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3,479 results for “Italie”
500-meter grid of Derived Soil Profiles (DSP) for Italy - SuoliCella500
<p>National database of Italian Soil Typological Units (STU) and corresponding Derived Soil Profiles (DSP) obtained on a 500 meters grid (1,109,672 points) by neural network. The most probable WRB Reference Soil Group (RSG), WRB Qualifiers, and USDA textural soil types were mapped on the 500 meters grid, by neural network. 18,707 Observed soil profiles and the respective 33,014 Soil Horizons were grouped into 4,472 STUs based on the combinations of Soil Region, WRB Reference Soil Group (RSG), WRB Qualifiers, and USDA textural soil types obtained on the 500 meters grid. Statistics were calculated (Mean Value, Standard Deviation Value, and Numerosity) for soil rooting depth and for the most common analytical parameters of the soil horizons (Coarse fragment content fraction; pH in water; Carbon (C) - organic; Carbonate (CO3--) - Total; Clay, Sand, and Silt fraction; Granulometry; Textural soil types). The 500 meters grid adopts EPSG 23032 (ED50 UTM-32). A reference scale of 1:250.000 may be attributed to the 500-meters grid map, on the base of the numerosity of DSP produced for the whole italian territory.</p>
SPHERA High Resolution Reanalysis over Italy - Hourly surface air temperature (2-meter height) 2013-2020
<p>SPHERA (High Resolution REAnalysis over Italy) is a convection-permitting regional reanalysis developed by ARPAE-Emilia Romagna and publicly available. The SPHERA domain covers Italy and the surrounding seas with a horizontal resolution of 2.2km. The temporal coverage corresponds to the period 1995-2020 and the dataset is available at hourly frequency. SPHERA reanalysis was developed using the Numerical Weather Prediction model COSMO (www.cosmo-model.org) nested in the global reanalysis ERA5 produced by ECMWF. Moreover, upper-air and surface observations were assimilated at the convection-permitting scale by the COSMO nudging scheme.</p> <p>This record reports the hourly surface air temperature at 2-meter height for the period 2013-2020. The full extension of the dataset over 1995-2020 is available over three different records due to space constraints:</p> <ul> <li>1995-2003: <a href="../records/12567563">https://zenodo.org/records/12567563</a></li> <li>2004-2012: <a href="../records/12582246">https://zenodo.org/records/12582246</a></li> <li>2013-2020: <a href="../records/12582797">https://zenodo.org/records/12582797</a></li> </ul> <p>Update (2024-06-28): inconsistencies were noted in a subset of grib messages contained the first version of the repository (slightly different spatial domain size and missing messages at 00-hour timesteps) which have been corrected in the current version v2.</p> <p>Other fields currently available on Zenodo are the surface relative humidity at 2-meter height (also over three different records due to space constraints):</p> <ul> <li>1995-2003: <a href="../records/12724026">https://zenodo.org/uploads/12724026</a></li> <li>2004-2012: <a href="../records/12724104">https://zenodo.org/uploads/12724104</a></li> <li>2013-2020: <a href="../records/12724140">https://zenodo.org/uploads/12724140</a></li> </ul> <p>and hourly accumulated total precipitation: <a href="https://zenodo.org/records/14617083">https://zenodo.org/records/14617083</a></p> <p>Details on the SPHERA dataset production, as well as data verification against surface observations are reported in peer-reviewed publications. See References.</p>
SPHERA High Resolution Reanalysis over Italy - Hourly surface air temperature (2-meter height) 2004-2012
<p>SPHERA (High Resolution REAnalysis over Italy) is a convection-permitting regional reanalysis developed by ARPAE-Emilia Romagna and publicly available. The SPHERA domain covers Italy and the surrounding seas with a horizontal resolution of 2.2km. The temporal coverage corresponds to the period 1995-2020 and the dataset is available at hourly frequency. SPHERA reanalysis was developed using the Numerical Weather Prediction model COSMO (www.cosmo-model.org) nested in the global reanalysis ERA5 produced by ECMWF. Moreover, upper-air and surface observations were assimilated at the convection-permitting scale by the COSMO nudging scheme.</p> <p>This record reports the hourly surface air temperature at 2-meter height for the period 2004-2012. The full extension of the dataset over 1995-2020 is available over three different records due to space constraints:</p> <ul> <li>1995-2003: <a href="../records/12567563">https://zenodo.org/records/12567563</a></li> <li>2004-2012: <a href="../records/12582246">https://zenodo.org/records/12582246</a></li> <li>2013-2020: <a href="../records/12582797">https://zenodo.org/records/12582797</a></li> </ul> <p>Update (2024-06-28): inconsistencies were noted in a subset of grib messages contained the first version of the repository (slightly different spatial domain size and missing messages at 00-hour timesteps) which have been corrected in the current version v2.</p> <p>Other fields currently available on Zenodo are the surface relative humidity at 2-meter height (also over three different records due to space constraints):</p> <ul> <li>1995-2003: <a href="../records/12724026">https://zenodo.org/uploads/12724026</a></li> <li>2004-2012: <a href="../records/12724104">https://zenodo.org/uploads/12724104</a></li> <li>2013-2020: <a href="../records/12724140">https://zenodo.org/uploads/12724140</a></li> </ul> <p>and hourly accumulated total precipitation: <a href="https://zenodo.org/records/14617083">https://zenodo.org/records/14617083</a></p> <p>Details on the SPHERA dataset production, as well as data verification against surface observations are reported in peer-reviewed publications. See References.</p>
SPHERA High Resolution Reanalysis over Italy - Hourly surface air temperature (2-meter height) 1995-2003
<p>SPHERA (High Resolution REAnalysis over Italy) is a convection-permitting regional reanalysis developed by ARPAE-Emilia Romagna and publicly available. The SPHERA domain covers Italy and the surrounding seas with a horizontal resolution of 2.2km. The temporal coverage corresponds to the period 1995-2020 and the dataset is available at hourly frequency. SPHERA reanalysis was developed using the Numerical Weather Prediction model COSMO (www.cosmo-model.org) nested in the global reanalysis ERA5 produced by ECMWF. Moreover, upper-air and surface observations were assimilated at the convection-permitting scale by the COSMO nudging scheme.</p> <p>This record reports the hourly surface air temperature at 2-meter height for the period 1995-2003. The full extension of the dataset over 1995-2020 is available over three different records due to space constraints:</p> <ul> <li>1995-2003: <a href="../records/12567563">https://zenodo.org/records/12567563</a></li> <li>2004-2012: <a href="../records/12582246">https://zenodo.org/records/12582246</a></li> <li>2013-2020: <a href="../records/12582797">https://zenodo.org/records/12582797</a></li> </ul> <p>Update (2024-06-28): inconsistencies were noted in a subset of grib messages contained the first version of the repository (slightly different spatial domain size and missing messages at 00-hour timesteps) which have been corrected in the current version v2.</p> <p>Other fields currently available on Zenodo are the surface relative humidity at 2-meter height (also over three different records due to space constraints):</p> <ul> <li>1995-2003: <a href="../records/12724026">https://zenodo.org/uploads/12724026</a></li> <li>2004-2012: <a href="../records/12724104">https://zenodo.org/uploads/12724104</a></li> <li>2013-2020: <a href="../records/12724140">https://zenodo.org/uploads/12724140</a></li> </ul> <p>and hourly accumulated total precipitation: <a href="https://zenodo.org/records/14617083">https://zenodo.org/records/14617083</a></p> <p>Details on the SPHERA dataset production, as well as data verification against surface observations are reported in peer-reviewed publications. See References.</p>
SPHERA High Resolution Reanalysis over Italy - Hourly surface relative humidity (2-meter height) 2013-2020
<p>SPHERA (High Resolution REAnalysis over Italy) is a convection-permitting regional reanalysis developed by ARPAE-Emilia Romagna and publicly available. The SPHERA domain covers Italy and the surrounding seas with a horizontal resolution of 2.2km. The temporal coverage corresponds to the period 1995-2020 and the dataset is available at hourly frequency. SPHERA reanalysis was developed using the Numerical Weather Prediction model COSMO (www.cosmo-model.org) nested in the global reanalysis ERA5 produced by ECMWF. Moreover, upper-air and surface observations were assimilated at the convection-permitting scale by the COSMO nudging scheme.</p> <p>This record reports the hourly surface relative humidity at 2-meter height for the period 2013-2020. The full extension of the dataset over 1995-2020 is available over three different records due to space constraints:</p> <ul> <li>1995-2003: <a href="12724026">https://zenodo.org/uploads/12724026</a></li> <li>2004-2012: <a href="12724104">https://zenodo.org/uploads/12724104</a></li> <li>2013-2020: <a href="12724140">https://zenodo.org/uploads/12724140</a></li> </ul> <p>Other fields currently available on Zenodo are the surface air temperature at 2-meter height (also over three different records due to space constraints):</p> <ul> <li>1995-2003: <a href="../records/12567563">https://zenodo.org/records/12567563</a></li> <li>2004-2012: <a href="../records/12582246">https://zenodo.org/records/12582246</a></li> <li>2013-2020: <a href="../records/12582797">https://zenodo.org/records/12582797</a></li> </ul> <p>and hourly accumulated total precipitation: <a href="https://zenodo.org/records/14617083">https://zenodo.org/records/14617083</a></p> <p>Details on the SPHERA dataset production, as well as data verification against surface observations are reported in peer-reviewed publications. See References.</p>
SPHERA High Resolution Reanalysis over Italy - Hourly surface relative humidity (2-meter height) 2004-2012
<p>SPHERA (High Resolution REAnalysis over Italy) is a convection-permitting regional reanalysis developed by ARPAE-Emilia Romagna and publicly available. The SPHERA domain covers Italy and the surrounding seas with a horizontal resolution of 2.2km. The temporal coverage corresponds to the period 1995-2020 and the dataset is available at hourly frequency. SPHERA reanalysis was developed using the Numerical Weather Prediction model COSMO (www.cosmo-model.org) nested in the global reanalysis ERA5 produced by ECMWF. Moreover, upper-air and surface observations were assimilated at the convection-permitting scale by the COSMO nudging scheme.</p> <p>This record reports the hourly surface relative humidity at 2-meter height for the period 2004-2012. The full extension of the dataset over 1995-2020 is available over three different records due to space constraints:</p> <ul> <li>1995-2003: <a href="12724026">https://zenodo.org/uploads/12724026</a></li> <li>2004-2012: <a href="12724104">https://zenodo.org/uploads/12724104</a></li> <li>2013-2020: <a href="12724140">https://zenodo.org/uploads/12724140</a></li> </ul> <p>Other fields currently available on Zenodo are the surface air temperature at 2-meter height (also over three different records due to space constraints):</p> <ul> <li>1995-2003: <a href="../records/12567563">https://zenodo.org/records/12567563</a></li> <li>2004-2012: <a href="../records/12582246">https://zenodo.org/records/12582246</a></li> <li>2013-2020: <a href="../records/12582797">https://zenodo.org/records/12582797</a></li> </ul> <p>and hourly accumulated total precipitation: <a href="https://zenodo.org/records/14617083">https://zenodo.org/records/14617083</a></p> <p>Details on the SPHERA dataset production, as well as data verification against surface observations are reported in peer-reviewed publications. See References.</p>
SPHERA High Resolution Reanalysis over Italy - Hourly surface relative humidity (2-meter height) 1995-2003
<p>SPHERA (High Resolution REAnalysis over Italy) is a convection-permitting regional reanalysis developed by ARPAE-Emilia Romagna and publicly available. The SPHERA domain covers Italy and the surrounding seas with a horizontal resolution of 2.2km. The temporal coverage corresponds to the period 1995-2020 and the dataset is available at hourly frequency. SPHERA reanalysis was developed using the Numerical Weather Prediction model COSMO (www.cosmo-model.org) nested in the global reanalysis ERA5 produced by ECMWF. Moreover, upper-air and surface observations were assimilated at the convection-permitting scale by the COSMO nudging scheme.</p> <p>This record reports the hourly surface relative humidity at 2-meter height for the period 1995-2003. The full extension of the dataset over 1995-2020 is available over three different records due to space constraints:</p> <ul> <li>1995-2003: <a href="12724026">https://zenodo.org/uploads/12724026</a></li> <li>2004-2012: <a href="12724104">https://zenodo.org/uploads/12724104</a></li> <li>2013-2020: <a href="12724140">https://zenodo.org/uploads/12724140</a></li> </ul> <p>Other fields currently available on Zenodo are the surface air temperature at 2-meter height (also over three different records due to space constraints):</p> <ul> <li>1995-2003: <a href="../records/12567563">https://zenodo.org/records/12567563</a></li> <li>2004-2012: <a href="../records/12582246">https://zenodo.org/records/12582246</a></li> <li>2013-2020: <a href="../records/12582797">https://zenodo.org/records/12582797</a></li> </ul> <p>and hourly accumulated total precipitation: <a href="https://zenodo.org/records/14617083">https://zenodo.org/records/14617083</a></p> <p>Details on the SPHERA dataset production, as well as data verification against surface observations are reported in peer-reviewed publications. See References.</p>
SERENA EJPSoil Soil loss by water erosion of Tuscany (Italy)
<p>The internal EJP SOIL project SERENA contributed to the evaluation of soil multifunctionality aiming at providing assessment tools for land planning and soil policies at different scales. By co-working with relevant stakeholders, the project provided co-developed indicators and associated cookbooks to assess and map them, to report both on soil degradation, soil-based ecosystem services and their bundles, under actual conditions and for climate and land-use changes, at the regional, national, and European scales.</p> <p>One of the objective of SERENA project was to develop methods to calculate and map soil-based ecosystem services and soil threats. The present data was prepared according to the methodology of the SERENA Soil erosion and soil erosion control cookbook. Soil loss was used as an indicator for soil erosion (ST). The map of soil loss by water erosion (soil threat) was based on the RUSLE model. For Italy, the cookbook was applied in the Tuscany region. <br> <br>To create the soil loss map we used:</p> <ul> <li>for R-factor, not freely available database of meteorological parameters spatialized at 250 m (minimum and maximum daily air temperature; cumulate daily precipitation) over Tuscany region (period 1990–2022, Lamma Consortium) and a local linear equation between R and mean annual precipitation (P);</li> <li>for C -factor, Regional Land use map 1:10.000 (2018, freely available at: https://www502.regione.toscana.it/geoscopio/usocoperturasuolo.html) and ESDAC method (https://doi.org/10.1016/j.landusepol.2015.05.021) ; </li> <li>for K-factor, sand, silt, clay, and O.C. (%) maps (built from 4.000 soil profiles, following FAO’s methodology in GSP-GSOC map, Lamma Consortium), and Torri et al. (1997) function;</li> <li>for LS-factor, DEM 10 m of Tuscany, (freely available at https://www502.regione.toscana.it/geoscopio/cartoteca.html99) and Desmet & Govers (1996) SAGA tool (applied at 10 m and upscaled);</li> <li>for P-factor, not freely available database 1:10.00 of terraced areas (Lamma Consortium, 2020) (for terraced areas a multiplication factor of 0.5 was considered, based on expert evaluation)</li> </ul> <p>Maps was delivered in the GeoTIFF format in the resolution of 100m. <br>Delivered data will be validated by stakeholders from Italy (scientist) in October, 2024.</p>
SERENA EJPSoil Soil erosion control in Tuscany (Italy)
<div> <p><span><span>The internal EJP SOIL project SERENA contributed to the evaluation of soil multifunctionality aiming at providing assessment tools for land planning and soil policies at different scales. By co-working with relevant stakeholders, the project provided co-developed indicators and associated cookbooks to assess and map them, to report both on soil degradation, soil-based ecosystem services and their bundles, under actual conditions and for climate and land-use changes, at the regional, national, and European scales.</span></span></p> <p><span><span>One of the </span><span>objective</span><span> of SERENA project was to develop methods to calculate and map soil-based ecosystem services and soil threats. The present data was prepared according to the </span><span>methodology</span><span> of the SERENA Soil erosion and soil erosion control cookbook</span><span>. </span><span>Soil loss was used as an indicator for soil erosion (ST). T</span><span>he map of soil mass not eroded was based on the RUSLE model. </span><span>Soil erosion control was calculated as the difference between potential and actual soil erosion (SES, ecosystem service of soil erosion protection, i.e. soil eroded mass </span><span>retained</span><span> by vegetation, Mg/ha/y)</span><span>. For Italy, the cookbook was applied in the Tuscany region. </span></span><span> </span></p> </div> <div> <p><span><span>To create the soil loss map we used:</span></span><span> </span></p> </div> <div> <ul> <li><span><span>for R-factor, not freely available database of meteorological parameters spatialized at 250 m (minimum and maximum daily air temperature; cumulate daily precipitation) over Tuscany region (period 1990–2022, Lamma </span><span>Consortium) and</span><span> a local linear equation between R and mean annual precipitation (P);</span></span> </li> <li><span>for C -factor, Regional Land use map 1:10.000 (2018, freely available at: </span><span>https://www502.regione.toscana.it/geoscopio/usocoperturasuolo.html</span><span>) and ESDAC method (</span><span>https://doi.org/10.1016/j.landusepol.2015.05.021</span><span>) ;</span> <span> </span></li> <li><span>for K-factor, sand, silt, clay, and O.C. (%) maps (built from 4.000 soil profiles, following FAO’s </span><span>methodology</span><span> in GSP-GSOC map, Lamma Consortium), and Torri et al. (1997) function;</span><span> </span></li> <li><span>for LS-factor, DEM 10 m of Tuscany, (freely available at </span><span>https://www502.regione.toscana.it/geoscopio/cartoteca.html99</span><span>) and Desmet & </span><span>Govers</span><span> (1996) SAGA tool (applied at 10 m and upscaled);</span><span> </span></li> <li><span>for P-factor, not freely available database 1:10.00 of terraced areas (Lamma Consortium, 2020) (for terraced areas a multiplication factor </span><span>of 0.5</span><span> was considered, based on expert evaluation)</span><span> </span></li> <li><span>for P-factor, not freely available database 1:10.00 of terraced areas (Lamma Consortium, 2020) (for terraced areas a multiplication factor </span><span>of 0.5</span><span> was considered, based on expert evaluation)</span><span> </span></li> </ul> </div> <div> <p><span><span>Maps was delivered in the </span><span>GeoTIFF</span><span> format in the resolution of 100m. </span></span><span> </span></p> </div> <div> <p><span><span>Delivered data will be </span><span>validated</span><span> by stakeholders from Italy (scientist) in </span><span>October,</span><span> 2024.</span></span><span> </span></p> </div>
High-precision Aftershock Locations and Fault Planes of the 2016-2017 Central Italy Sequence
<p>The earthquake catalog includes high-precision hypocenter relocations for 390,334<br> earthquakes recorded during the 2016-2017 Amatrice (Central Italy) <br> earthquake sequence. The relative locations were computed by double-difference inversion of a <br> combination of INGV phase picks and cross-correlation differential <br> times measured from correlated seismograms with correlation coefficients > 0.7.</p> <p>Planes of normal faults (idx=1-5) are derived from PCA analysis of 2 months of aftershock <br> locations in the CAT4 catalog following large events. Surfaces of detachment faults (idx=7-10) are derived from mapping out the location of correlated earthquakes. </p> <p>Citation: Waldhauser, F., Michele, M., Chiaraluce, L., Di Stefano, R., & Schaff, D. P. (2021). Fault planes, fault zone structure and detachment fragmentation resolved with highprecision aftershock locations of the 2016-2017 central Italy sequence. Geophysical Research Letters, 48, e2021GL092918. https://doi.org/10.1029/2021GL092918</p>
LTER-Italy Antarctic sites figure
<p>Geographical representation of the LTER-Italy Antarctic sites Macrosito Baia di Terranova (MBT - LTER_EU_IT_086), Mooring A: Southwestern Ross Sea, Ross Island (LTER_EU_IT_069), Mooring B: North Central Ross Sea, Joides Basin (LTER_EU_IT_070, Mooring D: Western Ross Sea, TerraNova Bay Polynya (LTER_EU_IT_071) and Mooring H: Central Ross Sea (LTER_EU_IT_072) - DEIMS-iDs <a href="https://deims.org/7fb8e2c6-b11f-41a7-b494-44ceeb3bed2d">https://deims.org/7fb8e2c6-b11f-41a7-b494-44ceeb3bed2d</a>, <a href="https://deims.org/86b6465c-b604-4efa-9145-0805f62216f4">https://deims.org/86b6465c-b604-4efa-9145-0805f62216f4</a>, <a href="https://deims.org/1fb62b9c-4d5c-4f1f-8882-807032337de7">https://deims.org/1fb62b9c-4d5c-4f1f-8882-807032337de7</a>, <a href="https://deims.org/b4121cd7-8b02-4872-b1d2-516d1c02056a">https://deims.org/b4121cd7-8b02-4872-b1d2-516d1c02056a</a> and <a href="https://deims.org/63a444a3-22e1-44fe-a7e3-7982366a2c1b">https://deims.org/63a444a3-22e1-44fe-a7e3-7982366a2c1b</a>.</p>
LTER-Italy Gulf of Naples sites figure
<p>Geographical representation of the LTER-Italy Gulf of Naples sites LTER Lacco Ameno (LTER_EU_IT_060) and LTER Marechiara (LTER_EU_IT_061) - DEIMS-ID <a href="https://deims.org/4a05a2fb-0015-4310-96d5-a94c019bda58">https://deims.org/4a05a2fb-0015-4310-96d5-a94c019bda58</a> and h<a href="http://ttps://deims.org/0b87459a-da3c-45af-a3e1-cb1508519411">ttps://deims.org/0b87459a-da3c-45af-a3e1-cb1508519411</a></p>
Dataset and R script for the analysis in the article "Food waste between environmental education, peers, and family influence. Insights from primary school students in Northern Italy", Journal of Cleaner Production
<p>We hereby publish the dataset (with metadata) and the R script (R Core team, 2018) used for implementing the analysis presented in the paper "Food waste between environmental education, peers, and family influence. Insights from primary school students in Northern Italy", <em>Journal of Cleaner Production </em>(Piras et al., 2023). The dataset is provided in csv format with semicolons as separators and "NA" for missing data. The dataset includes all the variables used in at least one of the models presented in the paper, either in the main text or in the Supplementary Material. Other variables gathered by means of the questionnaires included as Supplementary Material of the paper have been removed. The dataset includes inputted values for missing data on independent variables. These were inputted using two approaches: last observation carried forward (LOCF) - preferred when possible - and last observation carried backward (LOCB). The metadata are presented as a PDF file.</p>
Asilidae and Syrphidae (Insecta: Diptera) inhabiting beech forests in central Italy
<p>The published dataset contains of 2,295 specimens corresponding to 86 known species belonging to two Diptera families: Asilidae (robber flies) and Syrphidae (hoverflies). These data were collected during several sampling sessions in the framework of the projects LIFE09 ENV/IT/000078 - Management of Forests, Carbon and Biodiversity (ManFor CBD) (2012, 2014) and LIFE17 ESC/IT/001 360 - Volunteers for monitoring forest biodiversity in the Italian Natura 2000 Network (LIFE ESC360) (2019) and an agreement between Sapienza Università di Roma and the Laboratorio Nazionale Tassonomia e Bioindicazione Invertebrati - Reparto Biodiversità Carabinieri di Verona (LanaBit) (2019).</p> <p>Specimens were collected in two beech forests in Abruzzo region (central Italy), managed by Arma dei Carabinieri (Reparto Carabinieri Biodiversità di Castel di Sangro): “Foresta Demaniale Regionale Chiarano-Sparvera” (AQ) and “Vallone di Teve” in the Nature State Reserve “Monte Velino” (AQ). Moreover, the two areas overlap with the Natura 2000 Network: the first is partially included by the Special Area of Conservation (SAC) IT7110205 “Parco Nazionale d'Abruzzo”, the second by the SAC IT7110206 “Monte Sirente e Monte Velino” and the Special Protection Area (SPA) IT7110130 “Sirente Velino”.</p> <p>The samplings were carried out through the installation of 17 Malaise traps and direct chasing with net. Traps were settled in transition areas of clearings among beech trees, at an altitude range from 1397 m to 1746 m above sea level. </p> <p>The checklist includes information on the taxonomy of the species (i.e., order, family, genus, species, authorship, references about taxa identifications), number of individuals, sex, sampling period, geographic position, habitat type (following EUNIS habitat classification 2021), sampling protocol, collector name, specialist name.</p> <p>The terms used for the dataset fields follows the Darwin Core Maintenance Group. 2021. List of Darwin Core terms. Biodiversity Information Standards (TDWG) http://rs.tdwg.org/dwc/doc/list/http://rs.tdwg.org/dwc/doc/list/http://rs.tdwg.org/dwc/doc/list/. The harmonisation of the dataset concerning taxa, authorship, LSID and the massive upgrading of the related identifiers in Zenodo record was performed by the use of R script using respectively dplyr, taxize (Chamberlain and Szöcs, 2013) and zen4r (Blondel and Barde, 2020) packages.</p> <p>The provided dataset of specimens collected in Valle di Teve will contribute to the inventory of insects included in the Management Plan of the Riserva Naturale Orientata Monte Velino (Reparto Carabinieri Biodiversità di Castel di Sangro).</p> <p>Here we provide the checklist of Asilidae and Syrphidae species, with the aim of promoting the collection and publication of raw data and information on insect communities inhabiting the Italian Nature State Reserves. This dataset could be considered as the “point zero” to be implemented with future additional sampling campaigns.</p>
LTER-Italy terrestrial sites map
<p>Map of Italy where the Italian Long-Term Ecological Research (LTER-Italy) freshwater sites are evidenced. The colours of the dots correspond to the terrestrial ecosystem (brown) typologies. The main features of the sites can be found on DEIMS-SDR, the LTER-Europe repository for research sites and datasets (<a href="https://deims.org/">https://deims.org</a>).</p>
LTER-Italy marine sites map
<p>Map of Italy where the Italian Long-Term Ecological Research (LTER-Italy) freshwater sites are evidenced. The colours of the dots correspond to the marine ecosystem (dark blue) typologies. The main features of the sites can be found on DEIMS-SDR, the LTER-Europe repository for research sites and datasets (<a href="https://deims.org/">https://deims.org</a>).</p>
LTER-Italy freshwater sites map
<p>Map of Italy where the Italian Long-Term Ecological Research (LTER-Italy) freshwater sites are evidenced. The colours of the dots correspond to the freshwater ecosystem (light blue) typologies. The main features of the sites can be found on DEIMS-SDR, the LTER-Europe repository for research sites and datasets (<a href="https://deims.org">https://deims.org</a>).</p>
LTER-Italy sites map
<p>Map of Italy where the Italian Long-Term Ecological Research (LTER-Italy) sites are evidenced. The colours of the dots correspond to the main ecosystem typologies: Dark blue = marine, light blue = freshwater, green = transitional water, brown = terrestrial. The main features of the sites can be found on DEIMS-SDR, the LTER-Europe repository for research sites and datasets (<a href="https://deims.org">https://deims.org</a>).</p>
LTER-Italy marine and transitional sites map
<p>Map of Italy where the Italian Long-Term Ecological Research (LTER-Italy) sites are evidenced. The colours of the dots correspond to the main ecosystem typologies: Dark blue = marine, green = transitional water. The main features of the sites can be found on DEIMS-SDR, the LTER-Europe repository for research sites and datasets (<a href="https://deims.org">https://deims.org</a>).</p>
Regional scale surface of the top of the Variscan basement in some sector of Italy - Supplementary material
<p>The dataset represent the Supplementary material of thew manuscript entitled "Map of the top of the Variscan basement in some sectors of Italy" now under revision.</p> <p>The Supplementary material consist of 9 files:</p> <ul> <li>input data: <ul> <li>dataset_CROP.csv</li> <li>deep_wells.csv</li> <li>domains.geojson</li> <li>thrusts_2.geojson</li> <li>INA_data_point.csv</li> </ul> </li> <li>output data: <ul> <li>INA_depth_1km.csv</li> <li>ONA_OA_ISA_AF_depth_5km.csv</li> <li>INA_contour.geojson</li> <li>ONA_OA_ISA_AF_contour.geojson</li> </ul> </li> </ul>
ScienceDex guides
Understand access before you commit
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.