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99 results for “Anguilla anguilla”
Fig. 2 in Microhabitat Preference And Relationships B E T W E E N M E Ta Z O A N Pa R A S I T E S O N T H E G I L L A P Pa R At U S O F T H E E U R O P E A N E E L (A N G U I L L A Anguilla) From Freshwaters Of Latvia
Fig. 2. The metazoan parasite prevalence in different gill area of European eel Anguilla anguilla from freshwater bodies of Latvia. A – Pseudodactylogyrus bini; B – Pseudodactylogyrus anguillae; C – Ergasilus sieboldi; D – Anodonta sp.
Figures 4–5. Mitochondrial D-loop 474 in Molecular confirmation of the occurrence of Anguilla interioris (Actinopterygii: Anguilliformes) in North Maluku of Indonesia and mitochondrial DNA haplotype diversity among existing specimens
Figures 4–5. Mitochondrial D-loop 474 bp sequence analyses. (4) Phylogenetic analysis based on maximum likelihood algorithm with the sample codes, GenBank accession numbers and sample sites shown. Bootstrap percentages are shown at the tree nodes. (5) Haplotype network with the haplotypes labelled as H1 to H9. The circle size is proportional to the number of samples, and different sample sites are represented by different colours. Small white circle represents median vector which is the hypothesized or missing haplotype. Each dash on the line symbolizes one mutational step.
Figure 1 in Molecular confirmation of the occurrence of Anguilla interioris (Actinopterygii: Anguilliformes) in North Maluku of Indonesia and mitochondrial DNA haplotype diversity among existing specimens
Figure 1. Sampling locations of Anguilla interioris in North Maluku of East Indonesia. Sampling locations are shown in red (circle: COI, triangle: D-loop). Locations of Bougainville of Papua New Guinea, Papua New Guinea mainland, Negros Oriental and Sibutad of Philippines, and Ambon and Bengkulu of Indonesia, which were used in molecular phylogenetic and haplotype network analyses, are shown in purple (circle: COI, triangle: D-loop). Specimen records are shown in square with growth stages; L [larval (leptocephalus); Kuroki et al. 2006, Wouthuyzen et al. 2009, Aoyama et al. 2018], J [juvenile (glass eel); Sugeha et al. 2008, Fahmi et al. 2012, Wibowo et al. 2021] and A (adult; Watanabe et al. 2004, Fahmi et al. 2012, Wibowo et al. 2021, this study). Base maps were downloaded from http://viewer. nationalmap.gov/viewer (USGS 2022) and from the OpenStreetMap at https://www.openstreetmap.org.
Fig. 2 in Temporal dynamics of species associations in the parasite community of European eels, Anguilla anguilla, from a coastal lagoon
Fig. 2. Intensity of infection (mean ± SE number of parasites per host, including infected hosts only) of the six most common helminth parasites of eels, Anguilla anguilla, in Comacchio Lagoons, during three sampling periods. Graphs on the right-hand side do not include the 2015–2017 period, as these species were not found during that period. See Table 1 for full species names.
Fig. 4 in Temporal dynamics of species associations in the parasite community of European eels, Anguilla anguilla, from a coastal lagoon
Fig. 4. Pairwise relationships between numbers of parasites per host for the three most common digenean parasites of eels, Anguilla anguilla, in Comacchio Lagoons, across all three sampling periods combined. The line represents the relationship (with 95% confidence intervals) predicted by the generalized linear model; see text. Tick marks indicate partial residuals with either positive (top) or negative values (bottom). See Table 1 for full species names.
Fig. 3 in Temporal dynamics of species associations in the parasite community of European eels, Anguilla anguilla, from a coastal lagoon
Fig. 3. Scatterplots of pairwise relationships between numbers of parasites per host for the three most common digenean parasites of eels, Anguilla anguilla, in Comacchio Lagoons, across all three sampling periods combined. See Table 1 for full species names.
Fig. 1 in Temporal dynamics of species associations in the parasite community of European eels, Anguilla anguilla, from a coastal lagoon
Fig. 1. Abundance (mean number of parasites per host, including non-infected hosts) of the six most common helminth parasites of eels, Anguilla anguilla, in Comacchio Lagoons, during three sampling periods: 2005–2006 (N = 140 eels), 2010–2013 (N = 131), and 2015–2017 (N = 30). Note that some values for the time period 2015–2017 are based on very few fish; see Table 1 for actual numbers and for full species names.
Figure 1 in The diversity and distributions of the beetles (Insecta: Coleoptera) of the northern Leeward Islands, Lesser Antilles (Anguilla, Antigua, Barbuda, Nevis, Saba, St. Barthélemy, St. Eustatius, St. Kitts, and St. Martin-St. Maarten
Figure 1. The islands of the central and eastern West Indies and adjacent continental land masses, showing in the east the main island arc of the Lesser Antilles.
Fig. 14. Ascarophis arctica Polyanskiy, 1952 from Gasterosteus aculeatus Linnaeus, scanning electron micrographs. A in Rhabdochona angusticaudata sp. n. (Nematoda: Rhabdochonidae) from the Japanese eel Anguilla japonica, and new records of some other nematodes from inland fishes in Japan
Fig. 14. Ascarophis arctica Polyanskiy, 1952 from Gasterosteus aculeatus Linnaeus, scanning electron micrographs. A – posterior end of male, ventral view; B – tail of male, subventral view (arrows indicate postanal papillae); C – precloacal region, subventral view (arrows indicate preanal papillae; note weakly-developed ventral precloacal ridges); D – posterior end of male, sublateral view (arrows indicate two posteriormost pairs of postanal papillae; note ventral precloacal ridges); E – broken female body with eggs; F – egg with filaments on both poles; G – egg with filaments only on one pole.
Fig. 11. Rhabdochona zacconis Yamaguti, 1935 in Rhabdochona angusticaudata sp. n. (Nematoda: Rhabdochonidae) from the Japanese eel Anguilla japonica, and new records of some other nematodes from inland fishes in Japan
Fig. 11. Rhabdochona zacconis Yamaguti, 1935 from Tribolodon hakonensis (Günther), scanning electron micrographs. A, B – cephalic end of male, subapical and apical views, respectively (arrows indicate sublabia); C – deirid; D – tail of male, lateral view (arrow indicates cloaca); E – eggs dissected out from uterus; F – eggs with polar filaments. Abbreviations: a – cephalic papilla; b – amphid.
Fig. 13. Ascarophis arctica Polyanskiy, 1952 from Gasterosteus aculeatus Linnaeus, scanning electron micrographs. A–C in Rhabdochona angusticaudata sp. n. (Nematoda: Rhabdochonidae) from the Japanese eel Anguilla japonica, and new records of some other nematodes from inland fishes in Japan
Fig. 13. Ascarophis arctica Polyanskiy, 1952 from Gasterosteus aculeatus Linnaeus, scanning electron micrographs. A–C – cephalic end of female, lateral, apical and dorsoventral views, respectively; D – region of female mouth (another specimen), sublateral view; E – tail of female, ventral view; F – deirid; G – distal end of left spicule, ventral view. Abbreviations: a – amphid; b – cephalic papilla c – phasmid; d – anus; l – labium; p – pseudolabium with anterior tooth-like projection; s – sublabium.
Fig. 10 in Rhabdochona angusticaudata sp. n. (Nematoda: Rhabdochonidae) from the Japanese eel Anguilla japonica, and new records of some other nematodes from inland fishes in Japan
Fig. 10. Rhabdochona angusticaudata sp. n. from Anguilla japonica Temminck et Schlegel, scanning electron micrographs. A, B – anterior end of female body, sublateral and dorsoventral views (arrow indicates deirid); C – tail of male, lateral view; D – region of male tail with last postanal papilla and phasmid, lateral view; E – tail of gravid female, ventral view; F – vulva of gravid female, ventral view. Abbreviations: e – cloacal aperture; h – caudal papilla of last postanal pair; i – phasmid; k – anus.
Fig. 7. Heliconema anguillae Yamaguti, 1935 in Rhabdochona angusticaudata sp. n. (Nematoda: Rhabdochonidae) from the Japanese eel Anguilla japonica, and new records of some other nematodes from inland fishes in Japan
Fig. 7. Heliconema anguillae Yamaguti, 1935 from Anguilla japonica Temminck et Schlegel, scanning electron micrographs. A, B – cephalic end, subapical views (arrow indicates amphid); C – tail of male, sublateral view; D – ventral precloacal ridges and first two pairs of preanal papillae, ventral view; E – tail of male, ventral view; F – tail tip of male, ventral view (arrows indicate phasmids). Abbreviations: a – cephalic papilla; b – submedian tooth; c – lateral tooth; d – pseudolabial lateroterminal depression; e – cloacal aperture; f – papillae of first two preanal pairs; g – small ventral postanal papilla.
Fig. 8 in Rhabdochona angusticaudata sp. n. (Nematoda: Rhabdochonidae) from the Japanese eel Anguilla japonica, and new records of some other nematodes from inland fishes in Japan
Fig. 8. Rhabdochona angusticaudata sp. n. from Anguilla japonica Temminck et Schlegel. A – anterior part of male body, lateral view; B, C – anterior end of male, dorsoventral and lateral views, respectively; D – cephalic end of female, lateral view; E – cephalic end of male, apical view; F – deirid; G, H – distal end of left spicule (different specimens), lateral views; I – egg; J – female tail, lateral view; K – right spicule, lateral view; L – posterior end of male, lateral view; M – tail tip of female.
Fig. 2 in Rhabdochona angusticaudata sp. n. (Nematoda: Rhabdochonidae) from the Japanese eel Anguilla japonica, and new records of some other nematodes from inland fishes in Japan
Fig. 2. Hysterothylacium haze (Machida, Takahashi et Masuuchi, 1978) from Acanthogobius flavimanus (Temminck et Schlegel), scanning electron micrographs. A – anterior end of female with distinct lateral alae, dorsal view; B – cephalic end, apical view; C – dorsal lip; D – subventral lip; E – caudal end of male, lateral view (arrow indicates double papilla); F – distribution of papillae on caudal end, lateral view (another specimen; arrow indicates double papilla); G – posterior end of male, ventral view. Abbreviations: a – double cephalic papilla; b – single cephalic papilla; d – dorsal lip; e – amphid; i – interlabium; s – spicule.
Fig. 6 in Rhabdochona angusticaudata sp. n. (Nematoda: Rhabdochonidae) from the Japanese eel Anguilla japonica, and new records of some other nematodes from inland fishes in Japan
Fig. 6. Paraquimperia tenerrima (von Linstow, 1878) from Anguilla anguilla (Linnaeus), Czech Republic, scanning electron micrographs of mouth. A – apical view; B – subdorsal view. Abbreviations: a – amphid; b – cephalic papilla; c – two tooth-like structures of neighbouring sectors of mouth mound; d – oesophageal tooth.
Fig. 9 in Rhabdochona angusticaudata sp. n. (Nematoda: Rhabdochonidae) from the Japanese eel Anguilla japonica, and new records of some other nematodes from inland fishes in Japan
Fig. 9. Rhabdochona angusticaudata sp. n. from Anguilla japonica Temminck et Schlegel, scanning electron micrographs. A – cephalic end of male, lateral view; B – cephalic end of female, apical view; C – cephalic end of male, apical view; D – mouth region of female, apical view (arrow indicates sublabium); E – cephalic end of male (another specimen) with more numerous (16) anterior teeth, apical view; F – deirid. Abbreviations: a – amphid; b – cephalic papilla.
Genome-wide methylation in the panmictic European eel (Anguilla anguilla)
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Data from: Genomic footprints of hybridization in North Atlantic eels (Anguilla anguilla and A. rostrata)
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Eel data (Anguilla anguilla) and associated environment variables for eel in the SUDOE area (SUDOANG project)
<h2><strong>1. DESCRIPTION</strong></h2><h3><strong>1.1. THE SUDOANG PROJECT</strong></h3><p>The <a href="https://sudoang.eu/en/">SUDOANG</a> project aims at providing common tools to managers to support eel conservation in the SUDOE area (Spain, France and Portugal). </p><p>Three main datasets have been used to implement EDA.</p><ul><li>A database of rivers and their attributes along with tools for chaining</li><li>A database of dams.</li><li>A database of electrofishing (current dataset)</li></ul><p>Electrofishing data include site locations, fishing operations which can be done several times at one site, and fish data collected during each operation. The operations are attached to stretches of river or river segments whose characteristics describe the conditions for presence, density, size structure, or silvering rate of the eels. </p><p>The electrofishing operation are classified by type:</p><ul><li>com full two pass fishing</li><li>coa full two pass electrofishing for eel</li><li>iaa eel abundance point sampling</li><li>ber bank sampling</li><li>gm point fishing for large streams</li><li>oth other, or unspecified.</li></ul><h3><strong>1.2. TEMPORAL SCOPE </strong></h3><p>From 1985 to 2018, beware incomplete dataset after 2015 in France.</p><h3><strong>1.3. GEOGRAPHICAL RANGE</strong></h3><p>The SUDOE area including Iberian Peninsula and France.</p><h2><strong>2. DATASETS DESCRIPTION</strong></h2><h3><strong>2.1. DENSITIES AND PRESENCE ABSENCE</strong></h3><h4>Dataset: <a href="https://zenodo.org/api/files/c576c330-0219-4710-a831-717762b117aa/frsppt_12_2020.Rdata?versionId=ad5867d9-1a51-413d-9d27-d269462df9a2">frsppt_12_2020.Rdata</a></h4><p>Most variables are built <a href="https://forgemia.inra.fr/pole-migrateurs/eda/eda_model/-/blob/de433830a1a483fff6404e0f668a38e8e88663a6/eda2.3/report/report2.3/EDA_build.Rnw#L1233">here. </a></p><p>The script to create cumulated values for dams can be found <a href="https://forgemia.inra.fr/pole-migrateurs/eda/eda_model/-/blob/main/S4/BaseEdaRiosRiversegmentsDam.R#L624">here.</a></p><p>For a technical description see the <a href="https://sudoang.eu/wp-content/uploads/2022/02/E411_Briand_et_al_2022_EDA_report_opt-1.pdf">report.</a></p><p>This file contains the following datasets:</p><ul><li>ddd => dataset used to calibrate the presence absence model, 46147 lines</li><li>ddg => dataset used to calibrate the gamma model (only positive values retained), 19993 lines.</li><li>tdd => dataset corresponding to places where transport operation have been identified, presence absence model, 6582 lines.</li><li>tdg => dataset corresponding to places where transport operation have been identified, gamma model (only positive values) 984 lines.</li></ul><p>And the following columns (in alphabetical order):</p><ul><li><i>altitudem</i>: Altitude in meter truncated to 800 m</li><li><i>area_sudo</i>: Area for recruitment (Drouineau et al., 2021)</li><li><i>codesea</i>: Code of the Sea, factor A = Atlantic, M = Mediterranean</li><li><i>country</i>: A factor (FR, SP, PT) for France, Spain and Portugal</li><li><i>country2</i>: Country with grouping for the Iberian Peninsula (SPPT). Other level is France (FR)</li><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_pp</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_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 a score of efficient passage was attributed for eel on this structure</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</li><li><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>cumwettedsurfacebothkm2</i>.: Surface of water downstream from the segment in the river. Corresponds to both riversegment and waterbodies</li><li><i>cumwettedsurfacekm2</i>.: Surface of water downstream from the segment in the river. Corresponds only to rivers</li><li><i>cumwettedsurfaceotherkm2</i>.: Surface of water downstream from the segment in the river. Corresponds only waterbodies (water surfaces, associated with the segment).</li><li><i>densCS</i>: Density from Carle and Strub, number in second pass extrapolated from efficiency if only one pass</li><li><i>dist_from_gibraltar_km</i>: Distance to Gibraltar calculated using an enveloppe along the coastline (e.g. the estuaries ingress inland are not counted for this distance).</li><li><i>distanceseakm</i>: Distance to the sea</li><li><i>distanceseakm</i>.: Distance to the sea, truncated at 500</li><li><i>distancesourcem</i>: distance to the source in meters</li><li><i>downstdrainagewettedsurfaceboth</i>.: Percentage of wetted surface downstream for both rivers and associated waterbodies (cumwettedsurfacebothkm2) divided by land surface for all segments within the basin located at a same or lesser distance to the sea.</li><li><i>downstreamwettedsurface</i>: Percentage of wetted surface downstream (<i>cumwettedsurfacekm2</i>) divided by land surface for all segments within the basin located at a same or lesser distance to the sea</li><li><i>drainage_density_perm</i>.: River length / surface of basin in the basin downstream (m-1) Numeric, multiplied by $10^4$, truncated to 20</li><li><i>ef_fishingmethod</i>: Fishing method. See details in text and Briand et al., (2022)</li><li><i>ef_wetted_area</i>: Surface of the electrofishing station</li><li><i>emu</i>: Eel management unit. See <a href="https://github.com/ices-eg/wg_WGEEL/wiki">Git WGEEL</a></li><li><i>hydraulicdensityperm2</i>.: Number of riversegments per surface of basin (m-2). Numeric Multiplied by 10^6, truncated to 1.5</li><li><i>idsegment</i>: Unique identifier of the segment TEXT</li><li><i>laltitudem</i>.: Log transformed value of altitude (truncated)</li><li><i>lcs_height_10_n</i>.: Log transformed value of cumulated height</li><li><i>lddws</i>: Log transformed value of <i>downstdrainagewettedsurfaceboth</i></li><li><i>ldownstreamwettedsurface</i>: Log of previous column</li><li><i>lriverwidthm</i>.: Log transformed value of river width</li><li><i>month</i>: Month</li><li><i>NCS</i>: Number of eels estimated by Carle and Strub</li><li><i>ob_id</i>: Operation (observation) identifier</li><li><i>op_id</i>: Station (observation place) identifier</li><li><i>riverwidthm</i>: Width of the river in m (comes from various sources: see <a href="https://doi.org/10.5281/zenodo.7546419">Atlas</a> and Briand et al., 2022).</li><li><i>seaidsegment</i>: Identifier of the sea idsegment</li><li><i>temperature</i>: Average temperature from 1960-2000 from the CCM (Vogt, 2007)</li><li><i>temperature.1</i>: duplicate of temperature</li><li><i>transport</i>: code of transport operation</li><li><i>year</i>: year of electrofishing</li></ul><h3><strong>2.2. SIZE STRUCTURE OF EELS</strong> </h3><h4>Dataset <a href="https://zenodo.org/api/files/c576c330-0219-4710-a831-717762b117aa/table_ind.Rdata?versionId=a81c7bb4-0f36-44e3-82ea-86d9a2caac8e">table_ind.Rdata</a> </h4><p>A dataset of 494163 lines. In this dataset, one line correspond to one eel.</p><ul><li><i>altitudem</i>: Altitude in meter</li><li><i>altitudem</i>.: Altitude in meter truncated to 800 m</li><li><i>area_sudo</i>: Area for recruitment (Drouineau et al., 2021)</li><li><i>basin</i>: Name (or code from bd_carthage France) of the basin</li><li><i>codesea</i>: Code of the Sea, factor A = Atlantic, M = Mediterranean</li><li><i>country</i>: A factor (FR, SP, PT) for France, Spain, and Portugal</li><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_pp</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_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 a score of efficient passage was attributed for eel on this structure</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</li><li><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, including prediction for missing values, only the dams with pass are used to build the cumulated value</li><li><i>cs_height_10_pass1</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_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, no prediction for missing values, only the dams with pass are used to build the cumulated value</li><li><i>cs_height_10_ppass1</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_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, 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_pscore1</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_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, 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_score1</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_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>cumheightdam</i>: Cumulated height of dam (ignore)</li><li><i>cumnbdamp</i>: Cumulated number of dam from the sea</li><li><i>cumnbdamso</i>: Cumulated number of dam from the sea only for dams whose height is larger than zero</li><li><i>densCS</i>: Density from Carle and Strub, number in second pass extrapolated from efficiency if only one pass.</li><li><i>dist_from_gibraltar_km</i>: Distance to Gibraltar calculated using an enveloppe along the coastline (e.g. the estuaries ingress inland are not counted for this distance).</li><li><i>distanceseakm</i>: Distance to the sea in kilometers</li><li><i>distanceseakm</i>.: Distance to the sea, truncated at 500</li><li><i>distanceseam</i>: Distance to the sea in meters</li><li><i>distancesourcem</i>: Distance to the source in meters</li><li><i>ef_electrofishing_mean</i>: Percentage of wetted surface downstream (<i>cumwettedsurfacekm2</i>) divided by land surface for all segments within the basin located at a same or lesser distance to the sea</li><li><i>ef_fished_length</i>: Length of the fishing operation</li><li><i>ef_fished_width</i>: Width of the fishing operation</li><li><i>ef_fishingmethod</i>: Method of electrofishing</li><li><i>ef_nbpas</i>: Number of pass in the electrofishing operation</li><li><i>ef_wetted_area</i>: Surface of the electrofishing station</li><li><i>emu</i>: Eel Management Unit</li><li><i>id</i>: Comes from uncout R function, which transforms counts into lines</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><li><i>isendoreic</i>: Is the riversegment coming from an endoreic river?</li><li><i>issea</i>: Is the riversegment a sea outlet?</li><li><i>laltitudem</i>.: Log transformed value of altitude (truncated)</li><li><i>lcs_height_10_n</i>.: Log transformed value of cumulated height</li><li><i>lengthm</i>: Length of the electroshing station in meters</li><li><i>lengthriverm</i>: length of the riversegment in meters</li><li><i>lriverwidthm</i>.: Log transformed value of river width</li><li><i>medianflowm3ps</i>: Median flow of the river in cubic meter per second</li><li><i>month</i>: Month</li><li><i>name</i>: Name of the river (Spain and Portugal)</li><li><i>nb_size_measured</i>: Number of size measured in the electrofishing operation</li><li><i>nbp1</i>: Number of eel collected in the first pass</li><li><i>nbp2</i>: Number of eel collected in the second pass</li><li><i>nbp3</i>: Number of eel collected in the third pass</li><li><i>NCS</i>: Number estimated during the electrofishing operation by Carle and Strubb and interpolation of first pass efficiency if only one pass</li><li><i>nextdownidsegment</i>: Code of the next downstream <i>idsegment</i></li><li><i>Npred</i>: Number of eel predicted on the riversegment <i>pdeltagamma </i>* <i>watersurface</i></li><li><i>ob_dp_name</i>: Data provider for the operation</li><li><i>ob_id</i>: Operation (observation) identifier</li><li><i>ob_starting_date</i>: Date of the operation</li><li><i>op_id</i>: Station (observation place) identifier</li><li><i>pdelta</i>: prediction of the delta (presence absence model)</li><li><i>pdeltagamma: pdelta</i>*<i>pgamma</i></li><li><i>pgamma</i>: prediction of the gamma (positive densities model)</li><li><i>rdelta</i>: residuals of the delta (presence absence model)</li><li><i>rdeltagamma</i>: <i>rdelta</i>*<i>rgamma</i></li><li><i>rgamma</i>: residuals of the gamma (positive densities model)</li><li><i>riverwidthm</i>: River width in meters</li><li><i>riverwidthm</i>.: same variable as riverwidthm (no truncation for riverwidth)</li><li><i>rN</i>: residuals in number (difference in number of eels between observed and predicted there are some NA where we had to get the data from "density" as there was no water surface available</li><li><i>seaidsegment</i>: Identifier of the sea idsegment</li><li><i>sector</i>: please ignore</li><li><i>shreeve</i>: Shreve rank of the segment</li><li><i>size</i>: Size class, "1 - <150", "2 - [150-300[", "3 - [300-450[", "4 - [450-600[", "5 - [600-750[", "6 - >=750"</li><li><i>strahler</i>: Strahler rank of the segment</li><li><i>surfacebvkm2</i>: surface of the watershed in m2</li><li><i>surfacebvm2</i>: surface of the watershed in km3</li><li><i>surfaceunitbvm2</i>: surface of the unit basin surrounding the segment in m2</li><li><i>temperature</i>: Average temperature from 1960-2000 from the CCM (Vogt 2007)</li><li><i>temperaturejan</i>: January temperature (France)</li><li><i>temperaturejul</i>: July temperature (France)</li><li><i>totalnumber</i>: Total number of eel caught during the operation</li><li><i>transport</i>: transport area</li><li><i>wettedsurfacem2</i>: Surface of water downstream from the segment in the river. Corresponds only to rivers</li><li><i>wettedsurfaceotherm2</i>: Surface of water downstream from the segment in the river. Corresponds only waterbodies (water surfaces, associated with the segment).</li><li><i>year</i>: Year of electrofishing operation</li></ul><h3><strong>2.3. SILVER EEL DATA</strong></h3><h4>Dataset <a href="https://zenodo.org/api/files/c576c330-0219-4710-a831-717762b117aa/silver_eel.Rdata?versionId=9df184ef-241d-46af-989e-2bddc0179df0">silver_eel_2020.Rdata</a></h4><p>A dataset of 20101 lines corresponding to yellow and silver eel along with their measurements for silvering for eel > 150 mm.</p><p>This dataset has been built <a href="https://forgemia.inra.fr/pole-migrateurs/eda/eda_model/-/blob/main/eda2.3/report/report2.3/EDA_build.Rnw#L6454">here</a>, and validated <a href="https://forgemia.inra.fr/pole-migrateurs/eda/eda_model/-/blob/main/eda2.3/report/report2.3/EDA_build.Rnw#L6812">here</a> and <a href="https://forgemia.inra.fr/pole-migrateurs/eda/eda_model/-/blob/main/eda2.3/report/report2.3/EDA_build.Rnw#L8409">here</a>, For more information look at the <a href="https://sudoang.eu/wp-content/uploads/2022/02/E411_Briand_et_al_2022_EDA_report_opt-1.pdf">report</a> especially the annexes.</p><p>The columns are:</p><ul><li><i>BL</i>: Body length</li><li><i>Dv</i>: Vertical eye diameter</li><li><i>FL</i>: Pectoral fin length</li><li><i>MD</i>: Mean eye diameter</li><li><i>W</i>: Eel weight</li><li><i>contrast</i>: Body contrast for the eel</li><li><i>Dh</i>: Horizontal eye diameter</li><li><i>diam_max</i>: Max of horizontal and vertical eye diameter</li><li><i>diam_min</i>: Min of horizontal and vertical eye diameter</li><li><i>distance_foyer_c</i>: sqrt(diam_max^2 - diam_min^2)</li><li><i>excentricite</i>: Eye excentricity = distance_foyer_c / diam_max</li><li><i>IO</i>: Occular index Pankhurst = 100*((Dh+Dv/2)^2*pi/BL</li><li><i>K_ful</i>: Fulton coefficient= 100*W/(BL/10)^3</li><li><i>maturite_durif</i>: Durif (2009) maturity class</li><li><i>oc_surface</i>: Occular surface</li><li><i>sexe_durif</i>: Sex according to Durif (2009)</li><li><i>silver</i>: Is it a silver eel, corresponds to one of "MII", "FIV", "FV" in Durif stage [data type: Boolean]</li><li><i>stade_pankhurst</i>: Stage according to Pankhurst</li><li><i>stage_Durif</i>: I, MII, FII, FIII, FIV, FV see Durif (2009)</li><li><i>pdeltagamma</i>: Density predicted from the delta gamma model in EDA (Briand et al., 2022)</li><li><i>dist_from_gibraltar_km</i>: Distance from Gibraltar along the coastline, negative in the Mediterranean</li><li><i>surfacebvm2</i>: Surface of the watershed in m2</li><li><i>altitudem.</i>: Altitude in m truncated at 400</li><li><i>temperature</i>: Average temperature from 1960-2000 from the CCM (Vogt, 2007)</li><li><i>distanceseakm</i>.: Distance to the sea in km truncated at 500</li><li><i>strahler</i>: Strahler order of the stream</li><li><i>month2</i>: Month of electrofishing with values grouped for <=7 or >=10</li><li><i>month</i>: Month of electrofishing</li><li><i>year</i>: Year of electrofishing</li></ul><h2><strong>3. VERSIONS</strong></h2><ul><li><a href="https://doi.org/10.5281/zenodo.6023561">10.5281/zenodo.6023561 </a>1.0.0 - 2022-02-09 - Initial upload (open access)</li><li><a href="https://doi.org/10.5281/zenodo.6397009">10.5281/zenodo.6397009 </a>1.0.1 - 2023-08-02 - Fixed description (open access)</li></ul><h2><strong>4. 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>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>5. FUNDING</strong></h2><p>Project co-financed by the INTERREG SUDOE Programme through the European Regional Development Fund (ERDF).</p>
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