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The local extinction of Cedrus atlantica in the Iberian Peninsula could have been completed due to biological interaction
<p>This data set is used to explore the possibility that <em>Cedrus atlantica</em> (Endl.) Carrière and <em>Pinus nigra</em> Arnold could have interacted in the past, mutually excluding each other in the areas with suitable conditions for both species and, where, ultimately, the one that was most competitive would remain. The species show very well differenciated niches and a distribution of their habitats segregated by continents (<em>P. nigra</em> in Europe and <em>C. atlantica</em> in Africa), which responds to differences in climatic affinities. However, the contact of their distributions in bordering areas suggests that <em>C. atlantica</em> maintained its presence in the Iberian Peninsula until recent times, and that <em>P. nigra</em> could have displaced it due to its higher prevalence on the continent.</p>
PALEODEM/ What burned the forest? Wildfires, climate change and human activity during the Mesolithic – Neolithic transition in SE Iberian Peninsula
<p>This repository contains new XRD data from the Villena paleolake, archaeological radiocarbon evidence from the Villena area and the R code used to produce Summed Probability distribution analyses. </p> <p>They correspond to the following reference: </p> <p>Sánchez-García, C., Revelles, J., Burjachs, F., Euba, I., Expósito, I., Ibáñez, J., Schulte, L., Fernández-López de Pablo, J. What burned the forest? Wildfires, climate change and human activity during the Mesolithic – Neolithic transition in SE Iberian Peninsula (submitted to Catena). </p> <p>We specify the content of file further down:</p> <ul> <li>Vinalopo.csv: the list of radiocarbon dates from Villena spanning ca.9500-5500 cal BP from the following sites: Arenal de la Virgen, Cueva del Lagrimal and Casa Corona. </li> <li>ngrip.csv: NGRIP GICC05 paleotemperature record based on oxygen isotope series from Rasmussen SO <em>et al.</em>2006 A new Greenland ice core chronology for the last glacial termination. <em>J. Geophys. Res. Atmos.</em><strong>111</strong>. (doi:10.1029/2005JD006079) and Andersen KK <em>et al.</em>2006 The Greenland Ice Core Chronology 2005, 15–42ka. Part 1: constructing the time scale. <em>Quat. Sci. Rev.</em>25, 3246–3257.</li> <li>Char.csv: Sedimentary charcoal data set from the Villena Paleolake (VL3 core) published by Jones, S.E., Burjachs, F., Fernández-López de Pablo (2018) DOI/10.5281/zenodo.1244003, according to the new Bacon chronological model of the Villena paleolake (Fernández-López de Pablo et al., 2022 . Impacts of Early Holocene environmental dynamics on open-air occupation patterns in the Western Mediterranean: insights from El Arenal de la Virgen (Alicante, Spain). <a href="https://doi.org/10.31235/osf.io/5yqsr">https://doi.org/10.31235/osf.io/5yqsr</a>)</li> <li>SPD_analysis.R: R script with the code to reproduce the SPD analysis presented in the manuscript. </li> <li>SupplMat1xlsl: an excel file This file is composed by 8 spreadsheets:</li> </ul> <ol> <li>‘Selected variables 12.6-5.5’: all the data included in the time frame 12600-5500 cal BP, interpolated to 50 yr time windows. These data have been used for the Spearmans’rs correlation analysis (see spreadsheet ‘Spearmans’rs 12.6-5.5’ to track the results), Detrended Correspondence Analysis (see spreadsheet ‘Figure 5_DCA 12.6-5.5’ to track the results) and have been plotted in Figure 3 and 7. </li> <li>'Selected variables 9.1-5.5’: data included in the analysis focused on the time period 9.1-5.5 cal BP, interpolated to 50 yr time windows. These data have been used for the Spearmans’rs correlation analysis (see spreadsheet ‘Spearmans’rs 9.1-5.5’ to track the results), Detrended Correspondence Analysis (see spreadsheet ‘Figure 6_DCA 9.1-5.5’ to track the results) and have been plotted in Figure 8.</li> <li>‘Spearmans’rs 12.6-5.5’: Spearmans’rs correlation analysis applied to the 12600-5500 cal BP dataset (data from ‘Selected variables 12.6-5.5’).</li> <li>‘Spearmans’rs 9.1-5.5 cal BP’ Spearmans’rs correlation analysis applied to the 9100-5500 cal BP dataset, including here high-resolution XRD data (data from ‘Selected variables 9.1-5.5’).</li> <li>‘Figure 2 charcoal results’: original sedimentary charcoal results provided in this work. Data plotted in Figure 2. </li> <li>‘Figure 4 XRD results’: original XRD results provided in this work. Data plotted in Figure 4.</li> <li>‘Figure 5 DCA 12.6-5.5’: results of Detrended Correspondence analysis focused on the time period from 12600 to 5500 cal BP. Data plotted in Figure 5.</li> <li>‘Figure 6 DCA 9.1-5.5’ results of Detrended Correspondence analysis focused on the time period from 9100 to 5500 cal BP, including here high-resolution XRD data. Data plotted in Figure 6.</li> </ol>
Cumulated dam impact in France and the Iberian Peninsula (SUDOANG project)
<h2><strong>1. SUDOANG PROJECT</strong></h2><p>The SUDOANG project has provided common tools and assessment methods to managers to support the eel conservation in the SUDOE zone (Southern France, Spain and Portugal). One of the goals of the project was to develop an eel abundance and distribution <a href="https://zenodo.org/record/7546419">atlas</a> in the three countries, based on the results of the implementation of Eel Density Analysis (<a href="https://sudoang.eu/wp-content/uploads/2022/02/E411_Briand_et_al_2022_EDA_report_opt-1.pdf">EDA</a>). This model extrapolates eel abundance from a range of river segments sampled by electrofishing, to the whole river and lake network, by considering how eel abundance, size and sex vary according to different parameters related to eel habitat. To do this, we have created a dataset of "cumulated dam impact" which compiles different ways of calculating cumulated height from the sea.</p><h2><strong>2. SUDOANG DATABASE</strong></h2><p>The dataset on cumulated impact was first derived from information on obstacles collected by the SUDOANG project. Obstacles data for the three countries were imported in the SUDOANG database (<a href="https://sudoang.eu/wp-content/uploads/2020/11/E221_data_collection_storage-1.html#3_data_import_on_physical_obstacles_in_spain_and_portugal">deliverable 2.2.1</a>), whose structure is inherited from the DataBase for EEl (DBEEL), developed during a European research project (POSE - Pilot projects to estimate potential and actual escapement of silver eel, Walker et al., 2011). This database is designed to contain all data relative to eel biology and anthropogenic pressures applying to eel. During the course of SUDOANG, this database was used and ameliorated. </p><p>In France the obstacles were compiled from three pre-existing different databases:</p><ul><li>the Referential of flow obstacles (<a href="https://professionnels.ofb.fr/fr/node/367">ROE</a>) ,</li><li>the Information of Ecological Continuity (<a href="https://professionnels.ofb.fr/en/node/731">ICE</a>) and</li><li>the Flow Obstruction Database (Base de Données des Obstacles à l'Ecoulement, (BDOE).</li></ul><p>The data we have integrated into the SUDOANG 1.0.4. database came from a database dump of the 12th September 2019. The inventory includes bridges that have a significant impact on river continuity.</p><p>In Spain, data came from:</p><ul><li>the MITECO Ministry</li><li>the Basque Water Agency (URA) - Basque Country</li><li>the Catalan Water Agency (ACA) - Catalonia</li><li>the University of Girona - Catalonia</li><li>the University of Córdoba - Andalusia</li><li>Xunta de Galicia, Consellería de Medio Ambiente, Territorio e Vivenda - Galicia</li><li>the <a href="https://amber.international">AMBER </a>project</li></ul><p>In Portugal the data came from:</p><ul><li>the Portuguese Water Agency (APA)</li><li>MARE-ULisboa (University of Lisbon)</li><li>CIIMAR, the University of Porto</li><li>the <a href="https://amber.international">AMBER</a> project.</li></ul><p>In the case of the transboundary river Minho, the data came from:</p><ul><li>CIIMAR, the University of Porto (Portuguese area) (<a href="https://www.dgrm.mm.gov.pt/documents/20143/0/PGE+TIRM+Vers%C3%A3o+Portuguesa+Revis%C3%A3o+Novembro+2011.pdf/3c9d8b50-e5cc-2ed8-5714-90a115d4a6a5">report</a>)</li><li>EHEC, the University of Santiago de Compostela (Spanish area) (<a href="https://www.dgrm.mm.gov.pt/documents/20143/0/PGE+TIRM+Vers%C3%A3o+Portuguesa+Revis%C3%A3o+Novembro+2011.pdf/3c9d8b50-e5cc-2ed8-5714-90a115d4a6a5">report</a>)</li></ul><h2><strong>3. DATA DESCRIPTION</strong></h2><h3><strong>3.1. Data collected on artificial obstacles</strong></h3><p>Artificial obstacles were classified into 10 types according to the Adaptive Management of Barriers in European Rivers (<a href="https://amber.international">AMBER</a>) project. Some additional types (e.g., penstock pipes) were added to identify other obstacles in national databases that did not fit the AMBER classification (see the list below). Sometimes dams from different branches are connected, creating a dam-network. In those cases, we have only kept the dam(s) in the main course and use a hierarchical classification of the dams to only consider the cumulated height from the sea to the reference dam. We included only obstacles that are presently standing, <i>i.e.,</i> not planned, under construction, or destroyed. Dikes, longitudinal control structures and grates were excluded.</p><p><i>Obstacle classification according to the data collected and the AMBER project:</i></p><ul><li>BR - Bridge: A structure that is built over a river to allow people or vehicles to cross</li><li>CU - Culvert: A tunnel or pipe carrying a stream or open drain under a road or railway</li><li>DI - Dike: An embankment used to hold back water</li><li>DA - Dam: Structure that blocks the river and extends across the river bed to the flood plain</li><li>FO - Ford: A shallow crossing-place in a river</li><li>PP - Penstock: pipe Group of pipes that transport pressurised water from a reservoir (dam) to the turbines installed in a hydro-electric power plant</li><li>RR - Rock ramp: A weir made of rocks</li><li>WE - Weir: Structure across a river that does not extend to the flood plain</li><li>OT - Other: Structure that is not covered by previous definitions</li><li>UN - Unknown: Unknown</li></ul><p>We have projected obstacles on the SUDOANG river network at the nearest point within 300 m. To avoid projecting large obstacles in the wrong location in the southwestern France, SUDOANG experts have reviewed and corrected this information. We have also used an algorithm that extracts the best obstacle height data from the three existing databases in France. In the Iberian Peninsula, data providers validated and corrected obstacle location and height using a Shiny application developed by the project, in which they could directly correct the height of obstacles.</p><p>The variables in the <strong>obstacles </strong>table (csv delimiter ",") are:</p><ul><li><i>op_id</i>: Identifier of the observation place name</li><li><i>op_gis_layername</i>: Original data source</li><li><i>op_placename</i>: Name of the dam</li><li><i>op_op_id</i>: If the dam is linked within a complex (e.g. when there are multiple channels for the same river) the name of the parent dam</li><li><i>id_original</i>: Original id of the dam (in the raw table)</li><li><i>country</i>: Country code ('SP', 'ES' or 'FR')</li><li><i>dp_name</i>: Name of the data provider</li><li><i>obstruction_type_code</i>: Type of obstruction (see table obstruction type code)</li><li><i>obstruction_type_name</i>: Name of the dam</li><li><i>po_obstruction_height</i>: Difference of level of water between the downstream and the upstream part of the dam</li><li><i>po_presence_eel_pass</i>: Presence of a pass suitable for eel (see paper)</li><li><i>po_date_presence_eel_pass</i>: Date of construction of the eel (or eel compatible) pass</li><li><i>fishway_type_code</i>: Code of the fishway type</li><li><i>fishway_type_name</i>: Name of the fishway type</li><li><i>googlemapscoods</i>: Link to google map</li><li><i>x_espg_4326</i>: Longitude (with ESPG 4326)</li><li><i>y_espg_4326</i>: Latitude (with ESPG 4326)</li></ul><h3><strong>3.2. Modeling missing data and estimating the cumulative impact on obstacles</strong></h3><p>For those obstacles missing height information, we have calculated height using a Generalized Linear Models (GLM of log transformed height, <i>family = gaussian, link = identity</i>. In France the <a href="https://forgemia.inra.fr/pole-migrateurs/eda/dbeel/-/blob/main/eda2.3/report/Dams.Rmd">model</a> was based on river segment slope, river segment median flow and hydrographic basin. In the Iberian Peninsula, we have implemented a simpler <a href="https://forgemia.inra.fr/pole-migrateurs/eda/dbeel/-/blob/main/eda2.3/report/E221_data_collection_storage_sp_pt.Rmd">model</a> based on obstacle type, as information about flow or slope was not available for all river segments.</p><p>The cumulated impact of obstacles was assessed by creating a table joining each river segment with all the dams located in the downstream course. Using this, various metrics were computed using different assumptions concerning the effect of obstacles. The heights were power transformed to test for a different effect of obstacle's height (the cumulated effect of two obstacles of 1 m might be different than the cumulated effect of a single obstacle of 2 m), and functions were developed to calculate cumulated obstacle transformed variables. Other variables were also tested. In fact, tests in France have shown that factors such as presence of a fish pass, and eel passability did not improve the <a href="https://forgemia.inra.fr/pole-migrateurs/eda/eda_model/-/blob/main/S4/BaseEdaRiosRiversegmentsDam.R\#L624">model performance</a>. For this reason, but also because in the Iberian Peninsula this type of information was too limited, we used dam height to model the cumulative height of obstacles at a given river segment. </p><p>The variables in the <strong>cumulated_dam_impact_SUDOANG </strong>table (format Rdata - to be read with the R software, this will load as a data.frame called datadam) are:</p><ul><li><i>cs_height_08_n</i>: Cumulated height from the sea, dam height transformed with power 0.8, no prediction for missing values</li><li><i>cs_height_08_n</i>.: Same variable but truncated to 300</li><li><i>cs_height_08_p</i>: Cumulated height from the sea, dam height transformed with power 0.8, with prediction for missing values</li><li><i>cs_height_08_p</i>.: Same variable but truncated to 300</li><li><i>cs_height_08_pps </i>Cumulated height from the sea, dam height transformed with power 0.8, with prediction for missing values, the height of dam is set to zero if equiped with an efficient fishway for eel</li><li><i>cs_height_10_FR</i>: Cumulated height from the sea, no transformation, no prediction for missing values, only the dams from France are considered when building on a transnational water course</li><li><i>cs_height_10_n</i>: Cumulated height from the sea, no transformation, no prediction for missing values</li><li><i>cs_height_10_n</i>.: Same variable but truncated to 200</li><li><i>cs_height_10_p</i>: Cumulated height from the sea, no transformation, missing height are extrapolated from two different models in France and the Iberian Peninsula <i>cs_height_10_p</i>.: Same variable but truncated to 200</li><li><i>cs_height_10_pass0</i>: Cumulated height from the sea, no transformation, no prediction for missing values, only the dams without pass are used to build the cumulated value</li><li><i>cs_height_10_pass1</i>: Cumulated height from the sea, no transformation, no prediction for missing values, only the dams with pass are used to build the cumulated value</li><li><i>cs_height_10_pp</i>: Cumulated height from the sea, no transformation, with prediction for missing values, the height of dam is set to zero if equiped with an efficient fishway for eel</li><li><i>cs_height_10_ppass0</i>: Cumulated height from the sea, no transformation, including prediction for missing values, only the dams without pass are used to build the cumulated value</li><li><i>cs_height_10_ppass1</i>: Cumulated height from the sea, no transformation, including prediction for missing values, only the dams with pass are used to build the cumulated value</li><li><i>cs_height_10_pps</i>: Cumulated height from the sea, no transformation, with prediction for missing values, the height of dam is set to zero if a score of efficient passage was attributed for eel on this structure</li><li><i>cs_height_10_pscore0</i>: Cumulated height from the sea, no transformation, including prediction for missing values, only the dams without score are used to build the cumulated value</li><li><i>cs_height_10_pscore1</i>: Cumulated height from the sea, no transformation, including prediction for missing values, only the dams with score (that have been expertised as no or small barrier for eel) are used to build the cumulated value</li><li><i>cs_height_10_PT</i>: Cumulated height from the sea, no transformation, no prediction for missing values, only the dams from Portugal are considered when building on a transnational water course</li><li><i>cs_height_10_score0</i>: Cumulated height from the sea, no transformation, no prediction for missing values, only the dams without score are used to build the cumulated value</li><li><i>cs_height_10_score1</i>: Cumulated height from the sea, no transformation, no prediction for missing values, only the dams with score (that have been expertised as no or small barrier for eel) are used to build the cumulated value</li><li><i>cs_height_10_SP</i>: Cumulated height from the sea, no transformation, no prediction for missing values, only the dams from Spain are considered when building on a transnational water course</li><li><i>cs_height_12_n</i>: Cumulated height from the sea, dam height transformed with power 1.2, no prediction for missing values</li><li><i>cs_height_12_n</i>: Same variable but truncated to 500</li><li><i>cs_height_12_p</i>: Cumulated height from the sea, dam height transformed with power 1.2, with prediction for missing values</li><li><i>cs_height_12_p.</i>: Same variable but truncated to 500</li><li><i>cs_height_12_pp</i>: Cumulated height from the sea, dam height transformed with power 1.2, with prediction for missing values, the height of dam is set to zero if equiped with an efficient fishway for eel</li><li><i>cs_height_12_pps</i>: Cumulated height from the sea, dam height transformed with power 1.2, with prediction for missing values, the height of dam is set to zero if a score of efficient passage was attributed for eel on this structure</li><li><i>cs_height_15_n</i>: Cumulated height from the sea, dam height transformed with power 1.5, no prediction for missing values</li><li><i>cs_height_15_n:</i> Same variable but truncated to 800</li><li><i>cs_height_15_p</i>: Cumulated height from the sea, dam height transformed with power 1.5, with prediction for missing values</li><li><i>cs_height_15_p.:</i> Same variable but truncated to 800</li><li><i>cs_height_15_pp</i>: Cumulated height from the sea, dam height transformed with power 1.5, with prediction for missing values, the height of dam is set to zero if equiped with an efficient fishway for eel</li><li><i>cs_height_15_pps</i>: Cumulated height from the sea, dam height transformed with power 1.5, with prediction for missing values, the height of dam is set to zero if a score of efficient passage was attributed for eel on this structure </li><li><i>cumnbdamp</i>: Cumulated number of dam from the sea</li><li><i>cumnbdamso</i>: duplicate of cumnbdamp</li><li><i>idsegment</i>: Unique identifier of the segment [data type: UUID]. Use the <a href="https://doi.org/10.5281/zenodo.7546419">Atlas</a> to link with spatial table in PostgreSQL</li></ul><h2><strong>4. VERSIONS</strong></h2><ul><li><a href="https://doi.org/10.5281/zenodo.7825552">10.5281/zenodo.7825552 </a>1.0.0 - 2023-04-15 - Initial Upload (closed access)</li><li><a href="https://doi.org/10.5281/zenodo.8348374">10.5281/zenodo.8348374</a> 1.0.1 - 2023-09-15 - Update provider and names (closed access)</li><li><a href="https://doi.org/10.5281/zenodo.8348374">10.5281/zenodo.8348374</a> 1.0.1 - 2023-11-08 - Final version (open access)</li></ul><h2><strong>5. READ MORE</strong></h2><ul><li>Atlas of European Eel Distribution (<i>Anguilla anguilla</i>) in Portugal, Spain and France (<a href="https://doi.org/10.5281/zenodo.7546419">10.5281/zenodo.7546419</a>)</li><li>Electrofishing data for eel in the Iberian Peninsula (SUDOANG project) (<a href="https://doi.org/10.5281/zenodo.8348353">10.5281/zenodo.8348353</a>)</li><li>Eel data (<i>Anguilla anguilla</i>) and associated environment variables used to fit the EDA model in the SUDOE area (SUDOANG project) (<a href="https://doi.org/10.5281/zenodo.6397009">10.5281/zenodo.6397009</a>)</li></ul><h2><strong>6. FUNDING</strong></h2><p>Project co-financed by the INTERREG SUDOE Programme through the European Regional Development Fund (ERDF).</p>
Electrofishing data for eel in the Iberian Peninsula (SUDOANG project)
<h2><strong>1. SUDOANG PROJECT</strong></h2><p>The <a href="https://sudoang.eu/en/">SUDOANG</a> project has provided common tools to managers to support eel conservation in the SUDOE area (Spain, France and Portugal). One of the goals of the project was to develop an eel abundance and distribution <a href="https://zenodo.org/record/7546419">atlas</a> in the three countries, based on the results of the implementation of Eel Density Analysis (<a href="http://chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://sudoang.eu/wp-content/uploads/2022/02/E411_Briand_et_al_2022_EDA_report_opt-1.pdf">EDA</a>). This model extrapolates eel abundance from a range of river segments sampled by electrofishing, to the whole river and lake network, by considering how eel abundance, size and sex vary according to different parameters related to eel habitat.</p><h2><strong>2. SUDOANG DATABASE</strong></h2><p>Electrofishing data for Spain and Portugal were imported in the SUDOANG database (<a href="https://sudoang.eu/wp-content/uploads/2020/06/E121_import_tool-2.html#2_source_of_data">deliverable 1.2.1</a>), whose structure is inherited from the DataBase for EEl (DBEEL), developed during a European research project (POSE - Pilot projects to estimate potential and actual escapement of silver eel, Walker et al., 2011). This database is designed to contain all data relative to eel biology and anthropogenic pressures applying to eel. During the course of SUDOANG, this database was used and ameliorated. </p><p>The data providers (mainly SUDOE water managers, SUDOANG researchers and pilot basins from <a href="https://sudoang.eu/en/task-groups/">GT6: Task Group on eel stock monitoring transnational network</a>) are listed below:</p><ul><li><strong>SPAIN</strong><ul><li>Ministry for ecological transition and the demographic challenge (MITECO)</li><li>Spanish Fsih Chart (SIBIC): Data from different sources (indicated in the data)</li><li>Basque Water Agency (URA) - Basque Country</li><li>Gipuzkoa Council - Gipuzkoa (Basque Country)</li><li>Navarra Council (GAN-NIK) - Navarra</li><li>Asturias Council (DGPM) - Asturias</li><li>Xunta de Galicia, Consellería de Medio Ambiente, Territorio e Vivenda - Galicia</li><li>University of Córdoba (UCO) - Andalucía</li><li>Valencian Regional Hunting and Fishing Service (GVA) - Valencia</li><li>Catalan Water Agency (ACA) - Catalonia: <i>ACUERDO GOV/139/2013, de 15 de octubre, por el que se aprueba el Programa de seguimiento y control del Distrito de cuenca fluvial de Catalunya para el período 2013-2018</i></li></ul></li><li><strong>PORTUGAL</strong><ul><li>University of Porto (UP), CIIMAR</li><li>University of Lisbon, MARE: Data from different sources (indicated in the data)</li></ul></li></ul><h2><strong>3. DATA DESCRIPTION</strong></h2><p>Electrofishing data is mainly based on fishing stations, operations and eel biometry.</p><p>The <strong>station</strong> level corresponds to a location, identified by coordinates (Spatial Reference System 4326). The attributes associated with stations are:</p><ul><li><i>op_id</i>: identifier [data type: UUID]</li><li><i>institution</i>: data provider [data type: character]</li><li><i>ref_article</i>: reference to the article from which the data originated (only for SIBIC data source) [data type: character]</li><li><i>articletitle</i>: reference linked with data (only for SIBIC data source) [data type: character]</li><li><i>op_placename</i>: station name [data type: character]</li><li><i>x_espg_4326</i>: longitude (EPSG: 4326) [data type: numeric]</li><li><i>y_espg_4326</i>: latitude (EPSG: 4326) [data type: numeric]</li><li><i>country</i>: country [data type: character]</li></ul><p>The <strong>operation</strong> level corresponds to an event occurring at a specific date. At this level, a few more details such as the method or the material used, the wetted area, and electrofished length and width are added. The total number of eels, the numbers collected at each pass, and the number of measured eels are also included. The type of sampling used could not be specified but it is mostly single or several pass surveys. Therefore, the type was set to an unknown type of fishing. All electrofishing reporting eels in the second pass were considered as full electrofishing. The attributes associated with operation are:</p><ul><li><i>id</i>: identifier [data type: UUID]</li><li><i>op_id</i>: station identifier [data type: UUID]</li><li><i>op_gis_layername</i>: data provider [data type: character]</li><li><i>data_provider</i>: data provider [data type: character]</li><li><i>op_placename</i>: station name [data type: character]</li><li><i>ob_id</i>: observation identifier [data type: UUID]</li><li><i>ob_starting_date</i>: period starting date</li><li><i>ef_wetted_area</i>: wetted area of the station, in m2 [data type: numeric]</li><li><i>ef_nbpas</i>: the number of electrofishing pass during the observation [data type: numeric]</li><li><i>ef_fished_length</i>: the electrofished river length, in m [data type: numeric]</li><li><i>ef_fished_width</i>: the electrofished river width, in m [data type: numeric]</li><li><i>ob_origin</i>: origin of the observation, raw data [data type: character]</li><li><i>ob_type</i>: type of observation, electro-fishing [data type: character]</li><li><i>ob_period</i>: time step used for observation period, daily [data type: character]</li><li><i>ef_fishingmethod</i>: type of method used during the scientific sampling [data type: character]</li><li><i>ef_electrofishing_mean</i>: mean used to realize the scientific sampling, by foot [data type: character]</li><li><i>density</i>: density of eels collected, in nb/m2 [data type: numeric]</li><li><i>totalnumber</i>: total number of eels collected [data type: numeric]</li><li><i>nbp1</i>: number of eels collected during the 1st pass [data type: numeric]</li><li><i>nbp2</i>: number of eels collected during the 2nd pass [data type: numeric]</li><li><i>nbp3</i>: number of eels collected during the 3rd pass [data type: numeric]</li><li><i>nb_size_measured</i>: number of measured eels [data type: numeric]</li></ul><p>The <strong>individual </strong>level corresponds to the biological characteristics (length and weight) of the measured eels. The attributes associated with indivial are:</p><ul><li><i>dp_name</i>: name of data provider [data type: character]</li><li><i>ob_id</i>: observation identifier [data type: UUID]</li><li><i>bc_id</i>: batch (eels sampled during the observation) identifier [data type: UUID]</li><li><i>bc_ba_id</i>: sub-batch identifier [data type: UUID]</li><li><i>size</i>: total length of eel, in mm [data type: numeric]</li><li><i>fish_id</i>: individual identifier [data type: UUID]</li><li><i>weight</i>: body weight of eel, in g [data type: numeric]</li></ul><p>The three tables can be related to each other through the identifiers, meaning that the eels measured in the <strong>individual</strong> table can be identified with the <strong>operations</strong> through the <i>ob_id</i> identifier, and these operations can be linked to the <strong>stations </strong>through the <i>op_id</i> identifier, allowing for a comprehensive view of the electrofishing sampling collected for Spain and Portugal.</p><h2><strong>4. VERSIONS</strong></h2><ul><li><a href="https://doi.org/10.5281/zenodo.8009823">10.5281/zenodo.8009823 </a>1.0.0 - 2023-06-06 - Initial upload (closed access)</li><li><a href="https://doi.org/10.5281/zenodo.8207785">10.5281/zenodo.8207785</a> 1.0.1 - 2023-08-02 - Fixed data provider in station and operation tables (closed access)</li><li><a href="https://doi.org/10.5281/zenodo.8348353">10.5281/zenodo.8348353</a> 1.0.2 - 2023-15-09 - Fixed stations (providers) (closed access)</li><li><a href="https://doi.org/10.5281/zenodo.8348353">10.5281/zenodo.8348353</a> 1.0.2 - 2023-11-08 - Final version (open access)</li></ul><h2><strong>5. READ MORE</strong></h2><ul><li>Atlas of European Eel Distribution (<i>Anguilla anguilla</i>) in Portugal, Spain and France (<a href="https://doi.org/10.5281/zenodo.7546419">10.5281/zenodo.7546419</a>)</li><li>Eel data (<i>Anguilla anguilla</i>) and associated environment variables used to fit the EDA model in the SUDOE area (SUDOANG project) (<a href="https://doi.org/10.5281/zenodo.6397009">10.5281/zenodo.6397009</a>)</li><li>Cumulated dam impact in France and the Iberian Peninsula (SUDOANG project) (<a href="https://doi.org/10.5281/zenodo.8348374">10.5281/zenodo.8348374</a>)</li></ul><h2><strong>6. FUNDING</strong></h2><p>Project co-financed by the INTERREG SUDOE Programme through the European Regional Development Fund (ERDF).</p>
Moisture Recycling over the Iberian Peninsula
<p>These data are made available as part of paper: S. J. Gonzalez-Roji, J. Saenz, J. Diaz de Argandona, G. Ibarra-Berastegi (2020) "Moisture recycling over the Iberian Peninsula. The impact of 3DVAR data assimilation", published in <em>Atmosphere </em>(<a href="https://doi.org/10.3390/atmos11010019">https://doi.org/10.3390/atmos11010019</a>). The dataset holds selected postprocessed files that allow to reproduce all the results in the paper.</p> <p>Two WRF experiments nested in ERA-Interim were prepared. The first one (N) was configured as in standard numerical downscaling experiments. The second one (D), with the same parameterizations, included a step of 3DVAR data assimilation every 6 hours. The original experiments covered period 2010-2014 after a year of spin-up (2019). However, D was extended until the end of 2018. </p> <p>The following monthly averaged (accumulated for rain) nc files are included:</p> <p>- Qx/Qy: Refer to the zonal and meridional vertically integrated moisture fluxes for the domain. </p> <p>- Rain: Include the accumulated convective and large-scale precipitation output from the model. </p> <p>- SMOIS: Contains the soil moisture of the model runs.</p> <p>- mask: Defines the area where the recycling ratio is calculated over the Iberian Peninsula. </p> <p>- Rho: Holds the recycling ratio at every grid point. </p> <p>The -N- or -D- characters in the file names indicate whether the files come from the WRF N or WRF D experiments. </p> <p> </p>
Distribution of alien tetrapods in the Iberian Peninsula
<p>We present a dataset that assembles occurrence records of alien tetrapods (amphibians, reptiles, birds and mammals) in the Iberian Peninsula, a coherent biogeographically unit where introductions of alien species have occurred for millennia. These data have important potential applications for ecological research and management, including the assessment of invasion risks, formulation of preventive and management plans, and research at the biological community level on alien species. This dataset summarizes inventories and data sources on the taxonomy and distribution of alien tetrapods in the Iberia Peninsula, comprising known locations from published literature, expert knowledge and citizen science platforms. An expert-based assessment process allowed the identification of unreliable records (misclassification or natural dispersion from native range), and the classification of species according to their status of reproduction in the wild. Distributional data was harmonized into a common area unit, the 10x10 km Universal Transverse Mercator (UTM) system (n=6,152 cells). The year of observation and/or year of publication were also assigned to the records. In total, we assembled 35,940 unique distribution records (UTM x species x Year) for 253 species (6 amphibians, 16 reptiles, 218 birds and 13 mammals), spanning between 1912 and 2020. The species with highest number of distribution records were the Mediterranean painted frog <em>Discoglossus pictus</em> (n=59 UTM), the pond slider <em>Trachemys scripta </em>(n=471), the common waxbill <em>Estrilda astrild</em> (n=1,275) and the house mouse <em>Mus musculus </em>(n=4,043), for amphibians, reptiles, birds and mammals, respectively. Most alien species recorded are native to Africa (33%), followed by South America (21%), Asia (19%), North America (12%) and Oceania (10%). Thirty-six species are classified by IUCN as threatened in their native range, namely 2 Critically Endangered (CR), 6 Endangered (EN), 8 Vulnerable (VU), and 20 species Near Threatened (NT). </p>
Water availability and temperature scenarios for water-dependent power plants in the Danube river basin and the Iberian Peninsula
<p>The dataset is composed by 12 files reporting the water availability and temperature scenarios for 167 water-dependent power plants in the Danube river basin and the Iberian Peninsula.</p> <p>The dataset is split into multiple files by region (Danube river basin (Danube) or Iberian Peninsula (IP)), variable (discharge or river temperature) and scenario (baseline, RCP26 or RCP85) considered.</p> <p>The title of each file is composed by the variable reported (discharge or river temperature) and the scenario considered (baseline: 1951-2004, RCP26: 2006-2100, RCP85: 2006-2100). The first row is used to report the fields considered: the first three columns report the day, the month and the year. The remaining columns report the name of the power plant considered in each region (57 for the Daube river basin and 110 for the Iberian Peninsula). In each row day, month, year and streamflow or river temperature values are reported for every water-dependent power plant examined in the study.</p> <p>Temperature is reported as daily average temperature in degrees Celsius (°C) while water availability is reported as daily average streamflow in cubic meters per second (m^3/s).</p> <p>For a description on how these files were obtained, please refer to <a href="https://doi.org/10.2777/135510">https://doi.org/10.2777/135510</a>.</p>
Sub-speciation processes of equids in the Iberian Peninsula: ecological strategies and refuge areas
<p>Metrical raw data of teeth and bones of Equus caballus and Equus hydruntinus from Canyars (Catalunya, Spain)</p> <p>They document the publication : Uzunidis, Sanz, Daura, 2024, Sub-speciation processes of equids in the Iberian Peninsula: ecological strategies and refuge areas, Quaternary Science Reviews, 325, 108473. https://www.sciencedirect.com/science/article/abs/pii/S0277379123005218</p>
Long-term monitoring of the fish community in the Minho Estuary (NW Iberian Peninsula)
<p>The dataset contains data from fyke nets deployed in the Minho Estuary (Portugal) from 2010 to 2019. The fyke nets were used for fish sampling and data collection. The sampling frequency varied but, on average, data was collected weekly using five different fyke nets. However, due to technical issues (e.g. lost or damaged fyke nets), the sampling pattern is not constant, with some fyke nets staying underwater for shorter or longer periods, and occasionally having fewer than five fyke nets per parentEventID. The dataset includes various terms such as parentEventID, eventID, eventDate, year, startDayOfYear, endDayOfYear, country, countryCode, geodeticDatum, decimalLatitude, decimalLongitude, coordinateUncertaintyInMeters, DEIMS.iD, habitat, basisOfRecord, samplingProtocol, sampleSizeValue, sampleSizeUnit, samplingEffort, occurrenceStatus, occurrenceID, organismQuantity, organismQuantityType, degreeOfEstablishment, vernacularName, scientificName, acceptedNameUsageID, taxonRank, kingdom, phylum, order, family, genus, and scientificNameAuthorship.</p>
Positions for "First insights into migration routes and nonbreeding sites used by Red-rumped Swallows (Cecropis daurica rufula) breeding in the Iberian Peninsula"
<p><strong>Abstract</strong></p> <p>Using EURING data and geolocation, we describe migration routes and nonbreeding range of Red-rumped Swallows breeding in the Western Palearctic. One bird ringed in southern Spain and recovered in southern Morocco indicates southwestern migration; geolocator data from five birds from central and eastern Iberian Peninsula confirm migration to various nonbreeding sites in sub-Saharan west Africa between Senegal/Mauritania and Ghana. Two swallows showed non-breeding site itinerancy by using more than one nonbreeding site per season. Despite wide ranges in departure for autumn (August- October) and spring migration (February-March), all birds arrived at nonbreeding and breeding sites within ±1-week from each other.</p> <p><strong>Zusammenfassung</strong></p> <p>Erste Einblicke in Zugrouten und Überwinterungsgebiete von Rötelschwalben (<em>Cecropis daurica rufula</em>) der Iberischen Halbinsel.<br> In dieser Studie beschreiben wir Zugrouten und Überwinterungsgebiete westpaläarktischer Rötelschwalben basierend auf EURING- und Geolokations-Daten. Eine Rötelschwalbe, die in Südspanien beringt und im südlichen Marokko wiedergefunden wurde, spricht für einen südwestlichen Zug. Geolokalisation von fünf Vögeln der zentralen und östlichen Iberischen Halbinsel zeigen Überwinterungsorte im sub-Saharischen Westafrika zwischen Senegal/Mauretanien und Ghana. Zwei der getrackten Rötelschwalben nutzten mehrere Überwinterungsplätze pro Saison. Trotz der großen Schwankungsbreite der Abzugszeiten im Herbst (August-Oktober) und im Frühjahr (Februar-März) erreichten die getrackten Vögel ihre Nichtbrut- bzw. Brutplätze innerhalb von 1–2 Wochen.</p>
Fig. 2 in Schizorhynchia Meixner, 1928 (Platyhelminthes, Rhabdocoela) of the Iberian Peninsula, with a description of four new species from Portugal
Fig. 2. Copulatory organ of species of Proschizorhynchus Meixner, 1928. A. Proschizorhynchus algarvensis sp. nov., holotype (HU 615). B–C. P. arnautsae sp. nov. B. Holotype (HU 616). C. A specimen from the reference collection of Hasselt University (HU X.1.35). D–E. P. troglodytus sp. nov. D. Holotype (HU 617). E. A specimen from the reference collection of Hasselt University (HU X.1.40). F–G. P. pectinatus l'Hardy, 1965 (HU X.1.43). F. Copulatory organ. G. Sclerotised spermatic duct. H. P. reniformis Brunet, 1970 (HU X.1.45). Scale bars: A, F = 50 µm; B–E, G–H = 20 µm.
FIG. 3 in The last record of an ailuropod bear from the Iberian Peninsula
FIG. 3. — Indarctos punjabiensis (Lydekker, 1884) from Las Casiones, right IV metacarpal: A, plantar view; B, medial view; C, dorsal view; D, lateral view. Scale bar: 5 cm.
FIG. 8 in The last record of an ailuropod bear from the Iberian Peninsula
FIG. 8. — Biochronology showing the stratigraphic ranges of the genera Indarctos Pilgrim, 1913 and Agriotherium A. Wagner, 1837 in the Iberian Peninsula, related to the two biotic events recorded during the Messinian. Mammal ages and local zones according to Morales et al. 2013. Absolute age after Gibert et al. 2013.
Fig. 3. Male femur I in Leiolima iberica, a new harvestman genus and species from the Iberian Peninsula (Arachnida, Opiliones, Sclerosomatidae)
Fig. 3. Male femur I of three European species of Leiobuninae. A, D. Leiolima iberica gen. et sp. nov. (ZUPV 3330 at CHW). B, E. Nelima doriae (Canestrini, 1871) (from the Netherlands). C, F. Leiobunum rotundum (Latreille, 1798). A–C. Dorsal view. D–F. Lateral view (dorsal side on the right). Ch = sensillum chaeticum; Tr = trichome (trichomes in D drawn smaller). Scale bars: A–C = 0.05 mm; D–F = 0.5 mm.
Fig. 1 in Leiolima iberica, a new harvestman genus and species from the Iberian Peninsula (Arachnida, Opiliones, Sclerosomatidae)
Fig. 1. Leiolima iberica gen. et sp. nov. Dorsal view of the male holotype (MNCN 20.02/17372) (left, body length 3.15 mm) and a female paratype (MNCN 20.02/17374) (right, body length 5.58 mm). Scale bars: 1 mm.
Fig. 9 in Leiolima iberica, a new harvestman genus and species from the Iberian Peninsula (Arachnida, Opiliones, Sclerosomatidae)
Fig. 9. Body size and leg length measurements (in mm apart from the MBLI ratio) of all European/ Mahgrebian species of Leiobunum C.L. Koch, 1839 (grey bars, diamonds on averages) and Leiolima iberica gen. et sp. nov. (red rectangles). Only the measured parameters for L. iberica gen. et sp. nov. are shown. Source of data: Caporiacco (1929), Karaman (1996), Komposch (1998), Martens (1978), Prieto & Fernández (2007), Prieto & Wijnhoven (2017) and Šilhavý (1965).
Fig. 10 in Leiolima iberica, a new harvestman genus and species from the Iberian Peninsula (Arachnida, Opiliones, Sclerosomatidae)
Fig. 10. Orifices of repugnatorial glands of the type species of European genera of Leiobuninae in dorsal (upper) and lateral (lower) views. A. Leiolima iberica gen. et sp. nov. (male, ZUPV 4104). B. Nelima silvatica (Simon, 1879) (male, ZUPV 1316: Castarnés, Huesca, Spain). C. Leiobunum rotundum (Latreille, 1798) (male, ZUPV 5065: Oña, Burgos, Spain). D. Cosmobunus granarius Lucas, 1846 (male, ZUPV 1932: Hornos, Jaén, Spain). Coxae I were removed to improve vision and images have been resized in proportion to their respective prosomal width (A = 111 %; B = 125 %; C = 82 %; D = 73 %). Arrowheads in upper views point to the orifices. Scale bars: 0.1 mm.
Figs 1-7 in Notes on some Palliduphantes Saaristo & Tanasevitch, 2001, with the description of a new species from the Iberian Peninsula (Araneae: Linyphiidae)
Figs 1-7. Palliduphantes curvus sp. nov., details of palp and epigyne structure; male (1-4) and female (5-7) paratypes from Elda. (1) Right palp, retrolateral view. (2) Paracymbium, retrolateral view. (3) Embolic division, ventral view. (4) Lamella characteristica, dorsal view. (5-7) Epigyne, lateral, ventral and dorsal view, respectively.
Figure 9. Acrobeles bushmanicus Heyns, 1969 in Some rare species of cephalobs (Nematoda: Rhabditida: Cephalobidae) from Southern Iberian Peninsula
Figure 9. Acrobeles bushmanicus Heyns, 1969 (LM): (A) neck (arrow points at excretory pore); (B, C) lip region in dorsal and lateral views, respectively (I: primary axil, II: secondary axil; arrow points at amphid); (D) lateral field at deirid level (arrow); (E) male genital system; (F, G) female posterior end (arrow points at phasmid); (H) male posterior end (ph = phasmid, p1–p5 = genital papillae).
Figure 2 in Some rare species of cephalobs (Nematoda: Rhabditida: Cephalobidae) from Southern Iberian Peninsula
Figure 2. Heterocephalobellus magnificus (Andrássy, 1987) De Ley et al. 1993a (LM, juvenile): (A) neck region (arrow points at excretory pore); (B) stoma; (C) lip region; (D) genital primordium; (E) posterior end. Stegelleta ophioglossa Andrássy, 1967b (LM, female): (F) neck region (arrow points at excretory pore); (G) lip region (arrow points at amphid); (H) vagina region; (I, J) posterior end at rectum and lateral field levels, respectively (arrow points at phasmid); (K) cuticle.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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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.