyms, family-level classifications, and life cycle phase associations and definitions; 2) "Concatenated literature", which contains the merged datasets of size, PIC and POC and which were corrected for taxonomic unit synonyms; 3) "Resampled cellular datasets", which contains the resampled datasets of size, PIC and POC in long format as well as a summary table; 4) "Gridded data sets", which contains gridded datasets of abundance, PIC and POC; 5) "Species lists", which contains spreadsheets of the "common" (>20 obs) and "rare" (<20 obs) species and their number of observations. The CASCADE data set can be easily reproduced using the scripts and data provided in the associated github repository: https://github.com/nanophyto/CASCADE/ (zenodo.12797197) Correspondence to: Joost de Vries, joost.devries@bristol.ac.uk v.0.1.2 has some fixes: 1. The wrongly specified S. neapolitana was removed from synonyms.yml (this species is now S. nana)2. Longitudes were corrected for Guerreiro et al., 20233. A double entry for Dimizia et al., 2015 was fixed4. Units in Sal et al., 2013 were correct to cells/L (previously cells/ml)5. Data from Sal et al., 2013 was re-done, as some species were missing6. Duplicate entries from Baumann et al., 2000 were dropped

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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: ZENODO
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    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
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      ZENODO
      Dataset . 2024
      License: CC BY
      Data sources: ZENODO
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2024
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2024
      License: CC BY
      Data sources: Datacite
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2024
      License: CC BY
      Data sources: Datacite
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2024
      License: CC BY
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/

    Πρόκειται για τη συλλογή των γεωμετριών των δασικών περιοχών που βρίσκονται στο έδαφος της περιφέρειας Friuli Venezia Giulia. Οι περισσότερες από αυτές τις περιοχές καταλαμβάνονται από δάση, όπως ορίζονται στον περιφερειακό νόμο για τα δάση (αριθ. 9/2007). Οι γεωμετρίες προέρχονται από δύο διαφορετικές βάσεις δεδομένων: «Τύποι Forestali 1998», που επικαιροποιήθηκαν το 2010 και «Ολοκλήρωση του ΣΓΠ των τύπων δασών Friuli Venezia Giulia» που πραγματοποιήθηκαν το 2011 και επικυρώθηκαν οριστικά το 2013. Is é an bailiúchán de geometries na limistéar foraoise atá suite i gcríoch Réigiún Friuli Venezia Giulia. Tá an chuid is mó de na limistéir sin á n-áitiú ag foraoisí mar a shainítear leis an Dlí Réigiúnach Foraoise (Uimh.9/2007). Tagann na geoiméadrachtaí ó dhá bhunachar sonraí éagsúla: “Cineálacha Forestali 1998”, a tugadh cothrom le dáta in 2010 agus “Comhlánú GIS de Chineálacha Foraoise Friuli Venezia Giulia” a rinneadh in 2011 agus a bailíochtaíodh go cinntitheach in 2013. Es la colección de las geometrías de las zonas forestales ubicadas en el territorio de la región de Friuli Venezia Giulia. La mayor parte de estas zonas están ocupadas por bosques tal como se definen en la Ley Forestal Regional (N.º9/2007). Las geometrías provienen de dos geodatabases diferentes: «Tipos Forestali 1998», actualizado en 2010 y «Completación del SIG de los tipos forestales de Friuli Venezia Giulia», llevado a cabo en 2011 y validado definitivamente en 2013. Il s’agit de la collection des géométries des zones forestières situées sur le territoire de la région du Frioul-Vénétie Giulia. La plupart de ces zones sont occupées par des forêts telles que définies par la loi forestière régionale (No.9/2007). Les géométries proviennent de deux bases de données différentes: «Types Forestali 1998», mis à jour en 2010 et «Achevée du SIG des types forestiers du Frioul Venezia Giulia» réalisée en 2011 et validée définitivement en 2013. Costituisce la raccolta delle geometrie delle aree forestali situate nel territorio della Regione Friuli Venezia Giulia. In buona parte si tratta di superfici occupate da boschi così come definiti dalla vigente legge forestale regionale (n.9/2007). Le geometrie provengono da due diversi geodatabase: "Tipi Forestali 1998", aggiornato nel 2010 e "Completamento del GIS dei Tipi forestali del Friuli Venezia Giulia" realizzato nel 2011 e validato definitivamente nel 2013. Het is de verzameling van de geometrieën van de bosgebieden gelegen op het grondgebied van de regio Friuli Venezia Giulia. De meeste van deze gebieden worden bewoond door bossen zoals gedefinieerd in de Regional Forest Law (nr.9/2007). De geometrieën zijn afkomstig van twee verschillende geodatabases: „Types Forestali 1998”, bijgewerkt in 2010 en „Voltooiing van het GIS van de bossoorten Friuli Venezia Giulia”, uitgevoerd in 2011 en definitief gevalideerd in 2013. Huwa l-ġbir tal-ġeometriji taż-żoni forestali li jinsabu fit-territorju tar-Reġjun ta’ Friuli Venezia Giulia. Il-biċċa l-kbira ta’ dawn iż-żoni huma okkupati minn foresti kif definit mil-Liġi Reġjonali dwar il-Foresti (Nru.9/2007). Il-ġeometriji ġejjin minn żewġ ġeobażijiet tad-data differenti: “Types Forestali 1998”, aġġornata fl-2010 u “Tlestija tal-GIS tat-Tipi ta’ Foresti ta’ Friuli Venezia Giulia” imwettqa fl-2011 u vvalidata b’mod definittiv fl-2013. Este colecția geometriilor zonelor forestiere situate pe teritoriul regiunii Friuli Venezia Giulia. Cele mai multe dintre aceste zone sunt ocupate de păduri, astfel cum sunt definite în Legea regională privind pădurile (nr.9/2007). Geometriile provin din două baze de date geografice diferite: „Tipuri Forestali 1998”, actualizat în 2010 și „Finalizarea GIS a tipurilor de păduri de Friuli Venezia Giulia”, efectuată în 2011 și validată definitiv în 2013. É a coleção das geometrias das áreas florestais localizadas no território da Região Friuli Venezia Giulia. A maior parte destas áreas é ocupada por florestas, tal como definidas na Lei Regional das Florestas (n.º 9/2007). As geometrias vêm de duas bases de dados geométricas diferentes: «Tipos Forestali 1998», atualizado em 2010 e «Conclusão do SIG dos Tipos Florestais de Friuli Venezia Giulia», realizado em 2011 e validado definitivamente em 2013. It is the collection of the geometries of the forest areas located in the territory of the Friuli Venezia Giulia Region. Most of these areas are occupied by forests as defined by the Regional Forest Law (No.9/2007). The geometries come from two different geodatabases: “Types Forestali 1998”, updated in 2010 and “Completion of the GIS of the Forest Types of Friuli Venezia Giulia” carried out in 2011 and validated definitively in 2013.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ European Union Open ...arrow_drop_down
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    Authors: Ferreira, Igor José Malfetoni; Campanharo, Wesley Augusto; Fonseca, Marisa Gesteira; Escada, Maria Isabel Sobral; +7 Authors

    This file collection contains the estimated spatial distribution of the above-ground biomass density (AGB) by the end of the 21st century across the Brazilian Atlantic Forest domain and the respective uncertanty. To develop the models, we used the maximum entropy method with projected climate data to 2100, based on the Intergovernmental Panel on Climate Change (IPCC) Representative Concentration Pathway (RCP) 4.5 from the fifth Assessment Report (AR5). The dataset is composed of four files in GeoTIFF format: calibrated-AGB-distribution.tif: raster file representing the present spatial distribution of the above-ground biomass density in the Atlantic Forest from the calibrated model. Unit: Mg/ha estimated-uncertanty-for-calibrated-agb-distribution.tif: raster file representing the estimated spatial uncertanty distribution of the calibrated above-ground biomass density. Unit: percentage. projected-AGB-distribution-under-rcp45.tif: raster file representing the projected spatial distribution of the above-ground biomass density in the Atlantic Forest by the end of 2100 under RCP 4.5 scenario. Unit: Mg/ha estimated-uncertanty-for-projected-agb-distribution.tif: raster file representing the estimated spatial uncertanty distribution of the projected above-ground biomass density. Unit: percentage. Spatial resolution: 0.0083 degree (ca. 1 km) Coordinate reference system: Geographic Coordinate System - Datum WGS84

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: ZENODO
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: ZENODO
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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    Authors: Horton, Tammy; Serpell-Stevens, Amanda; Domedel, Georgina Valls; Bett, Brian James;

    These data record the results of processing otter trawl catches (OTSB14; Merrett & Marshall, 1980) from the National Oceanography Centre (NOC, UK) long-term study of the Porcupine Abyssal Plain (PAP), including the PAP-Sustained Observatory time-series. The data concern catches recovered during the RRS Challenger cruise 135 in 1997. Billett, D.S.M. et al. (1998). RRS Challenger Cruise 135, 15 Oct-30 Oct 1997. BENGAL: High resolution temporal and spatial study of the BENthic biology and Geochemistry of a north-eastern Atlantic abyssal Locality. Southampton Oceanography Centre Cruise Report, No. 19, 49pp.| https://www.bodc.ac.uk/resources/inventories/cruise_inventory/reports/ch135_97.pdf

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    Global Biodiversity Information Facility
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
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      Global Biodiversity Information Facility
      Dataset . 2024
      License: CC BY
      Data sources: Datacite
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    Description: Leaf and invertebrate biomass in streams Project: This dataset was collected as part of the following SAFE research project: A preliminary study of the allochthonous inputs into tropical streams across a land use gradient in Sabah, Malaysia XML metadata: GEMINI compliant metadata for this dataset is available here Data worksheets: There are 2 data worksheets in this dataset: Insects (Worksheet Insects) Dimensions: 23 rows by 11 columns Description: Insect capture rates Fields: Location: SAFE project riparian site (Field type: Location) Stream: SAFE project stream (Field type: ID) Repeat: sample number for that stream (Field type: ID) Total Mass of Insects (g): the total dried mass of insects collected for each of the repeats (Field type: Numeric) Total Insects: the total number of insects collected in each repeat (Field type: Abundance) Hymenoptera: the total number of hymenoptera in each repeat (Field type: Abundance) Diptera: the total number of diptera in each repeat (Field type: Abundance) Coleoptera: the total number of coleoptera in each repeat (Field type: Abundance) Other.Insect: the grouped total of Hemiptera, Thysanoptera, Orthoptera, Blattodea, Trichoptera, Mantodea, Ephemeroptera, Dermaptera for each repeat (Field type: Abundance) Other: the grouped total of Arachnida, Entognatha, Diplopoda, Chilopoda for each repeat (Field type: Abundance) Hydrology (Worksheet Hydrology) Dimensions: 60 rows by 17 columns Description: River characteristics and litter quantities Fields: Location: SAFE project riparian site (Field type: Location) Stream Code: The stream from which the sample was taken (LFE, 15m, 30m, VJR or OP) (Field type: ID) Transect No.: The point of each sample within the 100m transect at each stream (Field type: ID) Channel Width: The bank full width of the channel at this point (Field type: Numeric) Wetted Width: The width of the runnin water at this point (Field type: Numeric) SAFE Habitat Quality Right: the SAFE Habitat quality on the right of the channel when looking upstream (Field type: Ordered Categorical) SAFE Habitat Quality Centre: the SAFE Habitat quality in the centre of the channel when looking upstream (Field type: Ordered Categorical) SAFE Habitat Quality Left: the SAFE Habitat quality on the left of the channel when looking upstream (Field type: Ordered Categorical) Flow Rate Right (s): the time taken for a tennis ball to travel 10m in the water on the right of the channel when looking upstream (Field type: Numeric) Flow Rate Centre (s): the time taken for a tennis ball to travel 10m in the water in the centre of the channel when looking upstream (Field type: Numeric) Flow Rate Left (s): the time taken for a tennis ball to travel 10m in the water on the left of the channel when looking upstream (Field type: Numeric) Average Flow Rate (s): an average of flow rate centre, flow rate left and flow rate right (Field type: Numeric) Leaf Litter Retention (g): the dried mass of leaf litter retained across the wetted width of the stream at each point (Field type: Numeric) Average Substrate Size: the average size of the substrate across the channel width of the stream at each point (Field type: Numeric) Leaf Litter Trap Position: the position where the leaf litter trap was placed relative to the stream when looking upstream (left, right or centre) (Field type: Categorical) Leaf Litter Mass: the dried mass of leaf litter collected in the leaf litter trap at each point (Field type: Numeric) Date range: 2017-02-06 to 2017-07-06 Latitudinal extent: 4.6314 to 4.7273 Longitudinal extent: 117.4556 to 117.6233 Taxonomic coverage: All taxon names are validated against the GBIF backbone taxonomy. If a dataset uses a synonym, the accepted usage is shown followed by the dataset usage in brackets. Taxa that cannot be validated, including new species and other unknown taxa, morphospecies, functional groups and taxonomic levels not used in the GBIF backbone are shown in square brackets. Animalia - Arthropoda - - Insecta - - - Coleoptera - - - Diptera - - - Hymenoptera - - [Other.Insect]

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    Authors: John W. Williams, Karyn Tabor;

    This dataset contains two metrics for climate change exposure using downscaled climate projections with the SRES A2 emissions scenario (Tabor and Williams, 2007).The metrics represent dissimilarity measurements of the squared Euclidean distance between seasonal (June–August and December–February) temperature and precipitation variables in the 20th century climate and mid-21st century climate. (1) disappearing climate risk - measure of dissimilarity between a pixel’s late 20th century climate and its closest matching pixel in the global set of 21st-century climates (2) novel climate risk - measure of dissimilarity between a pixel’s future climate and its closest matching pixel in the global set of late 20th-century climates. The data are in arcASCII format. All data are in units of standard Euclidean distance and multiplied by 1000. This is the original data. To scale the data similar to Tabor et al. (2018), remove outliers above the 99th percentile distribution before rescaling from 0-1. Unprojected number of columns 2160 number of rows 857 Lower Left X Center -179.917 Lower Left Y Center -59.084 Cell size 0.166667 decimal degrees (10 minutes or ~17 km) {"references": ["Tabor, K. et al. (2018). Tropical Protected Areas Under Increasing Threats from Climate Change and Deforestation: https://doi.org/10.3390/land7030090", "Tabor and Williams (2010). Globally downscaled climate projections for assessing the conservation impacts of climate change. https://doi.org/10.1890/09-0173.1", "Williams, J.W. et al. (2007). Projected distributions of novel and disappearing climates by 20100 AD. https://doi.org/10.1073/pnas.0606292104"]} Support for this project was provided by Conservation International, the Land Tenure Center at the University of Wisconsin, the Center for Climatic Research at the University of Wisconsin, and the Environment Program at the University of Wisconsin–Madison. This research has been funded in part by the Walton Family Foundation, the Gordon and Betty Moore Foundation, and a gift from Betty and Gordon Moore.

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    Is éard atá ann bailiúchán nuashonraithe de gheoiméadrachtaí na limistéar foraoise a bhfuil idirdhealú cineáil eatarthu agus atá suite i gcríoch Réigiún Friuli Venezia Giulia. Tá an chuid is mó de na limistéir sin á n-áitiú ag foraoisí mar a shainítear leis an Dlí Réigiúnach Foraoise (Uimh.9/2007). Tagann na geoiméadrachtaí ó dhá bhunachar sonraí éagsúla: “Cineálacha Forestali 1998”, a tugadh cothrom le dáta in 2010 agus “Comhlánú GIS de Chineálacha Foraoise Friuli Venezia Giulia” a rinneadh in 2011 agus a bailíochtaíodh go cinntitheach in 2013. Is éard atá ann bailiúchán nuashonraithe de gheoiméadrachtaí na limistéar foraoise a bhfuil idirdhealú cineáil eatarthu agus atá suite i gcríoch Réigiún Friuli Venezia Giulia. Tá an chuid is mó de na limistéir sin á n-áitiú ag foraoisí mar a shainítear leis an Dlí Réigiúnach Foraoise (Uimh.9/2007). Tagann na geoiméadrachtaí ó dhá bhunachar sonraí éagsúla: “Cineálacha Forestali 1998”, a tugadh cothrom le dáta in 2010 agus “Comhlánú GIS de Chineálacha Foraoise Friuli Venezia Giulia” a rinneadh in 2011 agus a bailíochtaíodh go cinntitheach in 2013. Constituye la colección actualizada de las geometrías de las zonas forestales distinguidas por tipo y situadas en el territorio de la región de Friuli Venezia Giulia. La mayor parte de estas zonas están ocupadas por bosques tal como se definen en la Ley Forestal Regional (N.º9/2007). Las geometrías provienen de dos geodatabases diferentes: «Tipos Forestali 1998», actualizado en 2010 y «Completación del SIG de los tipos forestales de Friuli Venezia Giulia», llevado a cabo en 2011 y validado definitivamente en 2013. Constituye la colección actualizada de las geometrías de las zonas forestales distinguidas por tipo y situadas en el territorio de la región de Friuli Venezia Giulia. La mayor parte de estas zonas están ocupadas por bosques tal como se definen en la Ley Forestal Regional (N.º9/2007). Las geometrías provienen de dos geodatabases diferentes: «Tipos Forestali 1998», actualizado en 2010 y «Completación del SIG de los tipos forestales de Friuli Venezia Giulia», llevado a cabo en 2011 y validado definitivamente en 2013. Dan jikkostitwixxi l-ġbir aġġornat tal-ġeometriji taż-żoni forestali distinti skont it-tip u li jinsabu fit-territorju tar-Reġjun ta’ Friuli Venezia Giulia. Il-biċċa l-kbira ta’ dawn iż-żoni huma okkupati minn foresti kif definit mil-Liġi Reġjonali dwar il-Foresti (Nru.9/2007). Il-ġeometriji ġejjin minn żewġ ġeobażijiet tad-data differenti: “Types Forestali 1998”, aġġornata fl-2010 u “Tlestija tal-GIS tat-Tipi ta’ Foresti ta’ Friuli Venezia Giulia” imwettqa fl-2011 u vvalidata b’mod definittiv fl-2013. Dan jikkostitwixxi l-ġbir aġġornat tal-ġeometriji taż-żoni forestali distinti skont it-tip u li jinsabu fit-territorju tar-Reġjun ta’ Friuli Venezia Giulia. Il-biċċa l-kbira ta’ dawn iż-żoni huma okkupati minn foresti kif definit mil-Liġi Reġjonali dwar il-Foresti (Nru.9/2007). Il-ġeometriji ġejjin minn żewġ ġeobażijiet tad-data differenti: “Types Forestali 1998”, aġġornata fl-2010 u “Tlestija tal-GIS tat-Tipi ta’ Foresti ta’ Friuli Venezia Giulia” imwettqa fl-2011 u vvalidata b’mod definittiv fl-2013. Constitui a coleção atualizada das geometrias das áreas florestais distinguidas por tipo e localizadas no território da Região Friuli Venezia Giulia. A maior parte destas áreas é ocupada por florestas, tal como definidas na Lei Regional das Florestas (n.º 9/2007). As geometrias vêm de duas bases de dados geométricas diferentes: «Tipos Forestali 1998», atualizado em 2010 e «Conclusão do SIG dos Tipos Florestais de Friuli Venezia Giulia», realizado em 2011 e validado definitivamente em 2013. Constitui a coleção atualizada das geometrias das áreas florestais distinguidas por tipo e localizadas no território da Região Friuli Venezia Giulia. A maior parte destas áreas é ocupada por florestas, tal como definidas na Lei Regional das Florestas (n.º 9/2007). As geometrias vêm de duas bases de dados geométricas diferentes: «Tipos Forestali 1998», atualizado em 2010 e «Conclusão do SIG dos Tipos Florestais de Friuli Venezia Giulia», realizado em 2011 e validado definitivamente em 2013. Тя представлява актуализираната колекция от геометрии на горските райони, които се отличават по тип и се намират на територията на регион Friuli Venezia Giulia. Повечето от тези площи са заети от гори, определени в Регионалния закон за горите (№ 9 от 2007 г.). Геометриите идват от две различни геобази: „Types Forestali 1998„, актуализиран през 2010 г. и „Завършване на ГИС за типовете гори на Friuli Venezia Giulia“, извършени през 2011 г. и окончателно валидирани през 2013 г. Тя представлява актуализираната колекция от геометрии на горските райони, които се отличават по тип и се намират на територията на регион Friuli Venezia Giulia. Повечето от тези площи са заети от гори, определени в Регионалния закон за горите (№ 9 от 2007 г.). Геометриите идват от две различни геобази: „Types Forestali 1998„, актуализиран през 2010 г. и „Завършване на ГИС за типовете гори на Friuli Venezia Giulia“, извършени през 2011 г. и окончателно валидирани през 2013 г. Představuje aktualizovaný soubor geometrií lesních oblastí rozlišených podle druhu a nacházejících se na území regionu Friuli Venezia Giulia. Většina těchto oblastí je obydlena lesy, jak je definováno v regionálním lesním zákoně (č.9/2007). Geometrie pocházejí ze dvou různých geodatabází: „Types Forestali 1998“, aktualizované v roce 2010 a „Dokončení GIS lesních typů Friuli Venezia Giulia“ provedené v roce 2011 a s konečnou platností potvrzené v roce 2013. Představuje aktualizovaný soubor geometrií lesních oblastí rozlišených podle druhu a nacházejících se na území regionu Friuli Venezia Giulia. Většina těchto oblastí je obydlena lesy, jak je definováno v regionálním lesním zákoně (č.9/2007). Geometrie pocházejí ze dvou různých geodatabází: „Types Forestali 1998“, aktualizované v roce 2010 a „Dokončení GIS lesních typů Friuli Venezia Giulia“ provedené v roce 2011 a s konečnou platností potvrzené v roce 2013. Det utgör den uppdaterade samlingen av geometrier i de skogsområden som kännetecknas av typ och ligger i regionen Friuli Venezia Giulia. De flesta av dessa områden är bebodda av skogar enligt definitionen i den regionala skogslagen (nr.9/2007). Geometrierna kommer från två olika geodatabaser: ”Types Forestali 1998”, uppdaterad 2010 och ”Slutförande av GIS för skogstyperna av Friuli Venezia Giulia” som genomfördes 2011 och godkändes slutgiltigt 2013. Det utgör den uppdaterade samlingen av geometrier i de skogsområden som kännetecknas av typ och ligger i regionen Friuli Venezia Giulia. De flesta av dessa områden är bebodda av skogar enligt definitionen i den regionala skogslagen (nr.9/2007). Geometrierna kommer från två olika geodatabaser: ”Types Forestali 1998”, uppdaterad 2010 och ”Slutförande av GIS för skogstyperna av Friuli Venezia Giulia” som genomfördes 2011 och godkändes slutgiltigt 2013. Predstavuje aktualizovaný zber geometrií lesných oblastí, ktoré sa vyznačujú podľa typu a nachádzajú sa na území regiónu Friuli Venezia Giulia. Väčšinu týchto oblastí obsadzujú lesy vymedzené v regionálnom zákone o lesoch (č.9/2007). Geometrie pochádzajú z dvoch rôznych geodatabáz: „Types Forestali 1998“, aktualizované v roku 2010 a „Ukončenie GIS druhov lesov Friuli Venezia Giulia“ vykonané v roku 2011 a definitívne potvrdené v roku 2013. Predstavuje aktualizovaný zber geometrií lesných oblastí, ktoré sa vyznačujú podľa typu a nachádzajú sa na území regiónu Friuli Venezia Giulia. Väčšinu týchto oblastí obsadzujú lesy vymedzené v regionálnom zákone o lesoch (č.9/2007). Geometrie pochádzajú z dvoch rôznych geodatabáz: „Types Forestali 1998“, aktualizované v roku 2010 a „Ukončenie GIS druhov lesov Friuli Venezia Giulia“ vykonané v roku 2011 a definitívne potvrdené v roku 2013. Tai yra atnaujintas miško plotų, išskirtų pagal tipą ir esančių Friulio-Venecijos Džulijos regiono teritorijoje, geometrijų rinkinys. Daugumą šių vietovių užima miškai, kaip apibrėžta Regioniniame miškų įstatyme (Nr.9/2007). Geometrijos yra iš dviejų skirtingų geoduomenų bazių: „Types Forestali 1998“, atnaujintas 2010 m. ir „Friuli Venezia Giulia miškų tipų GIS užbaigimas“, atliktas 2011 m. ir galutinai patvirtintas 2013 m. Tai yra atnaujintas miško plotų, išskirtų pagal tipą ir esančių Friulio-Venecijos Džulijos regiono teritorijoje, geometrijų rinkinys. Daugumą šių vietovių užima miškai, kaip apibrėžta Regioniniame miškų įstatyme (Nr.9/2007). Geometrijos yra iš dviejų skirtingų geoduomenų bazių: „Types Forestali 1998“, atnaujintas 2010 m. ir „Friuli Venezia Giulia miškų tipų GIS užbaigimas“, atliktas 2011 m. ir galutinai patvirtintas 2013 m. Αποτελεί την επικαιροποιημένη συλλογή των γεωμετριών των δασικών περιοχών που διακρίνονται ανά τύπο και βρίσκονται στο έδαφος της περιφέρειας Friuli Venezia Giulia. Οι περισσότερες από αυτές τις περιοχές καταλαμβάνονται από δάση, όπως ορίζονται στον περιφερειακό νόμο για τα δάση (αριθ. 9/2007). Οι γεωμετρίες προέρχονται από δύο διαφορετικές βάσεις δεδομένων: «Τύποι Forestali 1998», που επικαιροποιήθηκαν το 2010 και «Ολοκλήρωση του ΣΓΠ των τύπων δασών Friuli Venezia Giulia» που πραγματοποιήθηκαν το 2011 και επικυρώθηκαν οριστικά το 2013.

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    Authors: Gebruk, Anna; Dgebuadze, Polina; Rogozhin, Vladimir; Ermilova, Yulia; +2 Authors

    The dataset comprises full list of species of macrozoobenthos collected from the Pechora Sea (SE Barents Sea). Grab samples were collected from 10 stations in the Pechora Bay from aboard RV Kartesh in 2020-2021. Macrobenthic invertebrates were identified with the maximum level of certainty through optical microscopy using regional taxonomic keys. All taxonomic names were standardised using the World Register of Marine Species (WoRMS). All specimens have been counted and weighted (wet biomass) on Ohaus Adventurer scales with reported accuracy to 0.01 g. Bivalve molluscs and gastropods were weighed in shells. Biomass (g. m-2) and abundance (ind m-2) are used to characterise macrozoobenthos. The sampling and identification work was carried out in collaboration with specialists from Lomonosov Moscow State University Marine Research Center and P.P. Shirshov Institute of Oceanology.

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    MASSIMO is a distance-independent individual-tree simulator that represents demographic processes (regeneration, growth and mortality) with empirical models that have been parameterized with data from the Swiss NFI. Tree regeneration, growth and mortality are simulated on the regular grid of sample plots of the Swiss NFI, which allows for statistically representative simulations of forest development. ![alt text](https://www.envidat.ch/dataset/8fd996d1-aa7e-41b1-ae6d-1192582c62cc/resource/a12e2cfd-da45-4faf-8291-446c5763ac3c/download/massimo2swissforlab.png)

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    Authors: Fedra Trujillano; G. Jiménez; Luis Edgar Tarazona-Manrique; Najat F. Kahamba; +5 Authors

    Abstract Background In the near future, the incidence of mosquito-borne diseases may expand to new sites due to changes in temperature and rainfall patterns caused by climate change. Therefore, there is a need to use recent technological advances to improve vector surveillance methodologies. Unoccupied Aerial Vehicles (UAVs), often called drones, have been used to collect high-resolution imagery to map detailed information on mosquito habitats and direct control measures to specific areas. Supervised classification approaches have been largely used to automatically detect vector habitats. However, manual data labelling for model training limits their use for rapid responses. Open-source foundation models such as the Meta AI Segment Anything Model (SAM) can facilitate the manual digitalization of high-resolution images. This pre-trained model can assist in extracting features of interest in a diverse range of images. Here, we evaluated the performance of SAM through the Samgeo package, a Python-based wrapper for geospatial data, as it has not been applied to analyse remote sensing images for epidemiological studies. Results We tested the identification of two land cover classes of interest: water bodies and human settlements, using different UAV acquired imagery across five malaria-endemic areas in Africa, South America, and Southeast Asia. We employed manually placed point prompts and text prompts associated with specific classes of interest to guide the image segmentation and assessed the performance in the different geographic contexts. An average Dice coefficient value of 0.67 was obtained for buildings segmentation and 0.73 for water bodies using point prompts. Regarding the use of text prompts, the highest Dice coefficient value reached 0.72 for buildings and 0.70 for water bodies. Nevertheless, the performance was closely dependent on each object, landscape characteristics and selected words, resulting in varying performance. Conclusions Recent models such as SAM can potentially assist manual digitalization of imagery by vector control programs, quickly identifying key features when surveying an area of interest. However, accurate segmentation still requires user-provided manual prompts and corrections to obtain precise segmentation. Further evaluations are necessary, especially for applications in rural areas.

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    International Journal of Health Geographics
    Article . 2024 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
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    https://dx.doi.org/10.60692/78...
    Other literature type . 2024
    Data sources: Datacite
    https://dx.doi.org/10.60692/z1...
    Other literature type . 2024
    Data sources: Datacite
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      International Journal of Health Geographics
      Article . 2024 . Peer-reviewed
      License: CC BY
      Data sources: Crossref
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      https://dx.doi.org/10.60692/78...
      Other literature type . 2024
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      https://dx.doi.org/10.60692/z1...
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: de Vries, Joost; Poulton, Alex J.; Young, Jeremy R.; Monteiro, Fanny M.; +5 Authors

    CASCADE is a global dataset for 139 extant coccolithophore taxonomic units. CASCADE includes a trait database (size and cellular organic and inorganic carbon contents) and taxonomic-specific global spatiotemporal distributions (Lat/Lon/Depth/Month/Year) of coccolithophore abundance and organic and inorganic carbon stocks. CASCADE covers all ocean basins over the upper 275 meters, spans the years 1964-2019 and includes 33,119 taxonomic-specific abundance observations. Within CASCADE, we characterise the underlying uncertainties due to measurement errors by propagating error estimates between the different studies. Full details of the data set are provided in the associated Scientific Data manuscript. The repository contains five main folders: 1) "Classification", which contains YAML files with synonyms, family-level classifications, and life cycle phase associations and definitions; 2) "Concatenated literature", which contains the merged datasets of size, PIC and POC and which were corrected for taxonomic unit synonyms; 3) "Resampled cellular datasets", which contains the resampled datasets of size, PIC and POC in long format as well as a summary table; 4) "Gridded data sets", which contains gridded datasets of abundance, PIC and POC; 5) "Species lists", which contains spreadsheets of the "common" (>20 obs) and "rare" (<20 obs) species and their number of observations. The CASCADE data set can be easily reproduced using the scripts and data provided in the associated github repository: https://github.com/nanophyto/CASCADE/ (zenodo.12797197) Correspondence to: Joost de Vries, joost.devries@bristol.ac.uk v.0.1.2 has some fixes: 1. The wrongly specified S. neapolitana was removed from synonyms.yml (this species is now S. nana)2. Longitudes were corrected for Guerreiro et al., 20233. A double entry for Dimizia et al., 2015 was fixed4. Units in Sal et al., 2013 were correct to cells/L (previously cells/ml)5. Data from Sal et al., 2013 was re-done, as some species were missing6. Duplicate entries from Baumann et al., 2000 were dropped

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    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: ZENODO
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    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2024
      License: CC BY
      Data sources: ZENODO
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      ZENODO
      Dataset . 2024
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2024
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2024
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2024
      License: CC BY
      Data sources: Datacite
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    Πρόκειται για τη συλλογή των γεωμετριών των δασικών περιοχών που βρίσκονται στο έδαφος της περιφέρειας Friuli Venezia Giulia. Οι περισσότερες από αυτές τις περιοχές καταλαμβάνονται από δάση, όπως ορίζονται στον περιφερειακό νόμο για τα δάση (αριθ. 9/2007). Οι γεωμετρίες προέρχονται από δύο διαφορετικές βάσεις δεδομένων: «Τύποι Forestali 1998», που επικαιροποιήθηκαν το 2010 και «Ολοκλήρωση του ΣΓΠ των τύπων δασών Friuli Venezia Giulia» που πραγματοποιήθηκαν το 2011 και επικυρώθηκαν οριστικά το 2013. Is é an bailiúchán de geometries na limistéar foraoise atá suite i gcríoch Réigiún Friuli Venezia Giulia. Tá an chuid is mó de na limistéir sin á n-áitiú ag foraoisí mar a shainítear leis an Dlí Réigiúnach Foraoise (Uimh.9/2007). Tagann na geoiméadrachtaí ó dhá bhunachar sonraí éagsúla: “Cineálacha Forestali 1998”, a tugadh cothrom le dáta in 2010 agus “Comhlánú GIS de Chineálacha Foraoise Friuli Venezia Giulia” a rinneadh in 2011 agus a bailíochtaíodh go cinntitheach in 2013. Es la colección de las geometrías de las zonas forestales ubicadas en el territorio de la región de Friuli Venezia Giulia. La mayor parte de estas zonas están ocupadas por bosques tal como se definen en la Ley Forestal Regional (N.º9/2007). Las geometrías provienen de dos geodatabases diferentes: «Tipos Forestali 1998», actualizado en 2010 y «Completación del SIG de los tipos forestales de Friuli Venezia Giulia», llevado a cabo en 2011 y validado definitivamente en 2013. Il s’agit de la collection des géométries des zones forestières situées sur le territoire de la région du Frioul-Vénétie Giulia. La plupart de ces zones sont occupées par des forêts telles que définies par la loi forestière régionale (No.9/2007). Les géométries proviennent de deux bases de données différentes: «Types Forestali 1998», mis à jour en 2010 et «Achevée du SIG des types forestiers du Frioul Venezia Giulia» réalisée en 2011 et validée définitivement en 2013. Costituisce la raccolta delle geometrie delle aree forestali situate nel territorio della Regione Friuli Venezia Giulia. In buona parte si tratta di superfici occupate da boschi così come definiti dalla vigente legge forestale regionale (n.9/2007). Le geometrie provengono da due diversi geodatabase: "Tipi Forestali 1998", aggiornato nel 2010 e "Completamento del GIS dei Tipi forestali del Friuli Venezia Giulia" realizzato nel 2011 e validato definitivamente nel 2013. Het is de verzameling van de geometrieën van de bosgebieden gelegen op het grondgebied van de regio Friuli Venezia Giulia. De meeste van deze gebieden worden bewoond door bossen zoals gedefinieerd in de Regional Forest Law (nr.9/2007). De geometrieën zijn afkomstig van twee verschillende geodatabases: „Types Forestali 1998”, bijgewerkt in 2010 en „Voltooiing van het GIS van de bossoorten Friuli Venezia Giulia”, uitgevoerd in 2011 en definitief gevalideerd in 2013. Huwa l-ġbir tal-ġeometriji taż-żoni forestali li jinsabu fit-territorju tar-Reġjun ta’ Friuli Venezia Giulia. Il-biċċa l-kbira ta’ dawn iż-żoni huma okkupati minn foresti kif definit mil-Liġi Reġjonali dwar il-Foresti (Nru.9/2007). Il-ġeometriji ġejjin minn żewġ ġeobażijiet tad-data differenti: “Types Forestali 1998”, aġġornata fl-2010 u “Tlestija tal-GIS tat-Tipi ta’ Foresti ta’ Friuli Venezia Giulia” imwettqa fl-2011 u vvalidata b’mod definittiv fl-2013. Este colecția geometriilor zonelor forestiere situate pe teritoriul regiunii Friuli Venezia Giulia. Cele mai multe dintre aceste zone sunt ocupate de păduri, astfel cum sunt definite în Legea regională privind pădurile (nr.9/2007). Geometriile provin din două baze de date geografice diferite: „Tipuri Forestali 1998”, actualizat în 2010 și „Finalizarea GIS a tipurilor de păduri de Friuli Venezia Giulia”, efectuată în 2011 și validată definitiv în 2013. É a coleção das geometrias das áreas florestais localizadas no território da Região Friuli Venezia Giulia. A maior parte destas áreas é ocupada por florestas, tal como definidas na Lei Regional das Florestas (n.º 9/2007). As geometrias vêm de duas bases de dados geométricas diferentes: «Tipos Forestali 1998», atualizado em 2010 e «Conclusão do SIG dos Tipos Florestais de Friuli Venezia Giulia», realizado em 2011 e validado definitivamente em 2013. It is the collection of the geometries of the forest areas located in the territory of the Friuli Venezia Giulia Region. Most of these areas are occupied by forests as defined by the Regional Forest Law (No.9/2007). The geometries come from two different geodatabases: “Types Forestali 1998”, updated in 2010 and “Completion of the GIS of the Forest Types of Friuli Venezia Giulia” carried out in 2011 and validated definitively in 2013.

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    Authors: Ferreira, Igor José Malfetoni; Campanharo, Wesley Augusto; Fonseca, Marisa Gesteira; Escada, Maria Isabel Sobral; +7 Authors

    This file collection contains the estimated spatial distribution of the above-ground biomass density (AGB) by the end of the 21st century across the Brazilian Atlantic Forest domain and the respective uncertanty. To develop the models, we used the maximum entropy method with projected climate data to 2100, based on the Intergovernmental Panel on Climate Change (IPCC) Representative Concentration Pathway (RCP) 4.5 from the fifth Assessment Report (AR5). The dataset is composed of four files in GeoTIFF format: calibrated-AGB-distribution.tif: raster file representing the present spatial distribution of the above-ground biomass density in the Atlantic Forest from the calibrated model. Unit: Mg/ha estimated-uncertanty-for-calibrated-agb-distribution.tif: raster file representing the estimated spatial uncertanty distribution of the calibrated above-ground biomass density. Unit: percentage. projected-AGB-distribution-under-rcp45.tif: raster file representing the projected spatial distribution of the above-ground biomass density in the Atlantic Forest by the end of 2100 under RCP 4.5 scenario. Unit: Mg/ha estimated-uncertanty-for-projected-agb-distribution.tif: raster file representing the estimated spatial uncertanty distribution of the projected above-ground biomass density. Unit: percentage. Spatial resolution: 0.0083 degree (ca. 1 km) Coordinate reference system: Geographic Coordinate System - Datum WGS84

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    ZENODO
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    ZENODO
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    Authors: Horton, Tammy; Serpell-Stevens, Amanda; Domedel, Georgina Valls; Bett, Brian James;

    These data record the results of processing otter trawl catches (OTSB14; Merrett & Marshall, 1980) from the National Oceanography Centre (NOC, UK) long-term study of the Porcupine Abyssal Plain (PAP), including the PAP-Sustained Observatory time-series. The data concern catches recovered during the RRS Challenger cruise 135 in 1997. Billett, D.S.M. et al. (1998). RRS Challenger Cruise 135, 15 Oct-30 Oct 1997. BENGAL: High resolution temporal and spatial study of the BENthic biology and Geochemistry of a north-eastern Atlantic abyssal Locality. Southampton Oceanography Centre Cruise Report, No. 19, 49pp.| https://www.bodc.ac.uk/resources/inventories/cruise_inventory/reports/ch135_97.pdf

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    Global Biodiversity Information Facility
    Dataset . 2024
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      Global Biodiversity Information Facility
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    Description: Leaf and invertebrate biomass in streams Project: This dataset was collected as part of the following SAFE research project: A preliminary study of the allochthonous inputs into tropical streams across a land use gradient in Sabah, Malaysia XML metadata: GEMINI compliant metadata for this dataset is available here Data worksheets: There are 2 data worksheets in this dataset: Insects (Worksheet Insects) Dimensions: 23 rows by 11 columns Description: Insect capture rates Fields: Location: SAFE project riparian site (Field type: Location) Stream: SAFE project stream (Field type: ID) Repeat: sample number for that stream (Field type: ID) Total Mass of Insects (g): the total dried mass of insects collected for each of the repeats (Field type: Numeric) Total Insects: the total number of insects collected in each repeat (Field type: Abundance) Hymenoptera: the total number of hymenoptera in each repeat (Field type: Abundance) Diptera: the total number of diptera in each repeat (Field type: Abundance) Coleoptera: the total number of coleoptera in each repeat (Field type: Abundance) Other.Insect: the grouped total of Hemiptera, Thysanoptera, Orthoptera, Blattodea, Trichoptera, Mantodea, Ephemeroptera, Dermaptera for each repeat (Field type: Abundance) Other: the grouped total of Arachnida, Entognatha, Diplopoda, Chilopoda for each repeat (Field type: Abundance) Hydrology (Worksheet Hydrology) Dimensions: 60 rows by 17 columns Description: River characteristics and litter quantities Fields: Location: SAFE project riparian site (Field type: Location) Stream Code: The stream from which the sample was taken (LFE, 15m, 30m, VJR or OP) (Field type: ID) Transect No.: The point of each sample within the 100m transect at each stream (Field type: ID) Channel Width: The bank full width of the channel at this point (Field type: Numeric) Wetted Width: The width of the runnin water at this point (Field type: Numeric) SAFE Habitat Quality Right: the SAFE Habitat quality on the right of the channel when looking upstream (Field type: Ordered Categorical) SAFE Habitat Quality Centre: the SAFE Habitat quality in the centre of the channel when looking upstream (Field type: Ordered Categorical) SAFE Habitat Quality Left: the SAFE Habitat quality on the left of the channel when looking upstream (Field type: Ordered Categorical) Flow Rate Right (s): the time taken for a tennis ball to travel 10m in the water on the right of the channel when looking upstream (Field type: Numeric) Flow Rate Centre (s): the time taken for a tennis ball to travel 10m in the water in the centre of the channel when looking upstream (Field type: Numeric) Flow Rate Left (s): the time taken for a tennis ball to travel 10m in the water on the left of the channel when looking upstream (Field type: Numeric) Average Flow Rate (s): an average of flow rate centre, flow rate left and flow rate right (Field type: Numeric) Leaf Litter Retention (g): the dried mass of leaf litter retained across the wetted width of the stream at each point (Field type: Numeric) Average Substrate Size: the average size of the substrate across the channel width of the stream at each point (Field type: Numeric) Leaf Litter Trap Position: the position where the leaf litter trap was placed relative to the stream when looking upstream (left, right or centre) (Field type: Categorical) Leaf Litter Mass: the dried mass of leaf litter collected in the leaf litter trap at each point (Field type: Numeric) Date range: 2017-02-06 to 2017-07-06 Latitudinal extent: 4.6314 to 4.7273 Longitudinal extent: 117.4556 to 117.6233 Taxonomic coverage: All taxon names are validated against the GBIF backbone taxonomy. If a dataset uses a synonym, the accepted usage is shown followed by the dataset usage in brackets. Taxa that cannot be validated, including new species and other unknown taxa, morphospecies, functional groups and taxonomic levels not used in the GBIF backbone are shown in square brackets. Animalia - Arthropoda - - Insecta - - - Coleoptera - - - Diptera - - - Hymenoptera - - [Other.Insect]

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    ZENODO
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    ZENODO
    Dataset . 2018
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    ZENODO
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    Authors: John W. Williams, Karyn Tabor;

    This dataset contains two metrics for climate change exposure using downscaled climate projections with the SRES A2 emissions scenario (Tabor and Williams, 2007).The metrics represent dissimilarity measurements of the squared Euclidean distance between seasonal (June–August and December–February) temperature and precipitation variables in the 20th century climate and mid-21st century climate. (1) disappearing climate risk - measure of dissimilarity between a pixel’s late 20th century climate and its closest matching pixel in the global set of 21st-century climates (2) novel climate risk - measure of dissimilarity between a pixel’s future climate and its closest matching pixel in the global set of late 20th-century climates. The data are in arcASCII format. All data are in units of standard Euclidean distance and multiplied by 1000. This is the original data. To scale the data similar to Tabor et al. (2018), remove outliers above the 99th percentile distribution before rescaling from 0-1. Unprojected number of columns 2160 number of rows 857 Lower Left X Center -179.917 Lower Left Y Center -59.084 Cell size 0.166667 decimal degrees (10 minutes or ~17 km) {"references": ["Tabor, K. et al. (2018). Tropical Protected Areas Under Increasing Threats from Climate Change and Deforestation: https://doi.org/10.3390/land7030090", "Tabor and Williams (2010). Globally downscaled climate projections for assessing the conservation impacts of climate change. https://doi.org/10.1890/09-0173.1", "Williams, J.W. et al. (2007). Projected distributions of novel and disappearing climates by 20100 AD. https://doi.org/10.1073/pnas.0606292104"]} Support for this project was provided by Conservation International, the Land Tenure Center at the University of Wisconsin, the Center for Climatic Research at the University of Wisconsin, and the Environment Program at the University of Wisconsin–Madison. This research has been funded in part by the Walton Family Foundation, the Gordon and Betty Moore Foundation, and a gift from Betty and Gordon Moore.

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    Is éard atá ann bailiúchán nuashonraithe de gheoiméadrachtaí na limistéar foraoise a bhfuil idirdhealú cineáil eatarthu agus atá suite i gcríoch Réigiún Friuli Venezia Giulia. Tá an chuid is mó de na limistéir sin á n-áitiú ag foraoisí mar a shainítear leis an Dlí Réigiúnach Foraoise (Uimh.9/2007). Tagann na geoiméadrachtaí ó dhá bhunachar sonraí éagsúla: “Cineálacha Forestali 1998”, a tugadh cothrom le dáta in 2010 agus “Comhlánú GIS de Chineálacha Foraoise Friuli Venezia Giulia” a rinneadh in 2011 agus a bailíochtaíodh go cinntitheach in 2013. Is éard atá ann bailiúchán nuashonraithe de gheoiméadrachtaí na limistéar foraoise a bhfuil idirdhealú cineáil eatarthu agus atá suite i gcríoch Réigiún Friuli Venezia Giulia. Tá an chuid is mó de na limistéir sin á n-áitiú ag foraoisí mar a shainítear leis an Dlí Réigiúnach Foraoise (Uimh.9/2007). Tagann na geoiméadrachtaí ó dhá bhunachar sonraí éagsúla: “Cineálacha Forestali 1998”, a tugadh cothrom le dáta in 2010 agus “Comhlánú GIS de Chineálacha Foraoise Friuli Venezia Giulia” a rinneadh in 2011 agus a bailíochtaíodh go cinntitheach in 2013. Constituye la colección actualizada de las geometrías de las zonas forestales distinguidas por tipo y situadas en el territorio de la región de Friuli Venezia Giulia. La mayor parte de estas zonas están ocupadas por bosques tal como se definen en la Ley Forestal Regional (N.º9/2007). Las geometrías provienen de dos geodatabases diferentes: «Tipos Forestali 1998», actualizado en 2010 y «Completación del SIG de los tipos forestales de Friuli Venezia Giulia», llevado a cabo en 2011 y validado definitivamente en 2013. Constituye la colección actualizada de las geometrías de las zonas forestales distinguidas por tipo y situadas en el territorio de la región de Friuli Venezia Giulia. La mayor parte de estas zonas están ocupadas por bosques tal como se definen en la Ley Forestal Regional (N.º9/2007). Las geometrías provienen de dos geodatabases diferentes: «Tipos Forestali 1998», actualizado en 2010 y «Completación del SIG de los tipos forestales de Friuli Venezia Giulia», llevado a cabo en 2011 y validado definitivamente en 2013. Dan jikkostitwixxi l-ġbir aġġornat tal-ġeometriji taż-żoni forestali distinti skont it-tip u li jinsabu fit-territorju tar-Reġjun ta’ Friuli Venezia Giulia. Il-biċċa l-kbira ta’ dawn iż-żoni huma okkupati minn foresti kif definit mil-Liġi Reġjonali dwar il-Foresti (Nru.9/2007). Il-ġeometriji ġejjin minn żewġ ġeobażijiet tad-data differenti: “Types Forestali 1998”, aġġornata fl-2010 u “Tlestija tal-GIS tat-Tipi ta’ Foresti ta’ Friuli Venezia Giulia” imwettqa fl-2011 u vvalidata b’mod definittiv fl-2013. Dan jikkostitwixxi l-ġbir aġġornat tal-ġeometriji taż-żoni forestali distinti skont it-tip u li jinsabu fit-territorju tar-Reġjun ta’ Friuli Venezia Giulia. Il-biċċa l-kbira ta’ dawn iż-żoni huma okkupati minn foresti kif definit mil-Liġi Reġjonali dwar il-Foresti (Nru.9/2007). Il-ġeometriji ġejjin minn żewġ ġeobażijiet tad-data differenti: “Types Forestali 1998”, aġġornata fl-2010 u “Tlestija tal-GIS tat-Tipi ta’ Foresti ta’ Friuli Venezia Giulia” imwettqa fl-2011 u vvalidata b’mod definittiv fl-2013. Constitui a coleção atualizada das geometrias das áreas florestais distinguidas por tipo e localizadas no território da Região Friuli Venezia Giulia. A maior parte destas áreas é ocupada por florestas, tal como definidas na Lei Regional das Florestas (n.º 9/2007). As geometrias vêm de duas bases de dados geométricas diferentes: «Tipos Forestali 1998», atualizado em 2010 e «Conclusão do SIG dos Tipos Florestais de Friuli Venezia Giulia», realizado em 2011 e validado definitivamente em 2013. Constitui a coleção atualizada das geometrias das áreas florestais distinguidas por tipo e localizadas no território da Região Friuli Venezia Giulia. A maior parte destas áreas é ocupada por florestas, tal como definidas na Lei Regional das Florestas (n.º 9/2007). As geometrias vêm de duas bases de dados geométricas diferentes: «Tipos Forestali 1998», atualizado em 2010 e «Conclusão do SIG dos Tipos Florestais de Friuli Venezia Giulia», realizado em 2011 e validado definitivamente em 2013. Тя представлява актуализираната колекция от геометрии на горските райони, които се отличават по тип и се намират на територията на регион Friuli Venezia Giulia. Повечето от тези площи са заети от гори, определени в Регионалния закон за горите (№ 9 от 2007 г.). Геометриите идват от две различни геобази: „Types Forestali 1998„, актуализиран през 2010 г. и „Завършване на ГИС за типовете гори на Friuli Venezia Giulia“, извършени през 2011 г. и окончателно валидирани през 2013 г. Тя представлява актуализираната колекция от геометрии на горските райони, които се отличават по тип и се намират на територията на регион Friuli Venezia Giulia. Повечето от тези площи са заети от гори, определени в Регионалния закон за горите (№ 9 от 2007 г.). Геометриите идват от две различни геобази: „Types Forestali 1998„, актуализиран през 2010 г. и „Завършване на ГИС за типовете гори на Friuli Venezia Giulia“, извършени през 2011 г. и окончателно валидирани през 2013 г. Představuje aktualizovaný soubor geometrií lesních oblastí rozlišených podle druhu a nacházejících se na území regionu Friuli Venezia Giulia. Většina těchto oblastí je obydlena lesy, jak je definováno v regionálním lesním zákoně (č.9/2007). Geometrie pocházejí ze dvou různých geodatabází: „Types Forestali 1998“, aktualizované v roce 2010 a „Dokončení GIS lesních typů Friuli Venezia Giulia“ provedené v roce 2011 a s konečnou platností potvrzené v roce 2013. Představuje aktualizovaný soubor geometrií lesních oblastí rozlišených podle druhu a nacházejících se na území regionu Friuli Venezia Giulia. Většina těchto oblastí je obydlena lesy, jak je definováno v regionálním lesním zákoně (č.9/2007). Geometrie pocházejí ze dvou různých geodatabází: „Types Forestali 1998“, aktualizované v roce 2010 a „Dokončení GIS lesních typů Friuli Venezia Giulia“ provedené v roce 2011 a s konečnou platností potvrzené v roce 2013. Det utgör den uppdaterade samlingen av geometrier i de skogsområden som kännetecknas av typ och ligger i regionen Friuli Venezia Giulia. De flesta av dessa områden är bebodda av skogar enligt definitionen i den regionala skogslagen (nr.9/2007). Geometrierna kommer från två olika geodatabaser: ”Types Forestali 1998”, uppdaterad 2010 och ”Slutförande av GIS för skogstyperna av Friuli Venezia Giulia” som genomfördes 2011 och godkändes slutgiltigt 2013. Det utgör den uppdaterade samlingen av geometrier i de skogsområden som kännetecknas av typ och ligger i regionen Friuli Venezia Giulia. De flesta av dessa områden är bebodda av skogar enligt definitionen i den regionala skogslagen (nr.9/2007). Geometrierna kommer från två olika geodatabaser: ”Types Forestali 1998”, uppdaterad 2010 och ”Slutförande av GIS för skogstyperna av Friuli Venezia Giulia” som genomfördes 2011 och godkändes slutgiltigt 2013. Predstavuje aktualizovaný zber geometrií lesných oblastí, ktoré sa vyznačujú podľa typu a nachádzajú sa na území regiónu Friuli Venezia Giulia. Väčšinu týchto oblastí obsadzujú lesy vymedzené v regionálnom zákone o lesoch (č.9/2007). Geometrie pochádzajú z dvoch rôznych geodatabáz: „Types Forestali 1998“, aktualizované v roku 2010 a „Ukončenie GIS druhov lesov Friuli Venezia Giulia“ vykonané v roku 2011 a definitívne potvrdené v roku 2013. Predstavuje aktualizovaný zber geometrií lesných oblastí, ktoré sa vyznačujú podľa typu a nachádzajú sa na území regiónu Friuli Venezia Giulia. Väčšinu týchto oblastí obsadzujú lesy vymedzené v regionálnom zákone o lesoch (č.9/2007). Geometrie pochádzajú z dvoch rôznych geodatabáz: „Types Forestali 1998“, aktualizované v roku 2010 a „Ukončenie GIS druhov lesov Friuli Venezia Giulia“ vykonané v roku 2011 a definitívne potvrdené v roku 2013. Tai yra atnaujintas miško plotų, išskirtų pagal tipą ir esančių Friulio-Venecijos Džulijos regiono teritorijoje, geometrijų rinkinys. Daugumą šių vietovių užima miškai, kaip apibrėžta Regioniniame miškų įstatyme (Nr.9/2007). Geometrijos yra iš dviejų skirtingų geoduomenų bazių: „Types Forestali 1998“, atnaujintas 2010 m. ir „Friuli Venezia Giulia miškų tipų GIS užbaigimas“, atliktas 2011 m. ir galutinai patvirtintas 2013 m. Tai yra atnaujintas miško plotų, išskirtų pagal tipą ir esančių Friulio-Venecijos Džulijos regiono teritorijoje, geometrijų rinkinys. Daugumą šių vietovių užima miškai, kaip apibrėžta Regioniniame miškų įstatyme (Nr.9/2007). Geometrijos yra iš dviejų skirtingų geoduomenų bazių: „Types Forestali 1998“, atnaujintas 2010 m. ir „Friuli Venezia Giulia miškų tipų GIS užbaigimas“, atliktas 2011 m. ir galutinai patvirtintas 2013 m. Αποτελεί την επικαιροποιημένη συλλογή των γεωμετριών των δασικών περιοχών που διακρίνονται ανά τύπο και βρίσκονται στο έδαφος της περιφέρειας Friuli Venezia Giulia. Οι περισσότερες από αυτές τις περιοχές καταλαμβάνονται από δάση, όπως ορίζονται στον περιφερειακό νόμο για τα δάση (αριθ. 9/2007). Οι γεωμετρίες προέρχονται από δύο διαφορετικές βάσεις δεδομένων: «Τύποι Forestali 1998», που επικαιροποιήθηκαν το 2010 και «Ολοκλήρωση του ΣΓΠ των τύπων δασών Friuli Venezia Giulia» που πραγματοποιήθηκαν το 2011 και επικυρώθηκαν οριστικά το 2013.

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    Authors: Gebruk, Anna; Dgebuadze, Polina; Rogozhin, Vladimir; Ermilova, Yulia; +2 Authors

    The dataset comprises full list of species of macrozoobenthos collected from the Pechora Sea (SE Barents Sea). Grab samples were collected from 10 stations in the Pechora Bay from aboard RV Kartesh in 2020-2021. Macrobenthic invertebrates were identified with the maximum level of certainty through optical microscopy using regional taxonomic keys. All taxonomic names were standardised using the World Register of Marine Species (WoRMS). All specimens have been counted and weighted (wet biomass) on Ohaus Adventurer scales with reported accuracy to 0.01 g. Bivalve molluscs and gastropods were weighed in shells. Biomass (g. m-2) and abundance (ind m-2) are used to characterise macrozoobenthos. The sampling and identification work was carried out in collaboration with specialists from Lomonosov Moscow State University Marine Research Center and P.P. Shirshov Institute of Oceanology.

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    MASSIMO is a distance-independent individual-tree simulator that represents demographic processes (regeneration, growth and mortality) with empirical models that have been parameterized with data from the Swiss NFI. Tree regeneration, growth and mortality are simulated on the regular grid of sample plots of the Swiss NFI, which allows for statistically representative simulations of forest development. ![alt text](https://www.envidat.ch/dataset/8fd996d1-aa7e-41b1-ae6d-1192582c62cc/resource/a12e2cfd-da45-4faf-8291-446c5763ac3c/download/massimo2swissforlab.png)

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    Authors: Fedra Trujillano; G. Jiménez; Luis Edgar Tarazona-Manrique; Najat F. Kahamba; +5 Authors

    Abstract Background In the near future, the incidence of mosquito-borne diseases may expand to new sites due to changes in temperature and rainfall patterns caused by climate change. Therefore, there is a need to use recent technological advances to improve vector surveillance methodologies. Unoccupied Aerial Vehicles (UAVs), often called drones, have been used to collect high-resolution imagery to map detailed information on mosquito habitats and direct control measures to specific areas. Supervised classification approaches have been largely used to automatically detect vector habitats. However, manual data labelling for model training limits their use for rapid responses. Open-source foundation models such as the Meta AI Segment Anything Model (SAM) can facilitate the manual digitalization of high-resolution images. This pre-trained model can assist in extracting features of interest in a diverse range of images. Here, we evaluated the performance of SAM through the Samgeo package, a Python-based wrapper for geospatial data, as it has not been applied to analyse remote sensing images for epidemiological studies. Results We tested the identification of two land cover classes of interest: water bodies and human settlements, using different UAV acquired imagery across five malaria-endemic areas in Africa, South America, and Southeast Asia. We employed manually placed point prompts and text prompts associated with specific classes of interest to guide the image segmentation and assessed the performance in the different geographic contexts. An average Dice coefficient value of 0.67 was obtained for buildings segmentation and 0.73 for water bodies using point prompts. Regarding the use of text prompts, the highest Dice coefficient value reached 0.72 for buildings and 0.70 for water bodies. Nevertheless, the performance was closely dependent on each object, landscape characteristics and selected words, resulting in varying performance. Conclusions Recent models such as SAM can potentially assist manual digitalization of imagery by vector control programs, quickly identifying key features when surveying an area of interest. However, accurate segmentation still requires user-provided manual prompts and corrections to obtain precise segmentation. Further evaluations are necessary, especially for applications in rural areas.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ International Journa...arrow_drop_down
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    International Journal of Health Geographics
    Article . 2024 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    https://dx.doi.org/10.60692/78...
    Other literature type . 2024
    Data sources: Datacite
    https://dx.doi.org/10.60692/z1...
    Other literature type . 2024
    Data sources: Datacite
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ International Journa...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      International Journal of Health Geographics
      Article . 2024 . Peer-reviewed
      License: CC BY
      Data sources: Crossref
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      https://dx.doi.org/10.60692/78...
      Other literature type . 2024
      Data sources: Datacite
      https://dx.doi.org/10.60692/z1...
      Other literature type . 2024
      Data sources: Datacite
      addClaim

      This Research product is the result of merged Research products in OpenAIRE.

      You have already added works in your ORCID record related to the merged Research product.